Specific and label-free sensing of biosensor signals using biological transistors

Abstract

The present disclosure provides bio-transistors for sensing target molecules. More specifically, the present disclosure provides systems and methods for determining the presence and / or quantity of target molecules, specifically, protein-based target molecules, such as NAGase, AFP, CRP and Ferritin in a biological sample, thereby providing diagnosis and monitoring of conditions associated with the target molecules.

Description

[0001] SPECIFIC AND LABEL-FREE SENSING OF BIOSENSOR SIGNALS USING BIOLOGICAL TRANSISTORS

[0002] TECHNOLOGICAL FIELD

[0003] The present disclosure relates to bio-transistors for sensing target molecules. More specifically, the present disclosure provides systems and methods for determining the presence and / or quantity of target molecules, specifically, protein-based target molecules.

[0004] BACKGROUND ART

[0005] References considered to be relevant as background to the presently disclosed subject matter are listed below:

[0006] 1. Djabri, B., Bareille, N., Beaudeau, F. & Seegers, H. Quarter milk somatic cell count in infected dairy cows: a meta-analysis. Vet Res 33, 335-357 (2002).

[0007] 2. Ball H J & Greer D. N-acetyl-beta-D-glucosaminidase test for screening milk samples for subclinical mastitis. Vet Rec. 129, 507-509 (1991).

[0008] 3. Chagunda, M. G., Larsen, T., Bjerring, M. & Ingvartsen, K. L. L-lactate dehydrogenase and N-acetyl-p-D-glucosaminidase activities in bovine milk as indicators of non-specific mastitis. Journal of Dairy Research 73, 431-440 (2006).

[0009] 4. Nirala, N. R. & Shtenberg, G. N-acetyl-P-D-glucosaminidase biomarker quantification in milk using Ag-porous Si SERS platform for mastitis severity evaluation. Appl Surf Sci 566, 150700 (2021).

[0010] 5. Kitchen, B. J., Middleton, G. & Salmon, M. Bovine milk N -acetyl-p-D- glucosaminidase and its significance in the detection of abnormal udder secretions. Journal of Dairy Research 45, 15-20 (1978).

[0011] 6. Nirala, N. R. & Shtenberg, G. Bovine mastitis inflammatory assessment using silica coated ZnO-NPs induced fluorescence of NAGase biomarker assay. Spectrochim Acta A Mol Biomol Spectrosc 257, 119769 (2021).

[0012] 7. Nirala, N. R., Asiku, J., Dvir, H. & Shtenberg, G. N-acetyl-P-d-glucosaminidase activity assay for monitoring insulin-dependent diabetes using Ag-porous Si SERS platform. Taianta 239, 123087 (2022). 8. Pemberton, R. M., Hart, J. P. & Mottram, T. T. An assay for the enzyme N-acetyl- I2-d-glucosaminidase (NAGase) based on electrochemical detection using screen-printed carbon electrodes (SPCEs). Analyst 126, 1866-1871 (2001).

[0013] 9. Kumar, D. N., Pinker, N. & Shtenberg, G. Inflammatory biomarker detection in milk using label-free porous SiO2 interferometer. Taianta 220, 121439 (2020).

[0014] 10. Kumar, D. N., Pinker, N. & Shtenberg, G. Porous Silicon Fabry-Perot Interferometer for N -Acetyl-0- <scp>d< / scp> -Glucosaminidase Biomarker Monitoring. ACS Sens 5, 1969-1976 (2020).

[0015] 11. US20230022648

[0016] Acknowledgement of the above references herein is not to be inferred as meaning that these are in any way relevant to the patentability of the presently disclosed subject matter.

[0017] 12. D. H. Kim, H. G. Oh, W. H. Park, D. C. Jeon, K. M. Lim, H. J. Kim, B. K. Jang, K. S. Song, Sensors 2018, 78, DOI 10.3390 / sl8114032.

[0018] 13. S. Hideshima, R. Sato, S. Kuroiwa, T. Osaka, Biosens. Bioelectron. 2011, 26, 2419.

[0019] 14. S. Cheng, K. Hotani, S. Hideshima, S. Kuroiwa, T. Nakanishi, M. Hashimoto, Y. Mori, T. Osaka, Materials (Basel). 2014, 7, 2490.

[0020] 15. C. Sun, R. Li, Y. Song, X. Jiang, C. Zhang, S. Cheng, W. Hu, Anal. Chem. 2021, 93, 6188.

[0021] 16. F. Zhou, Z. Li, Z. Bao, K. Feng, Y. Zhang, T. Wang, Scand. J. Clin. Lab. Invest. 2015, 75, 578.

[0022] 17. Yen, L.-C., Pan, T.-M., Lee, C.-H. & Chao, T.-S. Label-free and real-time detection of ferritin using a horn-like polycrystalline-silicon nanowire field-effect transistor biosensor. Sens Actuators B Chem 230, 398-404 (2016).

[0023] 18. Oshin, O. et al. Graphene-Based Biosensor for Early Detection of Iron Deficiency. Sensors 20, 3688 (2020).

[0024] 19. Sohn, Y.-S., Lee, S.-K. & Choi, S.-Y. Detection of C-Reactive Protein Using BioFET and Extended Gate. Sens Lett 5, 421-424 (2007).

[0025] 20. Min-Ho Lee, Kooknyung Lee & Suk Won Jung. Multiplexed detection of protein markers with silicon nanowire FET and sol-gel matrix, in 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society 570-573 (IEEE, 2012). doi:10.1109 / EMBC.2012.6345995. BACKGROUND

[0026] Field-effect transistors for biological sensing (bioFET) has been the scope of continuous research for the last 40 years. The bioFET sensing is based on the amplification capabilities to transduce small variations surface potential into significant variation in drain-source current (IDS)-

[0027] The leading bioFET sensing mechanism involves the electrostatic perturbation at the sensing area upon the introduction of specific or non-specific molecules which is then transduced by the bioFET into a variation in source-drain current IDS - This electrostatic perturbation is due to charges and / or dipoles associated with the chemical or physical adsorption of biomolecules at the sensing area, the generation of new bonds between the biomolecules and the surface, or any redistribution of electrostatic charges at the sensing area upon. BioFET sensing in complex environments such as serum, whole blood, milk, etc. entails its inevitable exposure to non-specific molecules. Therefore, in order to establish the specific sensing signal, the non-specific molecules must be removed from the sensing area. Traditionally, non-specific signals in bioFETs are managed in the very same manner as performed in conventional enzyme-linked immunosorbent assay (ELISA), and therefore surface blocking is frequently employed and washing of the non-specific signals is considered imperative.

[0028] One of the major infections in dairy cattle is bovine mastitis (BM), a prominent inflammatory disease associated with inflammation in the udder tissues and caused by pathogens such as Staphylococcus aureus, Streptococci (uberis, dysgalactiae, agalactiae), and Escherichia coli (E. coli) [1].

[0029] Humans consuming milk from BM infected dairy cattle can suffer from breast pain, skin infection and long-term health deterioration. More than 90% of human infections are subclinical, and hence the importance for early diagnosis of BM in dairy cows [2].

[0030] Somatic cell counts (SCC) is employed today to detect dairy cattle infected with BM using the California mastitis clotting test (CMT), and Fossomatic cell counter. However, CMT lacks the capability to detect early subclinical stage, and fossomatic cell counter is expansive to analyze. Both these methods, require sample preparation and screening which is not appliable for in-situ monitoring [3]. Recently, haptoglobin, serum amyloid A, and NAGase are reported as biomarkers for realtime BM sensing. Specifically, NAGase is reported for early subclinical stage BM detection. NAGase is a specific type of lysosomal glycosidase. It is an enzyme that acts on glycosidic bonds in various substrates containing N-acetylglucosamine units. NAGase is released upon damage or lysis of epithelial cells, thus representing increased damage to the udder tissue. The overall NAGase concentration has been found to correlate with SCC [4]. Kitchen et al develop qualitative fluorescence method for the identification of NAGase activity in untreated milk [5]. Nirala et al demonstrate silica-coated zinc oxide quantum dots for conventional NAGase activity assay by fluorescence method with a linearity of R2= 0.99 and an LOD of 0.05 pM [6]. Silver based Si for NAGase activity estimated by surface-enhanced raman resonance (SERS) with an LOD of 0.27 pM min-1[7]. Pemberton et al. detected NAGase activity employing unmodified screen-printed carbon electrode for electrochemical analysis by monitoring product oxidation with a linear response of R2= 0.988 in a concentration range of 3.1 to 108 pM ml1[8]. Nandha kumar et al develop porous silicon-based label-free optical device to identify biochemical activity of NAGase in the milk by Fabry-Perot interferometer reporting a dynamic range of 1.0-4.2 pM min1and an LOD of 0.5 pM min1[9]. Also, they reported gelatin coated porous silicon with a dynamic range of 1.04-16.7 pM min1and an LOD of 0.49 pM min1

[0010] .

[0031] Alpha-Eetoprotein (ALP) is a molecule produced by the fetus and the liver. ALP concentrations are measured during pregnancy, especially during the second trimester, as part of the prenatal screening program for fetal anomalies [G. E. Palomaki, et al. Genet. Med. 2020, 22, 462], gastroschisis, omphalocele and others [G. E. PALOMAKI, et al. Obstet. Gynecol. 1988 , 77], chromosomal abnormalities (trisomy 21 known as Down syndrome) [Y. Chen, et al. Reprod. Sci. 2022, 29, 1287; J. C. Graves, et al. Am. Fam. Physician 2002, 65, 915] and abnormal placentation (placental mediated pregnancy complications such as preeclampsia, along with invasive placentation including placenta accrete spectrum [G. J. Kim, J. S. Seong, J. A. Oh, Obs. Gynecol Sci 2023, 66, 1]. The maternal serum AFP concentration changes with gestational age. In the non-pregnant state elevated AFP is associated with embryonic tumors such as embryonal carcinoma, yolk sac tumor or teratoma [A. Talerman, et al. Cancer 1980, 46, 380] and hepatocellular carcinoma [A. M. D. B. and A. S. Befeler, Sleisenger and Fordtran’s Gastrointestinal and Liver Disease, Eleventh Edition, Elsevier, 2020]. The current state of the art requires the mother to have her second trimester biochemical testing for the assessment of the risk for fetal chromosomal abnormalities, congenital anomalies and placental-related disorders. The testing is performed at her prenatal clinic, and the blood sample is sent to a specified laboratory, where it is processed by trained personnel. The test results are provided after a few days or weeks and delay the timely counseling and intervention needed for the pregnant mother. An accurate and readily available POC test will improve substantially this important prenatal screening process allowing the mother to perform the test at home and send the data directly to their prenatal follow-up team for expedite counselling.

[0032] Several FET-based AFP biosensors have been reported to date. Kim et al. report a graphene FET biosensor for specific and label-free sensing of AFP with a limit of detection (EOD) of 0.1 ng / mE and 12.9 ng / mE in PBS and serum, respectively

[0012] . Hideshima et al. report an n-type FET biosensor for specific and label-free AFP detection in PBS with an LOD of 1 ng / mL

[0013] , and Cheng et al. design a FET-based biosensor for AFP sensing for the concentration range of 100 pg / mE - Ipg / mE in PBS buffer solution

[0014] . Sun et al. propose an organic-FET-based biosensor using 2,6-bis(4-formylphenyl)anthracene as the protective and functional layer for label-free determination of AFP with an EOD of 45 femtomolar in human serum

[0015] . Zhou et al. report a p-type silicon nanowire (SiNW) biosensor biofunctionalized with anti-AFP receptors and integrated with a PDMS microchannel for label-free detection of AFP in the concentration range of 0.1-1 ng / mE in O.lxPBS buffer solution

[0016] .

[0033] Ferritin is a crucial protein found in cells, particularly in the liver, spleen, and bone marrow, playing an important role in storing and regulating iron levels within the body. Ferritin serves as a valuable biomarker for assessing iron deficiency. Eow levels of ferritin in the blood are indicative of depleted iron stores, often preceding the development of anemia. Conversely, elevated ferritin levels can serve as an indicator of iron overload conditions, including hereditary hemochromatosis, thalassemia, or hemosiderosis. Ferritin is also associated with poor outcome following stem cell transplantation. A specific and label-free ferritin sensing was also reported for ferritin. Yen et al reported specific and label-free ferritin sensing with horn-like polycrystalline-silicon nanowire FET with a limit-of- detection (LOD) of 50 pg / ml and a dynamic range of 50 pg / ml - 500 ng / ml measured in 0.01 x PBS buffer solution, where the sensing signal is associated with the ferritin negative electric charge

[0017] , Oshin et al demonstrated specific sensing of ferritin using graphene FET with LOD of 10 fM and a dynamic range extending from 10 fM - IpM measured in O.Olx PBS solution, also reporting FET response consistent with the negatively-charged ferritin

[0018] .

[0034] C-reactive protein (CRP) is an acute-phase protein synthesized by the liver in response to inflammatory stimuli, both acute and chronic. It is a key marker of systemic inflammation and has a strong association with the risk of cardiovascular diseases [Balayan et al. Applied Surface Science Advances 12, 100343 (2022)]. Elevated levels of CRP in the blood are indicative of higher cardiovascular risk. Its stability in plasma, absence of circadian variation, and resistance to common medications like corticosteroids make CRP a reliable biomarker for assessing inflammation [Young et al. Pathology 23, 118-124 (1991)]. Additionally, there is growing interest in using serial CRP measurements for guiding therapeutic decisions, thereby enhancing clinical evaluation of inflammatory states [Guo et al. Respir Res 19, 193 (2018)]. Sohn et al. utilized FET technology with anti-CRP antibodies to measure CRP in PBS solution, detecting concentrations from 3 to 10 pg / ml

[0019] . Lee et al. applied the sol-gel method to immobilize anti-CRP antibodies, enabling CRP detection in human serum at levels ranging from 0.12 to 10 ng / ml

[0020] .

[0035] The inventors previously developed a biosensor to shorten and optimize the Debye length at an interface between the sensing region and the fluid

[0011] . This biosensor includes a semiconductor active region; a sensing region configured to contact a fluid; and multiple electrodes that comprise decoupling electrodes and additional electrodes. The decoupling electrodes may be configured, wherein operating in a first mode, to prevent a formation of a top conductive channel within the semiconductor active region; and the additional electrodes are configured, wherein operating in the first mode, to independently control (i) one or more properties of one or more other conductive channels formed within the semiconductor active region, and (ii) a Debye length at an interface between the sensing region and the fluid

[0011] .

[0036] GENERAL DESCRIPTION

[0037] The first aspect of the present disclosure relates to a bio-transistor system comprising at least one transistor unit and a control unit. The transistor unit comprises (i) at least one channel, (ii) source and drain electrodes, (iii) at least one gate electrode and (iv) at least one active region located in proximity to the channel region and carrying at least one affinity moiety. It should be noted that each affinity moiety is specific for a target molecule. The at least one active region is configured for accepting at least one sample. The transistor unit also comprises (v) at least one additional electrode positioned to be in electrical contact with the sample. The control system comprises at least one processor and memory circuitry. The control system is configured and operable for performing one or more measurements of the sample. Each measurement comprises maintaining a selected electric potential on the at least one additional electrode and determining current transmission profile through the at least one channel with respect to potential variation of the at least one gate electrode. The control unit thereby configured to determine data on the presence and / or quantity of one or more target molecules in the sample.

[0038] Another aspect of the present disclosure relates to a battery comprising two or more of the bio-transistor system as defined by the present disclosure.

[0039] A further aspect of the present disclosure, relates to a method for determining presence and / or quantity of at least one target molecule in at least one sample. The method comprising: (a) contacting the at least one sample with a bio-transistor having an active region (e.g., a modified active region) carrying at least one affinity moiety, or a battery comprising at least two of the bio-transistors. It should be noted that each affinity moiety is specific for a target molecule. The next step (b), involves performing one or more measurements, each measurement comprising: applying a selected electric potential on the sample, and determining current transmission profile through a channel of the bio-transistor with respect to potential variation of at least one gate electrode of the bio-transistor. In step (c), processing data on the current transmission through the channel for one or more selected gate potential and one or more selected electric potential values applied on the sample and determining presence and / or quantity of the one or more target molecules in accordance with pre-stored calibration data.

[0040] Another aspect of the current disclosure relates to a diagnostic method for determining a physiological and / or environmental condition or state of a subject and / or a media and / or a habitat. The method comprising: (a) contacting the at least one sample with a bio-transistor having an (e.g., modified) active region carrying at least one affinity moiety, or a battery comprising at least two of said bio-transistors. It should be noted that each affinity moiety is specific for a target molecule. In step (b), performing one or more measurements, each measurement comprising: applying a selected electric potential on the sample, and determining current transmission profile through a channel of the bio-transistor with respect to potential variation of at least one gate electrode of the bio-transistor. Step (c), involves processing data on the current transmission through the channel for one or more selected gate potential and one or more selected electric potential values applied on the sample. In step (d), determining presence and / or quantity of the one or more target molecules in accordance with pre-stored calibration data, thereby obtaining a target molecule value for the sample; and (e), determining that the subject and / or media and / or habitat display the physiological and / or environmental condition or state, if the at least one target molecule value obtained for the sample in step (d), is positive or negative with respect to a reference target molecule value pre-determined for the physiological and / or environmental condition or state, or with respect to a target molecule value determined for at least one control sample.

[0041] Another aspect of the present disclosure is a screening method for identifying a compound that modulates the interaction of an affinity moiety with a target molecule in at least one sample. The method comprising: (i) contacting the at least one sample with a bio-transistor system, in the presence and the absence of at least one candidate compound. The biotransistor having an active region (e.g., a modified active region) carrying at least one affinity moiety, wherein each affinity moiety is specific for a target molecule; (ii) performing one or more measurements for each sample, each measurement comprising: applying a selected electric potential on the sample, and determining current transmission profile through a channel of the bio-transistor with respect to potential variation of at least one gate electrode of the bio-transistor; (iii) processing data on the current transmission through the channel for one or more selected gate potential and one or more selected electric potential values applied on the sample; and (iv), determining presence and / or quantity of the one or more target molecules in accordance with pre-stored calibration data, thereby determining a target molecule value for the sample in the presence of the candidate compound, and a target molecule value in the absence of the candidate compound; (v) determining that the candidate compound is a modulator of the interaction between the affinity moiety and the target molecule, if the target molecule value obtained for the sample in the presence of the candidate compound is different from the target molecule value obtained in the absence of the candidate compound.

[0042] Another aspect of the present disclosure is a personalized method for treating, preventing, inhibiting, reducing, eliminating, protecting or delaying the onset of at least one pathological disorder in a subject. The method comprising the steps of: (a), determining the presence and / or quantity of at least one target molecule target molecule in at least one sample of the subject. The target molecule is associated directly or indirectly with the pathologic disorder. In step (b), administering an effective amount of at least one therapeutic agent for the pathological disorder to a subject exhibiting presence of one or more target molecule, or the quantity of said target molecule that is above or below the standard level, in some embodiments, determining the presence and / or quantity of at least one target molecule in (a), is performed by the steps of: (i) contacting the at least one sample of the subject with a bio-transistor having an active region carrying at least one affinity moiety, or a battery comprising at least two bio-transistors, wherein each affinity moiety is specific for a target molecule. Next (ii), performing each measurement comprising: applying a selected electric potential on the sample, and determining current transmission profile through a channel of the bio-transistor with respect to potential variation of at least one gate electrode of the bio-transistor; (iii) processing data on the current transmission through the channel for one or more selected gate potential and one or more selected electric potential values applied on the sample; and (iv) determining presence and / or quantity of the one or more target molecules in accordance with pre-stored calibration data, thereby obtaining a target molecule value for the sample, thereby obtaining a target molecule value for said sample; and (v), determining that the subject is suffering from said pathologic disorder, if the at least one target molecule value obtained for said sample in step (iv), is positive or negative with respect to a reference target molecule value pre-determined for said pathologic disorder, or with respect to a target molecule value determined for at least one control sample.

[0043] Another aspect of the present disclosure relates to a diagnostic kit. The diagnostic kit comprising: (a) at least one bio-transistor system, and optionally, at least on of: (b) at least one control sample; and (c) at least one therapeutic agent. The bio-transistor system comprises at least one transistor unit and a control system. The transistor unit comprising: (i) at least one channel; (ii) source and drain electrodes; (iii) at least one gate electrode; (iv) at least one active region located in proximity to the channel region and carrying at least one affinity moiety. It should be noted that each affinity moiety is specific for a target molecule. The at least one active region is configured for accepting at least one sample; and (v) at least one additional electrode positioned to be in electrical contact with the sample. The control system comprising at least one processor and memory circuitry. The control system is configured and operable for performing one or more measurements of the sample, wherein each measurement comprises maintaining a selected electric potential on the at least one additional electrode and determining current transmission profile through the at least one channel with respect to potential variation of said the least one gate electrode. The control unit thereby configured to determine on the presence and / or quantity of one or more target molecules in the sample.

[0044] These and other aspects of the present disclosure are further described by the hand of the following description.

[0045] BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to better understand the subject matter that is disclosed herein and to exemplify how it may be carried out in practice, embodiments will now be described, by way of nonlimiting example only, with reference to the accompanying drawings, in which:

[0047] Figure 1. schematically exemplifies a bio-transistor system according to some embodiments of the present disclosure.

[0048] Figure 2. schematically exemplifies a bio-transistor system formed from a plurality of transistor units according to some embodiments of the present disclosure. Figure 3. exemplifies method actions for determining presence and / or quantity of one or more target molecules according to some embodiments of the present disclosure.

[0049] Figure 4A-4C. MNC biosensor biofunctionalized with antibodies

[0050] Fig. 4A. An illustration of the MNC biosensor with representative cross-sections half-way between source and drain. SEM x-section of the MNC biosensor is presented with illustrated surface-bound antibodies. The three main channels are noted, and each can sustain an infinite number of different configurations differing in size, shape and location inside the channel volume.

[0051] Fig. 4B. SEM cross-section of the MNC biosensor.

[0052] Fig. 4C. An optical image of the MNC biochip. The electrical connections and the applied drop (e.g. serum, plasma, milk) are shown.

[0053] Figure 5A-5B. IDS-VGL curves for selected VGF values measured for MNC biosensor biofunctionalized with anti- NAGase antibodies (background measurement)

[0054] Fig. 5A. IDS-VGL curves for selected VGF values measured for MNC biosensor biofunctionalized with anti-NAGase antibodies. The measurements were performed for 20 successive 0.5 pL drops of 3% commercial milk. Each data point is an average of 20 drops each measured 3 times. The error bars are the respective standard deviations (see inset).

[0055] Fig. 5B. The corresponding second derivatives of the curves presented in Fig. 5A, indicating the excitations of the different channels.

[0056] Figure 6A-6B. IDS-VGL curves for selected VGF values performed for MNC biosensor biofunctionalized with anti-NAGase antibodies (target molecule measurement)

[0057] Fig. 6A-6B. IDS-VGL and iNormaizied curves for selected VGF for various NAGase concentrations spiked into 0.5 pL of 3% milk. The channel configurations are indicated at the top of the IN(>rmaizied figures.

[0058] Fig. 6A. VGL of 0V and -0.5V.

[0059] Fig. 6B. VGL of -1.0V and -1.5V. Figure 7. Control non-specific measurements of MNC biosensor biofunctionalized with anti-NAGase antibodies

[0060] Figure 8. Extracted calibration curves from MNC biosensor biofunctionalized with anti-NAGase antibodies

[0061] Extracted calibration curves for the specific and label-free sensing of NAGase in 0.5 pL drop 3% milk. The illustrations on the right of the curves illustrate the channel configuration midway between source and drain.

[0062] Figure 9. NAGase sensing performance

[0063] The figure discloses Table 1 that shows summary of sensing performance for NAGase in terms of LOD, dynamic range, linearity, and sensitivity. The channel configuration, in open circle (light gray) midway between source and drain, follows the analysis presented in Figure 5B.

[0064] Figure 10. IDS-VGL curves for selected VGF values measured for MNC biosensor biofunctionalized with anti-AFP antibodies (background measurement)

[0065] IDS-VGL curves for selected VGF values measured for MNC biosensor biofunctionalized with anti-AFP antibodies. Each data point is an average of 64 measurements (16 drops, each drop is measured 4 times), and the error bars are the corresponding standard deviations (see inset).

[0066] Figure 11A-11D. Process of Si / SiO surface biofunctionalization with anti-AFP antibodies

[0067] Fig. 11A. An illustration showing the process of Si / SiO2 surface biofunctionalization. The corresponding contact angle measurements are also shown.

[0068] Fig. 11B. Ellipsometry measurements and contact angle measurements of Si / SiO2 samples post various modification steps.

[0069] Fig. 11C. EIS measurements showing the real and imaginary capacitances for the various modification steps. Fig. 11D. IDS-VGL for various VGF values for unmodified MNC device and biofunctionalized MNC biosensor. The data points and the error bars (see inset) reflect the averages and standard deviations of 12 measurements (3 drops each measured 4 times).

[0070] Figure 12A- 12C. IDS-VGL for selected VGF values for MNC biosensor modified with anti-AFP molecules

[0071] Fig. 12A. IDS-VGL for selected VGF values for MNC biosensor modified with anti-AFP molecules. The measurements are performed in 1 : 100 diluted serum. The data points reflect an average of 42 measurements (Total of 14 drops each measured 3 times), and the error bars are the respective standard deviations (see inset).

[0072] Fig. 12B. The second derivatives of the curves presented in Figure 12A where a peak reflects the excitation of a conducting channel. The dependence of channel excitation on gates’ voltage configuration is shown.

[0073] Fig. 12C(i)-12C(iv). Non-specific measurements for: AFP introduced to an unmodified MNC biosensor (Fig. 12C(i)), AFP introduced to an MNC biosensor modified with APTMS (Fig. 12C(ii)), hCG molecules introduced to an MNC biosensor modified with anti-AFP antibodies (Fig. 12C(iii)), and PSA molecules introduced to an MNC biosensor modified with anti-AFP antibodies (Fig. 12C(iv)). All measurements are performed in 1: 100 diluted serum. The insets present magnifications showing the error bars reflecting the standard deviations of the measured populations.

[0074] Figure 13A-13C. IDS-VGL for selected VGF values for different concentrations of AFP molecules

[0075] Fig. 13A. IDS-VGL for selected VGF values for 10 concentrations of AFP molecules. The measurements are performed in 1: 100 diluted serum. Each concentration (=drop) is measured 4 times. The insets show the error bars reflecting the standard deviations. The non-specific signals are accounted for and removed.

[0076] Fig. 13B. The extracted Readout corresponding to the curves presented in Figure 13 A. The insets show the corresponding error bars. The labels at the top of the graphs indicate the corresponding conducting channels. Fig. 13C. An illustration showing one possible mechanism for the Readout polarity switch induced by the double layer electric field.

[0077] Figure 14A-14B. Readout calibration curves for AFP molecules

[0078] Fig. 14A. Readout calibration curves. The illustrations on the right reflect the channel configurations. The vertical dashed grey lines indicate the calibration threshold.

[0079] Fig. 14B(i)-14B(ii). The dependency of the calibration threshold on VGF (Fig. 14B(i)). The non-dependency of the calibration threshold on VGL (Fig. 14B(ii)). The shift between the lines for VGL = 0, -0.5, -1 and -1.5 V are only for the purpose of visualization.

[0080] Figure 15. AFP sensing performance

[0081] The figure presents Table 2, that shows a summary of the MNC biosensor sensing performance for specific and label-free detection of AFP.

[0082] Figure 16A-16B. Two-dimensional (2D) numerical calculations of a solution- dielectric-silicon system

[0083] The substrate is grounded and the potential is applied to Vs<>i

[0084] Fig. 16A. 2D distributions of the electrostatic potential for the selected Vs<>i. Insets: 2D distributions of the DL electrostatic potential.

[0085] Fig. 16B. ID distributions of the electric fields and ion concentrations in the solution for the applied VS(>i.

[0086] Figure 17A-17B. Three-dimensional (3D) numerical calculation of the suggested BioFET

[0087] Fig. 17A. A 3D illustration of a suggested BioFET with a side gate. Numerical IDS-VGS (Vsoi = 0 V) curve showing the triggering of the conducting channel.

[0088] Fig. 17B. Numerical 2D cross-section midway between source and drain presenting the distributions of the electrostatic potential for -2 V (off-state) and 0.5 V (on-state). Figure 18A-18C. Experimentally measured IDS-VGS curves

[0089] Fig. 18A. Side-gate sweep (IDS-VGS, VS(>I = -1.5 V) and solution sweep (IDS- VS(>I, VGS= -2 V). Each data point is an average 54 measurements (18 drops, each drop is measured 3 times), and the error bars are the corresponding standard deviations (see insets).

[0090] Fig. 18B. The corresponding range and standard deviation values of the I-V curves in Figure 18A.

[0091] Fig. 18C. Same as Fig. 18B only for a BioFET biofunctionalized with anti-ferritin antibodies.

[0092] Figure 19A-19D. Control measurements

[0093] IDS-VGS for Vs<>i = -1.5 V. The illustrations left of the graphs reflect the type of control measurements.

[0094] Fig. 19A. Ferritin introduced to unmodified BioFET.

[0095] Fig. 19B. Ferritin introduced to an APTMS-modified BioFET.

[0096] Fig. 19C. AFP introduced to a BioFET biofunctionalized with anti-ferritin.

[0097] Fig. 19D. PSA introduced to a BioFET biofunctionalized with anti-ferritin.

[0098] Figure 20A-20D. Side-gate sweep curves (for ferritin)

[0099] Fig. 20A. Side-gate sweep. IDS-VGS curves for Vro / =-1.5 V and for 0.5 pF drops of 1: 100 diluted plasma spiked with ferritin concentrations in the range of 1 fg / ml - 10 pg / ml. Note that every data point reflects the average of three measurements and the error bars are the standard deviations (see inset). The illustrations on the right and left of the curves are crosssections, midway between source and drain, showing the effect of VGS sweep on the conducting channel while maintaining the DE in electrochemical equilibrium.

[0100] Fig. 20B-20C. Solution sweep. Following the convention presented in Fig. 20A. only for IDS-VS I curves with VGS=0, -2 V. The illustrated cross-sections reflect the effect of Vs<>i sweep on both IDS and DE.

[0101] Fig. 20D. The corresponding I NORMALIZED curves for both side-gate and solution sweeps.

[0102] Figure 21A-21C. Specific and label-free sensing performance

[0103] Fig. 21A. Calibration curves for side-gate sweep for selected VGS values and Vmi=- 1.5 V. Fig. 21B. Calibration curves for solution sweep for selected V.mivalues and for VGS = 0 V.

[0104] Fig. 21C. Same as Fig. 2 IB only for VGS = -2 V.

[0105] Figure 22. Ferritin sensing performance

[0106] The figure presents Table 3, that shows a summary of the MNC biosensor sensing performance for specific and label-free detection of ferritin.

[0107] Figure 23A-23B. IDS-VGL curves for selected VGF values measured for biofunctionalized MNC biosensor with anti-CRP

[0108] Fig. 23A. An illustration of the FET biochip.

[0109] Fig. 23B. IDS-VGL curves for selected VGF values performed with 0.5 pL drops of whole blood. The FET biochip is unmodified and modified with anti-CRP. Each data point is an average of 60 measurements, and the error bars are the corresponding standard deviations.

[0110] Figure 24. IDS-VGL curves for selected values of VGF for the range of CRP concentrations

[0111] IDS-VGL curves for selected VGF values and for 0.5 pL drops of whole blood spiked with CRP concentrations ranging from Ifg / ml to Img / ml. The corresponding Inorm curves are presented along-side the IDS-VGL curves.

[0112] Figure 25. Inorm curves for CRP (controls)

[0113] InOrm curves for CRP introduced to an unmodified FET biochip and APTMS modified biochip. All measurements presented in Figure 13 are performed in 0.5 pL drops of whole blood.

[0114] Figure 26. Extracted calibration curves for the specific and label-free sensing of CRP Extracted calibration curves for the specific and label-free sensing of CRP and anti-CRP interaction in whole blood. DETAILED DESCRIPTION OF EMBODIMENTS

[0115] The bioFET platform employed for NAGase detection is the Meta-Nano-Channel biosensor biosensor) [Bhattacharyya, I. M. et al. Adv Electron Mater (2022) doi: 10.1002 / aelm.202200399; Bhattacharyya, I. M. et al. Nanoscale 14, 2837-2847 (2022); Ron, I. et al. Sens Actuators B Chem 393, 134171 (2023); Samanta, S. et al. Adv Mater Technol (2023) doi: 10.1002 / admt.202202200]. Briefly, the MNC biosensor addresses the challenge associated with the non-homogenous distribution of biological events at the sensing area as it provides means to tailor the shape, size and location of the conducting channel to best couple with the biological complexes distributions. As the distribution of the biological complexes at the sensing area is not known a priori, many configurations of conducting channels are measured and scanned for best sensing performance in terms of limit-of-detection (LOD), dynamic range, linearity and sensitivity. Additionally, the presence of side gates (or lateral gates) allows sweeping of the conducting channel from the off-state to the on-state while maintaining a fix solution potential. This implies that during the sensing measurement the solution is equilibrium conditions, as no transient currents (driven by gradients in the electrochemical potential) which could impede the sensing procedure are present. Moreover, the sensing performance depends on the biomolecular organization of the receptor-target complexes present at the double layer. The conditions at the double layer, namely the electric fields, the ionic strength and the pH depends on the solution potential. Therefore, as molecular interactions, and specifically biological interactions, depend on the presence of electric fields, pH and ionic strength levels, tuning of the solution potential will affect the interactions. As the determination of the solution potential is orthogonal to the tuning of the conducting channel, the solution potential governed by an electrode provide means to affect the interactions and hence the sensing performance. Biosensing based on biological field-effect transistors (bioFET) is a promising technology toward specific, label-free and multiplexed sensing in ultra-small samples. The leading bioFET sensing mechanism is the electrostatic perturbation induced at the sensing area upon the introduction of a specific or non-specific molecules. Therefore, traditionally, the non-specific signal in bioFETs is managed in the same manner as performed in the ubiquitous enzyme-linked immunosorbent assay (ELISA); namely, surface blocking is considered and washing of the non-specific signal is imperative. In the current study the inventors employ a field-effect meta-nano-channel biosensor (MNC biosensor) for the sensing of the enzyme N-acetyl-beta-D-glucosaminidase (NAGase), a biomarker for milk cow infections, in 3% commercial milk. The selection of NAGase is motivated by (1) the concentration of non-specific proteins in 3% commercial milk is very high (33 mg / ml), and (2) NAGase is not present in commercial milk. High-end specific and label-free sensing of NAGase spiked into 0.5 pL drops of 3% milk is demonstrated with a limit-of-detection of 1 fg / ml, a dynamic range of 10 orders of magnitude and with excellent linearity and sensitivity. Importantly, the sensing is performed without the application of either surface blocking and washing of the non-specific signal. The biofunctionalization of the MNC biosensor with anti-NAGase antibodies is described and extensive control measurements are provided.

[0116] Ultimate-coupling and active sensing approach is also demonstrated for AFP using the MNC biosensor. The ability to shape the conditions through the sample, creating a double layer using application of a selected electric potential (VGF) on the sample using the solution electrode enables the MNC biosensor of the present disclosure to provide selected sensing performance in terms of sensitivity and dynamic range. The ability for active sensing is provided using an additional gating electrode is present. This additional gating electrode should not induce potential variations at the dielectric-solution interface, as is made possible by the lateral gates of the MNC biosensor. Accordingly, the technique of the present disclosure may utilize a selected electric potential applied directly to the sample, while operating one or more lateral gates for affecting transistor source-drain current. Previously known techniques utilized a back gate electrode for determining a potential drop through the biosensor. Such potential backdrop affects the potential at the dielectricsolution interface limiting sensing capabilities of the biosensor.

[0117] As indicated above, the present disclosure provides a bio-transistor system configured and operable for detection of presence and / or quantity of one or more selected molecules. An exemplary configuration of bio-transistor system 100 is illustrated in Fig. 1. The system includes at least one transistor unit 110 including source 120 and drain 130 regions associated with respective source 124 and drain 134 electrodes, and a channel region 140 between them. The transistor unit 110 also includes one or more gate electrodes 144, located and configured to apply selected electric field on the channel 140 region to thereby enable switching of the transistor unit 110 by affecting charge carriers within the channel 140. Typically, as exemplified herein the source 120, drain 130 and channel 140 regions are placed on a back insulator layer 160 and covered by a top insulator 170. Further, in some embodiments, the at least one gate electrode may be a side (e.g., lateral) gate electrode with respect to the channel region 140, alternatively or additionally, the at least one gate electrode may be positioned between one of the source and drain electrodes 124 and 134 and the active region 150. The active region 150 is located on top of the channel region 140, electrically insulated from the channel region 1 40 by the top insulator 170. The at least one gate electrode 144 is generally separated from the channel region 140 by a gate insulator, which may be a portion of top insulator 170. In some configurations, the transistor unit 110 may be formed of one or more semiconductor materials such as silicon, having selected doped regions with selected p-type or n-type doping. For example, the active layer defining the source 120 and drain 130 regions and the channel region 140 between them may be formed of silicon semiconductor having varying p- and n-type doping regions.

[0118] The transistor unit 110 further includes an active region 150 located in vicinity (e.g., above) a region of the channel 140 and separated from the channel, e.g., by top insulator 170. The active region 150 is formed of a region of top insulator 170, which is modified to carry selected one or more types of binding molecules, or affinity moieties, selected to bind one or more target molecules. This configuration provides the bio-transistor system 100 with capabilities for detection of the selected target molecules. The transistor unit 110 is configured to accept a liquid sample 50, e.g., a liquid drop, positioned on, or in contact with, the active region 150. In some configurations, the active region 150 may be surrounded by edge 152 configured to limit flow of liquid sample and prevent contact of the sample with electrodes of the unit 110 such as gate electrodes 144. The edge 152 may be formed of any electrically insulating material and may be a part of top insulator 170. Transistor unit 110 may also include at least one additional electrode 154 positioned to be in electric contact with the liquid sample 50, the additional electrode 154 is also referred to as quasi-reference electrode or sample electrode. As indicated above, transistor unit 110 may be formed of silicone including n- and p-doped silicon regions forming the channel region 140 as well as source 120 and drain 130 regions. Top 170 and bottom 160 insulators may be formed of silicon oxide layers. It should be noted that in some other embodiments, the transistor may be formed of selected one or more other semiconductor materials as the case may be.

[0119] Bio-transistor system 100 may also include a control system 500. Control system 500 may include one or more processor and memory circuitries (PMC) 510 and may also include an electric circuit 52 configured to selectively apply electric potential and / or transmit electric current through the electrodes of transistor unit 110 to enable bio-transistor system 100 to determine data on presence and / or quantity of target molecules in the sample 50.

[0120] In this connection PMC 510 may include one or more processors and memory, and may include, or be associated with, an I / O interface for receiving input data and for transmitting output instructions and / or data for operation of the bio-transistor system 100. PMC 510 is operatively connected to the I / O interface and is configured to provide processing necessary for operation of the bio-transistor as described herein. PMC 510 is configured to execute one or more functional operations in accordance with computer readable instructions implemented on a computer readable medium (e.g., non-transitory memory) being pre-stored at the memory of PMC 510 or at a separate computer readable medium.

[0121] In this connection, PMC 510 may operate the electric circuit 520 for selectively providing electric potential to the electrodes of transistor unit 110, and for determining data on current flow between the source electrode 124 and drain electrode 134. In this connection the control unit 500 is configured and operable for performing one or more measurements of the sample 50 to determine data on presence and / or quantity of target molecules in the sample 50.

[0122] More specifically, in some embodiments, each of the one or more measurements may include operation of the control system to maintain a selected electric potential VGF on the at least one additional electrode 154 to maintain a selected potential on the sample 50. Additionally, while maintaining a selected potential VGF on the sample 50, the control system 500 may operate for determining current transmission profile between the source 124 and drain 134 electrodes with respect to varying potential VG on at least one gate electrode 144. For example, this may be done by applying a selected potential between the source 124 and drain 134 electrodes and determining level of current transmission between the source 120 and drain 130 regions through the channel 140 with respect to potential VG applied to the at least one gate electrode 144. Typically, each of the one or more measurements may be performed using a different selected potential VGF applied on the sample 50.

[0123] As described below, the present disclosure is based on the inventors’ understanding that interactions between target molecules and selected affinity moieties located on the active region 150 of the transistor unit 110 affect the transistor source-gate transmission in certain conditions. The interactions between target molecules and affinity moieties cause variation in distribution of electric charges resulting in variation of electric fields around the active region 150, which also affects the channel region 140. Accordingly, each measurement may include collecting data on current to gate potential (I-VG) characteristics of the transistor unit 110 for given sample potential VGF.

[0124] Typically, the control system 500 may be configured to perform a selected number of one or more, or two or more measurements, using different sample potentials VGF, and to store collected data on current for different gate potential values for each measurement. This measurement data, indicative of transistor unit 110 I-VG characteristics for one or more different sample potential values VGF is indicative of presence and / or quantity of the target molecules in the sample 50.

[0125] To this end, the control system 500 may include pre-stored data, e.g., pre-stored at the memory of PMC 510, or stored in a remote location accessible view network communication, for calibrating transistor unit 110 characteristics to data on presence and / or quantity of target molecules in the sample 50. The pre-stored data may be indicative of I- VG characteristics of the transistor unit 110 as a function of presence and / or quantity of the target molecules for one or more given sample potentials VGF. Additionally, or alternatively, the pre-stored data may be indicative of a relation between current transmission through the channel as a function of sample potential VGF, for one or more given gate voltage VG values. After determining data on presence and / or quantity of the target molecules, the control system 500 may operate to generate output signal indicative of the data and provide the output signal via I / O interface to be presented to an operator using user interface and / or for use in further processing.

[0126] As indicated above, the bio-transistor system 100 utilizes selected affinity moieties placed (adsorbed, attached) on an active region 150 located in vicinity to the channel region 140. The active region 150 may be separated from semiconductor region of the channel region 140 by an electric insulating layer 170 (top insulator), such that electrostatic changes at the active region 150 may apply electric fields affecting the channel region 140.

[0127] Selection of the affinity moieties determines one or more target molecules to be identified using the bio-transistor system 100. To enable detection of a plurality of different target molecules, the present disclosure may also provide a bio-transistor system 100 including a plurality of transistor units, each carrying a selected different type of affinity moieties, selected to interact with one or more target molecules, including e.g., one or more different target molecules. In this connection reference is made to Fig. 2 exemplifying a biotransistor array configuration of system 100. The system includes a selected number of transistor units 110a to 11 On, each having source and drain regions 120 and 130 and a channel region between them, and active region 150 carrying the selected affinity moieties, gate electrode 144, and an additional electrode (not shown) positioned to be in contact with a sample positioned on the active region 150. The plurality of transistor units 110a- 11 On are connected to a control system 500 and are independently operated for determining data on presence and / or quantity of the respective target molecules as described herein.

[0128] In some embodiments, the bio-transistor system 100 may include a sample channel configured for receiving a liquid sample and channeling portions of the liquid samples to different active regions of a plurality of transistor units as illustrated in Fig. 2. To avoid variation in electric potential between the sample portions located on the different active regions, the channel may include a selected number of electrical insulating valves configured to close prior to performing measurements on the samples.

[0129] Fig. 3 exemplifies a method for determining presence and / or quantity of at least one type of target molecules according to some embodiments of the present disclosure in a way of a block diagram. As shown, the method includes providing selected affinity moieties in contact (e.g., adsorbed, attached) with an active region 3010 of one or more transistor units.

[0130] The bio-transistor unit may be treated and / or reacted and / or activated with the selected affinity moieties (also referred to herein as selected affinity moieties) during production and provided for use in determining presence and / or quantity of the selected target molecules. To determine presence and / or quantity of at least one type of target molecules, the method includes contacting a sample with the active region of the one or more transistor units 3020 and operating the transistor unit to perform one or more measurements 3030. Generally, each measurement includes maintaining a sample potential 3032, using one or more additional electrodes being in electric contact with the sample, and determining current-voltage characteristics of the transistor unit 3034. As indicated, the method may include a selected number of measurements, typically using different one or more potentials VGF values applied to the sample. Following one or more (or two or more) measurements, the method includes processing the measurement data and determining data on presence and / or quantity of the target molecules 3040. The processing may generally include using pre-provided calibration data indicative of variation in transistor currentvoltage characteristics for given amounts of the target molecules in the sample.

[0131] Accordingly, the system and method of the present disclosure may utilize predetermined calibration data, determined for given activity region 150 carrying given amount of affinity moieties of selected type. In some examples, the calibration data may be in the form of a multi-dimensional calibration data including data on variation of the source-drain current with respect to different gate potentials VG and to different sample potentials VGF. Accordingly, as indicated above, variation of the sample potential VGF may be used as a parameter for determining presence and / or quantity of the target molecules. In some other embodiments, variation of the sample potential VGF may provide for varying detection range for difference ranges of quantity of the target molecule, where for each value of sample potential, variation of gate potential VG and the relation between gate potential and source-drain current provides the calibration for quantity of target molecules in the sample. Referring back to Fig. 3, the method of the present disclosure utilizes performing one or more measurements of the sample. As indicated above, each measurement includes maintaining sample potential VGF at a selected value and determining source-drain current for selected range of gate potentials VG. Typically, the different measurements utilize different values of the sample potential VGF. It should be understood that the measurement may also utilize a selected, generally constant, source-drain voltage to eliminate, or at least significantly reduce effects of the potential variation on the interaction between the affinity moieties and target molecules. Additionally, variation of sample potential VGF may affect concentration of the target molecules within the sample, e.g., forming layers of different concentrations of the target molecules, thereby limiting detection accuracy. To solve this issue, the present technique may utilize a selected number of different sample potential VGF values, and respective calibration data.

[0132] Accordingly, the systems and methods of the present disclosure provide for determining presence and / or quantity of selected target molecules within a sample. As described above, the present technique utilizes calibration data, determined in accordance with known concentrations of the target molecules. Typically, the calibration data may be determined in accordance with amount and / or density of affinity moieties associated with the active region 150.

[0133] In accordance with structure of the transistor unit 110, variation in source-drain current, associated with gate potential VG, and sample potential VGF, may be associated with concentration of charge carrier in the channel region 140. In some configurations of the transistor unit 110, variation of gate potential VG may affect size and / or shape of the channel region 140 and accordingly affect current transmission through the channel. An exemplary structure of transistor unit suitable for affecting channel shape and dimensions by variation of gate potential VG is described in US 2023 / 0022648 incorporated herein for reference with respect to configurations of the transistor unit.

[0134] Thus, the first aspect of the present disclosure relates to a bio-transistor system comprising at least one transistor unit and a control unit. The transistor unit comprises (i), at least one channel, (ii) source and drain electrodes, (iii) at least one gate electrode and (iv), at least one active region located in proximity to the channel region and carrying at least one affinity moiety (also referred to herein as selected affinity moieties). It should be noted that each affinity moiety is specific to a target molecule. Specifically, each of the affinity moieties is specific to one target molecule. In yet some further embodiments, the active region may carry two or more different affinity moieties, e.g., at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000 or more different affinity moieties, each specific for one target molecule. In some embodiments, the disclosed bio transistor may comprise various different affinity moieties each specific for one target molecule, but the target molecule for all affinity moieties may be different. Thus, the disclosed bio transistor may potentially comprise various affinity moieties that are specific to various target molecules or different recognition sites within one target molecule. In some embodiments, different affinity moieties may be specific for the same target molecule. Alternatively, different affinity moieties may be specific for different target molecules, wherein each of the affinity moieties is specific for one target molecule. The at least one active region is configured for accepting at least one sample (e.g., a liquid sample). The transistor unit also comprises (v), at least one additional electrode positioned to be in electrical contact with the sample. The control system comprises at least one processor and memory circuitry. The control system is configured and operable for performing one or more measurements of the sample. Each measurement comprises maintaining a selected electric potential on the at least one additional electrode and determining current transmission profile through the at least one channel with respect to potential variation of the at least one gate electrode. The control unit thereby configured to determine data on the presence and / or quantity of one or more target molecules in the sample.

[0135] In some embodiments of the present disclosure, the control system is configured to performed two or more measurements utilizing two or more different selected electric potentials applied to the at least one additional electrode.

[0136] In some other embodiments, the control system comprises pre-stored calibration data comprising data on electric transmission through the channel for given gate electrode potential with respect to one or more selected electric potentials applied to the at least one additional electrode. In some further embodiments, the control system comprises pre-stored calibration data comprising data on electric transmission trough the channel with respect to variation of the gate electrode potential.

[0137] It should be noted that the pre-stored calibration data may be generated from different concentrations of the target molecule in at least one sample. More specifically, the prestored calibration data may be generated from at least one concentration of target molecule. Still further, the pre-stored calibration data may be generated from at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1000 or more different concentrations of the target molecule in the sample. It should be noted that different concentrations of the target molecule may be also affected from the different dilutions of the samples.

[0138] In some embodiments of the present disclosure, the bio-transistor system comprising a plurality of two or more transistor units comprising respective plurality of two or more active regions carrying two or more different or identical types of affinity moieties.

[0139] In some other embodiments, the active region is separated from the channel region by an electrical insulator layer. In some further embodiments, the at least one gate electrode is electrically insulated from the active region.

[0140] Still further, in some embodiments, the control system comprises at least one electrical circuit coupled via electrical connection to the transistor unit and configured to provide selected electric potentials to electrodes of the transistor unit.

[0141] In some embodiments of the present disclosure, the at least one affinity moiety may comprise at least one of: an amino acid-based molecule, a nucleic acid-based molecule, a small molecule, a carbohydrate-based molecule, a lipid-based molecule or any combination thereof, as will be specified herein after. The at least one affinity moiety specifically binds, either directly or indirectly, the at least one target molecule in the sample, wherein each of the at least one affinity moieties are specific for a single target molecule. In some further embodiments, the affinity moiety comprises, or is derived from a component of an affinity pair. The term "affinity moiety" or "affinity molecule" or "affinity pair" as used herein refers to a corresponding binding couple biomolecule partners. The term "Affinity" or "binding affinity" is the strength of the binding interaction between a binding biomolecule to its binding partner or target (e.g., a protein, DNA or small molecule). Binding affinity is typically measured and reported by the equilibrium dissociation constant (KD), which is used to evaluate and rank order strengths of bimolecular interactions. The smaller the KD value, the greater the binding affinity of the binding molecule for its target. The larger the KD value, the weaker the target molecule and affinity molecule are attracted to and bind to one another. Binding affinity is influenced by non-covalent intermolecular interactions such as hydrogen bonding, electrostatic interactions, and hydrophobic and van der Waals forces between the two molecules. In addition, binding affinity between a binding molecule and its target molecule may be affected by the presence of other molecules. The affinity pair comprises at least one of: receptor-ligand, antibody-antigen, enzyme-substrate, aptamer-aptamer target, or any combination thereof.

[0142] It should be understood that the affinity molecule specifically binds the at least one target molecule in the sample.

[0143] In some embodiments, the target molecule comprises at least one of: an amino acid-based molecule, a nucleic acid-based molecule, a small molecule, a carbohydrate-based molecule, a lipid-based molecule or any combination thereof.

[0144] It should be understood that the target molecule is specifically recognized and bound by the affinity moiety. It should be noted that each affinity moiety is specific for one target molecule. In some embodiments, the affinity moiety and the target molecule recognized by the affinity moiety form together an affinity pair.

[0145] In some further embodiments, the target molecule comprises, or is derived from a component of an affinity pair. The term "target molecule" as used herein refers to at least one specific molecule in a sample for which determining its presence and / or quantity is desired. This target molecule will be the corresponding partner of the affinity moiety. A target molecule as used herein may be either a single molecule or a combination or a complex of two or more molecules or subunits forming a specific recognition partner recognized and bound by the specific affinity moiety of the disclosed bio-transistor systems.

[0146] The affinity pair comprises at least one of: receptor-ligand, antibody- antigen, enzymesubstrate, aptamer-aptamer target, or any combination thereof. The target molecule specifically interacts with the affinity moiety. Specifically, each of the affinity moieties recognizes a single target molecule, however, in some embodiments, a single or a particular target molecule may be recognized by more than one different affinity moieties. It should be understood that each component of the affinity pair may be either the target molecule or the affinity molecule and vice versa. For example, the target recognition component may comprise either the antibody or any fragment thereof and the target molecule may comprise the recognized antigen or any fragment thereof, or vice versa. Specifically, the target recognition component may comprise the antigen, and the target molecule may comprise the antibody or any fragment thereof. "Specifically binds" as used herein refers to an affinity moiety which interacts with a specific target molecule, while avoiding interactions with other molecules. Examples of moieties with specific binding capabilities include for example receptors, antibodies, enzymes, aptamers, as recognition sites. The target recognition component specifically binds the target molecule in any stoichiometric ratio. In some embodiments, one target recognition component binds at least one, at least two, at least three, at least four, at least five, at least ten, at least hundred, at least thousand and even more, target molecules. In some embodiments, the target-recognition component comprises more than one moiety, wherein the plurality of moieties may be the same and / or may be different (e.g. different receptors, different antibodies, a receptor and an antibody, an antibody and an enzyme, etc).

[0147] As mentioned, in some embodiments, an affinity pair may be an Antibody-antigen pair. An "antibody Ab)" , also known as an "immunoglobulin (Ig)", is a large, Y- shaped glycoprotein used by the immune system to identify and neutralize foreign objects such as pathogenic bacteria and viruses. The antibody recognizes a unique molecule called an "antigen". Each tip of the "Y" of an antibody contains a paratope (analogous to a lock) that is specific for one particular epitope (analogous to a key) on an antigen, allowing these two structures to bind together with precision. The term "antibody" as used herein, means any antigen-binding molecule or molecular complex comprising at least one complementarity determining region (CDR) that specifically binds to or interacts with a particular antigen. The term "antibody" includes immunoglobulin molecules comprising four polypeptide chains, two heavy (H) chains and two light (L) chains inter-connected by disulfide bonds, as well as multimers thereof (e.g., IgM). Each heavy chain comprises a heavy chain variable region (abbreviated herein as HCVR or VH) and a heavy chain constant region. The heavy chain constant region comprises three domains, CHI, CH2 and CH3. Each light chain comprises a light chain variable region (abbreviated herein as LCVR or VL) and a light chain constant region. The light chain constant region comprises one domain (CL1). The VH and VL regions can be further subdivided into regions of hypervariability, termed complementarity determining regions (CDRs), interspersed with regions that are more conserved, termed framework regions (FR). Each VH and VL is composed of three CDRs and four FRs, arranged from amino-terminus to carboxy-terminus in the following order: FR1, CDR1, FR2, CDR2, FR3, CDR3, FR4. Exemplary categories of antigen-binding domains that can be used in the context of the present invention include antibodies, antigen-binding portions of antibodies, peptides that specifically interact with a particular antigen (e.g., peptibodies), receptor molecules that specifically interact with a particular antigen, proteins comprising a ligand-binding portion of a receptor that specifically binds a particular antigen or antigen-binding scaffolds. The antigen binding domains in accordance with the invention may recognize and bind a specific antigen or epitope. It should be therefore noted that the term “binding specificity”, ’’specifically binds to an antigen”, “specifically immuno-reactive with”, “specifically directed against” or “specifically recognizes”, when referring to an antigen or particular epitope, refers to a binding reaction which is determinative of the presence of the epitope in a heterogeneous population of proteins and other biologies.

[0148] The term "epitope" is meant to refer to that portion of any molecule capable of being bound by an antibody which can also be recognized by that antibody. Epitopes or "antigenic determinants" usually consist of chemically active surface groupings of molecules such as amino acids or sugar side chains and have specific three-dimensional structural characteristics as well as specific charge characteristics. Still further, as indicated above, an "antigen-binding domain" can comprise or consist of an antibody or antigen-binding fragment of an antibody.

[0149] Still further, "antigen-binding fragment" of an antibody, and the like, as used herein, include any naturally occurring, enzymatically obtainable, synthetic, or genetically engineered polypeptide or glycoprotein that specifically binds an antigen to form a complex. Antigen-binding fragments of an antibody may be derived, e.g., from full antibody molecules using any suitable standard techniques such as proteolytic digestion or recombinant genetic engineering techniques involving the manipulation and expression of DNA encoding antibody variable and optionally constant domains. Such DNA is known and / or is readily available from, e.g., commercial sources, DNA libraries (including, e.g., phage-antibody libraries), or can be synthesized. The DNA may be sequenced and manipulated chemically or by using molecular biology techniques, for example, to arrange one or more variable and / or constant domains into a suitable configuration, or to introduce codons, create cysteine residues, modify, add or delete amino acids, etc. Non-limiting examples of antigen-binding fragments include: (i) Fab fragments; (ii) F(ab')2 fragments; (iii) Fd fragments; (iv) Fv fragments; (v) single-chain Fv (scFv) molecules; (vi) dAb fragments; and (vii) minimal recognition units consisting of the amino acid residues that mimic the hypervariable region of an antibody (e.g., an isolated complementarity determining region (CDR)). Other engineered molecules, such as domain-specific antibodies, single domain antibodies, domain-deleted antibodies, chimeric antibodies, CDR-grafted antibodies, diabodies, triabodies, tetrabodies, minibodies, nanobodies (e.g. monovalent nanobodies, bivalent nanobodies, etc.), small modular immunopharmaceuticals (SMIPs), and shark variable IgNAR domains, are also encompassed within the expression "antigen-binding fragment," as used herein. An antigen-binding fragment of an antibody will typically comprise at least one variable domain. The variable domain may be of any size or amino acid composition and will generally comprise at least one CDR which is adjacent to or in frame with one or more framework sequences. In antigen-binding fragments having a VH domain associated with a VL domain, the VH and VL domains may be situated relative to one another in any suitable arrangement. For example, the variable region may be dimeric and contain VH-VH, VH-VL or VL-VL dimers. Alternatively, the antigen-binding fragment of an antibody may contain a monomeric VH or VL domain.

[0150] Another well-known affinity pair applicable in the bio transistor systems of the present disclosure is a receptor-ligand pair. "Receptors" are chemical structures, composed of protein, that receive and transduce signals that may be integrated into biological systems. These signals are typically chemical messengers which bind to a receptor and produce physiological responses such as change in the electrical activity of a cell. Receptor proteins can be classified by their location. Cell surface receptors also known as transmembrane receptors, include ligand-gated ion channels, G protein-coupled receptors, and enzyme-linked hormone receptors. Intracellular receptors are those found inside the cell and include cytoplasmic receptors and nuclear receptors. A molecule that binds to a receptor is called a "ligand" and can be a protein, peptide , or another small molecule.

[0151] In yet some further embodiments, an affinity pair applicable for the present disclosure is an Enzyme-substrate pair. Enzymes differ from most other catalysts by being much more specific. An enzyme's specificity comes from its unique three-dimensional structure. Enzymes are usually much larger than their substrates. Sizes range from just 62 amino acid residues, for the monomer of 4-oxalocrotonate tautomerase, to over 2,500 residues in the animal fatty acid synthase. Only a small portion of their structure (around 2-4 amino acids) is directly involved in catalysis: the catalytic site. This catalytic site is located next to one or more binding sites where residues orient the substrates. The catalytic site and binding site together compose the enzyme's active site. The remaining majority of the enzyme structure serves to maintain the precise orientation and dynamics of the active site. In some enzymes, no amino acids are directly involved in catalysis; instead, the enzyme contains sites to bind and orient catalytic cofactors. Enzyme structures may also contain allosteric sites where the binding of a small molecule causes a conformational change that increases or decreases activity. Enzymes must bind their substrates before they can catalyze any chemical reaction. Specificity is achieved by binding pockets with complementary shape, charge and hydrophilic / hydrophobic characteristics to the substrates. Enzymes can therefore distinguish between very similar substrate molecules to be chemoselective, regioselective and stereospecific. The enzyme component of the enzyme-substrate affinity pair can be a whole enzyme, and / or any fragments thereof, such as the enzyme's active site or the enzyme's binding site as long as it's binding capability is maintained.

[0152] Still further, in some embodiments, the affinity pair may be aptamer-target affinity pair. "Aptamers" are short sequences of artificial DNA, RNA, XNA, or peptide that bind a specific target molecule, or family of target molecules. They exhibit a range of affinities (KD in the pM to pM range), and are sometimes classified as "chemical antibodies" or "antibody mimics". The nucleic acid-based structure of aptamers, which are mostly oligonucleotides, is very different from the amino acid-based structure of antibodies, which are proteins. Aptamers are usually obtained by selection from a large random sequence library, using methods well known in the art, such as SELEX and / or Molinex. In SELEX, the best aptamers from a starting DNA library made of about a quadrillion different randomly generated pieces of DNA or RNA are repeatedly selects. After SELEX, the chemistry of the aptamers might be mutated or changed and another selection can be done, or a rational design processes might be used to engineer improvements. Aptamers are optimized to achieve a variety of beneficial features. The most important feature is specific and sensitive binding to the chosen target. Some aptamers are engineered to fit into a biosensor or in a test of a biological sample. In various embodiments, aptamers may include single-stranded, partially single-stranded, partially double-stranded or double-stranded nucleic acid sequences; sequences comprising nucleotides, ribonucleotides, deoxyribonucleotides, nucleotide analogs, modified nucleotides and nucleotides comprising backbone modifications, branch points and nonnucleotide residues, groups or bridges; synthetic RNA, DNA and chimeric nucleotides, hybrids, duplexes, heteroduplexes; and any ribonucleotide, deoxyribonucleotide or chimeric counterpart thereof and / or corresponding complementary sequence. In certain specific embodiments, aptamers used by the invention are composed of deoxyribonucleotides.

[0153] In some embodiments, the aptamer that may be applicable herein may optionally comprise a spacer between the nucleic acid sequence and the reactive group. The spacer may be an alkyl chain such as (CH2)6 / 12, namely comprising six to twelve carbon atoms. Aptamer targets can include small molecules and heavy metal ions, larger ligands such as proteins, and even whole cells.

[0154] As indicated above, the affinity molecule, and / or the target molecule and / or the candidate compound disclosed herein after in connection with the screening methods, may be amino acid-based, a nucleic acid-based, a small molecule-based, a carbohydrate-based and / or a lipid-based molecules. The term "-based" as used herein refers to the at least one affinity moiety or molecule, and / or to the target molecule, which is composed of the building block specified prior to "-based". For example, amino acid-based affinity molecule / s and / or target molecule / s, are affinity molecule / s and / or target molecule / s, which are composed of amino acids, such as proteins, peptides, glycoproteins, lipoproteins, etc. Still further, nucleic acidbased affinity molecules and / or target molecule / s, are affinity molecule / s and / or target molecule / s, which are composed of nucleic acids such as polynucleotides, aptamers, etc. Small molecule-based affinity molecule / s and / or target molecule / s are affinity molecule / s and / or target molecule / s, which are composed of small molecules, which are low molecular weight organic compound, having a molecular weight lower than 900 Daltons. Carbohydrate-based affinity molecules are affinity molecules which are composed of carbohydrates such as monosaccharides, disaccharides, oligosaccharides, and polysaccharide as well as proteoglycans, glycoproteins, etc. lipid-based molecules are affinity molecule / s and / or target molecule / s, which are composed of lipids such as fats, waxes, sterols, fat-soluble vitamins (such as vitamins A, D, E and K), monoglycerides, diglycerides, phospholipids, proteolipids, and others.

[0155] As indicated above, in some embodiments the at least one affinity moiety and / or the at least one target molecule of the disclosed bio transistor systems and methods, may be, or may comprise an amino acid-based molecule. An "amino acid-based molecule", as used herein refers to a molecule that is primarily composed of amino acids or derivatives of amino acids. Amino acids are organic compounds that contain both an amino group (-NH2) and a carboxyl group (-COOH), along with a unique side chain specific to each amino acid. Amino-acid based molecules in accordance with the present disclosure encompass various structures including peptides, that are short chains of amino acids linked by peptide bonds (typically consist of 2 to 50 amino acids), polypeptides, that are intermediate-length chains of amino acids that can fold into specific structures and may function independently or as part of a larger protein complex and proteins, that are composed of long chains of amino acids, typically consisting of 50 or more amino acids, and fold into specific three- dimensional structures that determine their function in biological processes. An example for an affinity moiety-target pair composed of a protein include, but is not limited to the antibody-antigen, receptor-ligand and peptide aptamers and targets thereof. Still further, it should be understood that amino-acid-based molecule as used in the present disclosure further encompasses amino acid derivatives, specifically, molecules derived from amino acids through chemical modifications.

[0156] In yet some further embodiments, the at least one affinity moiety and / or the at least one target molecule of the disclosed bio transistor systems and methods, may be, or may comprise a nucleic acid molecule. The term “nucleic acid”, “nucleic acid sequence”, or "polynucleotide" and “nucleic acid molecule” refers to polymers of nucleotides, and includes but is not limited to deoxyribonucleic acid (DNA), ribonucleic acid (RNA), DNA / RNA hybrids including polynucleotide chains of regularly and / or irregularly alternating deoxyribosyl moieties and ribosyl moieties (i.e., wherein alternate nucleotide units have an —OH, then and — H, then an —OH, then an — H, and so on at the 2' position of a sugar moiety), and modifications of these kinds of polynucleotides, wherein the attachment of various entities or moieties to the nucleotide units at any position are included. The terms should also be understood to include, as equivalents, analogs of either RNA or DNA made from nucleotide analogs, and, as applicable to the embodiment being described, single-stranded (such as sense or antisense) and double-stranded polynucleotides. Preparation of nucleic acids is well known in the art. It should be appreciated that the invention may further refer to polyribonucleotide. The term "polyribonucleotide" refers to a polynucleotide comprising two or more modified or unmodified ribonucleotides and / or their analogs. The term "polyribonucleotide" is used interchangeably with the term "oligoribonucleotide”.

[0157] A small molecule in the context of the present disclosure refers to a low molecular weight organic compound, having a molecular weight lower than 900 Daltons, and in some embodiments less than about 2 kilodaltons (kDa) in mass. In some embodiments, the small molecule is less than about 1.5 kDa, or less than about 1 kDa. In some embodiments, the small molecule is less than about 900 daltons (Da), 800 Da 600 Da, 500 Da, 400 Da, 300 Da, 200 Da, or 100 Da. Often, a small molecule has a mass of at least 50 Da. In some embodiments, a small molecule is non-polymeric. In some embodiments, a small molecule is not an amino acid. In some embodiments, a small molecule is not a nucleotide. In some embodiments, a small molecule is not a saccharide. In some embodiments, a small molecule contains multiple carbon-carbon bonds and can comprise one or more heteroatoms and / or one or more functional groups important for structural interaction with proteins (e.g., hydrogen bonding), e.g., an amine, carbonyl, hydroxyl, or carboxyl group, and in some embodiments at least two functional groups. Small molecules often comprise one or more cyclic carbon or heterocyclic structures and / or aromatic or polyaromatic structures, optionally substituted with one or more of the above functional groups.

[0158] In accordance with the present disclosure, when referring to a small molecule it includes also crystalline and amorphous forms of those compounds, including, for example, polymorphs, pseudopolymorphs, solvates, hydrates, unsolvated polymorphs (including anhydrates), conformational polymorphs, and amorphous forms of the compounds, as well as mixtures thereof. "Crystalline form" or "polymorph," as used herein include all crystalline and amorphous forms of a small molecule, including, for example, polymorphs, pseudopolymorphs, solvates, hydrates, unsolvated polymorphs (including anhydrates), conformational polymorphs, and amorphous forms, as well as mixtures thereof, unless a particular crystalline or amorphous form is referred to.

[0159] In accordance with the present disclosure, the term "small molecule" may include pharmaceutically acceptable forms of the recited compounds, including chelates, non- covalent complexes, prodrugs, and mixtures thereof. Further and in accordance with the preset disclosure, the term "small molecule" includes also pharmaceutically acceptable forms of a particular molecule and as such the term small molecule also encompasses pharmaceutically acceptable salts.

[0160] In yet some further embodiments, the at least one affinity moiety and / or the at least one target molecule of the disclosed bio transistor systems and methods, may be, or may comprise a carbohydrate-based molecule. A carbohydrate-based molecule, as used herein, is a chemical compound that primarily consists of carbohydrate components, which are organic molecules made up of carbon (C), hydrogen (H), and oxygen (0) atoms, usually with the hydrogen and oxygen atoms in a ratio of 2: 1, as in water. Carbohydrates are one of the four main classes of biomolecules and can be simple sugars (monosaccharides like glucose and fructose), double sugars (disaccharides like sucrose and lactose), or complex carbohydrates (polysaccharides like starch, cellulose, and glycogen).

[0161] Still further, in some embodiments, the at least one affinity moiety and / or the at least one target molecule of the disclosed bio transistor systems and methods, may be, or may comprise a lipid-based molecule.

[0162] A lipid-based molecule, as used herein, is a chemical compound primarily composed of lipids, which are a diverse group of hydrophobic or amphipathic organic molecules. Lipids are insoluble in water but soluble in nonpolar solvents. It should be understood that the present disclosure encompasses any affinity moiety and / or target molecule composed of or comprising a lipid-based molecule, of any type, for example, triglycerides, that consist of three fatty acids attached to a glycerol backbone, phospholipids, that have two fatty acids and a phosphate group attached to glycerol, steroids, that have a structure based on a carbon skeleton with four fused rings (e.g., Cholesterol), glycolipids, that contain a carbohydrate group attached to a lipid, and fatty Acids, that are carboxylic acids with a long hydrocarbon chain, which can be saturated (no double bonds) or unsaturated (one or more double bonds).

[0163] In some embodiments of the present disclosure, the at least one sample is a biological sample and / or an environmental sample.

[0164] A "sample" as used herein may be any biological and / or environmental sample. A "biological sample" is a biological material collected from living and / or deceased organisms and / or living and / or dried out plants or their environment. There are many different types of biological samples, including biofluids, tissue, cells and other. Biological samples can be obtained from the body via a number of different methods such as excretion (e.g. urine), secretion (e.g. breast milk) or extraction (e.g. blood). Non limiting examples of biological samples include blood, bile, bone marrow aspirate, breast milk / mammary gland milk, Cerebral Spinal Fluid (CSF), feces, plasma, saliva, semen, serum, sputum, sweat, as well as oral, nasal and vaginal fluids (typically collected using a swab), and synovial fluid, tears and urine. Biological samples include also cells such as epithelial cells, fibroblasts, immune cells (e.g. T cell, B cells, NK cells etc.), peripheral blood mononuclear cells (PBMCs), red blood cells (RBCs), buffy coat, bone marrow mononuclear cells, dissociated tumor cells, mesenchymal stem cells, myoblasts, hepatocytes, etc as well as tissues. Cell samples are collected and isolated from either tissue samples, biofluid samples, or biopsy samples. Depending on the cell type, specific cell isolation protocols are required in order to obtain the purified cell sample.

[0165] Biological material collected from plants may be for example any sample derived from the leaf, roots, stems, nectar, seeds and / or fruits of any plant.

[0166] "Environmental sample" refers to any sample derived from any media or material in the environment. The most common environmental samples are air, water, soil, biological materials, and wastes (liquids, solids or sludges) such as sewage. Environmental sampling is typically performed to determine the presence of Hazardous Materials in any media or material, including indoor or outdoor air, soil, groundwater, surface water or building materials. Still further, I some embodiments, a sample may comprise any food product or any byproduct derived from any industrial activity or facility.

[0167] Samples also includes material that is extracted and / or prepared from any of the above biological and / or environmental samples using standard methods such as RNA, DNA, protein lysates, cell-free DNA (cfDNA), etc.

[0168] In some other embodiment, the sample is a biological sample. Of particular relevance in accordance with some particular and non-limiting embodiments of the present disclosure, are biological samples derived from body fluids. More specifically, milk samples of a mammalian organism, blood samples and / or plasma samples of any mammalian organism, at any developmental or physiologic stage or state. For example, at any embryonic or neonatal stage, or any Reproductive Stages, e.g., pregnancy, lactation, or on-reproductive, at any age or medical condition.

[0169] In some embodiments, the eukaryotic organism is at least one organism of the biological kingdom Animalia or of the biological kingdom Plantae. In some additional embodiments, the biological sample is derived from a eukaryotic organism. In some embodiments, the methods and systems of the present disclosure may be applicable for any organism of the biological kingdom Animalia. In more specific embodiments, such organism may be any unicellular or multicellular invertebrate or vertebrate organism. More specifically, invertebrates, may be organisms of the Phylum Porifera - Sponges, the Phylum Cnidaria - Jellyfish, hydras, sea anemones, corals, the Phylum Ctenophora - Comb jellies, the Phylum Platyhelminthes - Flatworms, the Phylum Mollusca - Molluscs, the Phylum Arthropoda - Arthropods, the Phylum Annelida - Segmented worms like earthworm and the Phylum Echinodermata - Echinoderms. Still further, in some embodiments, the methods of the present disclosure may be applicable for any vertebrate organism, specifically, any organism derived from any of the vertebrates' groups that include Fish, Amphibians, Reptiles, Birds and Mammals (e.g., Marsupials, Primates, Rodents and Cetaceans). In some particular embodiments, the methods of the present disclosure may be applicable for a mammal (specifically, at least one of a human, Cattle, rodent, domestic pig (swine, hog), sheep, horse, goat, alpaca, lama and Camels).

[0170] More specifically, in some embodiments, as indicated herein, the methods of the present disclosure may be applicable for a vertebrate organism. Vertebrates comprise all species of animals within the subphylum Vertebrata (chordates with backbones). The animals of the vertebrates group include Fish, Amphibians, Reptiles, Birds and Mammals (e.g., Marsupials, Primates, Rodents and Cetaceans).

[0171] Vertebrates represent the overwhelming majority of the phylum Chordata, with currently about 66,000 species described. Vertebrates include the jawless fish and the jawed vertebrates, which include the cartilaginous fish (sharks, rays, and ratfish) and the bony fish.

[0172] Still further, in some embodiments, the subject of the of the preset disclosure may be any one of a human or non-human mammal, an avian, an insect, a fish, an amphibian, a reptile, a crustacean, a crab, a lobster, a snail, a clam, an octopus, a starfish, a sea-urchin, jellyfish.! and worms.

[0173] In more specific embodiments, the subject of the present disclosure may be a mammal. In yet some further embodiments, such mammalian organisms may include any member of the mammalian nineteen orders, specifically, Order Artiodactyla (even-toed hoofed animals), Order Carnivora (meat-eaters), Order Cetacea (whales and purpoises), Order Chiroptera (bats), Order Dermoptera (colugos or flying lemurs), Order Edentata (toothless mammals), Order Hyracoidae (hyraxes, dassies), Order Insectivora (insect- eaters), Order Lagomorpha (pikas, hares, and rabbits), Order Marsupialia (pouched animals), Order Monotremata (egg-laying mammals), Order Perissodactyla (odd-toed hoofed animals), Order Pholidata, Order Pinnipedia (seals and walruses), Order Primates (primates), Order Proboscidea (elephants), Order Rodentia (gnawing mammals), Order Sirenia (dugongs and manatees), Order Tubulidentata (aardvarks).

[0174] In yet some further embodiments, the present disclosure may be applicable for any organism of the order primates. More specifically, primates are divided into two distinct suborders, the first is the strepsirrhines that includes lemurs, galagos, and lorisids. The second is haplorhines - that includes tarsier, monkey, and ape clades, the last of these including humans. In yet some further embodiments, the present disclosure may be applicable for any organism of the subfamily Homininae, that includes the hylobatidae (gibbons) and the hominidae that includes ponqunae (orangutans) and homininae [gorillini (gorilla) and hominini ((panina(chimpanzees) and hominina (humans))]. Thus, in some embodiments, a subject as disclosed herein relates to a human subject. In some embodiments, the human subject may be of any sex, ethnic group, age, developmental stage, or physical or mental condition.

[0175] In some specific embodiment, the bio transistor systems and methods of the present disclosure may be applicable for a mammal that may be at least one of a Cattle, domestic pig (swine, hog), sheep, horse, goat, alpaca, lama and Camels.

[0176] More specifically, the subject the present disclosure as well as the methods disclosed herein above offer great economic advantage for any industrial or agricultural use of animals, specifically, livestock. Thus, in some specific embodiments, the present disclosure may be applicable for mammalian livestock, specifically those used for meat, milk and leather industries. Livestock are domesticated animals raised in an agricultural setting to produce labor and commodities such as meat, eggs, milk, fur, leather, and wool. The term includes but is not limited to Cattle, sheep, domestic pig (swine, hog), horse, goat, alpaca, lama and Camels. Of particular interest are cattle applicable in the meat and milk industry, as well as in the leather industry. More specifically, in certain embodiments, the subject of the present disclosure may be Cattle, colloquially cows, that are the most common type of large, domesticated ungulates, that belong to the Bovidae family.

[0177] In yet some further embodiments, the organism applicable in the methods of the present disclosure, may be avian organisms. In yet some further specific embodiments, the present disclosure may be suitable for birds. More specifically, domesticated and undomesticated birds are also suitable organisms for the present disclosure.

[0178] Still further, in some embodiments the organism of the biological kingdom Plantae may be a dioecious plant, specifically, a plant presenting biparental reproduction. In some specific embodiments, the plant may be of the family Cannabaceae, specifically, any one of Cannabis (hemp, marijuana) and Humulus (hops). In more specific embodiments, the plant of the family Cannabaceae may be Cannabis (hemp, marijuana). In yet some further embodiments, the plant of the family Cannabaceae may be Humulus (hops).

[0179] In some embodiments, any plants are applicable in the present disclosure, for example, any model plants such as, Arabidopsis, Tobacco, Solanum licopersicum, Solanum tuberosum. In yet some further embodiments, Canola, Cereals (Corn wheat, Barley), rice, sugarcane, Beet, Cotton, Banana, Cassava, sweet potato, lentils, chickpea, peas, Soy, nuts, peanuts, Lemna, Apple, may be applicable in the present disclosure.

[0180] A non-comprehensive list of useful annual and perennial, domesticated or wild, monocotyledonous or dicotyledonous land plant or Algae - (i.e unicellular or multicellular algae including diatoms, microalgae, ulva, nori, gracilaria), applicable in accordance with the present disclosure may include but are not limited to crops, ornamentals, herbs (i.e., labiacea such as sage, basil and mint, or lemon grass, chives), grasses (i.e., lawn and biofuel grasses and animal feed grasses), cereals (i.e., rice, wheat, rye, oats, corn), legumes (i.e. soy, beans, lentils, chick peas, peas, peanuts), leafy vegetables (i.e. kale, bok-choi, cress, lettuce, spinach, cabbage), Amaranthacea (i.e. sugar beet, beet, quinoa, spinach), Compositea (i.e. sunflower, lettuce, aster), Malvaceae (i.e. cotton, cacao, okra, hibiscus), cucurbits (i.e., cucumber, squash, melon, watermelon), Solanaceous species (i.e tobacco, potato, tomato, petunia and pepper), Umbellifera (i.e. carrot, celery, dill, parsley, cumin), Crucifera (i.e., oilseed rape, mustard, brassicas, cauliflower, radish), Sesame, the monocot Aspargales (i.e. onion, garlic, leek, asparagus, vanilla, lilies, tulips, narcissus), Myrtacea (i.e., Eucalyptus, pomegranate, guava), Subtropical fruit trees (i.e. Avocado, Mango, Litchi, papaya), Citrus (i.e. orange, lemon, grapefruit), Rosacea (i.e. apple, cherry, plum, almond, roses), berry-plants (i.e. grapes, mulberries, blueberries, raspberry, strawberry), nut trees (i.e. macademia, hazelnut, pecan, walnut, chestnuts, brazil nut, cashew), banana and plantain, palms (i.e., oil-palm, coconut and dates), evergreen, coniferous or deciduous trees, woody species.

[0181] In some further embodiments, the eukaryotic organism of the biological kingdom Animalia is a mammalian subject.

[0182] In some additional embodiments, the mammalian subject is a mammal of the Bovinae family.

[0183] In some embodiments, the biological sample is mammary gland milk. Bovine milk is a complex biological fluid produced by the mammary glands of cows. The milk forms an emulsion of fat globules within a water-based fluid that contains dissolved carbohydrates, proteins, minerals, and vitamins, where approximately 87-88% of milk's total volume is water. Main milk proteins include casein, and whey proteins (e.g., beta-lactoglobulin, alpha-lactalbumin, serum albumin, and immunoglobulins), and milk fat includes phospholipids, sterols, and free fatty acids.

[0184] In some embodiments of the present disclosure, the target molecule indicates the existence of at least one pathogenic agent in the sample.

[0185] It should be understood that the target molecule may be associated directly or indirectly with the pathogenic agent, and thus reflects the existence and / or quantity of the agent.

[0186] In some embodiments of the present disclosure, the least one pathogenic agent is at least one of bacteria, archaea, virus, fungi, algae, parasite, protists and worms.

[0187] In some other embodiments, the at least one pathogenic agent causes and / or is associated with at least one infectious disease.

[0188] In some further embodiments, the at least one infectious disease is bovine mastitis (BM). Bovine mastitis is a significant inflammatory condition of the cow's mammary gland, caused by microbial infection and characterized by economic losses in the dairy industry due to decreased milk production, altered milk composition, and increased veterinary costs. Bovine mastitis involves the complex interaction between the invading pathogens, the cow’s immune response, and the mammary gland environment. The disease process includes invasion and inflammatory response, followed by changes in the milk composition. More specifically, pathogens enter the mammary gland through the teat canal, often facilitated by teat injuries or unhygienic milking practices. Inflammatory response, specifically, the immune system responds by recruiting neutrophils, macrophages, and lymphocytes to the site of infection, leading to inflammation and tissue damage. (Infected glands show increased somatic cell count (SCC) and alterations in milk composition, including decreased lactose and casein levels, and increased levels of sodium, chloride, and immunoglobulins. It should be noted that the present disclosure relates to bio-transistors applicable for the detection of mastitis at any stage and severity of the disease, particularly at early stage of the disease.

[0189] In some embodiments of the present disclosure, the at least one pathogenic agent is at least one of bacteria. Bacteria are microscopic, single-celled living organisms. The singular of bacteria is bacterium. Bacteria include Gram positive, Gram negative and Gram variable bacteria and intracellular bacteria. Examples of bacteria contemplated herein include the phylum Bacteroidota, more specifically the genus Bacteroidaceae and Phocaeicola.

[0190] Particular species include Bacteroides fragilis, Bacteroides thetaiotaomicron, Phocaeicola dorei, Akkermansia muciniphila , Bacteroides uniformis, Bacteroides ovatus, Bacteroides stercoris, Bacteroides cellulosilyticus, Bacteroides caccae, Bacteroides eggerthii, , Bacteroides intestinalis, Bacteroides clarus, Bacteroides fragilis A, Bacteroides finegoldii, Bacteroides faecis, Bacteroides massiliensis, Bacteroides togonis, Bacteroides nordii, Bacteroides salyersiae, Bacteroides intestinalis A, Bacteroides ndongoniae, Bacteroides sp003545565, Bacteroides sp905207245, Bacteroides bouchesdiirhonensis, Bacteroides fluxus, Bacteroides gallinarum, Bacteroides stercorirosoris, Bacteroides graminisolvens, Bacteroides pyogenes, Bacteroides oleiciplenus, Bacteroides sp002491635, Bacteroides cutis, Bacteroides sp900547205, Bacteroides acidifaciens, Bacteroides sp905197435, Bacteroides neonati, Bacteroides sp014385165 and / or Parabacteroides distasonis.

[0191] In some further embodiments, the bacteria may be at least one of Staphylococcus aureus, Streptococci uberis, Streptococci dysgalactiae, Streptococci agalactiae, and Escherichia coli (E. coli) or any combinations thereof. In some embodiments of the present disclosure, the affinity moiety is an amino acid-based molecule. The affinity moiety comprises, or is derived from, at least one antibody and the target molecule may comprise, or is derived from, at least one antigen.

[0192] In some further embodiments, the target antigen is N-acetyl-beta-D-glucosaminidase (NAGase)), and the affinity moiety comprises at least one antibody that specifically recognizes and binds NAGase (an anti- NAGase antibody).

[0193] N-acetyl-beta-D-glucosaminidase (NAGase), as used herein, is an enzyme that plays a key role in the breakdown of glycoproteins and glycolipids. It is found in various tissues throughout the body, particularly in the lysosomes of cells. NAGase catalyzes the hydrolysis of N-acetyl-D-glucosamine residues in glycoproteins and glycolipids, which is an essential step in the degradation and recycling of these molecules within cells.

[0194] In some embodiments, NAGase, as used herein refers to the human NAGase, that comprises the amino acid sequence as denoted by UniProt accession number 060502. In yet some further embodiments, the human NAGase as used herein comprises the amino acid sequence as denoted by SEQ ID NO: 1, or any homologs or variants thereof.

[0195] In yet some further embodiments, the Nagase as disclosed herein refers to the bovine Nagase. Accordingly, the bio transistor systems of the present disclosure comprise affinity moieties composed of antibodies specific for bovine NAGase. In these particular embodiments, the disclosed bio transistor may be applicable for detecting and diagnosing bovine mastitis as disclosed herein after. Still further, elevated levels of NAGase in the urine are often used as a marker for renal tubular damage. It is therefore understood that the bio-transistor system of the present disclosure may be also applicable for detecting and monitoring early kidney damage, particularly in conditions like diabetic nephropathy, hypertensive nephropathy, and drug-induced nephrotoxicity. Still further, in some embodiments, since deficiencies or mutations in enzymes similar to NAGase are implicated in lysosomal storage diseases, reduced levels of such target molecule may be also indicative of lysosomal storage disorders, in human subjects. According to such embodiments, the bio transistors comprise affinity moiety specific for human Nagase, for example, antihuman Nagase antibodies, or any fragments thereof. In yet some further embodiments, the disclosed bio-transistor system may be applicable for a sample derived from a mammal of the Hominidae family. More specifically, the Hominidae family, commonly known as the great apes or hominids, includes humans, chimpanzees, bonobos, gorillas, and orangutans. More specifically, in some embodiments the disclosed bio-transistor system may be applicable for samples obtained from a human subject.

[0196] In yet some further embodiments, the bio-transistor system of the present disclosure may be applicable for blood and / or serum and / or plasma sample / s. A blood sample, as used herein, encompasses blood drawn from a vein (venous blood), artery (arterial blood), or capillary (finger prick). A blood sample typically contains erythrocytes, leukocytes, platelets and electrolytes proteins hormones, glucose, metabolic waste products and nutrients, and is also composed of plasma (about 55% of its volume. It is composed mainly of water, but also contains proteins, glucose, hormones, electrolytes, and waste products) and serum.

[0197] A serum sample, as used herein, relates to blood plasma without clotting factors, and is obtained after the blood has clotted and the clot is removed.

[0198] In some embodiments, the target molecule detected and / or quantified by the disclosed biotransistor system, may be a molecule produced by the mammalian subject, specifically, a human subject, either normally (healthy) or abnormally. As used herein, naturally produced is meant that the specific product, for example, the specific protein product is naturally produced by cells, tissues and organs of the diagnosed subject. It should be appreciated that the term "naturally produced" as used herein, encompasses both, produced normally, in a healthy subject or alternatively produced abnormally in a diseased subject. Abnormal production relates to the amount and / or functionality and / or structure of the specific natural product used as a target molecule for the disclosed bio-transistors. In yet some further embodiments, a level of the target molecule that is below or above a standard level is indicative of a pathologic disorder in the subject tested by the disclosed bio-transistor system. In some embodiments, such pathologic disorder may be an immune related disorder. More specifically, such immune-related disorder may be at least one of a proliferative disorder, an inflammatory disease, an autoimmune disorder and / or a metabolic disorder.

[0199] In some specific and non-limiting embodiments, the bio-transistor system of the present disclosure is specifically designed for detecting and / or quantifying a target molecule that is the Alpha-fetoprotein (AFP). Accordingly, in some embodiments, the at least one affinity moiety carried by the active region of the bio-transistor system of the present disclosure comprises, is, or is derived from, at least one antibody specific for AFP.

[0200] Thus, in some embodiments, the detection and / or quantification of the AFP levels by the disclosed bio-transistor system, is of a diagnostic value. More specifically, in some embodiments, at least one of: (i) a level of the target AFP determined by the bio-transistor system of the present disclosure, that is above a standard level, is indicative of at least one of: a liver disease, a germ cell tumor, a pregnancy-related condition and at least one malignancy. Alternatively (ii), a level of the target AFP determined by the disclosed biotransistor systems, that is below a standard level, is indicative of at least one genetic disorder associated with chromosomal abnormalities. In some specific embodiments, such chromosomal abnormalities comprise at least one trisomy. In more specific embodiments, low levels of AFP, as compared to a standard level, is indicative of a trisomy 21, for example, Down Syndrome (DS), and / or a trisomy 18, for example, Edward's Syndrome.

[0201] Standard AFP levels for non-pregnant adults are less than 10 ng / mL, for pregnant women levels can be much higher and vary depending on the stage of pregnancy. The highest sensitivity of 25.98 readout per dec, for a dynamic range of 1.05 pM-10.5 nM with LOD of 10.5 aM achieved. Thus, in some embodiments, the disclosed bio transistor systems and bio transistor systems and methods provide a sensitive and specific tool for detecting AFP in a sample, specifically a biological sample. In some embodiments, the disclosed bio transistor systems and methods detect AFP in a serum sample (e.g., dilluted 1:100), in an amount of about 100 fM to about 1 nM.

[0202] Alpha-fetoprotein (AFP) is a glycoprotein produced primarily by the fetal liver, yolk sac, and gastrointestinal tract. It is a major plasma protein in the developing fetus and plays a role similar to that of serum albumin in adults. AFP is also produced in certain pathological conditions in adults, making it a valuable biomarker in clinical diagnostics. AFP is a singlechain glycoprotein composed of approximately 590 amino acids. The protein has carbohydrate moieties attached to specific asparagine residues, contributing to its stability and solubility. AFP contains three homologous domains, each contributing to its overall function and binding properties. These domains are involved in the transport and binding of various ligands, such as fatty acids and bilirubin. AFP binds and transports various molecules, including fatty acids, bilirubin, and steroids, and is thus essential for fetal development.

[0203] In some embodiments, AFP, as used herein refers to the human AFP, that comprises the amino acid sequence as denoted by UniProt accession number P02771. In yet some further embodiments, the human AFP as used herein comprises the amino acid sequence as denoted by SEQ ID NO: 2, or any homologs or variants thereof.

[0204] In some specific and non-limiting embodiments, the bio-transistor system of the present disclosure is specifically designed for detecting and / or quantifying a target molecule that is the Ferritin. Accordingly, in some embodiments, the at least one affinity moiety carried by the active region of the bio-transistor system of the present disclosure comprises, is, or is derived from, at least one antibody specific for Ferritin.

[0205] Thus, in some embodiments, the detection and / or quantification of the Ferritin levels by the disclosed bio-transistor system, is of a diagnostic value for detection of disorders associated with abnormal Ferritin levels. More specifically, in some embodiments, at least one of: (i) a level of the target Ferritin determined by the bio-transistor system of the present disclosure, that is above a standard level, is indicative of at least one of: Hemochromatosis, A Chronic Inflammatory Condition, A Liver Disease, a chronic infectious disease, a Malignancy, and Hemolytic Anemia. Alternatively (ii), a level of the target Ferritin determined by the disclosed bio-transistor systems, that is below a standard level, is indicative of at least one of: Iron Deficiency Anemia, Chronic Blood Loss, and Malabsorption Syndrome.

[0206] The standard Ferritin levels are 10 - 340 ng / ml. An excellent sensing performance is recorded for all selected VGS values of the side-gate sweep with an LOD of 10 fg / ml, dynamic range of 10 orders of magnitude in ferritin concentration and 0.99 linearity for s i = -1.5 V. In some embodiments, the disclosed bio transistor systems and methods provide a sensitive and specific tool for detecting Ferritin in a sample, specifically a biological sample. In some embodiments, the disclosed bio transistor systems and methods detect Ferritin in a plasma sample (e.g., dilluted 1: 100), in an amount of about lOfg / ml to about 10 ug / ml.

[0207] Ferritin, as used herein, is a ubiquitous intracellular protein that plays a critical role in iron storage and homeostasis. Ferritin is a globular protein complex consisting of 24 subunits, forming a hollow shell that stores iron in a soluble, non-toxic form. These subunits are of two types: heavy (H) chains and light (L) chains. The heavy (H) chains have ferroxidase activity, which catalyzes the conversion of Fe2+(ferrous iron) to Fe3+(ferric iron), facilitating iron storage within the ferritin molecule. The light (L) chains are involved in iron nucleation and mineralization, helping to stabilize the iron core. The specific ratio of H to L chains varies depending on the tissue type. The central cavity of ferritin can store up to 4,500 iron atoms in the form of a ferric oxyhydroxide mineral core. The iron is stored in a soluble, non-toxic form. The ability of ferritin to store and release iron in a controlled manner is essential for numerous physiological processes, including oxygen transport, DNA synthesis, and cellular respiration. Aberrations in ferritin levels are indicative of various pathological conditions, making it a valuable target for clinical diagnostics.

[0208] In some embodiments, Ferritin, as used herein refers to the human Ferritin, that comprises the amino acid sequence as denoted by UniProt accession number P02794-1. In yet some further embodiments, the human Ferritin as used herein comprises the amino acid sequence as denoted by SEQ ID NO: 3, or any homologs or variants thereof.

[0209] In some specific and non-limiting embodiments, the bio-transistor system of the present disclosure is specifically designed for detecting and / or quantifying a target molecule that is the C-reactive protein (CRP). Accordingly, in some embodiments, the at least one affinity moiety carried by the active region of the bio-transistor system of the present disclosure comprises, is, or is derived from, at least one antibody specific for CRP.

[0210] Thus, in some embodiments, the detection and / or quantification of the CRP levels by the disclosed bio-transistor system, is of a diagnostic value for any disorder that is reflected by changes in the level of CRP. More specifically, in some embodiments, a level of the target CRP determined by the bio-transistor system of the present disclosure, that is above a standard level, is indicative of at least one of an infectious disorder, a chronic inflammatory disease, a cardiovascular disease, autoimmune diseases, a cancer, and at least one metabolic disorder.

[0211] C-reactive protein (CRP), as used herein, is a pentameric protein found in blood plasma, whose levels rise in response to inflammation. It is an acute-phase reactant, produced predominantly by the liver, and plays a crucial role in the immune response. CRP consists of five identical, non-covalently bound subunits arranged in a disc-like configuration, forming a cyclic pentamer. Each subunit has a molecular weight of approximately 23 kDa, resulting in an overall molecular weight of around 115 kDa for the entire pentamer. CRP has specific binding sites for phosphocholine, which is found on the surface of dead or dying cells and certain bacteria.

[0212] In some embodiments, the disclosed bio transistor systems and methods provide a sensitive and specific tool for detecting CRP in a sample, specifically a biological sample such as blood. In some embodiments, the disclosed bio transistor systems and methods detect CRP in a blood sample in an amount of about Ipg / ml to about 1 ug / ml.

[0213] In some embodiments, CRP, as used herein refers to the human CRP, that comprises the amino acid sequence as denoted by UniProt accession number P02741. In yet some further embodiments, the human CRP as used herein comprises the amino acid sequence as denoted by SEQ ID NO: 4, or any homologs or variants thereof.

[0214] In some embodiments of the present disclosure, the at least one sample further comprises at least one candidate compound that modulates the interaction between the affinity moiety and the target molecule. The candidate compound comprises at least one of: an amino acidbased molecule, a nucleic acid-based molecule, a small molecule, a carbohydrate-based molecule, a lipid-based molecule, or any combination thereof.

[0215] As used herein, the term "modulating the interaction" when referred to a candidate compound that may change, for example, reduce, prevent, inhibit the interaction and / or binding of the affinity moiety to the specific target molecule includes altering or modifying binding / recognition by increasing or upregulating binding, or alternatively, by decreasing or downregulating binding of the binding par (affinity moiety and the target recognized by this affinity moiety).

[0216] More specifically, the terms "inhibition", "moderation", “reduction” or "attenuation" as referred to herein, relate to the retardation, restraining or reduction of the binding, attachment and / or stability of at least one of the target molecules of the present disclosure to its specific affinity moiety by any one of about 1% to 99.9%, as will be specified herein after. Alternatively, the terms "enhancement", "increase", “elevation” or "enlargement" as referred to herein, relate to the enhancement, increase and elevation of the binding, attachment and / or stability of at least one of the target molecules of the present disclosure to its specific affinity moiety in accordance with the present disclosure by any one of about 1% to 99.9%. Specifically, 1% to 99.9% as indicated herein refers to about 1% to about 5%, about 5% to 10%, about 10% to 15%, about 15% to 20%, about 20% to 25%, about 25% to 30%, about 30% to 35%, about 35% to 40%, about 40% to 45%, about 45% to 50%, about 50% to 55%, about 55% to 60%, about 60% to 65%, about 65% to 70%, about 75% to 80%, about 80% to 85% about 85% to 90%, about 90% to 95%, about 95% to 99%, or about 99% to 99.9%. It should be appreciated that 10%, 50%, 120%, 500%, etc., are interchangeable with "fold change" values, i.e., 0.1, 0.5, 1.2, 5, etc., respectively. 10%, 50%, 120%, 500%, etc., are interchangeable with "fold change" values, i.e., 0.1, 0.5, 1.2, 5, etc., respectively. Therefore, the term inhibits, or decrease or alternatively, induce and enhance refers to an inhibition or alternatively an increase of about 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000 folds or more.

[0217] Another aspect of the present disclosure relates to a battery comprising two or more of the bio-transistor system as defined above.

[0218] Another aspect of the present disclosure related to a method for determining presence and / or quantity of at least one target molecule in at least one sample. The method comprising: (a) contacting the at least one sample with a bio-transistor having an active region (e.g., modified) carrying at least one affinity moieties, or a battery comprising at least two of the bio-transistors. It should be noted that each of the at least one affinity moiety is specific for a target molecule. In the next step (b), performing one or more measurements, each measurement comprising: applying a selected electric potential on the sample, and determining current transmission profile through a channel of the bio-transistor with respect to potential variation of at least one gate electrode of the bio-transistor; and (c) processing data on the current transmission through the channel for one or more selected gate potential and one or more selected electric potential values applied on the sample and determining presence and / or quantity of the one or more target molecules in accordance with pre-stored calibration data.

[0219] In some embodiments of the present disclosure, the bio-transistor used by the disclosed methods, comprising: (i) at least one channel; (ii) source and drain electrodes; (iii) at least one gate electrode; and (iv) at least one additional electrode positioned to be in electrical contact with the sample. The at least one active region is located in proximity to the channel region, separated from the channel region by an electrically insulating layer. The control unit thereby configured to determine data on presence and / or quantity of one or more target molecules in the sample.

[0220] In some further embodiments, the methods comprising performing two or more measurements, wherein each measurement comprises applying respective selected different potential on the sample.

[0221] In some other embodiments, the bio-transistor is any of the bio transistor systems of the present disclosure as defined above.

[0222] Another aspect of the current disclosure provides a diagnostic method for determining a physiological and / or environmental condition or state of a subject and / or a media and / or a habitat. The method comprising: (a), contacting the at least one sample with a bio-transistor having an (e.g., modified) active region carrying at least one affinity moiety, or a battery comprising at least two of said bio-transistors. In some embodiments, each of the at least one affinity moiety is specific for a target molecule. In step (b), performing one or more measurements, each measurement comprising: applying a selected electric potential on the sample, and determining current transmission profile through a channel of the bio-transistor with respect to potential variation of at least one gate electrode of the bio-transistor. Step (c), involves processing data on the current transmission through the channel for one or more selected gate potential and one or more selected electric potential values applied on the sample. In step (d), determining presence and / or quantity of the one or more target molecules in accordance with pre-stored calibration data, thereby obtaining a target molecule value for the sample. In step (e), determining that the subject and / or media and / or habitat display the physiological and / or environmental condition or state, if the at least one target molecule value obtained for the sample in step (d), is positive or negative with respect to a reference target molecule value pre-determined for the physiological and / or environmental condition or state, or with respect to a target molecule value determined for at least one control sample.

[0223] In some embodiments, the bio-transistor system used by the diagnostic method is as defined by the present disclosure herein above.

[0224] Thus, the disclosed methods involve in the first step determination of the level of specific target molecule to obtain the value for each target in the sample, as will be elaborated herein after. The next step involves determination if the expression value is positive or negative. It should be understood that determination of a "positive" or alternatively "negative" value of the target molecule levels and / or amount with respect to a standard value or a control value may involve in some embodiments comparison of the value determined for the quantity and / or mount) of the target molecule of the examined sample as obtained in step (d), with the amount / level value of the target obtained for a control sample, or from any established or predetermined value of the target molecule level and / or amount and / or quantity (e.g., a standard value) obtained from a known control (either healthy controls or of subjects suffering from a pathological disorder). Thus, in some embodiments, "positive" is meant a value that is higher, increased, elevated, overexpressed in about 5% to 100% or more, specifically, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%, when compared to the amount / level / quantity value of the reference and / or the standard value of a healthy control, any other suitable control or any other predetermined standard. Still further, a "negative" value in some embodiments may be a reduced, low, non-existing or lack of expression of a target molecule in about 5% to 100% or more, specifically, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%, when compared to the value of the amount of the target molecule in a healthy control, any other suitable control or any other predetermined standard. As used herein, “healthy controls” or “healthy population” may refer to a population of subjects that does not suffer from a disease of interest or refer to a population before appearance of a disease of interest. In some embodiments, the value of the target molecule in a control population refers to a baseline level of the target molecule of a healthy population or to a baseline level of the target molecule before appearance of a disease in a studied population. In some other embodiment, a “healthy control” or “control” may refer to the to a baseline level of the target molecule before appearance of a disease in a specific subject.

[0225] In yet some further embodiments, "positive", specifically, higher, elevated levels and / or amount and / or quantity when compared to a control, the subject is classified as a subject that display a specific disorder as indicated herein for each of the target molecules.

[0226] It should be appreciated that a "reference value" or a "Standard” , or a "predetermined standard” or a "predetermined reference value" as used herein, denotes either a single standard value or a plurality of standards with which the level of at least one of the target molecule / s from the tested sample is compared. The standards may be provided, for example, in the form of discrete numeric values or in the form of a comparative curve prepared on the basis of such standards (standard curve).

[0227] Thus, in yet more specific embodiments, the method of the invention involves comparing the values of the amount and / or quantity of the target molecule / s determined for the tested sample with predetermined standard values or cutoff values, or alternatively, with the values of at least one control sample. As used herein the term "comparing” denotes any examination of the level and / or amount and / or quantity values obtained in the samples disclosed herein as detailed throughout in order to discover similarities or differences between at least two different samples. It should be noted that in some embodiments, comparing according to the present disclosure encompasses the possibility to use a computer-based approach.

[0228] Step (a) of the disclosed methods involves the action of contacting the bio transistors of the present disclosure with the examined sample. The term "contacting” means to bring, put or incubates together. As such, a first component, e.g., affinity moiety is contacted with a second component, specifically, the target molecule when the two components are brought or put together, e.g., by touching them to each other or combining them. In the context of the present disclosure, the term "contacting" includes all measures or steps which allow interaction between the at least one of the affinity moieties of at least one of the target molecules. The contacting is performed in a manner so that the at least one of affinity moieties of at least one of the target molecules, can interact with or bind to the target molecule in the tested sample. The binding will preferably be non-covalent, reversible binding, e.g., binding via salt bridges, hydrogen bonds, hydrophobic interactions or a combination thereof.

[0229] In some embodiments, the physiological state and / or condition of a subject comprises pathological condition / s and / or health condition / s in the subject. Thus, the present disclosure provides diagnostic methods for detecting, diagnosing and / or monitoring several pathologic conditions associated with a target product, detected by the bio-transistors disclosed by the present disclosure. In the present embodiments provided herein, the biotransistors comprise affinity moieties that are composed of a proteineous material, specifically, amino-acid-based material, for example, antibodies or fragments thereof specific for the desired diagnostic target. In yet some further embodiments, the disclosed targets are protein targets, that are antigens recognized by the antibodies provided with the bio-transistors. These target proteins are associated with a pathology disorder, and thus, provide effective means for diagnosing any related conditions.

[0230] In some further embodiments, the pathological condition as used herein encompasses at least one immune-related disorder. In some embodiments, the immune-related disorder is at least one of an infectious disease, a proliferative disorder, an inflammatory disease, an autoimmune disorder, a metabolic disorder and a neurodegenerative disease.

[0231] An "Immune-related disorder" or "Immune- mediated disorder", as used herein encompasses any condition that is associated with the immune system of a subject, more specifically through inhibition of the immune system, or that can be treated, prevented, or ameliorated by reducing degradation of a certain component of the immune response in a subject, such as the adaptive or innate immune response. An immune-related disorder may include infectious condition (e.g., by a pathogen, specifically, viral, bacterial, or fungal infections), inflammatory disease, autoimmune disorders, immunodeficiency (e.g., primary or a secondary) metabolic disorders and proliferative disorders, specifically, cancer.

[0232] In some embodiments, the immune-related disorder applicable in the methods of the present disclosure may be at least one infectious disease. An infectious disease as used herein encompasses any infectious disease caused by a pathogenic agent, specifically, a pathogen. More specifically, the infectious disease may be any pathological disorder caused by or associated with a pathogen. As used herein, the term “pathogen” refers to an infectious agent that causes a disease in a subject host. Pathogenic agents include prokaryotic microorganisms, lower eukaryotic microorganisms, complex eukaryotic organisms, viruses, fungi, mycoplasma, prions, parasites, for example, a parasitic protozoan, yeasts, or a nematode, as well as toxins and venoms.

[0233] In yet some specific embodiments, the methods and bio transistor systems of the present disclosure may be applicable for diagnosing, monitoring and treating an infectious disease caused by bacterial pathogens. More specifically, a prokaryotic microorganism includes bacteria such as Gram positive, Gram negative and Gram variable bacteria and intracellular bacteria. Examples of bacteria contemplated herein include the species of the genera Treponema sp., Borrelia sp., Neisseria sp., Legionella sp., Bordetella sp., Escherichia sp., Salmonella sp., Shigella sp., Klebsiella sp., Yersinia sp., Vibrio sp., Hemophilus sp., Rickettsia sp., Chlamydia sp., Mycoplasma sp., Staphylococcus sp., Streptococcus sp., Bacillus sp., Clostridium sp., Corynebacterium sp., Proprionibacterium sp., Mycobacterium sp., Ureaplasma sp. and Listeria sp.

[0234] Particular species include Mycoplasma pulmonis, Salmonella typhimurium, Treponema pallidum, Borrelia burgdorferi, Neisseria gonorrhea, Neisseria meningitidis, Legionella pneumophila, Bordetella pertussis, Escherichia coli, Salmonella typhi, Shigella dysenteriae, Klebsiella pneumoniae, Yersinia pestis, Vibrio cholerae, Hemophilus influenzae, Rickettsia rickettsii, Chlamydia trachomatis, Mycoplasma pneumoniae, Staphylococcus aureus, Streptococcus pneumoniae, Streptococcus pyogenes, Bacillus anthracis, Clostridium botulinum, Clostridium tetani, Clostridium perfringens, Corynebacterium diphtheriae, Proprionibacterium acnes, Mycobacterium tuberculosis, Mycobacterium leprae and Listeria monocytogenes. A lower eukaryotic organism includes a yeast or fungus such as but not limited to Candida albicans, Pneumocystis carinii, Aspergillus, Histoplasma capsulatum, Blastomyces dermatitidis, Cryptococcus neoformans, Trichophyton and Microsporum, are also encompassed by the invention. A complex eukaryotic organism includes worms, insects, arachnids, nematodes, aemobe, Entamoeba histolytica, Giardia lamblia, Trichomonas vaginalis, Trypanosoma brucei gambiense, Trypanosoma cruzi, Balantidium coli, Toxoplasma gondii, Cryptosporidium or Leishmania.

[0235] In yet some further embodiments, the bio transistor systems and methods of the present disclosure may be applicable for any infectious disorders caused by a viral pathogen or a virus. The term "virus" as used herein, refers to obligate intracellular parasites of living but non-cellular nature, consisting of DNA or RNA and a protein coat. Viruses range in diameter from about 20 to about 300 nm. Class I viruses (Baltimore classification) have a double-stranded DNA as their genome; Class II viruses have a single-stranded DNA as their genome; Class III viruses have a double-stranded RNA as their genome; Class IV viruses have a positive single-stranded RNA as their genome, the genome itself acting as mRNA; Class V viruses have a negative single- stranded RNA as their genome used as a template for mRNA synthesis; and Class VI viruses have a positive single-stranded RNA genome but with a DNA intermediate not only in replication but also in mRNA synthesis. It should be noted that the term “viruses” is used in its broadest sense to include viruses of the families Flaviviruses, Alphaviruses, Togaviruses, Coronaviruses, Hepatitis D, Orthomyxoviruses, Paramyxoviruses, Rhabdovirus. Still further, more specific embodiments relate to Influenza viruses A and B, coronaviruses (e.g. SARS-COV2), Ebola viruses, adenoviruses, papovaviruses, herpesviruses: simplex, varicella-zoster, Epstein-Barr (EBV), Cowpox viruses, Cytomegalo virus (CMV), pox viruses: smallpox, vaccinia, hepatitis B (HBV), rhinoviruses, hepatitis A (HBA), poliovirus, respiratory syncytial virus (RSV), Middle East Respiratory Syndrome (MERS), rubella virus, hepatitis C (HBC), arboviruses, rabies virus, measles virus, mumps virus, human deficiency virus (HIV), HTLV I and II, flaviviruses such as Dengue virus, west nile virus, yellow fever virus, and Zika virus. More specifically, in certain embodiments the methods and bio transistor systems of the present disclosure may be suitable for disorders caused by fungal pathogens. The term "fungi" (or a “fungus”), as used herein, refers to a division of eukaryotic organisms that grow in irregular masses, without roots, stems, or leaves, and are devoid of chlorophyll or other pigments capable of photosynthesis. Each organism (thallus) is unicellular to filamentous and possess branched somatic structures (hyphae) surrounded by cell walls containing glucan or chitin or both and containing true nuclei. It should be noted that "fungi" includes for example, fungi that cause diseases such as ringworm, histoplasmosis, blastomycosis, aspergillosis, cryptococcosis, sporotrichosis, coccidioidomycosis, paracoccidio-idoinycosis, and candidiasis.

[0236] As noted above, the present invention also provides for methods and bio transistor systems for the diagnosis and monitoring of a pathological disorder caused by “parasitic protozoan”, which refers to organisms formerly classified in the Kingdom “protozoa”. They include organisms classified in Amoebozoa, Excavata and Chromalveolata. Examples include Entamoeba histolytica, Plasmodium (some of which cause malaria), and Giardia lamblia. The term parasite includes, but not limited to, infections caused by somatic tapeworms, blood flukes, tissue roundworms, ameba, and Plasmodium, Trypanosoma, Leishmania, and Toxoplasma species. As used herein, the term “nematode” refers to roundworms. Roundworms have tubular digestive systems with openings at both ends. Some examples of nematodes include, but are not limited to, basal order Monhysterida, the classes Dorylaimea, Enoplea and Secernentea and the “Chromadorea” assemblage.

[0237] As used herein to describe the present disclosure, “proliferative disorder”, “cancer”, “tumor” and “malignancy” all relate equivalently to a hyperplasia of a tissue or organ. If the tissue is a part of the lymphatic or immune systems, malignant cells may include non-solid tumors of circulating cells. Malignancies of other tissues or organs may produce solid tumors. Malignancy, as contemplated in the present disclosure may be any one of carcinomas, melanomas, lymphomas, leukemia, myeloma and sarcomas. Therefore, in some embodiments any of the methods of the disclosure (specifically, the diagnostic methods), kits and biotransistor systems disclosed herein, may be applicable for any of the malignancies disclosed by the present disclosure. Further malignancies that may find utility in the present invention can comprise but are not limited to hematological malignancies (including lymphoma, leukemia, myeloproliferative disorders, Acute lymphoblastic leukemia; Acute myeloid leukemia), hypoplastic and aplastic anemia (both virally induced and idiopathic), myelodysplastic syndromes, all types of paraneoplastic syndromes (both immune mediated and idiopathic) and solid tumors (including GI tract, colon, lung, liver, breast, prostate, pancreas and Kaposi's sarcoma. The invention may be applicable as well for the treatment or inhibition of solid tumors such as tumors in lip and oral cavity, pharynx, larynx, paranasal sinuses, major salivary glands, thyroid gland, esophagus, stomach, small intestine, colon, colorectum, anal canal, liver, gallbladder, extrahepatic bile ducts, ampulla of vater, exocrine pancreas, lung, pleural mesothelioma, bone, soft tissue sarcoma, carcinoma and malignant melanoma of the skin, breast, vulva, vagina, cervix uteri, corpus uteri, ovary, fallopian tube, gestational trophoblastic tumors, penis, prostate, testis, kidney, renal pelvis, ureter, urinary bladder, urethra, carcinoma of the eyelid, carcinoma of the conjunctiva, malignant melanoma of the conjunctiva, malignant melanoma of the uvea, retinoblastoma, carcinoma of the lacrimal gland, sarcoma of the orbit, brain, spinal cord, vascular system, hemangiosarcoma, Adrenocortical carcinoma; AIDS -related cancers; AIDS-related lymphoma; Anal cancer; Appendix cancer; Astrocytoma, childhood cerebellar or cerebral; Basal cell carcinoma; Bile duct cancer, extrahepatic; Bladder cancer; Bone cancer, Osteosarcoma / Malignant fibrous histiocytoma; Brainstem glioma; Brain tumor; Brain tumor, cerebellar astrocytoma; Brain tumor, cerebral astrocytoma / malignant glioma; Brain tumor, ependymoma; Brain tumor, medulloblastoma; Brain tumor, supratentorial primitive neuroectodermal tumors; Brain tumor, visual pathway and hypothalamic glioma; Breast cancer; Bronchial adenomas / carcinoids; Burkitt lymphoma; Carcinoid tumor, childhood; Carcinoid tumor, gastrointestinal; Carcinoma of unknown primary; Central nervous system lymphoma, primary; Cerebellar astrocytoma, childhood; Cerebral astrocytoma / Malignant glioma, childhood; Cervical cancer; Childhood cancers; Chronic lymphocytic leukemia; Chronic myelogenous leukemia; Chronic myeloproliferative disorders; Colon Cancer; Cutaneous T-cell lymphoma; Desmoplastic small round cell tumor; Endometrial cancer; Ependymoma; Esophageal cancer; Ewing's sarcoma in the Ewing family of tumors; Extracranial germ cell tumor, Childhood; Extragonadal Germ cell tumor; Extrahepatic bile duct cancer; Eye Cancer, Intraocular melanoma; Eye Cancer, Retinoblastoma; Gallbladder cancer; Gastric (Stomach) cancer; Gastrointestinal Carcinoid Tumor; Gastrointestinal stromal tumor (GIST); Germ cell tumor: extracranial, extragonadal, or ovarian; Gestational trophoblastic tumor; Glioma of the brain stem; Glioma, Childhood Cerebral Astrocytoma; Glioma, Childhood Visual Pathway and Hypothalamic; Gastric carcinoid; Hairy cell leukemia; Head and neck cancer; Heart cancer; Hepatocellular (liver) cancer; Hodgkin lymphoma; Hypopharyngeal cancer; Hypothalamic and visual pathway glioma, childhood; Intraocular Melanoma; Islet Cell Carcinoma (Endocrine Pancreas); Kaposi sarcoma; Kidney cancer (renal cell cancer); Laryngeal Cancer; Leukemias; Leukemia, acute lymphoblastic (also called acute lymphocytic leukemia); Leukemia, acute myeloid (also called acute myelogenous leukemia); Leukemia, chronic lymphocytic (also called chronic lymphocytic leukemia); Leukemia, chronic myelogenous (also called chronic myeloid leukemia); Leukemia, hairy cell; Lip and Oral Cavity Cancer; Liver Cancer (Primary); Lung Cancer, Non-Small Cell; Lung Cancer, Small Cell; Lymphomas; Lymphoma, AIDS-related; Lymphoma, Burkitt; Lymphoma, cutaneous T-Cell; Lymphoma, Hodgkin; Lymphomas, Non- Hodgkin (an old classification of all lymphomas except Hodgkin's); Lymphoma, Primary Central Nervous System; Marcus Whittle, Deadly Disease; Macroglobulinemia, Waldenstrom; Malignant Librous Histiocytoma of Bone / Osteosarcoma; Medulloblastoma, Childhood; Melanoma; Melanoma, Intraocular (Eye); Merkel Cell Carcinoma; Mesothelioma, Adult Malignant; Mesothelioma, Childhood; Metastatic Squamous Neck Cancer with Occult Primary; Mouth Cancer; Multiple Endocrine Neoplasia Syndrome, Childhood; Multiple Myeloma / Plasma Cell Neoplasm; Mycosis Eungoides; Myelodysplastic Syndromes; Myelodysplastic / Myeloproliferative Diseases; Myelogenous Leukemia, Chronic; Myeloid Leukemia, Adult Acute; Myeloid Leukemia, Childhood Acute; Myeloma, Multiple (Cancer of the Bone-Marrow); Myeloproliferative Disorders, Chronic; Nasal cavity and paranasal sinus cancer; Nasopharyngeal carcinoma; Neuroblastoma; Non-Hodgkin lymphoma; Non-small cell lung cancer; Oral Cancer; Oropharyngeal cancer; Osteosarcoma / malignant fibrous histiocytoma of bone; Ovarian cancer; Ovarian epithelial cancer (Surface epithelial-stromal tumor); Ovarian germ cell tumor; Ovarian low malignant potential tumor; Pancreatic cancer; Pancreatic cancer, islet cell; Paranasal sinus and nasal cavity cancer; Parathyroid cancer; Penile cancer; Pharyngeal cancer; Pheochromocytoma; Pineal astrocytoma; Pineal germinoma; Pineoblastoma and supratentorial primitive neuroectodermal tumors, childhood; Pituitary adenoma; Plasma cell neoplasia / Multiple myeloma; Pleuropulmonary blastoma; Primary central nervous system lymphoma; Prostate cancer; Rectal cancer; Renal cell carcinoma (kidney cancer); Renal pelvis and ureter, transitional cell cancer; Retinoblastoma; Rhabdomyosarcoma, childhood; Salivary gland cancer; Sarcoma, Ewing family of tumors; Sarcoma, Kaposi; Sarcoma, soft tissue; Sarcoma, uterine; Sezary syndrome; Skin cancer (nonmelanoma); Skin cancer (melanoma); Skin carcinoma, Merkel cell; Small cell lung cancer; Small intestine cancer; Soft tissue sarcoma; Squamous cell carcinoma - see Skin cancer (nonmelanoma); Squamous neck cancer with occult primary, metastatic; Stomach cancer; Supratentorial primitive neuroectodermal tumor, childhood; T-Cell lymphoma, cutaneous (Mycosis Fungoides and Sezary syndrome); Testicular cancer; Throat cancer; Thymoma, childhood; Thymoma and Thymic carcinoma; Thyroid cancer; Thyroid cancer, childhood; Transitional cell cancer of the renal pelvis and ureter; Trophoblastic tumor, gestational; Unknown primary site, carcinoma of, adult; Unknown primary site, cancer of, childhood; Ureter and renal pelvis, transitional cell cancer; Urethral cancer; Uterine cancer, endometrial; Uterine sarcoma; Vaginal cancer; Visual pathway and hypothalamic glioma, childhood; Vulvar cancer; Waldenstrom macroglobulinemia and Wilms tumor (kidney cancer).

[0238] In some embodiments of the present disclosure, the pathogenic agent is bacteria, specifically, Staphylococcus aureus, Streptococci (uberis, dysgalactiae, agalactiae), and Escherichia coli (E. coli). In yet some further embodiments, the diagnostic methods are applicable for a mammalian subject, specifically, the subject is a mammal of the Bovinae family, and the infectious disease is bovine mastitis (BM).

[0239] In some embodiments, the specific bacteria causing BM.

[0240] In some embodiments, the diagnosis and monitoring provided by the disclosed methods is of mastitis in a mammalian subject of the Bovinae family.

[0241] In some embodiments of the disclosed diagnostic methods, the target molecule used to detect and monitor mastitis, is the NAGase protein. In yet some further embodiments, the affinity moiety used by the disclosed methods comprises at least one antibody that specifically recognizes and binds NAGase. In some embodiments, the present disclosure provides an effective and sensitive method for detecting mastitis in milk samples, specifically, bovine milk sample. In some specific and non-limiting embodiments, the sensing of NAGase, may be performed by using anti-NAGase antibodies (MBS2001469, MyBioSource), as the affinity moiety. It should be however noted that the present disclosure encompasses the use of any equivalent anti-NAGase antibodies.

[0242] In some embodiments, the immune-related disorder applicable in the methods of the present disclosure may be an inflammatory disease. The terms “inflammatory disease” or "inflammatory-associated condition" refers to any disease or pathologically condition which can benefit from the reduction of at least one inflammatory parameter, for example, induction of an inflammatory cytokine such as IFN-gamma and IL-2 and reduction in IL- 6 levels. The condition may be caused (primarily) from inflammation, or inflammation may be one of the manifestations of the diseases caused by another physiological cause. In some embodiments, an inflammatory disease that may be applicable for the methods of the present disclosure may be inflammatory bowel disease (IBD).

[0243] An autoimmune disorder is state in which the immune system gets directed against selfcells or tissues. Autoimmune disorders include for example, but not limited to inflammatory bowel disease (IBD), ulcerative colitis (UC), Crohn's disease (CD), Systemic Lupus Erythematosus (SLE), Rheumatoid Arthritis (RA), fatty liver disease, Lymphocytic colitis, Ischaemic colitis, Diversion colitis, Behget's syndrome, Indeterminate colitis, Graft versus Host Disease (GvHD), Eaton-Lambert syndrome, Goodpasture's syndrome, Greave's disease, Guillain-Barr syndrome, autoimmune hemolytic anemia (AIHA), hepatitis, insulin-dependent diabetes mellitus (IDDM) and NIDDM, multiple sclerosis (MS), myasthenia gravis, plexus disorders e.g. acute brachial neuritis, polyglandular deficiency syndrome, primary biliary cirrhosis, scleroderma, thrombocytopenia, thyroiditis e.g. Hashimoto's disease, Sjogren's syndrome, allergic purpura, psoriasis, mixed connective tissue disease, polymyositis, dermatomyositis, vasculitis, polyarteritis nodosa, arthritis, alopecia areata, polymyalgia rheumatica, Wegener's granulomatosis, Reiter's syndrome, ankylosing spondylitis, pemphigus, bullous pemphigoid, dermatitis herpetiformis, psoriatic arthritis, reactive arthritis, and ankylosing spondylitis, inflammatory arthritis, including juvenile idiopathic arthritis, gout and pseudo gout, as well as arthritis associated with colitis or psoriasis, Pernicious anemia, some types of myopathy and Lyme disease (Late).

[0244] Still further, the diagnostic methods may be applicable for any subject. In some embodiments, the disclosed diagnostic methods are applicable for a mammalian subject of the Hominidae family. More specifically, for a human subject.

[0245] Accordingly, in some embodiments, the disclosed diagnostic methods may use any biological samples of the diagnosed mammal, specifically, any sample disclosed by the present disclosure. For example, the sample may be in some embodiments, a blood or a serum sample.

[0246] In yet some further embodiments, the target molecule detected and / or quantified, and / or monitored by the disclosed diagnostic methods is a molecule produced (naturally produced) by the mammalian subject. In some embodiments, the level of such target molecule has a diagnostic applicability. For example, a level of the target molecule that is below, or alternatively, above a standard level is indicative of a pathologic disorder in the tested subject.

[0247] In some specific embodiments, the present disclosure provides a diagnostic method that uses the Alpha-fetoprotein (AFP) as a target molecule. According to such embodiments, the at least one affinity moiety used by the disclosed methods comprise, is or is derived from, at least one antibody specific for AFP. In some specific and non-limiting embodiments, the sensing of anti-AFP, may be performed by using anti-AFP antibodies (Abeam, ab3980), as the affinity moiety. It should be however noted that the present disclosure encompasses the use of any equivalent anti-AFP antibodies.

[0248] Thus, in some embodiments (i), a level of the AFP that is above a standard level is indicative of at least one of: a liver disease, a germ cell tumor, a pregnancy-related condition and at least one malignancy. In yet some further embodiments (ii), a level of the AFP that is below a standard level is indicative of at least one of chromosomal abnormality. In more specific embodiments, reduced levels of AFP indicate at least one trisomy, specifically, trisomy 21, and / or trisomy 18. In some embodiments, reduced levels of AFP detected by the methods of the present disclosure are indicative of Down Syndrome and / or Edward's Syndrome.

[0249] The terms chromosomal abnormalities or genetic abnormalities as used herein refer to changes in the normal structure or number of chromosomes in cells, which can lead to developmental and health issues. These abnormalities can be classified into several types, specifically, aneuploidy and structural abnormalities, each with specific characteristics and potential impacts. More specifically, aneuploidy, relates to the presence of an extra chromosome or the absence of a chromosome. Examples include trisomy and monosomy. More specifically, Trisomy, having three copies of a chromosome instead of the usual two. Common trisomies include Trisomy 21 (Down syndrome), Trisomy 18 (Edwards syndrome), and Trisomy 13 (Patau syndrome). Monosomy, having only one copy of a chromosome instead of two, for example, Turner syndrome (Monosomy X), where an individual has only one X chromosome.

[0250] Structural abnormalities, involve changes in the structure of chromosomes, and include deletions, where a portion of the chromosome is missing or deleted (e.g., Cri-du-chat syndrome, caused by a deletion on chromosome 5); duplications, where a portion of the chromosome is duplicated, resulting in extra genetic material; translocations, where segment of one chromosome is transferred to another chromosome; inversions, where a chromosome segment breaks off, flips around, and reattaches, changing the order of the genes, and rings, where a chromosome forms a ring structure due to deletions in telomeres, causing the ends to fuse.

[0251] Still further, in some embodiments, the methods of the present disclosure use as a target molecule, Ferritin. Accordingly, in some embodiments, the at least one affinity moiety used by the methods comprise, is or is derived from, at least one antibody specific for Ferritin. According to such embodiments, the disclosed methods may be used for detecting and monitoring disorders associated with reduced or with elevated levels of Ferritin. More specifically, in some embodiments (i), a level of the Ferritin that is above a standard level is indicative of at least one of: Hemochromatosis, A Chronic Inflammatory Condition, A Fiver Disease, a chronic infectious disease, a Malignancy, and Hemolytic Anemia. In yet some alternative or additional embodiments (ii), a level of the Ferritin that is below a standard level is indicative of at least one of: Iron Deficiency Anemia, Chronic Blood Loss, and Malabsorption Syndrome.

[0252] In some embodiments, the disclosed methods are applicable in detecting and monitoring AFP levels in a blood or a serum sample.

[0253] In yet some further embodiments, the present disclosure provides diagnostic methods based on CRP levels. More specifically, in some embodiments, the target molecule detected, quantified and / or monitored by the disclosed methods is C-reactive protein (CRP). Accordingly, in some embodiments, the affinity moiety used by the disclosed methods may comprise, is, or is derived from, at least one antibody specific for CRP.

[0254] Thus, in some embodiments, the disclosed diagnostic methods are applicable for detecting and / or monitoring disorders associated with elevated levels of CRP. More specifically, a level of CRP that is above a standard level is indicative of at least one of: an infectious disorder, a chronic inflammatory disease, a cardiovascular disease, autoimmune diseases, a cancer, and at least one metabolic disorder.

[0255] More specifically, in some embodiments, the disclosed diagnostic methods are applicable for diagnosing and / or monitoring at least one cardiovascular disease. More specifically, cardiovascular diseases (CVD) encompass a group of disorders affecting the heart and blood vessels. In some embodiments, these diseases as used herein, include coronary Artery Disease (CAD), that relates to the narrowing or blockage of the coronary arteries, usually caused by atherosclerosis, leading to reduced blood flow to the heart muscle and potentially resulting in angina or myocardial infarction (heart attack), hypertension, where the force of the blood against the artery walls is consistently too high, leading to heart damage and increase the risk of stroke and other cardiovascular complications, heart Failure where the heart is unable to pump sufficiently to maintain blood flow to meet the body's needs, arrhythmias, cardiomyopathy, peripheral Artery Disease (PAD), stroke, congenital Heart Disease rheumatic Heart Disease.

[0256] Another aspect of the present disclosure is a screening method for identifying a compound that modulates the interaction of an affinity moiety with a target molecule in at least one sample. The method comprising: (i) contacting the at least one sample with a bio-transistor system, in the presence and the absence of at least one candidate compound. The biotransistor having an [modified] active region carrying at least one affinity moiety. In some embodiments, each affinity moiety is specific for a target molecule; (ii) performing one or more measurements for each sample, each measurement comprising: applying a selected electric potential on the sample, and determining current transmission profile through a channel of the bio-transistor with respect to potential variation of at least one gate electrode of the bio-transistor; and (iii) processing data on the current transmission through the channel for one or more selected gate potential and one or more selected electric potential values applied on the sample; and (iv) determining presence and / or quantity of the one or more target molecules in accordance with pre-stored calibration data, thereby determining a target molecule value for the sample in the presence of the candidate compound, and a target molecule value in the absence of the candidate compound; (v) determining that the candidate compound is a modulator of the interaction between the affinity moiety and the target molecule, if the target molecule value obtained for the sample in the presence of the candidate compound is different from the target molecule value obtained in the absence of the candidate compound.

[0257] In some embodiments of the present disclosure, the disclosed screening method is particularly applicable for screening of a compound that inhibits the interaction of the affinity moiety with the target molecule. More specifically, a compound that "inhibits the interaction" as used herein, refers to a compound that reduces, prevents, blocks, impedes, suppresses, prevents, hinders and / or restricts interaction between the at least one affinity moiety and the target molecule either partially, or completely. For example, any inhibition of between about 10-50%, 51-80%, 81-99% or even, of 100% of the interaction or binding between the affinity moiety and the target molecule.

[0258] Another aspect of the present disclosure is personalized methods for treating, preventing, inhibiting, reducing, eliminating, protecting or delaying the onset of at least one pathological disorder in a subject. The method comprising the steps of: (a) determining the presence and / or quantity of at least one target molecule target molecule in at least one sample of the subject. The target molecule is associated directly or indirectly with the pathologic disorder; and (b) administering an effective amount of at least one therapeutic agent for the pathological disorder to a subject exhibiting presence of one or more target molecule, or the quantity of the target molecule that is above or below the standard level. Determining the presence and / or quantity of at least one target molecule in (a), is performed by the steps of: (i) contacting the at least one sample of the subject with a bio-transistor having an active region carrying at least one affinity moiety, or a battery comprising at least two bio-transistors, wherein each of the at least one affinity moiety is specific for one target molecule; (ii) performing each measurement comprising: applying a selected electric potential on the sample, and determining current transmission profile through a channel of the bio-transistor with respect to potential variation of at least one gate electrode of the biotransistor; and (iii) processing data on the current transmission through the channel for one or more selected gate potential and one or more selected electric potential values applied on the sample; and (iv), determining presence and / or quantity of the one or more target molecules in accordance with pre-stored calibration data, thereby obtaining a target molecule value for the sample; and (v) determining that the subject is suffering from said pathologic disorder, if the at least one target molecule value obtained for said sample in step (iv), is positive or negative with respect to a reference target molecule value predetermined for said pathologic disorder, or with respect to a target molecule value determined for at least one control sample.

[0259] In some embodiments, the presence and / or quantity of at least one target molecule in (a), is performed by the method of the present disclosure as defined herein above.

[0260] In some further embodiments, the subject is a mammalian subject of the Bovinae family. Accordingly, in some embodiments, the target molecule is NAGase, and the affinity moiety comprises at least one antibody that specifically recognizes and binds NAGase. Still further, in some embodiments, the disorder is mastitis. In some embodiments, the sample is a bovine milk sample.

[0261] In yet some further embodiments of the personalized method of the present disclosure, the subject is a mammalian subject of the Hominidae family. In more specific embodiments, the personalized therapeutic methods disclosed herein may be applicable for a human subject.

[0262] In some embodiments, the sample used by the disclosed personalized methods is a blood or a serum sample. Still further, in some embodiments, the target protein is AFP, and the affinity moiety used by the disclosed methods is or is derived from, at least one antibody specific for AFP.

[0263] Accordingly, the disclosed personalized methods may be applicable for at least one of: (i) a liver disease, a germ cell tumor, a pregnancy-related condition and / or at least one malignancy; and / or (ii) Down Syndrome and / or Edward's Syndrome.

[0264] In yet some alternative embodiments, the target molecule used is Ferritin, and the affinity moiety is or is derived from, at least one antibody specific for Ferritin. According to such embodiments, the personalized method disclosed herein may be applicable for at least one of: (i) Hemochromatosis, A Chronic Inflammatory Condition, A Liver Disease, a chronic infectious disease, a Malignancy, and / or Hemolytic Anemia; and / or (ii) Iron Deficiency Anemia, Chronic Blood Loss, and / or Malabsorption Syndrome.

[0265] In yet some additional or alternative embodiments, the target molecule used by the disclosed methods is CRP, and the affinity moiety is or is derived from, at least one antibody specific for CRP. According to such embodiments, the disclosed method may be applicable for at least one of: an infectious disorder, a chronic inflammatory disease, a cardiovascular disease, autoimmune diseases, a cancer, and at least one metabolic disorder.

[0266] It is to be understood that the terms "treat”, “treating”, “treatment" or forms thereof, as used herein in accordance with the personalized therapeutic methods, mean preventing, ameliorating or delaying the onset of one or more clinical indications of disease activity in a subject having a pathologic disorder. Treatment refers to therapeutic treatment. Those in need of treatment are subjects suffering from a pathologic disorder. Specifically, providing a "preventive treatment" (to prevent) or a "prophylactic treatment" is acting in a protective manner, to defend against or prevent something, especially a condition or disease.

[0267] The term “treatment or prevention” as used herein, refers to the complete range of therapeutically positive effects of administrating to a subject including inhibition, reduction of, alleviation of, and relief from, an immune-related condition and illness, immune-related symptoms or undesired side effects or immune-related disorders. More specifically, treatment or prevention of relapse or recurrence of the disease, includes the prevention or postponement of development of the disease, prevention or postponement of development of symptoms and / or a reduction in the severity of such symptoms that will or are expected to develop. These further include ameliorating existing symptoms, preventing- additional symptoms and ameliorating or preventing the underlying metabolic causes of symptoms. It should be appreciated that the terms "inhibition", "moderation", “reduction”, "decrease" or "attenuation" as referred to herein, relate to the retardation, restraining or reduction of a process by any one of about 1% to 99.9%, specifically, about 1% to about 5%, about 5% to 10%, about 10% to 15%, about 15% to 20%, about 20% to 25%, about 25% to 30%, about 30% to 35%, about 35% to 40%, about 40% to 45%, about 45% to 50%, about 50% to 55%, about 55% to 60%, about 60% to 65%, about 65% to 70%, about 75% to 80%, about 80% to 85% about 85% to 90%, about 90% to 95%, about 95% to 99%, or about 99% to 99.9%, 100% or more.

[0268] With regards to the above, it is to be understood that, where provided, percentage values such as, for example, 10%, 50%, 120%, 500%, etc., are interchangeable with "fold change" values, i.e., 0.1, 0.5, 1.2, 5, etc., respectively.

[0269] The term "amelioration" as referred to herein, relates to a decrease in the symptoms, and improvement in a subject's condition brought about by the methods according to the present disclosure, wherein said improvement may be manifested in the forms of inhibition of pathologic processes associated with the immune-related disorders described herein, a significant reduction in their magnitude, or an improvement in a diseased subject physiological state.

[0270] The term "inhibit" and all variations of this term is intended to encompass the restriction or prohibition of the progress and exacerbation of pathologic symptoms or a pathologic process progress, said pathologic process symptoms or process are associated with.

[0271] The term "eliminate" relates to the substantial eradication or removal of the pathologic symptoms and possibly pathologic etiology, optionally, according to the methods of the present disclosure described herein.

[0272] The terms "delay", "delaying the onset", "retard" and all variations thereof are intended to encompass the slowing of the progress and / or exacerbation of a disorder associated with the immune-related disorders and their symptoms slowing their progress, further exacerbation or development, so as to appear later than in the absence of the treatment according to the present disclosure.

[0273] Another aspect of the present disclosure relates to a diagnostic kit. The diagnostic kit comprising: (a) at least one bio-transistor system, and optionally, at least on of: (b) at least one control sample; and (c) at least one therapeutic agent. The bio-transistor system comprises at least one transistor unit and a control system. The transistor unit comprising: (i) at least one channel; (ii) source and drain electrodes; (iii) at least one gate electrode; (iv) at least one active region located in proximity to the channel region and carrying at least one affinity moiety. In some embodiments, each affinity moiety is specific for a target molecule. The at least one active region is configured for accepting at least one sample; and (v) at least one additional electrode positioned to be in electrical contact with the sample. The control system comprising at least one processor and memory circuitry. The control system is configured and operable for performing one or more measurements of the sample, wherein each measurement comprises maintaining a selected electric potential on the at least one additional electrode and determining current transmission profile through the at least one channel with respect to potential variation of said the least one gate electrode. The control unit thereby configured to determine on the presence and / or quantity of one or more target molecules in the sample.

[0274] In some embodiments, the kit is adapted for performing the methods described above.

[0275] All scientific and technical terms used herein have meanings commonly used in the art unless otherwise specified. The definitions provided herein are to facilitate understanding of certain terms used frequently herein and are not meant to limit the scope of the present disclosure.

[0276] The term "about" as used herein indicates values that may deviate up to 1%, more specifically 5%, more specifically 10%, more specifically 15%, and in some cases up to 20% higher or lower than the value referred to, the deviation range including integer values, and, if applicable, non-integer values as well, constituting a continuous range. Thus, as used herein the term "about" refers to ± 10 %.

[0277] The terms "comprises", "comprising", "includes", "including", "having" and their conjugates mean "including but not limited to". This term encompasses the terms "consisting of" and "consisting essentially of". The phrase "consisting essentially of" means that the composition or method may include additional ingredients and / or steps, and / or parts, but only if the additional ingredients and / or steps do not materially alter the basic and novel characteristics of the claimed composition or method. Throughout this specification and the Examples and claims which follow, unless the context requires otherwise, the word “comprise”, and variations such as “comprises” and “comprising”, will be understood to imply the inclusion of a stated integer or step or group of integers or steps but not the exclusion of any other integer or step or group of integers or steps.

[0278] It should be noted that various embodiments of this invention may be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the invention. Accordingly, the description of a range should be considered to have specifically disclosed all the possible sub ranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed sub ranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range. Whenever a numerical range is indicated herein, it is meant to include any cited numeral (fractional or integral) within the indicated range. The phrases "ranging / ranges between" a first indicate number and a second indicate number and "ranging / ranges from" a first indicate number "to" a second indicate number are used herein interchangeably and are meant to include the first and second indicated numbers and all the fractional and integral numerals there between.

[0279] As used herein the term "method" refers to manners, means, techniques and procedures for accomplishing a given task including, but not limited to, those manners, means, techniques and procedures either known to, or readily developed from known manners, means, techniques and procedures by practitioners of the chemical, pharmacological, biological, biochemical and medical arts.

[0280] It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the invention, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable sub combination or as suitable in any other described embodiment of the invention. Certain features described in the context of various embodiments are not to be considered essential features of those embodiments, unless the embodiment is inoperative without those elements.

[0281] Various embodiments and aspects of the present invention as delineated hereinabove and as claimed in the claims section below find experimental support in the following examples.

[0282] Disclosed and described, it is to be understood that this invention is not limited to the particular examples, methods steps, and compositions disclosed herein as such methods steps and compositions may vary somewhat. It is also to be understood that the terminology used herein is used for the purpose of describing particular embodiments only and not intended to be limiting since the scope of the present invention will be limited only by the appended claims and equivalents thereof.

[0283] It must be noted that, as used in this specification and the appended claims, the singular forms “a”, “an” and “the” include plural referents unless the content clearly dictates otherwise.

[0284] EXAMPLES

[0285] Experimental procedures

[0286] Device fabrication. The silicon part of the MNC biochip was fabricated using silicon-on- insulator (SOI) wafers in a CMOS-flavor process. Each MNC biochip contains 5 MNC biosensors. The thicknesses of the SOI device layer and the buried oxide (BOX) are 145 nm and 400 nm, respectively. The device layer is n-type doped to 1017cm'3. The p-type regions, NA (associated with the lateral gates and transverse gates) are degenerated, and the source and drains are degenerated n-type regions.

[0287] The doping levels, NA and ND, determine the lateral p-n junctions with a ~1V built-in T K rn • 1 voltage, Vbi= where k is the Boltzmann constant, T is the temperature, q is the elementary charge and n2is silicon intrinsic carrier concentration. The corresponding dielectric constant of silicon, So is the permittivity of vacuum. The generic analytical expressions are for a 1 -dimensional abrupt junction and under the full-depletion approximation. A fabrication skew is performed to determine the distance between the p- type regions (defining the width of the channel, W), and IV=700 nm is selected as it provides switching of the MNC device from the off-state (overlap of the lateral depletion regions of the lateral p-n junctions) to the on-state. The length of the channel is set to 10 pm to avoid short channel effects.

[0288] Standard CMOS silicidation is performed in all regions in which the aluminum metal lines interface the silicon to ensure low resistance ohmic contacts. The gate dielectric (active region or sensing area) is 5.5 nm of thermal oxide. The MNC biochip is passivated with 1 pm of SiO2 except the electrical pads and the sensing area.

[0289] Formation of the biorecognition layer composed of anti-NAGase antibodies. The biorecognition layer was firstly developed and physically characterized on Si / SiO2 (5-10 nm SiO2) substrates. The substrates were sonicated for 2 minutes and rotated for 1 minute with ethyl acetate, acetone, 2-propanol, and deionized (DI) water, successively. The substrates were immersed in piranha solution (4:1 H2SO4:H2O2) for 4 minutes for the purpose of surface activation. The substrates were rinsed with DI water, N2 dried, and immersed for 3 hours in a 0.1% v:v solution of 3-aminopropyltrimethoxysilane (APTMS) in methanol. Leftover APTMS was discarded with multiple cycles of methanol sonication and rinsing. The samples were hydrolysed for 24 hours and baked for 1 hour at 120 °C for durability and stabilization. The substrates were placed in a 0.5% glutaraldehyde (GA) crosslinker solution, and afterwards immersed for 12 hours at 4°C in a 10 mM pH 7.4 Tris- Buffered Saline (TBS) containing 1 pg / ml of anti-NAGase antibodies (MBS2001469, MyBioSource). Finally, the samples were washed with 10 mM PBS solution and dried with N2. Electrochemical Impedance Spectroscopy (EIS, Palmsens 4, Palmsens Inc.) was used to characterize the various modification steps. The measurements were performed in a pH 7.4 0.1 mM PBS. The sample was measured in a three-electrode 0.8 mL electrochemical cell. The back side of the silicon substrate (the working electrode) was manually scratched and contacted with a conductive carbon paint. SEC-C Pt Gauze working electrode (ALS Japan) was the selected counter electrode, and RE- IBP (Ag / AgCl) by ALS Japan was the selected reference electrode. Further surface physical characterization was performed with spectroscopic ellipsometry (Alpha-SE Ellipsometer, J.A. Woollam), and contact angle tensiometer (Model OCA 20, dataphysics). The above biofunctionalization steps were performed on the MNC bioFETs.

[0290] Formation of the biorecognition layer composed of anti-AFP antibodies. The MNC decorated with devices were biofunctionalized and transformed into MNC biosensors. The biofunctionalization was first developed on plain silicon samples (2 X 2 cm) 5 nm of SiCh. The various involved biofunctionalization steps were characterized by electrochemical impedance spectroscopy (EIS) (Palmsens 4, Palmsens Inc.), contact angle tensiometer (Model OCA 20, dataphysics), and spectroscopic ellipsometry (J.A. Woollam Alpha-SE Ellipsometer). The samples were successively cleaned with ethyl acetate, acetone, and 2- propanol for 2 min in a bath sonicator for each cleaning step. The cleaning was followed by surface activation with piranha for 4 minutes (4: 1 ratio of H2SO4:H2O2), DI water wash and N2 drying. The next step was surface chemical modification with 3- aminopropyltrimethoxysilane (APTMS) linker molecules. The samples were incubated in APTMS solution (0.1% v:v in methanol) for 3 hours, followed by three cycles of 3 minutes each of sonication in methanol. The samples were hydrolyzed by 24 hours incubation in DI water, dried and placed in an oven for 1 hour at 120°C [M. Zhu, M. Z. Lerum, W. Chen, Langmuir 2012, 28, 416-423. DOI 10.1021 / la203638g]. Prior to the binding of the anti- AFP antibodies, the APTMS was modified with glutaraldehyde (GA) (SAB4501531- 100UG, Sigma Aldrich). Finally, the samples were incubated for 12 hours in 1 pg / ml solution (10 mM PBS, pH 7.4) of anti-AFP (Abeam, AB-ab3980). The MNC chips were biofunctionalized in a similar manner. The various involved biofunctionalization steps were characterized by electrochemical impedance spectroscopy (EIS) (Palmsens 4, Palmsens Inc.), contact angle tensiometry (Model OCA 20, dataphysics), and spectroscopic ellipsometry (J.A. Woollam Alpha-SE ellipsometer). The contact angle of anti-AFP modified chip was 52°± 0.5° and the measured thickness of the anti-AFP layer was 2.2 ± 0.8 nm. Surface binding of anti-ferritin and surface characterization. The tethering of antiferritin antibodies to SiCh surfaces was developed using silicon substrates with a 10 nm decoration of SiCh. The substrates were rinsed with ethyl acetate for two minutes in a sonicator and rotated for another minute. This procedure was then repeated for acetone, 2- propanol, and deionized (DI) water. The substrates were submerged in a piranha solution (4: 1 H2SO4:H2O2) for a duration of four minutes for the formation of surface hydroxyls, washed with DI water, and dried with N2. The substrates were submerged for three hours in a 0.1% v:v solution of 3-aminopropyltrimethoxysilane (APTMS) in methanol, and sonicated and rinsed in methanol for several times in order to remove unbound APTMS. The APTMS-bound samples were incubated for 24 hours in DI water for hydrolysis, and then baked in a furnace for one hour at 120°C. The substrates were submerged in 0.5% glutaraldehyde (GA) crosslinker solution and placed on a rotator for 80 minutes at 80 rpm, and then washed with a 10 mM pH7.4 PBS. The samples were incubated at 4°C for twelve hours in 1 pg / ml of anti-ferritin (AB33574, ABCAM) in 10 mM PBS buffer at pH 7.4. The modified samples were characterized using ellipsometry (Alpha-SE Ellipsometer, J.A. Woollam), contact angle tensiometer (Model OCA 20, dataphysics), and electrochemical impedance spectroscopy (EIS) (Palmsens 4, Palmsens Inc.). The EIS was performed in an electrochemical cell containing 0.8 mL of 10 mM pH7.4 phosphate-buffered saline (PBS). An Ag / AgCl reference electrode (RE- IBP, ALS Japan), and a platinum counter electrode (SEC-C Pt Gauze working electrode, ALS Japan) were employed. The bottom side of the samples (working electrodes) was scratched and applied with a conductive carbon paint. The developed surface modification protocol was applied to the functionalization of the BioFETs. The contact angle of anti-Ferritin modified chip was 37°± 0.8° and the measured thickness of the anti-Ferritin layer was 1.9 ± 0.5 nm.

[0291] NAGASE electrical and sensing measurements. A fully equipped probe station was employed for the electrical measurements. Probe needles were used to contact the MNC biochip aluminum pads to the source measuring units (SMUs) (B1500 semiconductor parameter analyzer, Keysight Ltd). 0.5 |1L drops of unfiltered and undiluted 3% commercial milk (for milk content) were drop cast on the MNC bioFET. The gating of the milk was performed by an Ag / Ag+ quasi-reference electrode (additional or sample electrode, e.g., electrode 154 in Fig. 1) realized from a commercial reference electrode (012171 RE-7, ALS Co., Ltd); the glass holder of the reference electrode was detached, and the exposed Ag wire was decorated with an Ag / AgCl ink (011464, ALS Co., Ltd). The quasi-reference electrode was mounted on a probe holder and connected to the B 1500 SMU for potential determination (VG ) and leakage current measurement. The NAGase biomolecules were purchased from MyBioSource (MBS2012338, MyBioSource). The considered molecular weight of the NAGase is 33 kDa.

[0292] AFP electrical and sensing measurements. The MNC devices were electrically measured on a probe station with probe needles contacting the chip metal pads to source measuring units (SMUs) of the B1500 semiconductor parameter analyzer by Keysight Ltd. A neutral solution of 0.1 mM pH 7.4 phosphate-buffered saline (PBS) with a volume of 0.5 pL was manually applied with a pipette to the MNC sensing area. The drop was electrically contacted with a quasi-reference electrode made of an Ag / Ag+reference electrode (012171 RE-7, ALS Co., Ltd) where the glass holder was removed by exposing the Ag wire which was coated with an Ag / AgCl ink for reference electrode (011464, ALS Co., Ltd). The quasi-reference electrode (VG ) was connected to an additional B1500 SMU for determining potential of the solution. The quasi-reference electrode was mounted on a probe manipulator. The drop lifetime before evaporation is 2-3 minutes, which provides a time window for the various current-voltage (LV) measurements. The I-V measurements were repeated during the drop lifetime, and the measurements were performed for successive applied drops in order to confirm and establish repeatability. The measurements in neutral solution were performed solely during the process of MNC device biofunctionalization in order to validate device functionality post modification. The excellent repeatability of unmodified MNC devices and biofunctionalized MNC biosensors ensure the buffer capacity of the small solution drops [R. E. G. Van Hal, et al. Sensors Actuators B 1995, 24-25, 201], as well as the stability of the quasi-reference electrode for possible drop-to-drop variations [L. R. E. Allen J. Bard, Electrochemical Methods: Fundamentals and Applications, 2nd Edition, John Wiley And Sons Inc., 2008].

[0293] The ALP sensing measurements were performed with 0.5 pL drops of 1: 100 diluted serum obtained from Kaplan Medical Center blood bank. The dilution of the serum was performed with Tris-Buffered saline (TBS) 0.1 mM pH 7.4. Mixtures of diluted serum spiked with different concentrations of AFP (Abeam, ab 114216) were prepared. The serum drop was biased in the same manner described for the neutral solution drop. The stability of the quasireference electrode with respect to drop-to-drop variations of the diluted serum [L. R. F. Allen J. Bard, Electrochemical Methods: Fundamentals and Applications, 2nd Edition, John Wiley And Sons Inc., 2008], and non-specific adsorption of biomolecules (on the quasi-reference electrode) was addressed by the non-specific measurements (Figure 11C). Successive I- V measurements were performed for a diluted serum drop in order to validate and establish repeatability. Afterwards, the diluted serum drop was collected with a cleanroom wipe, and a new drop spiked with a higher AFP concentration is introduced on the MNC sensing area, and the procedure was repeated. The non-specific measurements were performed in the following manner: AFP was introduced to an unmodified MNC device, and AFP was introduced to an MNC modified with APTMS. Also, human chorionic gonadotropin (hCG) hormone (Sigma- Aldrich, hCG-C1063), and prostate specific antigen (PSA) (Sigma Aldrich, P3338-25UG) physiological biomarkers were introduced to MNC biosensor modified with anti- AFP antibodies. hCG was selected as a different glycoprotein type of biomarker with a dimer consisting of a 145 amino acid beta- subunit that is unique to hCG and a 92 amino acid alpha-subunit, having a molecular weight -37 kDa. Similarly, PSA is a 237 amino-acids long single chain glycoprotein with a molecular weight of ~28 kDa. AFP is a glycoprotein which consists of a polypeptide chain with 591 amino acids and a carbohydrate chain with a molecular mass of -68.8 kDa. For all the non-specific measurements, the concentrations of the biomarkers (AFP, PSA and hCG) were 10 ng / ml, 100 ng / ml, and 1 pg / ml corresponding with the highest AFP concentrations (equivalent to 105pM, 1.05nM and 10.5nM, respectively) considered in this work for the specific measurements. The excellent repeatability of the non-specific measurements also removes the concern of pH fluctuations due to the presence of biomolecules in the drops [R. E. G. Van Hal, et al. Sensors Actuators B 1995, 24-25, 201].

[0294] Ferritin sensing measurements in 1:100 diluted plasma. The electrical measurements are performed with the B 1500 Semiconductor parameters analyzer (SPA) by Keysight Ltd. The chip is placed on a probe station and probe needles electrically connect the chip with the SPA source measuring units (SMUs). Plasma (supplied by Kaplan hospital center blood bank, Israel) is diluted 1: 100 with a Tris-buffered saline (TBS) 0.1 mM pH 7.4. The 0.5 pL drop of 1: 100 diluted plasma, with or without target molecules, is manually applied to the BioFET sensing area using a pipette. The size of the drop is considerably larger than the size of the sensing area, and it is ensured that the drop does not reach the pads nor the edges of the chip. The solution potential is determined by contacting the drop with a pseudoreference electrode which is connected to an SPA SMU (Vro / ). To this end an Ag / Ag+ commercial reference electrode (012171 RE-7, ALS Co., Ltd) is employed where the glass holder and removed and the exposed Ag wire is applied with Ag / AgCl ink (011464, ALS Co., Ltd). The pseudo-reference electrode is steadily positioned using a probe manipulator. The 1:100 diluted plasma is spiked with ferritin molecules (AB281293, ABCAM) to conclude samples of diluted plasma with ferritin concentrations in the range of 1 fg / ml to 10 pg / ml. In a similar manner, for the non-specific control measurements, samples of 1 : 100 diluted plasma are spiked with prostate specific antigen (PSA-P3338, SIGMA- ALDRICH) and alpha fetoprotein (AB 114216, ABCAM).

[0295] Determination of specific sensing signal (for ferritin). Various current-voltage (LV) measurements are performed for each drop (described in the Results and discussion section), and each different LV is repeated for three times for each drop. A population of identical LV curves is defined by X ± a where X and o are the average and standard deviation, respectively. The specific sensing is extracted by the evaluation of two criteria: 1) A baseline composed of 18 drops (0.5 pL 1: 100 diluted plasma) applied successively, where each drop is measured for three time, is formed. The baseline average difference between drops is extracted. A data point is considered as specific sensing only if the difference between two successive drops (=populations), containing two different ferritin concentrations, is higher than the baseline average difference. 2) Control non-specific measurements are performed. A data point is considered as specific sensing only if the difference between two successive drops (=populations), containing two different ferritin concentrations, is higher than the difference between the corresponding non-specific populations. Numerical calculations (for ferritin). Advanced TCAD by Synopsys (Mountain View, CA, USA) is employed for the two-dimensional (2D) three-dimensional (3D) device calculations. At every mesh point, the Poisson and Continuity equations are solved considering doping dependent mobility. The 1:1 electrolyte (permittivity set to 80) is emulated as a semiconductor with a forbidden gap (Eg) of 1.5 eV to ensure Boltzmann statistics [I. M. Bhattacharyya and G. Shalev, ACS Sens, 2020, 5, 154-161; I.-Y. Chung, et al. Nanotechnology, 2012, 23, 065202]. The anion and cation concentrations are considered as NAV x co x 10’3cm'3where NAV and c(> are the Avogadro constant and the solution ion molar concentration, respectively. The effective density of states of the conduction band (Ac) and valence band (Nv bands are considered as: Nc= Nv= [E. Mohammadi and N. Manavizadeh, IEEE Trans Electron Devices, 2018, 65, 3950-3956]. The mobility values of the anion and cation are set topmax=4-.98xl0'4cmV's1and pnmax = 6.88xl0'4em 's'1respectively to reflect Na+and Cl' ions in an NaCl solution [S. Koneshan, Jet al. J Phys Chem B, 1998, 102, 4193-4204]. Finally, in order to reach the expected surface potential of -100 mV for SiCh at pH 7 [R. E. G. van Hal, J. C. T. Eijkel and P. Bergveld, Adv Colloid Interface Sci, 1996, 69, 31-62], the affinity of the solution is set to 3.957 eV.

[0296] Development and characterization of the Anti-CRP Antibody Biorecognition Interface. The development and characterization of the biorecognition interface utilize 1.5 cm x 1.5 cm silicon samples coated with a 5 nm SiO2 layer. The cleaning process involves ethyl acetate, acetone, 2-propanol, and deionized (DI) water, with each step performed for 2 minutes in a sonicator, followed by 1 minute of rotation and desiccate with an N2 stream. Surface activation, creating surface hydroxyl groups, is achieved using a piranha solution (4: 1 H2SO4) for 5 minutes. After purging with DI water and desiccate with an N2 stream, the samples are incubated in a 0.1% v / v solution of 3-aminopropyltrimethoxysilane (APTMS) in methanol for 3 hours. Excess APTMS is removed by subjecting the samples to sonication and multiple methanol rinses. Subsequently, the samples are immersed in DI water for 24 hours to facilitate hydrolysis, thereby promoting the extension of amine functional groups from the surface. To ensure stabilization and durability, the samples are annealed in an oven at 120°C for 1 hour. The subsequent step involves the immobilization of anti-CRP antibodies on the SiCh surface. The samples undergo immersion in a 0.5% glutaraldehyde (GA) solution for 45 minutes using a digital rotator set at 90 RPM to establish an anchoring point for the antibodies. Excess GA is removed through purging with 10 mM PBS in multiple cycles. Following this, the samples are subjected to incubation for 12 hours in a solution containing 10 pg / ml of anti-CRP (C3527, Sigma- Aldrich) in 10 mM TBS buffer at pH 7.4, maintained at 4°C. Any unbound anti-CRP is eliminated through multiple washes with 10 mM TBS, followed by desiccate with an N2 stream. The selected incubation duration ensures optimal surface coverage by the antibody molecules while preventing the formation of multiple layers due to the tailored surface chemistry. Characterization of the biorecognition interface steps electrochemical impedance spectroscopy (EIS) (Palmsens 4, Palmsens Inc.). EIS measurements are performed in a 10 mM PBS buffer at pH 7.4. The sample is placed in a three-electrode electrochemical cell (0.8 mL). The backside of the silicon working electrode is scratched and contacted with conductive carbon paint. A Pt wire (SEC-C Pt Gauze working electrode, ALS Japan) serves as the counter electrode, and an Ag / AgCl electrode (RE- IBP, ALS Japan) functions as the reference electrode. Further surface physical characterisation is conducted using contact angle tensiometer (Model OCA 20, dataphysics) and spectroscopic ellipsometry (Alpha- SE Ellipsometer, J.A. Woollam). The same protocol is applied to the FET biochip device.

[0297] FET biochip electrical measurement in whole blood (for CRP)

[0298] Electrical measurements are executed on a probe station, where the aluminum pads of the FET biochip are contacted with probe needles connected to source measuring units (SMUs) using the Bl 500 semiconductor parameter analyzer from Keysight Ltd. Measurements utilize 0.5 pE drops of whole blood, manually applied to the FET biochip sensing area with a pipette. The drop size is deliberately larger than the sensing area to ensure it does not reach the pads or the chip's edges. An Ag / Ag+quasi-reference electrode is used to gate the whole blood. This electrode is created from a commercial reference electrode (012171 RE- 7, ALS Co., Ltd) by removing the glass holder and coating the exposed Ag wire with Ag / AgCl ink (011464, ALS Co., Ltd). The quasi-reference electrode is mounted on a probe holder and linked to the Bl 500 SMU for potential determination (VG ). CRP biomolecules are obtained from antibodies (A60981, antibodies). EXAMPLE 1

[0299] MNC biosensor biofunctionalized with antibodies

[0300] Figure 4A presents an illustration of the silicon MNC biosensor. The MNC biosensor is an accumulation-mode FET where the source-drain current IDS) is composed of conducting electrons. The MNC biosensor includes six gates: the front gate which sets the solution potential (VGF), backgate (VGB), two lateral gates (VGLI, VGL2), and two transverse gates (VGTI, Ven)- VGTI VGT2 are not considered in the current work [I. M. Bhattacharyya, et al. Adv Electron Mater, 2022, 8, 2200399; I. M. Bhattacharyya, et al. Nanoscale, 2022, 14, 2837-2847]. VGF is a commercial quasi-reference electrode, and in the following VGLI = VGL2- Importantly, the drop size is larger than the MNC sensing area, and it is insulated from the contacts by a SiCh passivation layer (not illustrated for the purpose of clarity). Every configuration of VGF, VGB, VGLI and VGL2 generates corresponding depletion areas in the channel volume which determines the size, shape, and location of IDS, as presented in the representative cross-sections of Figure 4A. In general, the channel volume can accommodate three main channels: top, middle and bottom channels, as illustrated in Figure 4A. Any combination of these three channels can be excited, and each channel can take different size, shape and location which depend on the depletion regions generated by the surrounding gates. In fact, every data point in an IDS-VGL curve, for example, defines a unique shape, size, and location of IDS- This is in contrast with the known MOSFET where gating affects primarily the density of IDS conducting carriers, but not the size, shape, and location of IDS- This is at the heart of the MNC biosensor discussed herein: as the distribution of antibody-antigen complexes at the sensing area is unknown, there is a need to tailor an IDS to couple best to this unknown distribution. In other words, there is a need to tailor an IDS to translate the non-uniform surface potential, induced by the biological complexes, to a significant variation in IDS- This inherent challenge of biological sensing with FET devices is addressed by the MNC biosensor discussed by the present disclosure. The conduction channel of the MNC biosensor channel is formed at the channel volume and is composed of electron majority carriers. The channel volume is laterally bound on both sides with p-type regions forming pn junctions. The p-type regions are electrically connected to aluminum lines and form the lateral gates (VGL)- The backgate (VGB) is grounded throughout the current study. The solution potential is determined by a commercial quasi-reference electrode (VGF, see experimental procedures). The importance of the tuneability of the MNC biosensor conducting channel is to address the non-uniform distributions of biological complexes post binding [Bhattacharyya, I. M. et al. Adv Electron Mater (2022) doi:10.1002 / aelm.202200399; Bhattacharyya, I. M. et al. Nanoscale 14, 2837-2847 (2022); Ron, I. et al. Sens Actuators B Chem 393, 134171 (2023); Samanta, S. et al. Adv Mater Technol (2023) doi: 10.1002 / admt.202202200]. Moreover, the presence of the lateral gates serves additional two goals: 1) the transistor can be swept from off-state to on-state independently of the solution potential. In this way the solution remains in equilibrium conditions during the measurement. 2) IDS-VGL sweeps can be performed with different solution potentials (different values of VGF - In this way the conditions at the double layer are altered such to affect the interactions. This can potentially produce enhanced transduction of the biological events to an electrical current.

[0301] Figure 4A also illustrates the biorecognition layer composed of surface bound affinity moieties (e.g. antibodies specific for the target molecule, e.g., NAGase, AFP, Ferritin, CRP etc.) at the sensing area. The surface biofunctionalization is developed on Si / SiCF substrates and afterwards applied to the MNC biochip. Briefly, the MNC biochips are thoroughly and sequentially cleaned with ethyl acetate, acetone and isopropyl alcohol each for 2 minutes sonication, and dried with N2. The MNC biochips are hydroxylated by 4 minutes immersion in piranha, followed by DI wash and N2 dry. The MNC biochips are immersed for 3 hours in methanol with 1: 100 concentration of (3- aminopropy)triethoxysilane (APTMS) to serve as the linker layer, and afterwards are sonicated in methanol for three cycles each for a duration of 2 minutes. The MNC biochips are then hydrolyzed for 15 hours, dried with N2, and placed on hot plate at 120°C for 1 hour. The MNC biochips are immersed in 10 mM phosphate buffer saline (PBS), placed on a rotator at 80 RPM for 5 minutes, and dried with N2. Afterwards the MNC biochips are immersed in 0.5% glutaraldehyde (GA), placed on a rotator at 80 RPM for 40 minutes, washed with 10 mM PBS and dried with N2. The MNC biochips are placed in a solution containing the affinity molecules (e.g. 0.1 mM PBS solution containing 1 pg / ml concentration of anti-NAGase antibodies for 12 hours at 4°C, 12 hours incubation in 1 mM PBS containing 1 pg / ml of anti-AFP, 1 pg / ml of anti-Ferritin in 10 mM PBS buffer at 4°C for 12 hours, or 12 hours in a solution containing 10 pg / ml of anti-CRP (C3527, Sigma- Aldrich) in 10 mM TBS buffer at pH 7.4 at 4°C). Finally, the MNC biochips are washed with 10 rnM PBS solution and dried with N2.

[0302] Figure 4B presents a scanning electron microscopy (SEM) cross-section of the MNC biosensor halfway between source and drain which shows the device layer (the device layer accommodates the channel volume in which the various channels are generated electrostatically, as illustrated in the cross-sections of Figure 4A), the buried oxide (BOX), the SiO2 passivation, and VGLI, VGL2 contacts (i.e., the associated metal lines, contacts and silicide areas are shown). The 6 nm thick sensing area (gate dielectric) is also labeled.

[0303] Figure 4C presents an optical image of the MNC biochip in which the contacting of the MNC biochip electrical pads with the probe needles are evident, as the applied drop and the quasi-reference electrode, VGF- VD and Vs are the drain and source voltages, respectively.

[0304] EXAMPLE 2

[0305] MNC biosensor biofunctionalized with anti-NAGase antibodies (background measurements)

[0306] Figure 5A presents IDS-VGL curves for selected VGF values performed for MNC biosensor biofunctionalized with anti-NAGase antibodies. The measurements are performed for 20 successive 0.5 pL drops of 3% commercial milk in the following manner: (1) a drop of milk is applied manually with a pipette on top of the MNC biochip at the location of the active sensing area, (2) IDS is measured 3 times for all the selected VGF values, (3) the drop is collected with a wet (deionized water) clean room wipe, (4) another drop of PBS 10 mM pH 7.4 is applied and removed in the same manner in order to wash the MNC biochip from leftover 3% milk, (5) the PBS drop is removed with a wet (deionized water) clean room wipe, and (6) the next drop of 3% milk is applied. The data points of the IDS-VGL curves are the averages of all 20 measurements and the corresponding standard deviations are plotted as well but not noticeable due to the high repeatability; the inset of Figure 5 A presents a selected data point with the enlarged standard deviation. Figure 5A reflects the excellent repeatability and robustness of the MNC biosensor post surface biofunctionalization. The excellent repeatability removes concerns related to pH fluctuations generated by the presence of humans, potential variations due to quasi-reference (sample) electrode potential instability, and non-specific adsorption on either the MNC sensing area and / or the quasi-reference electrode. Any of the above mechanisms will be reflected in lack of repeatability, and therefore the excellent repeatability removes these concerns.

[0307] Figure 5B presents the second derivatives of the IDS-VGL curves presented in Figure 5A in which a peak formation represents channel excitation (bottom, middle, top, as presented in the illustrated cross-section in Figure 4). It should be noted that higher VGF implies less depletion and therefore lower VGL for a given channel excitation. Also, it should be noted that post excitation the shape and size of any channel keeps changing with increasing VGL, and therefore the inventors consider a unique channel configuration for each VGL value.

[0308] EXAMPLE 3

[0309] IDS-VGL curves for selected VGF values performed for MNC biosensor biofunctionalized with anti-NAGase antibodies (loaded with 3% milk spiked with NAGase)

[0310] Figure 6 shows IDS-VGL curves for selected VGF, both on linear and logarithmic scales, and for 0.5 pL drops of 3% milk spiked with NAGase concentrations ranging from 30.3 aM to 3.03 pM (equivalent to Ifg / ml to lOpg / ml). The drops are applied in increasing order from lowest NAGase concentration to highest. The application of the drops and the measurements are performed in the same manner as described in Figure 5A only in this case the drops are spiked with NAGase. Figure 6A presents the IDS-VGL curves for VGF of 0V and -0.5V and Figure 6B presents the IDS-VGL curves for VGF of -1.0V and -1.5V. The data points are the average of the 3 in-drop measurements and the error bars are the corresponding standard deviations which can hardly be discerned due to the excellent repeatability of the MNC biosensor. The inset presents a representative enlarged data point in which the error bars are evident. Next to each IDS-VGL curve is the corresponding I normalized curves defined as In rmaiized = (INAGOSC - Imiik) / 1 milk where INAGASB and Imiik are IDS values measured for a sample spiked with NAGAse and milk sample without NAGase, respectively. The channel configuration is indicated at the top of the figure, as determined in Figure 5B. For example, for VGF = 0 V and VGL = 0.4 V the excited channels marked in Figure 6A are TMB, which is in agreement with Figure 5B where VGF = 0 V already implies that T and M channels are normally-on (IDS is not closed) and B channel is also excited for VGL > 0.3 V. The data points, the error bars and the insets follow the convention described for the IDS-VGL curves.

[0311] The monotonous increase in IDS and INormaiized with NAGase concentrations suggests the introduction of positive charges to the sensing area upon complex formation. Importantly, the repeatability measurements presented in Figure 5A exclude the possibility of monotonous IDS increase due to non-specific protein adsorption (a background concentration of 33 mg / ml) associated with the application of successive drops. The IDS- VGL and INormaiized curves reflect the dependency of the sensing signal on the channel configuration. For example, note how INormaiized values reach -300 and -17 for NAGase concentration of 3.03 pM for middle channel V7; / =-0.5 V configuration, and top-middle channel V7; / =0 V configuration, respectively.

[0312] Two additional non-specific control measurements are performed and presented in Figure 7. The control measurements are performed for the same biasing conditions performed in Figure 6 and four representative NAGase concentrations are considered. The first set of control measurements is performed for the application of NAGase to an unmodified MNC biosensor, and the other set is performed for the application of NAGase to MNC biosensor modified with APTMS. In both cases, both IDS-VGL and INormaiized curves show negligible and non-monotonous response compared with the data of Figure 6.

[0313] EXAMPLE 4

[0314] Calibration curves for the specific and label-free sensing of NAGase

[0315] Next, the specific sensing performance was extracted from Figure 6 and 7. To this end, a drop population is defined as (X) ± (a), where X is the average of the three in-drop measurements and a is the corresponding standard deviation. Specific sensing is determined provided the following two criteria are fulfilled: 1 ) The difference between two successive drops (=two different NAGase concentrations) is higher than the natural difference between two identical drops of milk containing no NAGase of Figure 5A. First, the average difference between consecutive drops, for the 20 drops in Figure 5A, is extracted. Next, the difference between populations of consecutive drops of Figure 6 is extracted. A data point in Figure 6 is recognized for specific sensing once the difference between populations, of two consecutive drops (=two NAGase concentrations), is greater than the respective average difference between the 20 drops baseline of Figure 5B. 2) The difference between iNormaiized of two consecutive drop populations of Figure 6 is higher than the respective difference between INormaiized of two consecutive drop populations of Figure 7 (non-specific measurements). The NAGase concentration of Figure 7 selected for the comparison with Figure 6 is the one with the smallest NAGase concentration still greater than the concentration of the respective ones in Figure 6. The resulting extracted calibration curves, for the specific and label-free NAGase sensing, for the various channel configurations are presented in Figure 8 where the averages and the standard deviations (error bars) are as calculated in Figure 6. As shown, a number of calibration curves are determined for different gate potential VGL and sample potential VGF are determined. It should be noted that each curve in Figure 8 presents a calibration curve measured for a specific channel configuration. The insets on the right illustrate the channel configuration, in open circle, midway between source and drain based on the second derivatives analysis presented in Figure 5A.

[0316] Accordingly, to provide selected dynamic range for detection of NAGAse concentration, the bio-transistor system may operate using one or more (or two or more) different values of sample potential VGF, while determining source-drain current to a selected number of gate potential values VGL (or VG in accordance with specific one or more gates being used).

[0317] The sensing performance is summarized in Figure 9 that presents Table 1 showing the sensitivity, linearity, dynamic range and LOD for selected gates’ voltages. The channel configuration, in open circle, midway between source and drain, follows the analysis presented in Figure 5B. Only channel configurations with linearity of > 0.97 and a dynamic range of at least 9 orders of magnitude in NAGase concentrations are presented. Note that VGF=-1.5 V concludes sensing performance with excellent sensitivity, linearity of 0.97, a dynamic range of 11 orders and an LOD of 30.3 aM. Also, note that the lower part of the dynamic range varies with VGF (i.e., 30 aM for VG =-1.5 V, 303 aM for VGF=-1 V, 3.03 fM for V; / =-0.5). This suggests that Kd depends on VGF as this determines the pH level, ion concentrations and electric fields at the sensing area diffused layer. It should be noted that 30.3aM, 303aM, 3.03fM, 303fM, 3.03pM, 30.3pM, 303pM, 3.03nM, 30.3nM and 303nM NAGase corresponds to Ifg / ml, lOfg / ml, lOOfg / ml, Ipg / ml, lOpg / ml, lOOpg / ml, Ing / ml, lOng / ml, lOOng / ml, Ipg / ml and lOpg / ml NAGase, respectively.

[0318] EXAMPLE 5

[0319] MNC biosensor biofunctionalized with anti-AFP antibodies (background measurements)

[0320] Figure 10 shows the dependency of IDS on VGL for different VGF values measured with a 0.5 pL drop of 1: 100 diluted serum for an unmodified MNC device. Each curve was an average of 16 drops and each drop was measured 4 times with a total of 64 measurements. The inset shows a magnification of the data points showing the errors bar reflecting the standard deviations of the 64 measurements. The data presents an excellent repeatability of an unmodified MNC device in 1: 100 diluted serum. The repeatability removes the concern of drop-to-drop pH fluctuations [R. E. G. Van Hal, J. C. et al. Sensors and Actuators B, 1995, 24-25, 201-205], and establishes the potential stability of the quasi-reference electrode under possible drop-to-drop variations [L. R. F. Allen J. Bard, Electrochemical Methods: Fundamentals and Applications, 2nd Edition, John Wiley and Sons Inc., 2008]. The dependency of IDS on VGL and VGF is detailed below in Figure 12 for MNC biofunctionalized with AFP-antibodies.

[0321] EXAMPLE 6

[0322] Process of Si / SiCh surface biofunctionalization with anti-AFP antibodies

[0323] Figure 11A illustrates the main steps towards sensing area biofunctionalization with anti- AFP antibodies [I. M. Bhattacharyya, et al. Nanoscale, 2022, 14, 2837-2847; I. M. Bhattacharyya, et al. Adv. Electron. Mater. 2022, n / a, 2200399]. In short, the Si / SiO2 sensing area was activated with piranha followed by surface chemical modification with APTMS linker molecules, and final surface-tethering of the anti-AFP antibodies (see Experimental procedure). Figure 11A also presents the corresponding contact angle measurements. The surface modifications were developed and characterized using 1 cm x 1 cm samples of silicon substrates decorated with 5 nm SiO2 (Figure 11B-11C). Figure 11B presents contact angle measurements for Si / SiCh samples post piranha activation, post APTMS modification and surface biofunctionalization with anti-AFP antibodies. The measurements are performed at three locations on the samples with two measurements performed at each location, such that the data points and the error bars reflect the averages and standard deviations, respectively, of six measurements. The contact angle dependency on the various surface modifications follows behavior well documented previously [R. G. Frieser, J. Electrochem. Soc. 1974, 121, 669; Z.-Z. Liu, et al. Thin Solid Films 2008, 517, 635]. Figure 11B also shows ellipsometry measurements performed on the same Si / SiCh samples. First, the SiCF sample is measured and the 5 nm SiCF thickness is validated. Afterwards, the sample is measured post APTMS modification where the SiCF is fixed and the APTMS thickness is fitted. Finally, the sample is measured post surface biofunctionalization with anti-AFP antibodies where both the SiCF and the APTMS thicknesses are fixed to the measured values and the antibody layer is fitted. The mean square error (MSE) for all measurements is smaller than 2. The thicknesses presented in Figure 11C reflect the expected values of APTMS and the antibody layer [I. M. Bhattacharyya, et al. Nanoscale 2022, 14, 2837; K. Bierbaum, et al. Langmuir 1995, 11, 512; I. M. Bhattacharyya, et al. Adv. Electron. Mater. 2022, 2200399]. Figure 11C presents the EIS measurements of the imaginary capacitance (C”) vs. the real capacitance (C’) for unmodified Si / SiCh, post APTMS modification and post biofunctionalization with anti- AFP antibodies. Three distinct curves are shown, which reflect the effect of the modifications on the sensing area. The capacitance post APTMS modification is not significantly different from the unmodified sample, but the presence of an antibody layer is well reflected in the formation of an additional semi-circle characteristic of the generation of an additional layer. Finally, the biofunctionalization is applied to an MNC biosensor and Figure 11D shows IDS VS. VGL for different VGF values performed for unmodified, and MNC modified with anti-AFP antibodies. All the measurements are performed for 0.5 pL drops of 0.1 mM 7.4 pH PBS solution. Three drops are measured for the unmodified MNC biosensor, and three drops are measured for the modified MNC biosensor, and each drop is measured four times. Figure 11D presents an excellent robustness and repeatability of a modified MNC device in 0.1 mM 7.4 pH PBS solution, as well as asserts the stability of the quasi-reference electrode under possible drop-to-drop variations [L. R. F. Allen J. Bard, Electrochemical Methods: Fundamentals and Applications, 2nd Edition, John Wiley And Sons Inc., 2008]. Finally, the repeatability addresses the concern of possible drop-to-drop pH fluctuations [R. E. G. Van Hal, J. C. T. Eijkel, P. Bergveld, Sensors Actuators B 1995, 24-25, 201].

[0324] EXAMPLE 7

[0325] IDS-VGL for selected VGF values for MNC biosensor modified with anti-AFP molecules Figure 12A presents IDS-VGL for the selected 6 VGF values of MNC biosensor modified with anti-AFP measured in 1:100 diluted serum. The contact angle of anti-AFP modified chip was 52°± 0.5° and the measured thickness of the anti-AFP layer was 2.2 ± 0.8 nm. The data points and the error bars (see inset) reflect the averages and standard deviations, respectively, of 14 measured drops where each drop is measured 3 times. Note the excellent repeatability and robustness of the biofunctionalized MNC biosensor in 1:100 diluted serum. Furthermore, the repeatability reflects the buffering capability of the 0.5 pL drops of 1: 100 diluted serum [R. E. G. Van Hal, J. C. T. Eijkel, P. Bergveld, Sensors Actuators B 1995, 24-25, 201], as well as the stability of the quasi-reference electrode under possible drop-to-drop variations [L. R. F. Allen J. Bard, Electrochemical Methods: Fundamentals and Applications, 2nd Edition, John Wiley And Sons Inc., 2008]. Figure 12B presents the corresponding second derivatives of the curves presented in Figure 12A where each peak represents the excitation of a conducting channel [I. M. Bhattacharyya, et al. Nanoscale 2022, 14, 2837; A. Ortiz-Conde, et al. Microelectron. Reliab. 2002, 42, 583]. For V7; / =0 V and 0.5 V, top and middle channels were normally-on, and the back channel was excited for higher VGL values. Note that lower VGF values force a higher voltage for the excitation of the back channel. IDS is zero for V7; / =-0.5 V and low VGL, the middle channel is excited upon VGL increase (at VGL — 0.6 V), and the top channel is excited afterwards (at VGL~0A V). Obviously, lower VGF values shift the excitation of the middle and top channels to higher VGL values. Also, Figure 12B illustrates the excitation sequence of the 3 channels for the various applied voltages. Importantly, as described above, although 3 channels are discussed, in practice each combination of VGL and VGF induces the formation of IDS of a different shape and size. The measurements were performed in 1:100 diluted serum, which implies protein background concentrations of 600-800 pg / ml (primarily albumin and globulins). More control measurements are provided in Figure 12C. Figure 12C(i)-12C(iv) show the nonspecific response of the MNC biosensor for the introduction of AFP to an unmodified MNC biosensor, the introduction of AFP to an APTMS-modified MNC biosensor, and for the introduction of PSA and hCG to anti-AFP-modified MNC biosensors. The measurements were performed for 0.5 pL drops of 1: 100 diluted serum spiked with the respective target molecule concentration. In each case, the target molecule concentrations for hCG were 0.27 nM, 2.70 nM and 27.0 nM and for PSA were 0.35 nM, 3.50 nM and 35.0 nM in accordance with the 3 highest concentrations selected for AFP-specific sensing (0.11 nM, 1.05 nM and 10.5 nM). The IDS-VGL curves are very dense and the distinction between the different concentrations can be ascertained from the insets, where every data point is the average of 4 measurements performed for each drop (=concentration) and the error bars represent the corresponding standard deviations. In all cases, the negligible non-specific signals and the excellent repeatability remove the concerns of: 1) a sensing signal due to serum pH fluctuations induced by the presence of biomolecules [R. E. G. Van Hal, J. C. T. Eijkel, P. Bergveld, Sensors Actuators B 1995, 24-25, 201], 2) a sensing signal originating from physical adsorption of target molecules on the quasi-reference electrode, 3) a sensing signal due to effect of drop-to-drop variations on the quasi-reference electrode potential [L. R. F. Allen J. Bard, Electrochemical Methods: Fundamentals and Applications, 2nd Edition, John Wiley And Sons Inc., 2008], and 4) a sensing signal due to non-specific adsorption of target molecules on the MNC biosensor sensing area.

[0326] EXAMPLE 8

[0327] IDS-VGL for selected VGF values for different concentrations of AFP molecules

[0328] Next, real-time, specific, and label-free sensing of AFP molecules, from 0.5 pL drops of 1: 100 diluted serum spiked with various AFP concentrations, was demonstrated with the MNC biosensor. Figure 13A shows IDS-VGL curves for the 6 selected VGF values, on both linear and logarithmic scales, and for all 10 AFP concentrations. The data points and the error bars (see insets) reflect the averages and standard deviations, respectively, of 4 measurements performed for each drop (=concentration). In order to confirm that the measured IDS-VGL curves do reflect specific signals, the following procedure was followed. First, it is ensured that the variation between one drop to the second (variation between successive AFP concentrations) is not due to the natural variation between two successive drops. Hence, the IDS difference between two adjacent concentrations, for each VGF and VGL values, is required to be higher than the average difference between the 14 drops of Figure 12A. Second, it is ensured that the variation between one drop to the next is not due to nonspecific signals. Hence, the IDS difference between a given AFP concentration and the baseline (diluted serum without AFP), for each VGF and VGL values, is required to be higher than the corresponding non-specific measurements presented in Figure 12C. In this manner the following concerns are removed: sensing signals originating from pH fluctuations induced by the target molecules or drop-to-drop variation in pH [R. E. G. Van Hal, J. C. T. Eijkel, P. Bergveld, Sensors Actuators B 1995, 24-25, 201], non-specific adsorption on the quasi-reference electrode and the MNC biosensor sensing area, and the effect of drop-to-drop variation on the quasi-reference electrode potential [L. R. F. Allen J. Bard, Electrochemical Methods: Fundamentals and Applications, 2nd Edition, John Wiley And Sons Inc., 2008].

[0329] Figure 13B shows the Readout curves corresponding to the IDS-VGL curves of Figure 13A. The Readout was calculated as (IDSAFP-IDSbasehne) / IDsbaselme, where IDSAFPis the measured IDS for a given AFP concentration and for set values of VGF and VGL, and iDSbaselmeisthe IDS measured for 1 : 100 diluted serum without AFP spiking. Importantly, the x-axis scales were adjusted to ensure that values reflecting a null IDS (noise level) are not considered. The relevant excited channels are also marked in Figure 13B (T for top channel, M for middle channel, and B for back channel). First, the dependency of the 10.5 aM concentration, for VG / =-0.5 V and VGL=-0.7 V, is 75% which corresponds with an excited middle channel. Note how the Readout drops with increasing VGL which corresponds to the widening of the middle channel. Also, the Readout for the same 10.5 aM concentration is just about nulled for VGF=-2N and VGL=0.2 V which corresponds also to an excited middle channel. However, the former middle channel is very different in shape from the latter. The latter middle channel is further removed from the front interface (VGF=-2 V vs. V / =-0.5 V), and it is also considerably wider compared with the former channel (VGL=0.2 V vs. VGL=-0.7 V). This is the important merit of the MNC biosensor: the variety of available channels provides multitude of ways to couple the random electrostatic distribution of the biological interactions at the sensing area, and the consequential surface potential distribution, with the electrodynamics of the underlying conducing channels to provide a meaningful IDS- Next, the effect of active sensing was demonstrated and discussed. All measured channels exhibit positive Readout values which imply an overall total positive charge at the sensing area, except the middle channel of VGI --2 V. For this middle channel of VGI --2 V the Readout switches polarity: for AFP concentration range of 10.5 fM-10.5 nM the Readout increases with AFP concentration increase, but it is negative for 10.5 fM-10.5 pM and positive for 105 pM-10.5 nM. The switch in Readout polarity suggests that the four gates do not only affect the transduction of the sensing area potential into IDS, but also affects the interactions themselves, refereed to as active sensing. In other words, if the total charge distribution of the complexes at the sensing area is positive, then the Readout must be positive and cannot take negative values. As a corollary, a switch in Readout polarity suggests that the biological interactions at the sensing area are affected by the gating configuration (active sensing). The effect of VGL on biological interactions does not seem probable as VGL produces horizontal electric fields in the silicon device layer. On the other hand, VGF affects the double layer (which is also affected by the biological entities and interactions) adjacent to the sensing area. Hence, VGF determines the double layer electric field, the pH level and the ionic strength, all can potentially affect biological interactions at the sensing area [L. R. F. Allen J. Bard, Electrochemical Methods: Fundamentals and Applications, 2nd Edition, John Wiley And Sons Inc., 2008; I. M. Bhattacharyya, G. Shalev, ACS Sensors 2020, 5, 154]. Therefore, it is suggested that VGF=-2 V produces a double layer environment which results in total negative charge and a Readout decrease. Note that VGF also affects the Debye screening length at the sensing area (by the determination of surface ionic strength), but in this case the Readout is not expected to switch polarity. Figure 13C illustrates one possible mechanism to induce a switch in Readout polarity which relates to the direction of the double layer electric field determined by VGF- Such a switch in the polarity of the electric field can affect the orientation of the biological complexes and to generate either positive or negative Readout. Of course, the effect of the double layer electric field on the orientation of the target molecules also depends on the density of the surface-bound complexes, as presented in Figure 13C. Active sensing with the MNC biosensor is provided by the solution potential which affects the biological interactions indirectly by determining the conditions at the double layer. Still, more research is needed to underpin the mechanism by which VGF affects the biological interactions at the sensing area.

[0330] EXAMPLE 9

[0331] Readout calibration curves for AFP molecules

[0332] Figure 14A shows the Readout calibration curves for the considered channel configurations. The illustrations on the right of the calibration curves show the crosssections, midway between the source and drain, of the various channels visualizing the size, shape, and location of the corresponding channels. Note, that each horizontal line represents a calibration curve obtained for a different channel configuration. Also, dashed vertical grey lines indicate the ‘calibration threshold’ of the calibration curves which marks the onset of the linear region of the dynamic range. Two interesting observations are in place. First, VGL determines the sensitivity (the slope of the linear region) and lower VGL generates higher sensitivity. This directly reflects the effect of channel configuration on sensing performance. Second, active sensing is allowed as VGF affects the calibration threshold value. The dependency of the calibration threshold on VGF is presented in Figure 14B(i). Evidently, VGF affects the calibration threshold significantly in the range of three orders of magnitude in AFP concentration from 105 fM to 10.5 pM. The importance of the calibration threshold is with respect to its association with Kd. Kd is defined in accordance with the law of mass action in equilibrium: [ligand]- [receptor] -kon = [1 igand: receptor] -koff, where [ligand] and [receptor] are the concentrations or activities of the reactants, [ligand:receptor] is the concentration or activity of the complexes, and k(mand k()ff are rate constants for the forward and reverse reactions, respectively. Kd is defined as Kd = ([ligand] - [receptor]) / [ligand:receptor], such that Kd= [ligand] reflect a state in which half of the receptors are unbound and half are bound to ligands [D. B. Finlay, S. B. Duffull, M. Glass, Br J Pharmacol. 2020, 177, 1472]. Therefore, experimentally, Kd is extracted from calibration curves by intersecting the ligand concentration with the middle of the calibration curve linear region, halfway between calibration threshold and saturation. However, need to keep in mind that this description does not apply accurately to the current work as the surface-bound anti-AFP antibodies, at the MNC biosensor sensing area, do not interact with all the AFP molecules present in the 0.5 pL drop, as the surface occupied by the drop is significantly greater than the sensing area. Still, following the conventional definition of Kd, as provided above, a shift in the calibration thresholds presented in Figure 14A directly implies a shift in Kd, and the calibration threshold shift from 105 fM to 10.5 pM suggests a shift from a higher binding affinity to a lower binding affinity, respectively. Figure 14B(ii) shows the lack of dependency of the calibration threshold value on VGL- This lack of dependency is expected as VGL affects solely the electron charge carriers in the silicon, and its effect on the potential of the solid-biological interface is negligible. On the other hand, the dependency of the calibration threshold on VGF is expected, as VGF determines N+0 and the double layer conditions in terms of pH, ionic strength and electric field, each of these can potentially affect the ligand-receptor interaction.

[0333] A summary of the sensing performance is provided in Figure 15 that discloses Table 2, which presents the dependency of the sensitivity, linearity (R2), dynamic range, and LOD on channel configuration. The sensitivity, which is the slope of the linear fit in units of Readout per decade of concentration (%dec-1), and the LOD, defined as the lowest concentration with an IDS greater than the average IDS plus three standard deviations of the background diluted serum, are extracted in accordance with the IUPAC conventions [M. Nic, J. Jirat, et al. IUPAC Compendium of Chemical Terminology: Gold Book, IUPAC, Research Triagle Park, NC, 2.1.0., 2009]. The requirements for the presented performances are a dynamic range of at least four orders of magnitude, and R2higher or equal to 0.96. Highest sensitivity of 25.98 Readout / dec, for a dynamic range of 1.05 pM-10.5 nM, was measured for a narrow middle channel ( VG / =-0.5 V, VGL=-0.6 V). Note that the sensitivity exhibits a maxima behavior in terms of VGF (the sensitivity decreases for VGF smaller or greater than -0.5 V), and it is always higher for a narrow middle channel (small VGL values). Therefore, VG / =-0.5 V provides the optimal double layer in terms of sensitivity, and VGL=- 0.6 V provides the most efficient transduction of the surface potential, induced by the biological interactions, to an electronic signal. On the other hand, VG / =0.5 V provides the highest dynamic range from 105 fM to 10.5 nM, and, similar to the other VGF values, lower VGL values conclude an enhanced sensitivity. The dependency of the sensing performance on channel configuration is shown. The criteria for channel configuration selection is 7?2>0.96 and a dynamic range of at least 4 orders of magnitude. The LOD and the dynamic range are extracted in accordance with the IUPAC definition [M. Nic, et al. IUPAC Compendium of Chemical Terminology: Gold Book, IUPAC, Research Triagle Park, NC, 2.1.0., 2009].

[0334] It should be noted that 105fM, 1.05pM, 10.5pM, 105pM, 1.05nM, and 10.5nM AFP corresponds to lOpg / ml, lOOpg / ml, Ing / ml, lOng / ml, lOOng / ml and Ipg / ml AFP, respectively.

[0335] EXAMPLE 10

[0336] Illustration of a suggested BioFET for biofunctionalization with anti-ferritin antibodies

[0337] Figure 16 shows 2D numerical calculations demonstrating the effect of VS(>i on DL. Figure 16A presents 2D distributions of the electrostatic potential of a system composed of 200 nm 1016cm'3n-type (phosphorus) silicon substrate, a 6 nm SiCF and a 1 mM electrolyte solution (see Experimental procedures). The silicon is grounded, and voltage is applied to Vsoi. The electrostatic potential distributions are presented for Vs<>i = -0.5, 0, 0.5 V, where a clear variation in solution potential is evident. Moreover, the insets show the distinct DL potential levels reflecting the critical role of Vsl>i in the determination of the DL conditions. Figure 16B presents ID distributions (along the dashed lines in Figure 16A) of the electric field, and the cation and anion populations for the selected Vs<>i values. Note how the electric field reaches values of 104V / cm in contrast with the zero field at the bulk solution, and the ion concentrations differ by dozens of percents from the bulk values. The dependency of DL properties on the solution electrode voltage reflects the challenge involved with IDS- Vs<>i BioEET measurement, which perturbate the DL and the surface-bound biological molecules for the entire duration of the measurement.

[0338] Figure 17A presents a three-dimensional (3D) numerical calculation of the suggested BioFET which allows switching of the conducting channel without affecting the DL. The proposed BioFET is composed of a middle n-type (phosphorus, 1016cm'3) region which accommodates the conducting channel composed of electron majority carriers. The length of the middle n-type region is 1 pm, the width is 0.25 pm and the thickness is 0.3 pm. The middle n-type region is bordered at the bottom by a 10 nm Si CL connected to a backgate electrode (VGB). At the ends of the long axis of the middle n-type region, are the degenerated n-type source and drain regions (phosphorus, 1019cm'3). And at one end of the short axis of the middle n-type region is a degenerated p-type region (boron, 1019cm'3). The p-type region is electrically contacted and forms the side-gate (VGS). The middle n- type region is decorated with 5 nm SiCL gate dielectric, and a solution of 1 mM is considered. The electrical connections are provided in Figure 17B. Figure 17A also shows IDS-VGS curves for a fix Vs<>i = 0 V, demonstrating the switching of the conducting channel from off-state to the on-state. Figure 17B also shows 2D cross-sections of the electric potential midway between source and drain for VGS=-2 V (off-state) and VGS=0.5 V (on- state), and the insets provide the DL distributions. Clearly, the DL is not affected by the voltage application at the side gate. In this way, the side-gate allows the modulation of a channel from the off-state to the on-state, while maintaining the DL and the associated biomolecules (in a ‘real’ BioFET) at an electrochemical equilibrium during IDS-VGS measurement.

[0339] Figure 18A presents experimentally measured IDS-VGS curves for Vs<>i = -1.5 V (side-gate sweep). Vs<>i = -1.5 V is selected to ensure that the top part of the silicon device layer is deeply depleted of electron majority carriers, such that any affect, even smallest, by the side-gates on surface potential is negligible. This Vs<>i value is adopted throughout this work for the side-gate sweep. Figure 18A also presents IDS-V^I curves for VGS = -2 V (solution sweep). VGS = -2 V is selected to match the IDS level measured for the side-gate sweep to allow the analysis below. All the current-voltage (LV) curves presented in the current work are measured for drain-source voltage (VDS) of 100 mV. The measurements are performed for 0.5 pL drops of 1: 100 diluted plasma (See Experimental procedures). Each drop is measured three times for a side-gate sweep and three times for a solution sweep, removed with a clean room wipe, and the next drop is applied and measured. A total of 18 successively applied drops are measured. The data points reflect the average of the 54 measurements and the error bars are the respective standard deviations (the insets show selected standard deviations). Figure 18B presents the corresponding range and standard deviation values for the LV curves of Figure 18A. Note the elevated values of the range and standard deviation for the solution sweep in comparison with the side-gate sweep, which underline the ramifications involved with the continuous perturbation of the DL during an IDS-VSOI measurement. Next, the active sensing area of the BioFET is biofunctionalized with anti-ferritin antibodies to form a specific recognition layer. Briefly, the anti-ferritin antibodies are tethered to the sensing area (SiCh gate dielectric) using (3- Aminopropyl) trimethoxysilane and glutaraldehyde linker molecules. The biofunctionalization process and characterization are provided in the Experimental procedures section. The contact angle of anti-Ferritin modified chip was 37°± 0.8° and the measured thickness of the anti-Ferritin layer was 1.9 ± 0.5 nm. Figure 18C (presents the range and standard deviation values for BioFET biofunctionalized with anti-ferritin antibodies, for both the solution and side-gate sweeps (18 drops measured, each drop measured 3 times). Note how the values of the range and standard deviation are relatively unaltered post biofunctionalization for the side-gate sweep, while a significant increase in these is recorded for the solution sweep. This further accentuates the effect of Vs<>i on the DL in the presence of the biological molecules.

[0340] EXAMPLE 11

[0341] IDS-VGL curves for selected VGF values performed for MNC biosensor biofunctionalized with anti-ferritin antibodies

[0342] Figure 19A-19D show four control measurements performed to quantify the non-specific response. Figure 19A and Figure 19B present IDS-VGS for VGF = -1.5 V for the application of 0.5 pL drop of 1:100 diluted plasma spiked with 10 fg / ml, lOpg / ml, 10 ng / ml, and 10 pg / ml ferritin concentrations to unmodified and APTMS -modified (post hydrolysis) BioFET, respectively. Next, the MNC BioFET was biofunctionalized with anti-ferritin antibodies and subjected to the introduction of 10 fg / ml, 10 pg / ml, 10 ng / ml, and 10 pg / ml of both prostate specific antigen (PSA) (Figure 19C) and Alpha-Fetoprotein (AFP) (Figure 19D). In all cases the non-specific signals, upon the introduction of the various target molecules, is negligible and can hardly be distinguished from the baseline measurement.

[0343] The illustrations on the left of the graphs reflect the different non-specific measurements. Each data point reflects an average of 4 in-drop measurements, and the insets present magnifications showing the error bars of the corresponding standard deviations. Clearly, for all performed measurements, negligible non-specific signals are recorded which lack any dependency on target molecule concentration (this is visually presented in the insets). Also, solution sweep measurements are performed on the same drops with similar negligible non-specific signals.

[0344] Sensing of ferritin in diluted plasma is pursued next. Figure 20A presents side-gate sweep curves (Vra / =-1.5 V) for 0.5 pL drops of 1: 100 diluted plasma spiked with ferritin concentrations in the range of 1 fg / ml to 10 pg / ml. Each drop is spiked with a different concentration of ferritin, and each drop is measured three times. The application of the drops is from lowest concentration to highest. The method of measurement is detailed in the Experimental procedure section. The corresponding illustrated BioFET x-sections, midway between source and drain, reflect how VGS sweep affects IDS while maintaining the solution and the biological complexes in thermal and electrochemical equilibria. Figure 20B and Figure 20C show solution sweep curves for representative VGS=0, -2 V which are performed on the same drops presented in Figure 20A (note that values of VGS > 0 V concludes forward current in the side p-n junctions as the built-in voltage is ~0.5 V). In this case, the corresponding illustrated BioFET x-sections, midway between source and drain, reflect how solution sweep affects both IDS and the properties of the DL. Figure 20D shows the corresponding INORMALIZED curves defined as INORMALIZED = (I ferritin - Ipiasma) / Ipiasma, where Iferritin and Ipiasma are IDS values measured for a given spiked ferritin concentration and for the diluted plasma, respectively. The INORMALIZED curves are presented for the considered side-gate and solution sweeps of Figure 20A-20C. A clear monotonous IDS decrease with increasing ferritin concentration is demonstrated for the side-gate sweep. The decrease in IDS with increase in ferritin concentration suggests of an overall negative charge introduction to the DL with the ferritin, as reported by others [L.-C. Yen, et al. Sens Actuators B Chem, 2016, 230, 398-404; O. Oshin, et al. Sensors, 2020, 20, 3688; S. Boonkaew, et al. Analyst, 2020, 145, 5019-5026; E. Piccinini, et al. Adv Mater Interfaces , D01: 10.1002 / admi.202102526]. On the other hand, both solution sweeps present an inconsistent IDS response to increase in ferritin concentration. Figures 21A-21C present the extracted calibration curves for the sensing of ferritin. A calibration curve is extracted for a given VGS in a side-gate sweep, as each VGS in a sidegate sweep implies a different shape of a conducting channel (See illustrations Figure 20A). Similarly, a calibration curve is extracted for a given Vs<>i in a solution sweep, as each Vs i in a solution sweep implies a different shape of a conducting channel (See illustrations Figure 20B-20C). This is in contrast with a conventional inversion-mode BioFET where the shape of the conducting channel does not depend on the gate voltage, rather it is the charge carrier density that is changing and affecting IDS- The extracted calibration curves reflect specific and label-free sensing of ferritin in 1:100 diluted plasma as the signals due to non-specific response and due to drop-to-drop variations are excluded. This exclusion process is performed with respect to two criteria: 1) the difference between successive drops in Figure 20 reflects a difference between two successive concentrations of ferritin. It is ensured that this difference is higher than the average drop-to-drop difference measured post biofunctionalization with anti-ferritin antibodies, 2) It is ensured that the difference between every IDS data point and the baseline IDS (diluted plasma) of Figure 20 is higher than the corresponding difference presented in Figure 19A-19D. Only data points which fulfill these two criteria are presented in Figures 21A-21C (See Experimental procedures for a more detailed description of the two criteria). For example, note that ferritin concentration of 1 fg / ml is excluded as it failed drop-to-drop criteria. Finally, note the excellent sensing performance provided by the side-gate sweep calibration curves presented Figure 21A, in contrast with the poor performance of the solution sweeps ( VGS=0 and 2 V) presented in Figure 21B-21C.

[0345] Figure 22 discloses Table 3 that summarizes the sensing performance for both side-gate and solution sweeps. An excellent sensing performance is recorded for all selected VGS values of the side-gate sweep with an LOD of 10 fg / ml, dynamic range of 10 orders of magnitude in ferritin concentration and 0.99 linearity. In stark contrast, solution sweep provides only a single calibration curve with 0.99 linearity (all the other calibration curves are with linearity of 0.96 and lower), a dynamic range of four orders of magnitude in ferritin concentration, and an LOD of 100 fg / ml. EXAMPLE 12

[0346] IDS-VGL curves for selected VGF values performed for MNC biosensor biofunctionalized with anti-CRP

[0347] Figure 23 presents IDS-VGL curves for different VGF values. Measurements are conducted with 0.5 pL drops of whole blood on both unmodified and anti-CRP modified FET biochip. Each curve represents an average of 20 drops, with three measurements per drop, totaling 60 measurements. These curves demonstrate the exceptional repeatability and robustness of the FET biochip.

[0348] Figure 24 shows IDS-VGL curves for selected VGF values, using 0.5 pL drops of whole blood spiked with CRP concentrations ranging from 1 fg / ml to 1 mg / ml. The drops are applied sequentially, starting from the lowest to the highest CRP concentration. Additionally, Figure 24 includes the corresponding Inorm curves, which are defined as Inorm = I CU - Ibiood) I hiood, where ICRP represents the IDS values measured for a sample spiked with CRP, and Ibiood represents the IDS values measured for whole blood without spiked CRP.

[0349] Figure 25 presents Inorm curves for selected VGF values, comparing CRP introduction to an unmodified FET biochip and an APTMS -modified biochip. This measurement aims to quantify the non-specific signal resulting from CRP molecules that are physically adsorbed on the sensing area and / or on the surface of the quasi-reference electrode.

[0350] Figure 26 presents the extracted calibration curves for specific and label-free sensing of CRP and anti-CRP binding.

Claims

CLAIMS:

1. A bio-transistor system comprising: a. at least one transistor unit comprising: i. at least one channel; ii. source and drain electrodes; iii. at least one gate electrode; and iv. at least one active region located in proximity to the channel region and carrying at least one affinity moiety, each affinity moiety is specific for a target molecule; said at least one active region is configured for accepting at least one sample; and v. at least one additional electrode positioned to be in electrical contact with the sample; and b. a control system comprising at least one processor and memory circuitry, wherein said control system is configured and operable for performing one or more measurements of the sample, wherein each measurement comprises maintaining a selected electric potential on the at least one additional electrode, and determining current transmission profile through the at least one channel with respect to potential variation of said at least one gate electrode; said control unit thereby configured to determine data on the presence and / or quantity of one or more of said target molecules in the sample.

2. The bio-transistor system of claim 1 , wherein the control system is configured to perform two or more measurements utilizing two or more different selected electric potentials applied to the at least one additional electrode.

3. The bio-transistor system of claim 1 or 2, wherein said control system comprises pre-stored calibration data comprising data on electric transmission through the channel for given gate electrode potential with respect to one or more selected electric potentials applied to the at least one additional electrode.

4. The bio-transistor system of any one of claims 1 to 3, wherein said control system comprises pre-stored calibration data comprising data on electric transmission trough the channel with respect to variation of the gate electrode potential.

5. The bio-transistor system of any one of claims 1 to 4, comprising a plurality of two or more transistor units comprising respective plurality of two or more active regions carrying two or more different or identical types of affinity moieties.

6. The bio-transistor of any one of claims 1 to 5, wherein the active region is separated from the channel region by an electrical insulator layer.

7. The bio-transistor system of any one of claims 1 to 6, wherein the at least one gate electrode is electrically insulated from the active region.

8. The bio-transistor system of any one of claims 1 to 7, wherein the control system comprises at least one electrical circuit coupled vie electrical connection to the transistor unit and configured to provide selected electric potentials to electrodes of the transistor unit.

9. The bio-transistor system of any one of claims 1 to 8, wherein said at least one affinity moiety comprises at least one of: an amino acid-based molecule, a nucleic acidbased molecule, a small molecule, a carbohydrate-based molecule, a lipid-based molecule or any combination thereof, and wherein said at least one affinity moiety specifically binds said at least one target molecule in said sample.

10. The bio-transistor system of any one of claims 1 to 9, wherein said at least one affinity moiety comprising, or is derived from a component of an affinity pair, said affinity pair comprises at least one of: receptor-ligand, antibody-antigen, enzyme-substrate, aptamer- aptamer target, or any combination thereof.

11. The bio-transistor system of claim 1 to 10, wherein said target molecule comprises at least one of: an amino acid-based molecule, a nucleic acid-based molecule, a small molecule, a carbohydrate-based molecule, a lipid-based molecule or any combination thereof.

12. The bio-transistor system of any one of claims 1 to 11 , wherein said target molecule comprises, or is derived from a component of an affinity pair, said affinity pair comprises at least one of: antibody- antigen, receptor-ligand, enzyme-substrate, aptamer- aptamer target, or any combination thereof.

13. The bio-transistor system of any one of claims 1 to 12, wherein said at least one sample is a biological sample and / or an environmental sample.

14. The bio-transistor system of any one of claims 1 to 13, wherein said sample is a biological sample.

15. The bio-transistor system of claim 14, wherein said biological sample is derived from a eukaryotic organism.

16. The bio-transistor system of claim 15, wherein said eukaryotic organism is at least one organism of the biological kingdom Animalia or of the biological kingdom Plantae.

17. The bio-transistor system of claim 16, wherein said eukaryotic organism of the biological kingdom Animalia is a mammalian subject.

18. The bio-transistor system of claim 17, wherein said mammalian subject is a mammal of the Bovinae family.

19. The bio-transistor system of any one of claims 13 to 18, wherein said biological sample comprise a mammary gland milk.

20. The bio-transistor system of any one of claims 1 to 19, wherein said target molecule indicates the existence of at least one pathogenic agent in the sample.

21. The bio-transistor system of claim 20, wherein said at least one pathogenic agent is at least one of bacteria, archaea, virus, fungi, algae, parasite, protists and worms.

22. The bio-transistor system of claim 20 or 21, wherein said at least one pathogenic agent causes and / or is associated with at least one infectious disease.

23. The bio-transistor system of claim 22, wherein said at least one infectious disease is bovine mastitis (BM).

24. The bio-transistor system of any one of claims 20 to 23, wherein said at least one pathogenic agent is at least one bacteria.

25. The bio-transistor system of claim 24, wherein said bacteria is at least one of Staphylococcus aureus, Streptococci uberis, Streptococci dysgalactiae, Streptococci agalactiae, and Escherichia coli (E. coli) or any combinations thereof.

26. The bio-transistor system of any one of claims 1 to 25, wherein said affinity moiety is an amino acid-based molecule, said affinity moiety comprises, or is derived from, at least one antibody or any functional fragments thereof, and wherein said target molecule comprises, or is derived from, at least one antigen.

27. The bio-transistor system of claims 26, wherein said antigen is N-acetyl-beta-D- glucosaminidase (NAGase), and the affinity moiety comprises at least one antibody that specifically recognizes and binds NAGase, or any functional fragments thereof.

28. The bio-transistor system of claim 17, wherein said mammalian subject is a mammal of the Hominidae family.

29. The bio-transistor system of any one of claims 13 to 17, and 28, wherein said sample is a blood or a serum sample.

30. The bio-transistor system of any one of claims 28 to 29, wherein said target molecule is produced by said mammalian subject and wherein a level of said target molecule that is below or above a standard level is indicative of a pathologic disorder in said subject.

31. The bio-transistor system of any one of claims 28 to 30, wherein said pathologic disorder is an immune related disorder, said disorder is at least one of a proliferative disorder, an inflammatory disease, an autoimmune disorder and a metabolic disorder.

32. The bio-transistor system of any one of claims 28 to 30, wherein said target molecule is Alpha-fetoprotein (AFP), and wherein said affinity moiety is or is derived from, at least one antibody specific for AFP.

33. The bio-transistor system of claim 32, wherein at least one of: (i) a level of said AFP that is above a standard level is indicative of at least one of: a liver disease, a germ cell tumor, a pregnancy-related condition and at least one malignancy; and (ii) a level of said AFP that is below a standard level is indicative of at least one of: Down Syndrome and Edward's Syndrome.

34. The bio-transistor system of any one of claims 28 to 30, wherein said target molecule is Ferritin, and wherein said affinity moiety is or is derived from, at least one antibody specific for Ferritin, or any functional fragments thereof.

35. The bio-transistor system of claim 34, wherein at least one of: (i) a level of said Ferritin that is above a standard level, is indicative of at least one of: Hemochromatosis, A Chronic Inflammatory Condition, A Liver Disease, a chronic infectious disease, a Malignancy, and Hemolytic Anemia; and (ii) a level of said Ferritin that is below a standard level is indicative of at least one of: Iron Deficiency Anemia, Chronic Blood Loss, and Malabsorption Syndrome.

36. The bio-transistor system of any one of claims 28 to 30, wherein said target molecule is C-reactive protein (CRP), and wherein said affinity moiety is or is derived from, at least one antibody specific for CRP, or any functional fragments thereof.

37. The bio-transistor system of claim 36, wherein a level of said CRP that is above a standard level is indicative of at least one of: an infectious disorder, a chronic inflammatory disease, a cardiovascular disease, an autoimmune disease, a cancer, and at least one metabolic disorder.

38. The bio-transistor system of any one of claims 1 to 37, wherein said at least one sample further comprises at least one candidate compound that modulates the interaction between said affinity moiety and said target molecule, wherein said candidate compound comprises at least one of: an amino acid-based molecule, a nucleic acid-based molecule, a small molecule, a carbohydrate-based molecule, a lipid-based molecule, or any combination thereof.

39. A battery comprising two or more of the bio-transistor system as defined in any one of claims 1 to 38.

40. A method for determining presence and / or quantity of at least one target molecule in at least one sample, comprising: a. contacting the at least one sample with a bio-transistor having an active region carrying at least one affinity moiety, or a battery comprising at least two of said biotransistors, wherein each of said at least one affinity moiety is specific for a target molecule; b. performing one or more measurements, each measurement comprising: applying a selected electric potential on the sample, and determining current transmission profile through a channel of the bio-transistor with respect to potential variation of at least one gate electrode of the bio-transistor; and c. processing data on the current transmission through the channel for one or more selected gate potential and one or more selected electric potential values applied on the sample and determining presence and / or quantity of the one or more target molecules in accordance with pre-stored calibration data.

41. The method of claim 40, wherein the bio-transistor comprising: i. at least one channel; ii. source and drain electrodes;iii. at least one gate electrode; and iv. at least one additional electrode positioned to be in electrical contact with the sample; wherein the at least one active region is located in proximity to the channel region, separated from the channel region by an electrically insulating layer, and wherein the control unit thereby configured to determine data on presence and / or quantity of one or more target molecules in the sample.

42. The method of claim 40 or 41 , wherein said performing one or more measurements comprises performing two or more measurements, wherein each measurement comprises applying respective selected different potential on the sample.

43. The method of any one of claims 40 to 42, wherein said bio-transistor is as defined by any one of claims 1 to 38.

44. A diagnostic method for determining a physiological and / or environmental condition or state of a subject and / or a media and / or a habitat, comprising: a. contacting the at least one sample with a bio-transistor having an active region carrying at least one affinity moiety, or a battery comprising at least two of said biotransistors; each affinity moiety is specific for a target molecule; b. performing one or more measurements, each measurement comprising: applying a selected electric potential on the sample, and determining current transmission profile through a channel of the bio-transistor with respect to potential variation of at least one gate electrode of the bio-transistor; c. processing data on the current transmission through the channel for one or more selected gate potential and one or more selected electric potential values applied on the sample; d. determining presence and / or quantity of the one or more target molecules in accordance with pre-stored calibration data, thereby obtaining a target molecule value for said sample; and e. determining that the subject and / or media and / or habitat display said physiological and / or environmental condition or state, if the at least one target molecule value obtained for said sample in step (d), is positive or negative with respect to a reference target moleculevalue pre-determined for said physiological and / or environmental condition or state, or with respect to a target molecule value determined for at least one control sample.

45. The diagnostic method of claim 44, wherein said bio-transistor system is as defined in any one of claims 1 to 38.

46. The diagnostic method of claim 44 or 45, wherein said physiological state and / or condition of a subject comprises pathological condi tion / s and / or health condi tion / s in said subject.

47. The diagnostic method of claim 46, wherein said pathological condition is at least one immune-related disorder, said disorder is at least one of an infectious disease, a proliferative disorder, an inflammatory disease, an autoimmune disorder and a metabolic disorder.

48. The diagnostic method of claim 47, wherein said immune-related disorder is an infectious disease caused by a pathogenic agent.

49. The diagnostic method of any one of claims 44 to 48, wherein at least one of: (i) said pathogenic agent is bacteria; (ii) said subject is a mammal of the Bovinae family; (iii) said target is NAGase; (iv) the sample is a bovine milk sample; (v) the affinity moiety comprises at least one antibody that specifically recognizes and binds NAGase; and (vi) said infectious disease is bovine mastitis (BM).

50. The method of any one of claims 44 to 49, for the diagnosis and monitoring of mastitis in a mammalian subject of the Bovinae family.

51. The method of any one of claims 44 to 47, wherein at least one of:(i) said subject is a mammalian subject of the Hominidae family;(ii) said sample is a blood or a serum sample; and(iii) said target molecule is produced by said mammalian subject and wherein a level of said target molecule that is below or above a standard level is indicative of a pathologic disorder in said subject.

52. The method of claim 51, wherein said target molecule is Alpha-fetoprotein (AFP), and wherein said affinity moiety is or is derived from, at least one antibody specific for AFP.

53. The method of claim 52, wherein at least one of: (i) a level of said AFP that is above a standard level is indicative of at least one of: a liver disease, a germ cell tumor, apregnancy-related condition and at least one malignancy; and (ii) a level of said AFP that is below a standard level is indicative of at least one of: Down Syndrome and Edward's Syndrome.

54. The method of claim 51 , wherein said target molecule is Ferritin, and wherein said affinity moiety is or is derived from, at least one antibody specific for Ferritin.

55. The method of claim 54, wherein at least one of: (i) a level of said Ferritin that is above a standard level is indicative of at least one of: Hemochromatosis, A Chronic Inflammatory Condition, A Fiver Disease, a chronic infectious disease, a Malignancy, and Hemolytic Anemia; and (ii) a level of said Ferritin that is below a standard level is indicative of at least one of: Iron Deficiency Anemia, Chronic Blood Foss, and Malabsorption Syndrome.

56. The method of claim 51, wherein said target molecule is C-reactive protein (CRP), and wherein said affinity moiety is or is derived from, at least one antibody specific for CRP.

57. The method of claim 56, wherein a level of said CRP that is above a standard level is indicative of at least one of: an infectious disorder, a chronic inflammatory disease, a cardiovascular disease, autoimmune diseases, a cancer, and at least one metabolic disorder.

58. A screening method for identifying a compound that modulates the interaction of an affinity moiety with a target molecule in at least one sample, comprising:(i) contacting said at least one sample with a bio-transistor system, in the presence and the absence of at least one candidate compound, said bio-transistor having an active region carrying at least one affinity moiety, each affinity moiety is specific for a target molecule;(ii) performing one or more measurements for each sample, each measurement comprising: applying a selected electric potential on the sample, and determining current transmission profile through a channel of the bio-transistor with respect to potential variation of at least one gate electrode of the bio-transistor; and(iii) processing data on the current transmission through the channel for one or more selected gate potential and one or more selected electric potential values applied on the sample; and(iv) determining presence and / or quantity of the one or more target molecules in accordance with pre-stored calibration data, thereby determining a target molecule valuefor said sample in the presence of said candidate compound, and a target molecule value in the absence of said candidate compound;(v) determining that said candidate compound is a modulator of the interaction between the affinity moiety and the target molecule, if the target molecule value obtained for said sample in the presence of said candidate compound is different from the target molecule value obtained in the absence of said candidate compound.

59. A personalized method for treating, preventing, inhibiting, reducing, eliminating, protecting or delaying the onset of at least one pathological disorder in a subject, the method comprising the steps of: a. determining the presence and / or quantity of at least one target molecule target molecule in at least one sample of said subject, wherein said target molecule is associated directly or indirectly with said pathologic disorder; and b. administering an effective amount of at least one therapeutic agent for said pathological disorder to a subject exhibiting the presence of said one or more target molecule, or the quantity of said target molecule that is above or below a standard level; wherein determining the presence and / or quantity of at least one target molecule in (a), is performed by the steps of:(i) contacting the at least one sample of said subject with a bio-transistor having an active region carrying at least one affinity moiety, or a battery comprising at least two of said bio-transistors, wherein each of said at least one affinity moiety is specific for a target molecule;(ii) performing each measurement comprising: applying a selected electric potential on the sample, and determining current transmission profile through a channel of the bio-transistor with respect to potential variation of at least one gate electrode of the bio-transistor; and(iii) processing data on the current transmission through the channel for one or more selected gate potential and one or more selected electric potential values applied on the sample; and(iv) determining presence and / or quantity of the one or more target molecules in accordance with pre-stored calibration, thereby obtaining a target molecule value for said sample; and(v) determining that the subject is suffering from said pathologic disorder, if the at least one target molecule value obtained for said sample in step (iv), is positive or negative with respect to a reference target molecule value predetermined for said pathologic disorder, or with respect to a target molecule value determined for at least one control sample.

60. The personalized method of claim 59, wherein determining the presence and / or quantity of at least one target molecule in (a) is performed by the method as defined in any one of claims 40 to 43.

61. The personalized method of any one of claims 59 to 60, wherein at least one of; (i) the subject is a mammalian subject of the Bovinae family; (ii) said target molecule is NAGase; (iii) the affinity moiety comprises at least one antibody that specifically recognizes and binds NAGase; (iv) the sample is a bovine milk sample; and (v) wherein said disorder is mastitis.

62. The personalized method of any one of claims 59 to 60, wherein the subject is a mammalian subject of the Hominidae family.

63. The personalized method of claim 62, wherein said sample is a blood or a serum sample, and wherein at least one of:(a) wherein said target protein is AFP, and said affinity moiety is or is derived from, at least one antibody specific for AFP; and wherein said disorder is at least one of: (i) a liver disease, a germ cell tumor, a pregnancy -related condition and / or at least one malignancy; and (ii) Down Syndrome and / or Edward's Syndrome;(b) wherein said target protein is Ferritin, and said affinity moiety is or is derived from, at least one antibody specific for Ferritin and wherein said disorder is at least one of: (i) Hemochromatosis, A Chronic Inflammatory Condition, A Liver Disease, a chronic infectious disease, a Malignancy, and / or Hemolytic Anemia; and (ii) Iron Deficiency Anemia, Chronic Blood Loss, and / or Malabsorption Syndrome; and(c) wherein said target protein is CRP, and said affinity moiety is or is derived from, at least one antibody specific for CRP, and wherein said disorder is at least one of: an infectious disorder, a chronic inflammatory disease, a cardiovascular disease, autoimmune diseases, a cancer, and at least one metabolic disorder.

64. A diagnostic kit comprising: a. at least one bio-transistor system, and optionally, at least on of: b. at least one control sample; and c. at least one at least one therapeutic agent; wherein said bio-transistor system comprises:(I) at least one transistor unit comprising: i. at least one channel; ii. source and drain electrodes; iii. at least one gate electrode; iv. at least one active region located in proximity to the channel region and carrying at least one affinity moiety, each affinity moiety is specific for a target molecule; said at least one active region is configured for accepting at least one sample; and v. at least one additional electrode positioned to be in electrical contact with the sample; and(II) a control system comprising at least one processor and memory circuitry, wherein said control system is configured and operable for performing one or more measurements of the sample, wherein each measurement comprises maintaining a selected electric potential on the at least one additional electrode, and determining current transmission profile through the at least one channel with respect to potential variation of said at least one gate electrode; said control unit thereby configured to determine on the presence and / or quantity of one or more target molecules in the sample.

65. The kit of claim 64, adapted for performing the method of any one of claims 40 to 43.

Images