Methods for detecting analytes

Abstract

This disclosure provides a method for detecting a target analyte in a sample, the method comprising: a) providing a certain amount of magnetizable particles having a known or measurable reference magnetic signal before or after the addition of a sample (the particles are coated with a binding molecule complementary to the target analyte); b) contacting a sample containing the target analyte with the magnetizable particles to generate bound and unbound binder complexes; c) applying a magnetic field to the sample for a certain period of time; d) obtaining a magnetic signal (the magnetic signal being the magnetic signal of the bound and unbound binder complexes in the presence of a magnetic field); e) removing the magnetic field for a certain period of time; and f) comparing the reference magnetic signal with the magnetic signal (the difference between the reference magnetic signal and the magnetic signal correlates with the presence and / or amount of the target analyte in the sample).

Description

Technical Field

[0001] The present invention relates to a method for detecting one or more target analytes in a sample, more specifically, to the use of magnetizable nanoparticles and magnetic sensor systems. The present invention also relates to a device for detecting analytes based on the use of magnetizable nanoparticles.

Background Art

[0002] Numerous methods are known for detecting and quantifying analytes in a sample. Such systems require an indirect method of quantifying the analyte by detecting and measuring a complex bound to the analyte. Typically, such methods rely on a binding or recognition system that coats or links a visualization aid to a binding molecule that binds to the analyte within the sample.

[0003] The binding molecule may include an antibody, enzyme, or pharmacological agent that is specifically selected based on its affinity for the target analyte. The molecule itself that binds directly to the analyte may be labeled with an enzyme or a phosphor (in the case of a fluorescent label).

[0004] Alternatively, the molecule itself that binds directly to the analyte may be unlabeled and instead bound to an additional binding agent that is itself labeled with an enzyme or a phosphor. This additional labeling procedure can amplify the signal and reduce background staining. Well-known complexes are the avidin-biotin complex and the peroxidase-anti-peroxidase technique.

[0005] Techniques for detecting and quantifying analytes in a sample need to be rapid, sensitive, qualitative, and / or miniaturizable to meet the needs of in vitro diagnostics. When a device is miniaturized, the mixing of fluids may slow down and become inefficient due to an increase in viscous forces.

[0006] Immediate clinical testing can shorten the turnaround time for diagnostic tests, improve workflows, and thereby contribute to improved patient care. Such systems must include sensing technologies for detecting biomarkers (e.g., protein markers or nucleic acid markers). Magnetizable particles are used to detect analytes in manual assays, from basic research to high-throughput testing.

[0007] Many existing devices for detecting analytes attached to magnetizable particles are either unsuitable for miniaturization in real-time clinical testing applications or require complex configurations that cannot be easily adapted for miniaturization.

[0008] The use of magnetizable particles relies on the functionalization of the particles by binding molecules (e.g., antibodies with high affinity for the target analyte), enabling binding to the target analyte and subsequently allowing a fluid exchange step to achieve separation and purification. The capture rate of the analyte has been reported to correspond to the total surface area of ​​the suspended particles, and therefore to the particle concentration. However, the use of very high particle concentrations is detrimental to the downstream processes of integrated multi-step lab-on-chip assays. This is because high particle concentrations generally increase nonspecific particle-particle and particle-surface interactions, promote magnetic field-induced particle aggregation, cause steric hindrance in the particle concentration step, interfere with chemical reactions on the particles, and sterically hinder reactions between the particles and the biosensing surface.

[0009] The target analyte may be present at low concentrations in a sample that also contains high concentrations of background material (e.g., blood or saliva). In such complex matrices, the nonspecific attachment of non-target molecules to magnetizable particles can reduce the effectiveness of the assay.

[0010] The magnetic particle-based capture process of a target analyte consists of an encounter between two components (the target analyte and the magnetic particles), and may depend on the alignment of the two components' outer surfaces in a highly specific manner relative to each other. Therefore, the association rate of the two components may be limited by diffusion and the geometric constraints of the binding site between the two components, and may also be reduced by the final chemical reaction.

[0011] The analyte can be captured in a flowing or stationary fluid. In the absence of flow, methods relying on surface-immobilized antibodies may be limited by diffusion, potentially reducing binding rates.

[0012] After the target analyte is captured by magnetic particles, additional processing is required for detection. When used solely as a carrier, magnetizable particles are typically bound to a identifying molecule (e.g., an luminescent label or fluorescent molecule). For accurate detection, it is crucial that only the bound analyte is labeled and only the bound label is detected. This requires multiple washing or separation steps.

[0013] Magnetizable particles can also be used as labels to indicate the binding of target analytes to a sensing surface. Agglutination assays utilize the process by which particle aggregates form when a specific analyte is present in a sample solution. The degree of agglutination is a measure of the concentration of the analyte in the fluid. Agglutination assays have stringent reagent requirements because the assay is performed in one step without requiring separation or rigor.

[0014] In magnetic aggregation assays, particle cluster formation is accelerated by aggregating particles under the influence of a magnetic field. A problem with such methods is that when the analyte concentration is much lower than the magnetizable particle concentration, only a small number of particle aggregates are formed according to Poisson statistics. The application of a magnetic field can be enhanced by applying it during incubation. However, the magnetic field can also increase nonspecific binding between particles. Nonspecific binding (i.e., binding not mediated by the target analyte) results in a false-positive signal. Nonspecific binding can arise from several types of interactions (e.g., van der Waals interactions, electrostatic interactions, and hydrophobic interactions) that cause background levels and statistical variations in the results.

[0015] The use of magnetizable particles means that additional forces can be applied to the particles, for example, to separate bound particles from unbound particles.

[0016] The analytical performance of a detection method is evaluated based on the limit of quantification (LoQ) (i.e., the lowest biomarker concentration that can be quantified with a given required accuracy).

[0017] As the demands for detection sensitivity, molecular specificity, and application complexity increase, optimizing magnetizable particles for specific applications and selecting appropriate detection methods remains a challenge for the magnetic nanotechnology community.

[0018] The use of GMR in immunoassays is employed in sandwich-type approaches (e.g., ELISA), where molecular targets are immobilized on the sensor surface by the addition of tagged magnetic probes (see below: Koh and Josephson, “Magnetic nanoparticle sensors,” Sensors 2009:9;8130-45 and Yao and Xu, “Detection of magnetic nanomaterials in molecular imaging and diagnostic applications,” Nanotechnol. Rev 2014:3;247-268).

[0019] Several methods use superconducting quantum interference devices (SQUIDs) to detect and measure Néel relaxation (magnetic dipole misalignment) in magnetically labeled bacteria. In such methods, a magnetic field is pulsed to induce alignment of magnetic dipoles, and then misalignment of the dipoles is detected.

[0020] The object of the present invention is to address one or more of the above-mentioned problems, and / or to provide a method for detecting analytes in a sample, and / or to provide at least a useful alternative to the public. [Overview of the project]

[0021] According to a first aspect, the present disclosure provides a broad method for detecting a target analyte in a sample, the method including: ● Provide an amount of magnetizable particles having a known or measured reference magnetic signal before or after the addition of the sample (the particles are coated with a binding molecule complementary to the target analyte). ● The process involves bringing a sample containing the target analyte into contact with magnetizable particles to generate bound and unbound binder composites. ● Apply a magnetic field to the sample for a certain period of time. ● Obtaining a magnetic signal (the magnetic signal is the magnetic signal of the coupled and uncoupled binder complex in the presence of a magnetic field), ● Remove the magnetic field for a certain period of time. ●Compare the reference magnetic signal with the magnetic signal (the difference between the reference magnetic signal and the magnetic signal correlates with the presence and / or amount of the target analyte in the sample).

[0022] The reference magnetic signal can be determined by measuring the magnetic signal of the amount of magnetizable particles in the absence of the target analyte.

[0023] The reference magnetic signal may be measured at any point during the following steps: bringing a sample containing the target analyte into contact with magnetizable particles; applying a magnetic field to the sample for a certain period of time; acquiring a magnetic signal; and removing the magnetic field for a certain period of time.

[0024] A magnetic field can be generated using an electromagnet.

[0025] A magnetic field can be generated using a permanent magnet.

[0026] A magnetic signal can be obtained after the electromagnetic coil of an electromagnet reaches saturation.

[0027] The target analyte in a sample can be determined by correlating the measured change in magnetic signal with a reference / predetermined magnetic signal.

[0028] The method further involves generating a reference dataset based on known analyte amounts, and comparing the reference magnetic signal with the value obtained from the difference between the magnetic signals to determine the amount of analyte in the sample.

[0029] A magnetic field can be applied for a predetermined period of time.

[0030] The magnetic field can be applied for approximately 0.1, 0.25, 0.5, 1, 2, 3, 4, or 5 seconds, and any range in between.

[0031] The magnetic field can be removed for approximately 0.1, 0.25, 0.5, 1, 2, 3, 4, or 5 seconds, and any range in between.

[0032] The magnetic field can be removed for a predetermined period of time.

[0033] The magnetic field can be removed for approximately 3 to 7 seconds.

[0034] The magnetic field can be applied and removed for substantially equal periods of time.

[0035] The magnetic field can be applied and removed for approximately 1 second.

[0036] The steps of applying a magnetic field to the sample for a certain period of time, acquiring a magnetic signal, and removing the magnetic field for a certain period of time may be repeated two or more times.

[0037] The magnetizable particles may be superparamagnetic nanoparticles.

[0038] The magnetizable particles may be ferromagnetic nanoparticles.

[0039] The average particle size of superparamagnetic nanoparticles may be approximately 20 nm to 40 nm.

[0040] The average particle size of superparamagnetic nanoparticles may be approximately 30 nm.

[0041] The average particle size of the magnetizable particles may be approximately 5 to 5000 nm.

[0042] The method may further include magnetically shielding the sample from the surrounding magnetic field.

[0043] The method may further include detecting the ambient magnetic field and adjusting the reference magnetic signal and the magnetic signal based on the ambient magnetic field.

[0044] The magnetic signal can be measured at a sampling rate of at least approximately 10,000 samples per second.

[0045] The sample can be incubated at a temperature of approximately 20°C.

[0046] The magnetic signal may be the magnetic field strength.

[0047] The method may also include the following: ● Applying a second magnetic field to the magnetizable particles (the second magnetic field may be placed above or below the sample), ● Measure the magnetic signals of coupled and uncoupled binder composites in the presence of a magnetic field and a second magnetic field.

[0048] The method may be carried out using a sample test device that includes the following: ● Sample well or sample reservoir, ● One or more magnets placed on either the top or bottom of the sample well or sample reservoir. ● One or more permanent magnets located at the top or bottom of the sample well or sample reservoir, and ● A magnetic field sensor for measuring changes in magnetic signals over time within a sample well or sample reservoir.

[0049] Magnetizable particles can be functionalized with molecules that specifically bind to the target analyte.

[0050] The sample and magnetizable particles can be processed using a microfluidic device.

[0051] Microfluidic devices can facilitate the coupling of magnetizable particles and analytes.

[0052] One or more electromagnets can generate a magnetic field that changes over time.

[0053] One or more electromagnets can generate a continuity of size.

[0054] One or more electromagnets can alternately switch the magnetic field on and off.

[0055] A magnetic field sensor can measure changes in magnetic field strength generated by magnetizable particles over time.

[0056] The signal output from the magnetic field sensor can be amplified by a signal amplifier.

[0057] The signal output from the magnetic field sensor may be a voltage reading proportional to the magnetic signal measured by the magnetic field sensor.

[0058] The amplified signal can be converted from a voltage reading into a digital bitstream, which can then be recorded and / or analyzed by a computer.

[0059] The conversion can be carried out using an analog-to-digital converter.

[0060] The method is, ● Generate a sufficient magnetic signal within 15 seconds to detect and / or quantify the target analyte in the sample, or ●It may have a limit of detection (LOD) of at least approximately 0.05 pg / mL, or ●It may have a limit of quantification (LOQ) of at least approximately 0.1 pg / mL, or ●It could be one or more of the above.

[0061] A second magnetic field can be applied from the opposite side of the magnetic field.

[0062] A second magnetic field can be provided using a permanent magnet.

[0063] A second magnetic field can be provided using an electromagnet.

[0064] Electromagnets can be placed closer to the sample than permanent magnets.

[0065] Electromagnets can be calibrated to have at least twice the magnetic density of permanent magnets.

[0066] Magnetic signals can be processed using the Fast Fourier Transform (FFT).

[0067] The magnetic signal may be preprocessed by truncating and / or concatenating it in one or more dimensions before processing it using the FFT.

[0068] The magnetic signal can be windowed before the FFT processing.

[0069] In another aspect, the present disclosure may broadly provide devices for detecting analytes in a sample, including: ● Sample wells that are separate from or integrated with microfluidic devices, ●Magnets for generating a magnetic field, ● A magnetic field sensor configured to measure the magnetic signal of magnetizable particles in a sample well in the presence of a magnetic field (the magnetic signal is detected from the overall magnetic response, which is proportional to the size of the aggregate).

[0070] As used herein, the term “contains” means “consisting of at least a portion of.” When interpreting any statement herein containing the term, all the functions that the term presupposes must be present in each statement, although other features may also be present. Related terms (e.g., “contains” and “included”) should be interpreted similarly.

[0071] References to numerical ranges disclosed herein (e.g., 1 to 10) also incorporate references to all rational numbers within that range (e.g., 1, 1.1, 2, 3, 3.9, 4, 5, 6, 6.5, 7, 8, 9, and 10), and also to any range of rational numbers within that range (e.g., 2 to 8, 1.5 to 5.5, and 3.1 to 4.7).

[0072] The present invention is also said to consist, in general terms, of the parts, elements, and features referred to or indicated individually or collectively in this specification, as well as any combination of any two or more such parts, elements, or features. Where a particular integer has known equivalents in the art to which the present invention relates, such known equivalents are to be considered incorporated herein as if they were individually described.

[0073] Those skilled in the art in which the present invention relates will understand that many structural modifications of the present invention, as well as significantly different embodiments and uses, will be suggested without departing from the scope of the invention as defined in the appended claims. The disclosures and descriptions herein are illustrative and not limiting in any sense.

[0074] The present invention will now be described merely as an example and with reference to the drawings: [Brief explanation of the drawing]

[0075] [Figure 1] This is the magnetic field sensor signal output over N cycles (times) during the sample reading stage according to one embodiment of the present disclosure. 'a' represents the magnet on phase at the start of the reading cycle and represents the average value profile acquired over time from the magnetic field sensor according to one embodiment of the present disclosure. 'b' represents the magnet off phase, showing the average value profile from the magnetic field sensor according to one embodiment of the present disclosure over time. [Figure 2] This is a sample introduction device / microfluidic chip according to an embodiment of the present disclosure. [Modes for carrying out the invention]

[0076] This disclosure provides a broad range of methods for detecting and / or quantifying target analytes in a sample.

[0077] The described method for detecting the target analyte in a sample may generally include the following steps: ● Provide an amount of magnetizable particles having a known or measured reference magnetic signal before or after the addition of the sample (the particles are coated with a binding molecule complementary to the target analyte). ● The process involves bringing a sample containing the target analyte into contact with magnetizable particles to generate bound and unbound binder composites. ● Apply a magnetic field to the sample for a certain period of time. ● Obtaining a magnetic signal (the magnetic signal is the magnetic signal of the coupled and uncoupled binder complex in the presence of a magnetic field), ● Remove the magnetic field for a certain period of time. ●Compare the reference magnetic signal with the magnetic signal (the difference between the reference magnetic signal and the magnetic signal correlates with the presence and / or amount of the target analyte in the sample).

[0078] The described method is based on the concept of measuring changes in the magnetic signal generated by magnetizable particles by Brownian motion or diffusion, which allows for the quantification of the amount of magnetizable particle-analyte complex (binding binder complex), and subsequently, the determination of the amount of analyte in the sample.

[0079] The Brownian motion (i.e., rotational or translational motion) of particles can be influenced by many factors (but not limited to temperature, viscosity of the suspension medium, particle size, and particle surface properties). For example, surface properties (e.g., analytes bonded to magnetizable particles) alter the hydrodynamic properties of the resulting chemical conjugate.

[0080] As the concentration of the analyte changes, the bonding / aggregation of magnetizable particles differs depending on the chemical bonds between the analyte and the binder, between binders, and between particles, resulting in particles with a spectrum of hydrodynamic sizes across various analyte concentrations.

[0081] For example, if a relatively high concentration of analyte is present in the sample, the binder on the magnetizable particles becomes more saturated with the analyte, reducing the likelihood of binder-to-binder and / or interparticle interactions (e.g., nonspecific bonding), and leading to the formation of smaller aggregates.

[0082] Conversely, when relatively low concentrations of the analyte are present in the sample, the binders on the magnetizable particles become less likely to be saturated with the analyte, increasing the likelihood of binder-to-binder and / or particle-to-particle interactions, which can lead to the formation of larger aggregates.

[0083] Brownian motion is inversely proportional to the hydrodynamic size of the magnetizable particles and the analyte composite. Therefore, a change in the amount of analyte alters the hydrodynamic size of the magnetizable particles, which affects the effective translational or rotational Brownian motion under an external magnetic field. The change in Brownian motion may be detectable and measurable as an overall magnetic response proportional to the size of the aggregate.

[0084] Large aggregations of magnetizable particles can lead to denser particle formation (increased dipole interactions (or dipole coupling)). Increased dipole coupling results in a stronger magnetic signal.

[0085] The difference between aggregate formation and the resulting magnetic signal can be used to determine the concentration of the analyte in the sample.

[0086] While not bound by theory, in magnetic equilibrium, magnetizable particles attract each other in one dimension but repel each other in another, thereby forming microassemblies. Factors (e.g., size of magnetizable particles, amount of analyte, size of analyte) can influence the distance between microassemblies. For example, increasing the amount of analyte can effectively increase the size of magnetizable particle-analyte complexes. As a result, larger complexes can remain at greater distances while retaining the same attractive force that influences the formation of microassemblies, which can be detected as changes in the signal produced by the magnetizable particles.

[0087] The amount of analyte in a sample is determined, if detected by a sensor, based on changes in the signal generated by magnetizable particles. The sensor detects changes based on particle aggregation.

[0088] The described method may include multiple steps.

[0089] The first stage may be a pre-sample stage. The pre-sample stage may include providing a certain amount of magnetizable particles to a sample device such as a microfluidic device.

[0090] Magnetizable particles can be functionalized with a binder that binds to a specific target analyte.

[0091] The amount of magnetizable particles may have a known or predetermined reference signal, for example, based on a known number of beads present in the device. The reference signal may be any measurable signal generated by the magnetizable particles in the absence of a target analyte. For example, the signal may include a magnetic signal or an electrical signal.

[0092] The signals generated by magnetizable particles may be intrinsic or induced. For example, the generated signals may be intrinsic to the atomic structure or they may be induced by a magnetic field (e.g., an external magnetic field).

[0093] Alternatively or additionally, the method may include a reference calibration step, which involves measuring the total signal generated by magnetizable particles in the absence of the analyte. In the reference calibration step, after a large quantity of magnetizable particles have been added to the sample device, and before the sample is added, the signal generated by the magnetizable particles is measured using a suitable signal sensor.

[0094] In some embodiments, the reference calibration step may be performed concurrently with the sample reading step described in the previous paragraph. For example, this may be done using a multiplexing system in which one channel or well is used for reference calibration and the other channel is used for sample readings.

[0095] The reference signal provides a basic comparison for subsequent sample readings. The reference calibration step may take 1, 2, 3, 4, or 5 seconds, and a preferred range may be selected from any of these values ​​(e.g., approximately 1 second to 5 seconds, approximately 1 second to 4 seconds, approximately 2 seconds to 5 seconds, approximately 2 seconds to 3 seconds, or approximately 3 seconds to 5 seconds).

[0096] The second step may include introducing the sample to be analyzed into magnetizable particles.

[0097] At this stage, the sample is brought into contact with magnetizable particles, and any analytes present in the sample can be bound with a binder on the magnetizable particles to form a complex with the particles. This step results in bound and unbound binder complexes.

[0098] Alternatively, the sample to be analyzed can be incubated with functionalized magnetizable nanoparticles before being introduced into a microfluidic device.

[0099] This step may include sample mixing and analyte-binder compounding (i.e., functionalized magnetizable particles binding to the analyte). This step may take about 3, 4, 5, 6, 7, or 8 minutes, and a preferred range may be selected from any of these values ​​(e.g., about 3 to about 8, about 3 to about 7, about 3 to about 5, about 4 to about 8, about 4 to about 6, or about 5 to about 8 minutes).

[0100] The third stage may be the sample reading stage.

[0101] During the sample reading phase, one or more external magnetic fields may be used to induce and alter the equilibrium of magnetizable particles (bonded and unbonded binder composites), and transitions between equilibrium states can be measured over time as changes in the signal.

[0102] In some embodiments, an external magnetic field may be generated using magnets. These magnets may be selected from permanent magnets and / or electromagnets.

[0103] In embodiments using electromagnets, an external magnetic field may be applied or removed by switching the electromagnet on and off. For example, electricity may be supplied to or interrupted from the electromagnet coil to activate or deactivate the external magnetic field.

[0104] In embodiments using a permanent magnet, an external magnetic field can be applied and removed by changing the relative position between the permanent magnet and the sample. For example, the permanent magnet or sample well may be configured so that the sample moves within or outside the effective range of the permanent magnet depending on the phase of the reading cycle.

[0105] In other embodiments, the permanent magnet and the sample remain stationary relative to each other, but a magnetic shielding member may be used to control or redirect the magnetic field generated by the permanent magnet. For example, a movable magnetic shielding member placed between the permanent magnet and the sample may be controlled to move so that the magnetic field generated by the permanent magnet reaches the sample or is prevented from reaching the sample.

[0106] In some embodiments, an external magnetic field may be applied, and the sample may be read over multiple cycles. In each cycle, the external magnetic field may be activated (applied) and deactivated (removed) once or more times for a specified duration. For example, the external magnetic field may be applied for 2 seconds and removed for 5 seconds.

[0107] Figure 1 shows the magnetic field sensor signal output over N cycles (times) during the sample reading phase, according to an embodiment that uses an electromagnet to generate an external magnetic field. In some embodiments, each cycle may be defined as the time between activations of the external magnetic field. For example, each reading cycle begins when the external magnetic field is activated and ends when the external magnetic field is reactivated after a period of deactivation.

[0108] The activation of the external magnetic field is known as the magnet on phase, and the deactivation of the external magnetic field may be known as the magnet off phase.

[0109] Figure 1a is an enlarged inset of the start of a reading cycle, representing a profile of average values ​​obtained over time from a magnetic field sensor according to one embodiment of the present disclosure. The magnet on-phase may be characterized by a number of events. The events described may overlap or occur simultaneously.

[0110] In event 2a, the electromagnet is activated at the start of the reading cycle, and the electromagnetic coil reaches saturation.

[0111] In event 2b, the external magnetic field generated by the electromagnet propagates throughout the sample, and the electromagnetic coil reaches an equilibrium state with respect to the input voltage detected by the magnetic field sensor.

[0112] In event 2c, the propagation of an external magnetic field causes coupled and uncoupled magnetizable particles (e.g., SPIONs) to spontaneously acquire magnetic moments. In particular, coupled and uncoupled magnetizable particles may adopt polarities opposite to their net vectors and align and optimize in harmony with nearby magnetizable particles (which are also magnetic).

[0113] In event 2d, existing aggregates of bonded and unbonded magnetizable particles, and / or aggregates formed by spontaneous magnetic interactions, represent rotational and / or translational motion. Magnetic repulsion and attraction bring about a region of magnetic equilibrium.

[0114] In event 2e, aggregates of magnetizable particles align along the magnetic field lines of the magnetic coil and move toward the increasing magnetic field gradient (the source of the external magnetic field).

[0115] The magnet is in the on-phase state (i.e., an external magnetic field) for a certain period of time (activated). This period may be a predetermined time.

[0116] The magnet on-phase may be approximately 0.1, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0, 2.25, 2.5, 2.75, 3.0, 3.25, 3.5, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, or 12.0 seconds, and a preferred range is these. The values ​​(for example, approximately 0.25 to 12, approximately 0.25 to 5.0, approximately 0.25 to 3.0, approximately 0.25 to 2.0, approximately 0.25 to 1, approximately 0.1 to 12, approximately 0.1 to 5.0, approximately 0.1 to 3.0, approximately 0.1 to 2.0, approximately 0.1 to 1, approximately 0.5 to 12, approximately 0.5 to 5.0, approximately 0.5 to 3.0, approximately 0) 0.5 to approximately 2.0, approximately 0.5 to approximately 1, approximately 0.75 to approximately 12, approximately 0.75 to approximately 5, approximately 0.75 to approximately 3.0, approximately 0.75 to approximately 2.0, approximately 0.75 to approximately 1.0, approximately 1.0 to approximately 3.5, approximately 1.0 to approximately 3.25, approximately 1.0 to approximately 3.0, approximately 1.0 to approximately 2.75, approximately 1.0 to approximately 2.5, approximately 1.0 to approximately 2.25, approximately 1.0 to approximately 2 It can be selected from any of the following (0.0, approximately 1.0 to 1.75, approximately 1.0 to 1.5, approximately 1.0 to 1.25, approximately 1.5 to 3.0, approximately 1.5 to 2.5, approximately 1.5 to 2.0, approximately 2.0 to 2.25, approximately 2.5, approximately 2.0 to 2.75, approximately 2.0 to 3.0, approximately 2.0 to 3.25, approximately 2.0 to 3.5 seconds).

[0117] Preferably, the magnet on-phase is about 1.0 to about 2.0 seconds.

[0118] Without being bound by theory, minimizing the on-time of the magnet can reduce the accumulation of heat within the electromagnet coil, which can affect the accuracy of readings obtained by the sensor.

[0119] If the magnet on-phase can be extended, a calibration reference can be used to compensate for any inaccuracies in sensor readings that may be introduced due to heat buildup from the electromagnetic coil.

[0120] Figure 1b is an enlarged inset of the magnet off-phase showing the average value profile from a magnetic field sensor over time, according to one embodiment of the present disclosure.

[0121] The magnet off-phase is the inverse of the magnet on-phase and is generally characterized by the desaturation of the electromagnetic coil (event 3a) and the inverse of events 2b-2e, which were described in the previous paragraph in relation to the magnet on-phase.

[0122] The magnet off-phase may be approximately 0.1, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0, 2.25, 2.5, 2.75, 3.0, 3.25, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 8.0, 9.0, 10.0, 11.0, or 12.0 seconds, and a preferred range is these values ​​(e.g., approximately 0.25 to 12, approximately 0.25 to 5.0, approximately 0.25 to 3.0, approximately 0.25 to 2.0, approximately 0.25 to 1, approximately 0.1 to 12, approximately 0. The time can be selected from any of the following ranges: 1 to approximately 5.0, approximately 0.1 to approximately 3.0, approximately 0.1 to approximately 2.0, approximately 0.1 to approximately 1, approximately 0.5 to approximately 12, approximately 0.5 to approximately 5.0, approximately 0.5 to approximately 3.0, approximately 0.5 to approximately 2.0, approximately 0.5 to approximately 1, approximately 0.75 to approximately 12, approximately 0.75 to approximately 5, approximately 0.75 to approximately 3.0, approximately 0.75 to approximately 2.0, approximately 0.75 to approximately 1.0, approximately 3.0 to approximately 7.0, approximately 3.0 to approximately 6.0, approximately 3.0 to approximately 5.0, approximately 3.0 to approximately 4.0, approximately 4.0 to approximately 7.0, approximately 4.0 to approximately 6.0, or approximately 4.0 to approximately 5.0 seconds.

[0123] In some embodiments, the magnet on-phase and magnet off-phase may be substantially equal. For example, the times of the magnet on-phase and magnet off-phase may be substantially equal to each other within approximately 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 20%, 25%, 30%, 35%, 40%, 45%, or 50%.

[0124] If the magnet on-phase and magnet off-phase are not equal, in some embodiments, as described above, the device may include an onboard reference standard. For example, an onboard standard curve generator that reads a known amount of analyte and creates a standard curve. Thus, any deviation from the measured result to the expected result can be used to generate a multiplier, which can be applied to the sample result to account for any drift in the reading.

[0125] In some embodiments, the sample reading step may include two or more sample reading cycles. For example, the sample reading step may include 2, 3, 4, 5, 6, 7, 8, 9, or 10 cycles.

[0126] The sample reading interval may be approximately 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, or 70 seconds, and a preferred range may be selected from any of these values ​​(e.g., approximately 5 to 70, approximately 5 to 60, approximately 5 to 50, approximately 5 to 40, approximately 5 to 30, approximately 5 to 20, approximately 5 to 10, approximately 10 to 70, approximately 10 to 60, approximately 10 to 50, approximately 10 to 40, approximately 10 to 30, approximately 10 to 20, approximately 20 to 70, approximately 20 to 50, approximately 20 to 30 seconds).

[0127] In some embodiments, the external magnetic field may include a first magnetic field and a second magnetic field.

[0128] The first and second magnetic fields can be generated by magnets placed on the opposite side of the sample.

[0129] In some embodiments, a first magnetic field may be generated below the sample, and a second magnetic field may be generated above the sample. In this embodiment, the first magnetic field may attract magnetizable particles downward, while the second magnetic field may attract magnetizable particles upward.

[0130] In some embodiments, the first and second magnetic fields may have the same polarity or different polarities.

[0131] The first magnetic field may be a permanent magnetic field, which is applied continuously at a constant magnitude for the duration of the sample reading stage.

[0132] The second magnetic field may be a non-permanent magnetic field, which is applied only during the reading state, and both the permanent and non-permanent magnetic fields are active during the reading state.

[0133] When multiple external fields are used, the signals generated by magnetizable particles (coupled and uncoupled binder composites) are measured by a signal sensor in read-out state when both magnetic fields are active and the magnetizable particles are transitioning between equilibrium states.

[0134] The signal generated by magnetizable particles can be measured over a portion or duration of the reading state.

[0135] Permanent magnetic fields can be weaker than non-permanent magnetic fields.

[0136] A permanent magnetic field can be generated at a distal location to the sample, while a non-permanent magnetic field can be generated at a proximal location to the sample.

[0137] The intensity of a non-permanent magnetic field can be modulated.

[0138] While not bound by theory, the modulation of the magnetic field (i.e., the bias field) has the primary function of aligning magnetizable particles with the sensor to achieve maximum detection sensitivity during detection. In the case of ferromagnetic particles, if they have their own permanent magnetic field, the bias field is turned off, causing the magnetic particles to shift position. In the case of paramagnetic (or superparamagnetic) particles, the magnetic field needs to be induced by an external field, so the bias field has the additional function of inducing such a field.

[0139] To support different magnetizable particles, non-permanent magnetic fields can be modulated. This is because different particles (whether due to their chemical composition or physical size) may require different bias magnetic field strengths and configurations.

[0140] A magnetic field can be generated by one or more magnetic field generators.

[0141] A permanent magnetic field can be generated using one or more permanent magnets. Alternatively, one or more electromagnets can be configured to apply a continuous and constant magnetic field during the sample reading phase.

[0142] A non-permanent magnetic field can be generated using one or more electromagnets.

[0143] In some embodiments, the electromagnet may be configured to have at least twice the magnetic density of a permanent magnet.

[0144] Non-permanent magnetic fields may be applied for durations of approximately 1.0, 1.25, 1.5, 1.75, 2.0, 2.25, 2.5, 2.75, 3.0, 3.25, or 3.5 seconds, with preferred ranges being these values ​​(e.g., approximately 1.0 to approximately 3.5, approximately 1.0 to approximately 3.25, approximately 1.0 to approximately 3.0, approximately 1.0 to approximately 2.75, approximately 1.0 to approximately 2.5, approximately 1.0 to approximately 3.0) The time can be selected from approximately 2.25, 1.0 to 2.0, 1.0 to 1.75, 1.0 to 1.5, 1.0 to 1.25, 1.5 to 3.0, 1.5 to 2.5, 1.5 to 2.0, 2.0 to 2.25, 2.5, 2.0 to 2.75, 2.0 to 3.0, 2.0 to 3.25, or 2.0 to 3.5 seconds.

[0145] In some embodiments, each sample reading cycle may include a first state (where the first magnetic field is active and the second magnetic field is inactive), a second state (where both the first and second magnetic fields are active), and a third state (where both the first and second magnetic fields are active and the second magnetic field is inactive).

[0146] The fourth stage may be the data analysis stage.

[0147] The method may include processing raw data output from a magnetic field sensor and analyzing the processed data to quantify the amount of target analyte in the sample. Processing of the raw data may be carried out using a combination of hardware and software implementations described in detail elsewhere in this specification.

[0148] The signals detected and measured during the reading phase are recorded as data and analyzed. The output of the magnetic field sensor may be recorded during the sample reading phase.

[0149] The amount of analyte in the sample can be determined based on the change in the magnetic response of the composite of chemically bonded magnetic nanoparticles and the analyte, as detected by a magnetic field sensor.

[0150] In some embodiments, the obtained data is analyzed to identify portions of the dataset corresponding to events 2a-2f and 3a-3b shown in Figures 1a and 1b, as described in paragraphs

[0103] to

[0110] .

[0151] In some embodiments, detection and quantification are derived using data acquired when an external magnetic field is applied or activated. For example, data used for processing and analysis may be derived from events 2b-2f while the magnet is on after the electromagnetic coil has reached saturation.

[0152] In embodiments using permanent magnets, the data used for processing and analysis can be derived from events 2b to 2f while the magnet is turned on, immediately after the magnetic field from the permanent magnet is applied.

[0153] The analytical performance of a detection method is often evaluated by measuring a dose-response curve from which the limit of detection (LoD) can be derived. The LoD is the smallest amount of substance (e.g., a biomarker) that can be detected at a selected confidence level. The selected assay (biomarker, biomaterial, sample matrix, incubation time, etc.) can strongly influence the LoD. The limit of quantification (LoQ), the lowest biomarker concentration that can be quantified with a given required precision, is also used. If the sensitivity of the dose-response curve is good, i.e., the signal changes significantly as a function of the target concentration, the LoQ will be close to the LoD.

[0154] This method can provide LoQ values ​​of approximately 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.5, or 2.0 pg / mL, and a preferred range can be selected from any of these values.

[0155] This method can provide a LoD of approximately 0.1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, or 2.0 pg / mL, and a preferred range can be selected from any of these values.

[0156] In some embodiments, the ambient magnetic field is measured at one or more stages. For example, the ambient magnetic field may be measured at the sample pre-stage, sample introduction stage, sample reading stage, and data analysis stage. The measured ambient magnetic field may be used to adjust the reference magnetic field signal and magnetic field signal acquired at the sample reading stage.

[0157] In some embodiments, the sample may be magnetically shielded from interference from the ambient magnetic field.

[0158] The Discrete Fourier Transform can be used, for example, to analyze the spectrum of a signal acquired from a sensor by separating the time-domain signal into its frequency components.

[0159] In some embodiments, a Fast Fourier Transform (FFT) algorithm may be used to process signal data acquired from a sensor. The FFT process can convert the signal acquired from the sensor into individual spectral components, including, but not limited to, frequency and magnitude.

[0160] Sensor data can be preprocessed before FFT processing. Signal data can be truncated (and concatenated) in one or more dimensions to obtain a dataset optimized for FFT processing. For example, sensor signal output data can be truncated in the time dimension corresponding to events 2a-2f and / or event 3a shown in Figures 1a and 1b.

[0161] In some embodiments, one or more portions of the sensor data may be truncated in one or more dimensions.

[0162] In some embodiments, the portion of the signal data between coil saturation and desaturation in each cycle is truncated.

[0163] In some embodiments, truncated signal data can be concatenated. The concatenated dataset is then subjected to an FFT (Fast-Fast Transform) analysis.

[0164] In some embodiments, windowing can be applied to a dataset. For example, one or more data windows can be concatenated and subjected to FFT processing.

[0165] In some embodiments, signal data for FFT processing may be selected from intermediate cycles during the sample reading phase. For example, from a sample reading phase including five cycles, signal data from the third cycle may be selected for FFT processing.

[0166] The magnetic properties of nano- and micron-sized magnetic materials differ from those of their corresponding bulk magnetic materials. Typically, magnetizable particles are classified as paramagnetic, ferromagnetic, ferrimagnetic, antiferromagnetic, or superparamagnetic based on their magnetic behavior with and without an applied magnetic field.

[0167] According to the embodiment, superparamagnetic nanoparticles (e.g., superparamagnetic iron oxide nanoparticles (SPION)) can be used to accurately detect and measure changes in Brownian motion as an overall magnetic response proportional to the size of the aggregate.

[0168] Superparamagnetic nanoparticles tend to align their magnetic moments in the presence of an external magnetic source and lose their magnetization in the absence of a magnetic field.

[0169] Diamagnetic materials do not exhibit a dipole moment in the absence of a magnetic field, and when a magnetic field is present, they align in the opposite direction to the magnetic field.

[0170] Paramagnetic particles exhibit random dipole moments in the absence of a magnetic field, and align themselves in the direction of the magnetic field when one is present.

[0171] Ferromagnetic materials exhibit aligned dipole moments.

[0172] Ferromagnetic and antiferromagnetic materials exhibit alternately aligned dipole moments.

[0173] In one embodiment, the magnetizable particles are paramagnetic particles. Such particles will become magnetic when a magnetic field is applied. When the magnetic field is removed, the particles will begin to lose their magnetic properties.

[0174] In another embodiment, the magnetizable particles are ferromagnetic particles; that is, they always exhibit magnetic properties regardless of whether a magnetic field is applied.

[0175] Commercially available magnetizable particles include Thermo Fisher Scientific's Dynaparticles M-270, Dynaparticles M-280, Dynaparticles MyOne T1, and Dynaparticles MyOne C1; Miltenyi Biotec's μMACS microparticles; and Spherotech's SPHERO® superparamagnetic particles, SPHERO® paramagnetic particles, and SPHERO® ferromagnetic particles.

[0176] The magnetizable particles may be ferromagnetic particles coated with streptavidin. For example, commercially available streptavidin-coated superparamagnetic particles include Ocean Nano Tech SHS30-01. Streptavidin-coated ferromagnetic particles can be functionalized with biotinylated "detection" antibodies.

[0177] Magnetizable particles can be formed from ferrites (e.g., magnetite and maghemite) that themselves are formed from iron oxide. Various methods (e.g., coprecipitation, pyrolysis, and hydrothermal) are known for synthesizing iron oxide and metal-substituted ferrite magnetizable particles. The coprecipitation process uses stoichiometric amounts of ferrous and ferric salts in an alkaline solution in combination with a water-soluble surface coating material (e.g., polyethylene glycol (PEG)), and the coating provides colloidal stability and biocompatibility. The size and properties of the magnetizable particles can be controlled by adjusting the reducing agent concentration, pH, ionic strength, temperature, iron salt source, or the ratio of Fe2+ to Fe3+.

[0178] The size and shape of the magnetizable particles can be adjusted by changing the reaction conditions (e.g., type of organic solvent, heating rate, surfactant, and reaction time). This method narrows the size distribution of the magnetizable particles to the range of 10–100 nm. To increase the saturation magnetization, Fe2+ can be substituted with other metals.

[0179] The magnetizable particles may be coated with a hydrophobic coating during the synthesis process. If so, the method for producing the magnetizable particles may include an additional step of ligand exchange so that the magnetizable particles can be dispersed in water for further use.

[0180] Magnetizable particles can be produced by hydrothermal reduction of polyols, which generates water-dispersible magnetizable particles in the size range of tens to hundreds of nanometers. The size and surface functionalization of iron oxide magnetizable particles can be optimized by adjusting the type of solvent system, reducing agent, and surfactant used. This process can be used to synthesize FePt magnetizable particles.

[0181] Magnetizable particles can be produced by the reverse water-in-oil micelle method. This method forms a microemulsion of aqueous nanodroplets of an iron precursor stabilized by a surfactant in an oil phase containing magnetic nanoparticles obtained by precipitation. Iron oxide nanocrystals can be assembled by combining the microemulsion and silica sol gel, which can be obtained by coprecipitation as magnetizable particles with a diameter greater than 100 nm.

[0182] Metallic magnetizable particles may be single metals (e.g., Fe, Co, or Ni) or two metals (e.g., FePt and FeCo). Alloy magnetizable particles can be synthesized by physical methods (e.g., vacuum deposition and vapor deposition). These methods can produce FeCo magnetizable particles with high saturation magnetization (about 207 emu / g), which can be synthesized by reduction of Fe³⁺ and Co²⁺ salts.

[0183] Magnetizable particles may include a single metal or metal oxide core. Magnetizable particles may include multiple cores, a multilayer structure of magnetic materials, and non-magnetic materials. Magnetizable particles may include a coating of silica or polymer core having a magnetic shell. Non-magnetic core particles may include silica or other polymers.

[0184] The magnetizable particles may include a dielectric silica core coated with a magnetic shell. The magnetic shell may be formed from Co, FePt, or Fe3O4. The shell may contain a stabilizer (e.g., a silica shell or a polymer electrolyte layer). The magnetizable particles may be mesoporous magnetizable particles.

[0185] Coatings on magnetizable particles can define the interaction between the magnetizable particles and biological molecules (e.g., analytes) and their biocompatibility. Coatings can be used to define surface charge and, in combination with other coatings, can alter the hydrodynamic size of the magnetic particles. The hydrodynamic size of the magnetizable particles can alter their functionality.

[0186] Magnetizable particles may be coated with a specific coating that provides electrostatic and steric repulsion. Such a coating may help stabilize the magnetizable particles, which may prevent aggregation or precipitation of the magnetizable particles.

[0187] The magnetizable particles may include a coating formed from an inorganic material. Such magnetizable particles may be formed in a core-shell structure. For example, magnetizable particles coated with biocompatible silica or gold (e.g., alloy magnetic nanoparticles, silica-coated FeCo and CoPt). The shell may provide a platform for modifying the magnetizable particles with ligands (e.g., thiols). Other inorganic coating materials may include titanates or silver. For example, silver-coated iron oxide magnetizable particles may be synthesized and integrated with a carbon paste.

[0188] The shell can be formed from silica. The advantage of silica coating is the ability of silica-coated magnetizable particles to covalently bond with a variety of functional molecules and surface reactive groups. Silica shells can be manufactured, for example, by the Stöber process, the Phillips process, or a combination thereof, using the sol-gel principle. The core of the magnetizable particle can be coated with tetraethoxysilane (TEOS), for example, by hydrolysis of TEOS under basic conditions. This causes TEOS to condense and polymerize, forming a silica shell on the surface of the magnetic core. Cobalt magnetizable particles can be coated using a modified Stöber process combining 3-aminopropyl)trimethoxysilane and TEOS.

[0189] The Phillips method forms a silica shell of sodium silicate on a magnetic core. A second silica layer can be deposited by the Stöber method. The reverse microemulsion method can be used to coat with silica. This method can be used in conjunction with a surfactant. The surfactant can be selected from Igeoal CO-520 to provide a silica shell thickness of about 5 to about 20 nm. Preferably, the reagent for producing the silica shell is selected from an amino-terminated silane or an alkene-terminated silane. Preferably, the amino-terminated silane is (3-aminopropyl)trimethoxysilane (APTMS). Preferably, the alkene-terminated silane is (3-methacryloxypropyl)trimethoxysilane.

[0190] Magnetizable particles can be coated with gold. Gold-coated iron oxide nanoparticles can be synthesized by any one of the following methods: chemical methods, reverse microemulsion methods, and laser-accelerated methods. Gold-coated magnetizable particles can be synthesized by directly coating a magnetizable particle core with gold. Alternatively, gold-coated magnetizable particles can be synthesized by using silica as an intermediate layer for the gold coating. Preferably, a reduction method is used to deposit the gold shell on the magnetizable particles.

[0191] A metal oxide or silica-coated magnetic core may first be electrostatically deposited on its surface with gold nanocrystalline seeds (from chloroauric acid) of about 2-3 nm in size, and then functionalized with (3-aminopropyl)trimethoxysilane before a reducing agent is added to form a gold shell. Preferably, the reducing agent is a mild reducing agent selected from sodium citrate or tetrakis(hydroxymethyl)phosphonium chloride. In some embodiments, the gold shell is formed from the reduction of gold(III) acetate (Au(OOCCH3)3). In some embodiments, the gold shell is formed on a metal magnetic core (e.g., nickel and iron) by reverse micelles.

[0192] Magnetizable particles can be functionalized with organic ligands. This can be done in-situ (i.e., the functional ligand is provided on the magnetizable particles during the synthesis step) or post-synthesis. Magnetizable particles can be functionalized with terminal hydroxyl groups (-OH), amino groups (-NH2), and carboxyl groups (-COOH). This can be achieved by modifying the surfactant used in the hydrothermal synthesis (e.g., dextran, chitosan, or polyacrylic acid).

[0193] Functionalization of magnetizable particles after synthesis may enable the functionalization of customized ligands on the surface of any magnetizable particle. Post-synthesis functionalization can be performed by ligand addition and ligand exchange. Ligand addition involves adsorption of amphiphilic molecules (containing both hydrophobic segments and hydrophilic components) to form a bilayer structure. Ligand exchange involves replacing the original surfactant (or ligand) with a new functional ligand. Preferably, the new ligand contains a functional group that can bond to the magnetizable particle surface via either strong chemical bonds or electrostatic attraction. In some embodiments, the magnetizable particles also include functional groups for stabilization in water and / or biofunctionalization.

[0194] Magnetizable particles may be coated with ligands to enhance ionic stability. Functional groups may be selected from carboxylates, phosphates, and catechols (e.g., dopamine). The ligand may be a siloxane group for coating a hydroxyl-rich surface (e.g., metal oxide magnetic particles or silica-coated magnetic particles). The ligand may be a small silane ligand that binds the magnetizable particles to various functional ligands (e.g., amines, carboxylates, thiols, and epoxides). To provide carboxylate-terminated magnetic particles, the silane ligand may be selected from N-(trimethoxysilylpropyl)ethylenediaminetriacetic acid and (triethoxysilylpropyl)succinic anhydride. Functional groups may be selected from phosphonic acids and catechols (to provide hydrophilic end groups). Functional groups may be selected from amino-terminated phosphonic acids. Functional groups may be selected from 3-(trihydroxysilyl)propylmethylphosphonate for dispersion in aqueous solution. The ligand for magnetizable particles to be dispersed in water can be selected from dihydroxyhydrocinnamic acid, citrate, or thiomalic acid.

[0195] In some embodiments, magnetizable particles are functionalized with a polymer ligand. The polymer may be selected from natural polymers (e.g., starch, dextran, or chitosan), PEG, polyacrylic acid (PAA), polymethacrylic acid (PMAA), poly(N,N-methylenebisacrylamide) (PMBBAm), and poly(N,N / -methylenebisacrylamide-co-glycidyl methacrylate) (PMG).

[0196] Functional groups on the surface of magnetizable particles function as linkers for binding to complementary biomolecules. These biomolecules may be small. Small biomolecules can be selected from vitamins, peptides, and aptamers. The biomolecules may also be larger. Larger biomolecules can be selected from DNA, RNA, and proteins.

[0197] Regarding the binding of nucleic acids, they can be conjugated by non-chemical methods (e.g., electrostatic interactions) or chemical methods (e.g., covalent bonding). Nucleic acid chains can be modified with functional groups. Functional groups can be selected from thiols, amines, or any combination thereof.

[0198] The conjugation of larger biomolecules may depend on their specific binding interactions with a wide range of substrates and synthetic analogs (e.g., specific receptor-substrate recognition, i.e., antigen-antibody interactions and biotin-avidin interactions).

[0199] Specific protein pairs can be used to immobilize species onto magnetic particles. Physical interactions include electrostatic interactions, hydrophilic-hydrophobic interactions, and affinity interactions.

[0200] In some embodiments, biomolecules have opposite charges to a magnetic polymer coating (e.g., polyethyleneimine or polyethyleneimine). For example, positively charged magnetizable particles that bind to charged DNA.

[0201] Magnetizable particles can utilize biotin-avidin interactions. Biotin molecules and tetrameric streptavidin have low site-specific affinity with low nonspecific binding, which is used to control the orientation of interacting biomolecules (e.g., directing the Fab region of an antibody toward its antigen).

[0202] Magnetizable particles can bind to biomolecules using covalent conjugations. These covalent conjugations can be selected from homobifunctional / heterobifunctional crosslinking agents (amino groups), carbodiimide coupling (carboxyl groups), maleimide coupling (amino groups), direct reactions (epoxide groups), maleimide coupling (thiol groups), Schiff base condensation (aldehyde groups), and click reactions (alkyne / azide groups).

[0203] The magnetizable particles may have an average particle size of approximately 5, 10, 15, 20, 25, 30, 35, 40, 50, 100, 150, 200, 250, 300, 350, 400, 450, or 500 nm, and a preferred range is these values ​​(e.g., approximately 5 to approximately 500, approximately 5 to approximately 400, approximately 5 to approximately 250, approximately 5 to approximately 100, approximately 5 to approximately 50, approximately 1 The following ranges can be selected: 0 to approximately 500, approximately 10 to approximately 450, approximately 10 to approximately 300, approximately 10 to approximately 150, approximately 10 to approximately 50, approximately 50 to approximately 500, approximately 50 to approximately 350, approximately 50 to approximately 250, approximately 50 to approximately 150, approximately 100 to approximately 500, approximately 100 to approximately 300, approximately 150 to approximately 500, approximately 150 to approximately 450, or approximately 200 to approximately 500 nm.

[0204] The magnetizable particles may have an average particle size of approximately 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, or 1000 nm, and a suitable range can be selected from any of these values ​​(e.g., approximately 500 to approximately 1000, approximately 500 to approximately 850, approximately 500 to approximately 700, approximately 550 to approximately 1000, approximately 550 to approximately 800, approximately 600 to approximately 1000, approximately 600 to approximately 900, approximately 650 to approximately 1000, approximately 650 to approximately 950, approximately 650 to approximately 800, or approximately 700 to approximately 1000 nm).

[0205] The magnetizable particles may have an average particle size of approximately 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, or 5000 nm, and a suitable range may be selected from any of these values ​​(e.g., approximately 1000 to approximately 5000, approximately 1000 to approximately 4000, approximately 1500 to approximately 5000, approximately 1500 to approximately 4500, approximately 1500 to approximately 3500, approximately 2000 to approximately 5000, approximately 2000 to approximately 4000, approximately 2500 to approximately 5000, approximately 2500 to approximately 3500, approximately 3000 to approximately 5000 nm).

[0206] The variation in the particle size of the magnetizable particles may be less than 25, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1%, and a preferred range may be selected from any of these values.

[0207] In some embodiments, the magnetizable particles may include 30 nm superparamagnetic particles.

[0208] In some embodiments, the magnetizable particles may include superparamagnetic particles with a size of 50 nm.

[0209] In some embodiments, the binder and magnetizable particles (beads) may be provided in a predetermined ratio.

[0210] The binder and magnetizable particles have a binder-to-magnetizable particle ratio of approximately 10:1, 9:1, 8:1, 7:1, 6:1, 5:1, 4:1, 3:1, 2:1, 1.5:1, 1:1, 0.75:1, 0.5:1, 0.25:1, 1:0.25, 1:0.5, 1:0.75, 1:1.5, 1:2, 1:3, 1:4, 1:5, 1:6, 1:7, 1:8, 1: The ratio may be 9 or 1:10, and a preferred range may be selected from any of these values ​​(e.g., about 10:1 to about 1:10, about 9:1 to about 1:9, about 8:1 to about 1:8, about 7:1 to about 1:7, about 6:1 to about 1:6, about 5:1 to about 1:5, about 4:1 to about 1:4, about 3:1 to about 1:3, about 2:1 to about 1:2, about 0.75:1 to about 1:0.75).

[0211] The ratio of binder to magnetizable particles may be the ratio of the number of magnetizable particles to the number of binders. For example, if the ratio of binder to beads is 0.75:1, then 0.75 ng of binder corresponds to 1 μg of beads.

[0212] Following the above example, the 30 nm beads (Ocean NanoTech) may have a molar concentration of 34 fmole / μl or 0.034 μM, which means the number of beads per μl (bead concentration is 1 μg / μl) is approximately 2.047 × 10⁶. 10 It can be calculated as beads (34 × 10 -15 Avogadro's number doubled = 34 × 10⁻¹⁴ -15 ×6.0 23 ×1023 = 2.047 × 10 10 (Individual beads).

[0213] The molecular weight of the binder may be about 150977.24 g / mol. Next, the number of binders of 0.75 ng is 2.99×10 9 binders (the number of moles of the binder is 0.75 ng / 150977.24 g / mol = 4.97×10 -15 moles). To obtain the number of binders per 0.75 Ng, the number of moles can be multiplied by Avogadro's number (4.97×10 -15 moles × 6.023×10 23 = 2.99x10 9 binders).

[0214] The molar ratio is calculated as 2.047×10 10 beads / 2.99×10 9 binders = 6.846. That is, there is 1 binder for every approximately 7 beads. The surface area of one bead with a diameter of 30 nm is about 2827.43 nm 2 . Therefore, one binder would correspond to 7×2827.43 nm 2 = 19792.01 nm 2 .

[0215] ]>In some embodiments, the binder and the surface of the magnetizable particles may be provided in a predetermined ratio of binder to surface area.

[0216] The ratio of binder to surface area is approximately 1 to 2,000, 2,500, 3,000, 3,500, 4,000, 4,500, 5,000, 5,500, 6,000, 6,500, 7,000, 7,500, 8,000, 8,500, 9,000, 9,500, 10,000, 10,500, 11,000, 11,500, 12,000, 12,500, 13,000, and 13,500. 0, approximately 14,000, approximately 14,500, approximately 15,000, approximately 15,500, approximately 16,000, approximately 16,500, approximately 17,000, approximately 17,500, approximately 18,000, approximately 18,500, approximately 19,000, approximately 19,500, approximately 20,000, approximately 20,500, approximately 21,000, approximately 21,500, approximately 22,000, approximately 22,500, approximately 23,000, approximately 23,500, approximately 24,000, approximately 24,500, or approximately 25,000 nm 2 This may be the case, and a suitable range may be selected from any of these values.

[0217] Particles may or may not be anchored. Anched particles are anchored to larger secondary particles (polymers). Unanchored particles can diffuse freely throughout the sample, while anchored particles have limited diffusivity and can diffuse freely within the range of their anchorage in the sample. As described above, the amount of analyte in the sample is determined based on changes in the signal detected by the sensing module. The sensing module detects changes based on the pure movement of particles.

[0218] The particles can adhere to other objects (e.g., larger secondary particles or molecules). Magnetizable particles can also adhere to surfaces. Adhesion to other objects or surfaces allows the magnetizable beads to be positioned in specific locations while retaining the ability to cause Brownian diffusion (within the limits of adhesion or mooring) that is detectable and measurable by instrument.

[0219] When anchored appropriately, particles can retain their ability to undergo Brownian diffusion while being localized as specific locations within a larger shared volume. Therefore, multiple types of magnetizable particles (types based on analyte recognition or other properties) can all exist in separate locations (e.g., aligned with specific magnetic sensors) while remaining within the shared volume, enabling multiplexed detection of different target analytes within a single volume.

[0220] This multiplexed detection is made possible by anchoring non-magnetic beads or microchannels to the surface. Non-magnetizable beads can act as "anchors" that retain anchored particles in the field, depending on the combination of their size, surface chemistry, and interaction with the local environment.

[0221] For example, magnetizable particles can be molecularly anchored to larger non-magnetizable particles (e.g., latex beads), causing the magnetizable particles to localize to specific regions due to the larger non-magnetizable beads, but still allowing them to diffuse freely within the limits of anchoring. In another example, magnetizable particles can be molecularly anchored to a surface (e.g., the surface of a microfluidic device corresponding to the sensing zone of a sensing module).

[0222] The non-magnetizable particles may include any suitable non-magnetizable particles (including, but not limited to, latex beads, polystyrene beads, or other types of polymer beads).

[0223] In some embodiments, non-magnetizable particles (e.g., latex beads having surface chemicals (e.g., amines and carboxyl groups)) may have molecular anchors (e.g., polyethylene glycol-PEG) attached to them, one end of which is bonded to the latex bead (a chemical that is compatible with the surface of the latex bead), and the other end of which is bonded to a magnetizable bead (where the chemical is compatible with the surface of the magnetic bead, for example, biotin on the anchor is bonded to streptavidin on the surface of the magnetic bead), thereby forming an anchored link between the two beads.

[0224] The molecular anchoring length may be approximately 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, or 80 nm.

[0225] The method can be carried out using a microfluidic device or system.

[0226] Microfluidics may require some degree of sample preparation. Sample preparation may include cell lysis, washing, centrifugation, separation, filtration, and elution. In some embodiments, sample preparation is performed off-chip. Alternatively, sample preparation is performed on-chip.

[0227] In some configurations, the sample to be analyzed can be added directly to the sample well or microfluidic device without additional processing. The microfluidic system may contain a fluid. The fluid may be selected from phosphate-buffered saline (PBS). The phosphate-buffered saline may contain dipotassium phosphate (K2HPO4), sodium chloride (NaCl), and disodium phosphate (Na2HPO4). PBS provides a continuous phase in which particles are suspended.

[0228] Microfluidic systems enable faster analysis and shorter response times. They also offer the ability to automate sample preparation, thereby reducing the risk of contamination and human error. Furthermore, microfluidic systems require small sample volumes. Microfluidics can reduce diffusion distance by increasing the surface area-to-volume ratio, reducing reagent consumption through micro- and nano-fabricated channels and chambers, and automating all steps of the process.

[0229] In some configurations, the microfluidic system may include rigid or flexible materials and may include electronic devices that can be integrated into the device. The electronic devices may include wireless communication electronics.

[0230] The microfluidic system may be a flow-type or stationary system. For example, the microfluidic system may include a magnetic field sensor stationary to the microfluidic system.

[0231] Microfluidic systems can operate passively. For example, a microfluidic system can operate under passive diffusion. In other words, a microfluidic system does not require actively generated flow to function effectively.

[0232] The microfluidic system may include a network of reservoirs, which may be connected by microfluidic channels. These microfluidic channels may be configured for active or passive measurements. This allows the sample fluid to be drawn into the microfluidic channels and passed through the sample chamber.

[0233] Microfluidic systems enable miniaturization, which is crucial for lab-on-a-chip applications. Microfluidic systems can be used as part of a biosensor, which may include, for example, channels for acquiring biological samples (e.g., saliva and / or gingival crevicular exudate and / or tears and / or sweat), channels for processing fluids (e.g., combining with one or more reagents and / or detecting interactions with biomolecules).

[0234] Microfluidic systems can be implemented in the form of microfluidic chips. A microfluidic chip includes a set of micrometer or millimeter-sized channels provided, for example, by molding or etching a material (e.g., glass, silicon, or other types of polymers) or a combination of materials. The microfluidic channels can be interconnected to form a network of channels. The length of the channels may vary from millimeters to centimeters.

[0235] The microfluidic chip may include one or more ports for receiving samples and / or reagents. For example, the microfluidic chip may include a sample inlet port and a reagent port.

[0236] The microfluidic chip may include multiple detection regions. Each detection region defines a portion of the channel where the analyte or biomarker in the sample is detected and quantified. The detection regions of the microfluidic chip correspond to the locations of the device's magnetic sensors, and each detection region is aligned perpendicularly to its corresponding magnetic / other sensor when the microfluidic chip is placed on the device's detection surface.

[0237] The detection region can be positioned at any location along the channel. In some embodiments, the detection region is located at a channel junction; that is, at the intersection of two or more channels.

[0238] The channel junction may include a reaction / detection well. The reaction / detection well may have dimensions larger than the channel.

[0239] Microfluidics may require some degree of sample preparation. Sample preparation may include cell lysis, washing, centrifugation, separation, filtration, and elution. In some embodiments, sample preparation is performed off-chip. Alternatively, sample preparation is performed on-chip.

[0240] Microfluidic chips can be supplied in a "ready-to-use" format. For example, a microfluidic chip may be pre-loaded with all the necessary components and cell separation (e.g., binder complex and reagents) for analyte detection and quantification. In other words, in a "ready-to-use" format, all that is required is to add the sample to the microfluidic device.

[0241] The reaction / detection wells may be pre-loaded with a binder complex for binding one or more target analytes. The binder complex may be provided within a gel matrix in the reaction / detection well. For example, each reaction / detection well may contain a hydrogel, agarose gel, or agar containing the binder complex. The binder complex is described in detail later in this specification.

[0242] The binder complex and / or reagents may be added to the reaction / detection wells before use.

[0243] The microfluidic system may include rigid or flexible materials and may include electronic devices that can be integrated into the microfluidic chip. The electronic devices may include wireless communication electronic devices.

[0244] The microfluidic system may be a flowing or stationary system. For example, the microfluidic system may include a magnetic field or other sensors stationary relative to the microfluidic system.

[0245] Microfluidic systems can operate passively. For example, a microfluidic system can operate under passive diffusion. In other words, a microfluidic system does not require actively generated flow to function effectively.

[0246] The microfluidic system may include a network of reservoirs, which may be connected by microfluidic channels. These microfluidic channels may be configured for active or passive measurements. This allows the sample fluid to be drawn into the microfluidic channels and passed through the sample chamber.

[0247] The channels can be arranged in a crosshatch configuration.

[0248] A microfluidic system may include microfluidic channels configured to allow access to various samples and / or detection areas on the device at different points in time. For example, a microfluidic device incorporated in or on an aligner may be configured to provide timing through temporal sampling of the fluid. For instance, a microfluidic system can be designed to allow sampling at time-series controlled timings. In some variations, the timing of the fluid in a microchannel can be actively regulated by opening the channel, for example, through the release of a valve (e.g., an electromechanical valve, solenoid valve, or pressure valve). Examples of valves for controlling the fluid in a microfluidic network include piezoelectric, electro-dynamic, and chemical approaches.

[0249] The channels of the microfluidic chip may include a wicking structure. The wicking structure can improve the rate of fluid transport by capillary action. The wicking structure may include a porous medium (e.g., paper-based material).

[0250] The microfluidic chip may include multiple microfluidic channels arranged in a continuous pattern. Fluid can be drawn into the microfluidic channels at a measured velocity. The timing of sample access to the channels can be adjusted.

[0251] Microfluidics can perform signal multiplexing; that is, microfluidics can be used to sample and / or measure multiple biomarkers at controlled intervals. For example, microfluidics can be used to provide access to one or more sample chambers. The microfluidics may include one or more valves controlled by a control circuit within the device. One or more valves can be connected to each other. Thus, microfluidics can be adapted to perform simultaneous detection of multiple analytes in a common sample body. Additionally or alternatively, microfluidics can be configured to perform simultaneous multiplex detection of multiple samples of the same target.

[0252] Microfluidic channels may have cross-sectional areas in the range of approximately 0.001–0.01 mm², 0.01–0.1 mm², 0.1–0.25 mm², 0.25–0.5 mm², 0.1–1 mm², 0.5–1 mm², 1–2 mm², or 2–10 mm², and a useful range may be selected from any of these values.

[0253] In some embodiments, the microfluidic receives a predetermined sample volume in the range of approximately 0.1–1 μL, 1–5 μL, 5–10 μL, 10–20 μL, or 20–50 μL or more, and a useful range can be selected from any of these values.

[0254] An example of a sample introduction device / microfluidic chip is shown in Figure 2. The microfluidic chip may include multiple channels arranged to guide the sample from the sample insertion area to the detection area, and functionalized particles for analyte detection.

[0255] The channel may have the cross-sectional dimensions described above, more preferably about 0.01 mm² (0.1 mm × 0.1 mm). The length of the channel may be variable. For example, the channel length may be 1, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 120, 140, 160, 180, 200, 250, or 300 mm, and a useful range may be selected from any of these values ​​(e.g., approximately 1-10, 1-20, 1-50, 1-100, 1-200, 1-300, 10-20, 10-40, 10-60, 10-80, 10-100, 50-100, 50-150, 50-200, 250-50, 300-100, or 100-300 mm).

[0256] The channel dimensions described above promote passive capillary flow.

[0257] During use, the sample is introduced into the microfluidic device through the sample insertion area. The sample insertion area may include an inlet port.

[0258] A filter membrane may be present in the insertion region to separate and allow passage of the desired components of the sample. For example, plasma derived from blood can pass through the microfluidic chip, but cells cannot. The presence of the filter membrane is determined by the nature of the sample and whether it contains components that are not desired to pass through the microfluidic chip.

[0259] Plasma cell separation can occur either within or outside of the device configuration.

[0260] Once introduced into the insertion region, the sample contacts the microfluidic channel and flows through the remainder of the channel circuit.

[0261] The microfluidic system can be implemented as a lab-on-a-chip. The lab-on-a-chip may include one or more magnetic sensors proximate to the channel. For example, the microfluidic device 1 may include 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30 magnetic sensors disposed around the microfluidic device.

[0262] The lab-on-a-chip may include, for example, two or more magnets (e.g., permanent magnets or electromagnets) disposed proximate to the channel, which can operate to attract magnetizable particles through the liquid in the channel to promote mixing. Mixing can be performed, for example, for 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 minutes, and a suitable range can be selected from any of these values. The timing of mixing can be determined by assay requirements (e.g., sample volume, viscosity, composition, and detection range of the target analyte).

[0263] To facilitate mixing, magnets (e.g., electromagnets) may be positioned at substantially opposite ends of the channel or microfluidic device. For example, the magnets may be controlled or switched to push / pull magnetizable particles toward one end of the well / channel or microfluidic device. The effect is then reversed to attract the magnetizable particles toward the other end of the well / channel or microfluidic device. This cycle may be repeated multiple times until the desired level of mixing is achieved.

[0264] According to one embodiment, the described method may be carried out using an apparatus for detecting an analyte in a sample, which essentially consists of the following: ● Sample wells that are separate from or integrated with microfluidic devices, ●Magnets for generating an external magnetic field, ● A magnetic signal sensor for measuring the magnetic signal in the sample well (the magnetic signal sensor is adapted to measure the magnetic signal, but an external magnetic field is active).

[0265] According to another embodiment, the described method may be carried out using a device for detecting an analyte in a sample, which essentially consists of: ● Sample wells that are separate from or integrated with microfluidic devices, ● A first magnet is positioned below the sample well (the first magnet is adapted to continuously apply a magnetic field), ● A second magnet is positioned above the sample well (the second magnet is adapted to apply a magnetic field discontinuously), ● A magnetic signal sensor for measuring the magnetic signal in the sample well (the magnetic signal sensor is adapted to measure the magnetic signal when both continuous and discontinuous magnetic fields are active).

[0266] A magnetic field generator may include a magnet.

[0267] A magnetic field generator can generate a magnetic field perpendicular to the sensor. For example, a magnetic field generator can generate a magnetic field from above and / or below the magnetic field sensor such that the magnetic field is perpendicular to the body of the magnetic field sensor.

[0268] A magnetic field generator can generate a magnetic field parallel to the sensor. For example, a magnetic field generator can generate a magnetic field from the side of the magnetic field sensor so that the magnetic field is parallel to the body of the magnetic field sensor.

[0269] The device may include a combination of magnetic field generators that generate magnetic fields perpendicular to and parallel to the sensor, respectively.

[0270] The magnetic field generator may be configured to generate a magnetic field from below and / or above the sample.

[0271] The magnet may be an electromagnet. The electromagnet can exert a magnetic field strength of approximately 0.5, 1, 5, 10, 15, 20, 25, 30, 35, 40, 45, or 50 gauss, and a preferred range may be selected from any of these values.

[0272] In some embodiments, the magnet may include a combination of a permanent magnet and an electromagnet. For example, the first magnet may be a permanent magnet that exerts a continuous magnetic field, and the second magnet may be an electromagnet that applies a discontinuous magnetic field.

[0273] The permanent magnet may include any suitable permanent magnet. In some embodiments, the permanent magnet may be selected from one or more of the following: ceramic, samarium cobalt (SmCo), aluminum nickel cobalt (AlNiCo), and neodymium iron boron magnets.

[0274] The magnet can exert a magnetic field strength of approximately 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 5, 10, 50, or 100 gauss, and a preferred range can be selected from any of these values. Next, sample data is obtained as described.

[0275] Magnetizable particles are sensed by magnetic sensors.

[0276] Magnetic sensors can be selected from spintronic sensors, atomic magnetometers (AM), nuclear magnetic resonance (NMR) systems, fluxgate sensors, Faraday induction coil sensors, diamond magnetometers, and domain wall-based sensors.

[0277] Capacity-based sensors (e.g., planar Hall effect (PHE) sensors) offer simple and rapid sample preparation and detection. Surface-based sensors (e.g., giant magnetoresistance (GMR)) have a lower detection limit (single particle) due to the short distance between the magnetizable particle and the sensor. However, these methods typically require cumbersome sample and / or substrate preparation. As the demands for detection sensitivity, molecular specificity, and application complexity increase, optimizing magnetizable particles and selecting the appropriate detection method for specific applications remains a challenge for the magnetic nanotechnology community. Spintronic sensors can be selected from giant magnetoresistance (GMR), tunnel magnetoresistance (TMR), anisotropic magnetoresistance (AMR), and planar Hall effect (PHE) sensors.

[0278] The GMR effect was discovered in the 1980s and has traditionally been used for data recording. Spin valves offer high sensitivity due to their micron-sized design. Spin valve GMR sensors consist of an artificial magnetic structure with alternating ferromagnetic and non-magnetic layers. The magnetoresistance effect is caused by spin-orbit coupling between conduction electrons across different layers. Variations in magnetoresistance allow for quantitative analysis with this spin-dependent sensor. GMR sensors can be used to detect DNA-DNA interactions or protein (antibody)-DNA interactions. The dimensions of the sensor array can be adjusted for the detection of individual magnetizable particles. GMR sensors can be used in combination with antiferromagnetic particles.

[0279] The planar Hall effect is an exchange-biased permalloy planar sensor based on the anisotropic magnetoresistance effect of ferromagnetic materials. The PHE sensor may be a spin valve PHE or a PHE bridge sensor. The PHE sensor may be capable of performing single particle sensing.

[0280] As will be understood by those skilled in the art, Brownian motion or Brownian diffusion can mean that particles can move in any direction (e.g., the direction towards a magnetic field sensor or an electric field sensor). The magnetic signal detected by the magnetic field sensor is based on the net movement of bound and unbound magnetizable particles. The electrical signal detected by the electric field sensor is based on the change in impedance when the particles move through the continuous phase (e.g., PBS).

[0281] When bound and unbound particles are placed near a magnetic sensor or an electric field sensor, the bound and unbound particles can be located on or near the surface of the wall of the sample well or sample reservoir until they are released. When released from near the magnetic or electric field sensor, the particles can move by translation or rotation. Considering that they are close to the surface of the sample well or sample reservoir immediately before being released from the bias system, bound and unbound magnetizable particles typically tend to move with an approximately 180° free movement with respect to the surface of the sample well or sample reservoir initially.

[0282] The magnetic field can be generated and arranged to maximize the influence on magnetizable particles while minimizing the influence on the magnetic field sensor. The magnetic field generator can be generated and / or arranged very close to the poles of the magnetic field sensor. In some embodiments, the magnetic field generator is arranged above, below, or to the side of the magnetic field sensor. In some embodiments, the magnetic field generator can be arranged on the same vertical or horizontal plane as the magnetic field sensor.

[0283] The magnetic field can be gradually reduced.

[0284] The magnetic field can be removed immediately.

[0285] The shape of the magnetic field may be variable.

[0286] When the magnetic field applied to the sample is reduced and / or removed, the bound and unbound binder complexes are released from the magnetic field and can freely diffuse (translate) away from the vicinity of the magnetic field sensor. When the magnetic field applied to the sample is reduced and / or removed, the binder complexes can also rotate (rotate) relative to the magnetic field sensor.

[0287] The magnetic field sensor may be an on-chip magnetometer. The magnetic field sensor may have a sensitivity of at least 1 mV / V / Gauss. In some embodiments, the magnetic field sensor may detect and / or measure magnetic fields of at least about 10 mGauss, 1 mGauss, 100 μGauss, or 10 μGauss.

[0288] A magnetic field sensor may include multiple axes (for example, one axis, two axes, or three axes).

[0289] The magnetic field sensor may be a Honeywell HMC1021S magnetometer. In another embodiment, the magnetic field sensor may be a Honeywell HMC1041Z magnetic sensor. In yet another embodiment, the magnetic field sensor may be selected from the group including Honeywell HMC1001, HMC1002, HMC1022, HMC1051, HMC1052, HMC1053, or HMC2003 magnetometers.

[0290] The magnetic field sensor may include a custom-made magnetic field sensor with custom components.

[0291] To achieve a high level of accuracy and sensitivity, the magnetic sensor of the device may include a high sampling rate. The magnetic sensor may sample at sampling rates of approximately 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, or 250 kHz, and a preferred range can be selected from any of these values ​​(e.g., approximately 10 to approximately 250, approximately 10 to approximately 200, approximately 10 to approximately 150, approximately 10 to approximately 100, approximately 100 to approximately 250, approximately 100 to approximately 200, approximately 100 to approximately 150 kHz).

[0292] The ADC sampling rate of a magnetic sensor can have a sampling rate of approximately 100kHz to approximately 200kHz.

[0293] The magnetic sensor may have a sampling rate of approximately 150 kHz per channel.

[0294] Multiple magnetic sensors may be provided on the detection surface to simultaneously measure changes in the magnetic field. For example, the detection surface may include 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, and 50 magnetic sensors.

[0295] Magnetic field sensors can be provided in a relatively small area within a device. For example, 24 magnetic field sensors can be provided in an area of ​​approximately 13 mm x 19 mm. Such a configuration allows for shorter sample-to-data times because the microfluidic channels used in this magnetic field sensor configuration are short. This configuration also enables small, portable devices.

[0296] The device may include approximately 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15 magnetic field sensors per cm² of the printed circuit board, and a useful range can be selected from any of these values ​​(e.g., approximately 5 to 15, 5 to 13, 5 to 10, 6 to 15, 6 to 12, 6 to 9, 7 to 15, 7 to 14, 7 to 13, 7 to 10, 8 to 15, 8 to 14, 8 to 11, 9 to 15, 9 to 13, or 10 to 15 sensors per cm² of the printed circuit board).

[0297] In some embodiments, multiple magnetic field sensors may be used simultaneously to measure changes in the magnetic field. For example, 50, 60, 70, 80, 90, 100, 110, or 120 magnetic field sensors for small portable applications and in situ laboratory or clinical applications, and a useful range may be selected from any of these values ​​(e.g., approximately 50 to approximately 120, approximately 50 to approximately 100, approximately 50 to approximately 90, approximately 50 to approximately 80, approximately 60 to approximately 120, approximately 60 to approximately 110, approximately 60 to approximately 90, approximately 70 to approximately 110, approximately 70 to approximately 90, approximately 80 to approximately 120, or approximately 80 to approximately 110 magnetic field sensors).

[0298] In some embodiments, multiple magnetic field sensors may be used simultaneously to measure changes in the magnetic field. For example, 1000, 1250, 1500, 1750, 2000, 2250, 2500, 2750, or 3000 magnetic field sensors for laboratory or clinical, research, or industrial applications.

[0299] Sensor-based data acquisition can be synchronized with microfluidic devices. This allows the data from a detection sensor to be characterized as either sample data, environmental data, or ambient data. For example, if a magnetic sensor detects a signal without sample injection into a microfluidic device, that data would be characterized as environmental or ambient data. Characterizing the data as environmental or ambient data helps establish a background and can also be useful in preparing calibration data.

[0300] If a magnetic sensor detects a signal after a sample has been injected into a microfluidic device, this is consistent with the magnetizable particles being positioned in close proximity to the magnetic sensor, and such data can be characterized as sample data.

[0301] By utilizing such a sensing system, an embodiment can be realized in which microfluidic quality control measurements can be performed while confirming the displacement of the sample and the sensing time.

[0302] Data acquisition from the sensor may be continuous. That is, the magnetic sensor continuously transmits a signal, and the data is characterized as sample data or background data based on the synchronization of data acquisition with the injection of the sample into the microfluidic device.

[0303] Sensor data may be acquired over a period of time to measure changes in the magnetic signal from magnetizable particles. An action or event may be inferred to be the change in the sensed magnetic signal. The action or event may include the movement of magnetizable particles from fluid flow, external magnetic force, or diffusion.

[0304] The target analyte can be any substance or molecule that is complementary to and can bind to the binding molecule provided to the magnetizable particle. For example, the target analyte can be selected from the group consisting of proteins, peptides, nucleic acids, lipids, or carbohydrates, biochemicals, biological substances, viruses, bacteria, etc.

[0305] The target analyte may be a protein or fragment thereof selected from the group consisting of antibodies, enzymes, signaling molecules, or hormones.

[0306] The target analyte may be a nucleic acid selected from the group consisting of DNA, RNA, cDNA, mRNA, or rRNA.

[0307] The method can detect multiple target analytes in a single sample. For example, the method can detect two or more, three or more, four or more, five or more, ten or more, fifteen or more, twenty or more, forty or more, or fifty or more target analytes in a single sample.

[0308] The sample to be analyzed may be any sample that may contain one or more target analytes. For example, the sample may be a clinical, veterinary, environmental, food, forensic, or other suitable biological sample.

[0309] Clinical samples may be selected from body fluids. For example, body fluids may be selected from blood, sweat, saliva, urine, sputum, semen, mucus, tears, cerebrospinal fluid, amniotic fluid, gastric juice, gingival crevicular fluid, or interstitial fluid.

[0310] Environmental samples may be selected from the group consisting of water, soil, or aerosols.

[0311] An advantage of the present invention may be that sample preparation is not cumbersome or difficult. Sample preparation utilizes established biochemistry for the functionalization and binding of molecules on microfluidic surfaces or magnetizable particle surfaces.

[0312] The sample to be analyzed can be added directly to the sample well or microfluidic device without any additional processing.

[0313] A sample may be subjected to one or more sample processing steps. It will be understood that the preferred sample processing step may depend on the type and / or nature of the sample to be analyzed. In some embodiments, the sample processing step may be selected from the group including dilution, filtration, or extraction (e.g., liquid phase, solid phase). This may also be achieved by the microfluidic features and design, or by the use of centripetal force. For example, to separate the plasma to be analyzed, a whole blood sample may be filtered using a cellulose-based filter or other filter.

[0314] The method may include combining the sample to be analyzed with a preparation containing freely diffusible magnetizable particles coated with a binding molecule (binder complex) complementary to the target analyte in a sample well or sample reservoir. If necessary, the term “binder complex” may be used interchangeably to refer to magnetizable particles coated with the binding molecule.

[0315] In some embodiments, magnetizable particles may limit their diffusivity. This can occur if the magnetizable particles are crosslinked or derivatized with a polymer. The polymer may be a hydrogel or a PEG linker. This can occur when using the device in a multiplexed assay to detect multiple targets or samples within a single sample.

[0316] This method can improve the rate at which binding molecules bind to the target analyte by providing a binder complex that is mobile and freely diffusible in solution. When the sample and binder complex preparation are combined, the binder complex diffuses freely, and the binding molecules can interact with the target analyte throughout the entire sample volume. Since both the binder complex and the target analyte diffuse freely and are suspended within the sample volume, the average physical distance between the target analyte and the binder complex can be reduced. Therefore, the binding rate may be improved, and binding equilibrium may be achieved much faster.

[0317] In detection assays (e.g., ELISA), the binding molecule (e.g., antibody) is immobilized on a macro-scale object (e.g., the surface of the test well). In such methods, the physical distance between the target analyte and the antibody can vary considerably depending on the position of the analyte within the sample volume. For example, the target analyte near the top of the sample volume may be quite far from the immobilized antibody and less likely to be captured and bound. Therefore, the binding rate may be limited by the rate at which the target analyte diffuses toward the immobilized antibody within the sample volume.

[0318] The sample-binder complex may be mixed for an appropriate amount of time so that the binding molecules can reach binding equilibrium. In some embodiments, the preferred time to allow binding to reach equilibrium may be about 1, 2, 3, 4, 5, 10, 20, 30, 45, 60, 90, 120, 180, 240, 300, or 360 seconds (multiple), and a useful range may be selected from any of these values ​​(e.g., about 1-30, 1-60, 1-120, 10-30, 10-60, 10-90, 30-60, 30-90, 30-120, 60-90, 60-120, 60-180, 90-120, 90-180, 90-240, 180-240, 180-300, 180-360 seconds).

[0319] A magnetic field generator can be used to induce magnetohydrodynamic mixing of a sample to improve the rate at which it reaches coupling equilibrium. In such embodiments, the magnetic field generator is used to induce the movement of the binder complex within the sample volume.

[0320] This method can be understood to be widely applicable to any application requiring the detection and / or quantification of a target analyte. In particular, the method can be used in applications requiring the following: ●Rapid measurement, or ● High-sensitivity measurement, or ●Quantitative measurement, or ● Or any combination of (i) to (iii), (Regarding the presence of the target analyte in the sample).

[0321] For example, suitable applications may include clinical, veterinary, environmental, food safety, or forensic applications.

[0322] In some embodiments, clinical applications may include the diagnostic detection of biomarkers in samples that may indicate a clinical condition. For example, the method may be used for the rapid, highly sensitive, and quantitative diagnostic detection of specific antibodies in blood samples that may indicate a potential infection by a pathogen. In further embodiments, the method may be used for the diagnostic detection of specific protein biomarkers that are overexpressed in cancer. Diagnostic detection may be performed on samples of various species.

[0323] Clinical conditions may be selected from infectious diseases (e.g., bacteria, fungi, viruses (e.g., hepatitis, SARS-CoV-19, and HIV) (e.g., biomarkers such as hepatitis, SARS-CoV-19, and HIV antibodies)), parasitic conditions (e.g., microorganisms, parasites [e.g., malaria], nematodes, insects, parasites), etc.

[0324] Clinical conditions may be selected from diseases (e.g., heart disease (biomarkers such as BNP), cancer (e.g., solid organ cancer, hematological cancer, other cancers) (biomarkers such as Ca-125 and other tumor markers), neurological diseases (e.g., multiple sclerosis, Alzheimer's disease, Parkinson's disease, Huntington's disease) (biomarkers such as CNS immunoglobulins), respiratory diseases (biomarkers such as serum ACE), liver diseases (e.g., liver function tests and biomarkers such as albumin), and kidney diseases (biomarkers such as creatinine and protein)).

[0325] The clinical condition may be selected from organ injury or dysfunction (e.g., brain injury (e.g., biomarkers such as glial fibrillary acidic protein or GFAP), kidney injury (e.g., biomarkers such as serum creatine), heart injury (e.g., biomarkers such as creatine kinase-muscle), lung injury (e.g., biomarkers such as intercellular adhesion molecule-1 or ICAM1), or liver injury (e.g., biomarkers such as alkaline phosphatase).

[0326] Clinical conditions may be selected from endocrine disorders (e.g., diabetes (e.g., insulin, elevated HbA1c, thyroid dysfunction, biomarkers such as thyroid hormones), pituitary disorders (e.g., ACTH, prolactin, gonadotropins, thyroid-stimulating hormone, growth hormone, antidiuretic hormone, biomarkers such as these), parathyroid disorders (e.g., biomarkers such as parathyroid hormone), adrenal disorders (e.g., biomarkers such as cortisol, aldosterone, adrenaline, DHEAS), sex hormone imbalance (e.g., biomarkers such as androgens and estrogens), carcinoid tumors (e.g., 5-HIAA, VIPoma, biomarkers such as serum VIP), and hypermetabolism (e.g., biomarkers such as P1NP).

[0327] The clinical condition may be selected from dyslipidemia (e.g., biomarkers such as cholesterol and triglycerides).

[0328] Clinical conditions may be selected from nutritional disorders (e.g., vitamin deficiencies, malabsorption syndromes, malnutrition, vitamin metabolic disorders) and biomarkers (e.g., vitamin levels, iron levels, mineral levels, etc.).

[0329] The clinical condition may be selected from inflammation or inflammatory diseases (e.g., biomarkers such as ESR, Crp, and other acute-phase proteins).

[0330] The clinical condition may be selected from autoimmune diseases (e.g., biomarkers such as specific antibody markers).

[0331] The clinical condition may be selected from allergic diseases (e.g., biomarkers such as tryptase).

[0332] Clinical conditions may be selected from physical trauma, such as electric shock (e.g., biomarkers such as creatinine kinase).

[0333] The clinical condition may be selected from immunodeficiency disorders (e.g., unclassified immunodeficiency) (e.g., biomarkers such as complement, leukocytes, and immunoglobulins).

[0334] The clinical condition may be selected from coagulation disorders (e.g., thrombosis) (e.g., biomarkers such as coagulation factors and other markers).

[0335] Clinical conditions may be selected from hereditary or acquired enzyme disorders, metabolic deficiencies or excesses, and other congenital or acquired defects (e.g., Bartter syndrome, congenital adrenal hyperplasia) (e.g., biomarkers such as electrolytes, enzyme levels, enzyme metabolites).

[0336] The clinical condition may be selected from electrolyte abnormalities (e.g., hyperkalemia and hypernatremia, e.g., biomarkers such as electrolytes).

[0337] The clinical condition may be selected from drug side effects or intoxication (e.g., biomarkers such as drug levels and drug metabolite levels).

[0338] Clinical conditions may be selected from adverse effects or poisoning resulting from exposure to chemical weapons, biological weapons, or other chemical and biological substances in the environment.

[0339] Clinical conditions specific to veterinary medicine may be selected from renal failure, FIV / AIDS (feline), cancer, and any biomarkers of organ function / failure.

[0340] In some embodiments, the clinical condition may be a condition in a veterinary subject (e.g., a feline, canine, bovine, sheep, equid, pig, or mouse).

[0341] In some embodiments, environmental applications may include the detection of contaminants in environmental samples. Environmental contaminants may be selected from, for example, lead, particulate matter, microplastics, and hormones.

[0342] For example, the method can be used to monitor and quantify heavy metals in water samples.

[0343] In some embodiments, food safety applications may include the detection of pathogens in food samples. For example, the method may be used to rapidly and sensitively detect bacterial pathogens causing contaminants in pasteurized milk. [Examples]

[0344] 1. Detection Sensitivity The purpose of this study was to test the detection sensitivity.

[0345] For detection, a specific amount of magnetizable particles was added to the microfluidic system. The system configuration is summarized below. ● Magnetic field generator ○ Electromagnet above the microfluidic system ○ Permanent magnets below the microfluidic system ● Signal sensor ○Honeywell HMC2003 3-axis magnetic sensor ○ An analog-to-digital converter (ADC) connected to an oscilloscope that records data at 10,000 samples / second. ●Magnetizable particles ○Functionalized 30nm superparamagnetic beads - coated with streptavidin and bound to anti-human serum albumin binder via biotin. ●Target analytes ○ Human serum albumin ●Number of particles: ○Sample 1: (21.6℃): Control ~0 pg / mL particles ○Sample 2: 0.1 pg / mL particles ○Sample 3: 1 pg / mL particles ○Sample 4: 10 pg / mL particles ○Sample 5: 100 pg / mL particles ○Sample 6: 1,000 pg / mL particles ○Sample 7: 10,000 pg / mL particles ● Number of sample reading cycles ○5 cycles ● Electromagnet (EM) activation on / off time per cycle ○ 2 seconds EM-on ○ EM off for 5 seconds

[0346] After being introduced into the microfluidic system, the particles were able to reach a first equilibrium state (equilibrium state A) under the influence of a permanent magnetic field. Next, the electromagnet was activated for 2 seconds to allow the particles to reach a second equilibrium state (equilibrium state B). Then, the electromagnet was deactivated, allowing the particles to return to a third equilibrium state (equilibrium state C)—see Table 1. Magnetic field sensors measured the changes in the magnetic signal generated by the particles as they transitioned between different equilibrium states.

[0347] Table 1 shows the results of five sample reading cycles for seven samples.

[0348] Table 1 shows the magnetic field sensor output (voltage) for values ​​from 0 pg / ml to 10,000 pg / ml. [Table 1]

[0349] 2. Magnetic Equilibrium Detection (MED) The objective of this embodiment was to demonstrate the quantitative detection of biomarker analytes using the claimed methodology. The method used 30 nm superparamagnetic particles. In this embodiment, a binder-to-particle ratio of 0.75:1 was tested to determine whether such a ratio could affect the interaction between particles in the absence of the analyte. [Table 2]

[0350] The R² value for the results in Table 2 is 0.95.

[0351] Due to a sample handling error, the analyte sample with a concentration of 1,000 pg / ml was excluded.

[0352] 2.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles ○Nanocs MP25-AV-0.5 (30nm) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ● Magnetic sensor ○Honeywell HMC2003 magnetometer ● Amplifier ○Honeywell HMC2003 built-in amplifier ●Data acquisition ○Silent SDS1204X-E Oscilloscope ○ Sampling rate of 10,000 samples per second ○Total execution time on the device: approximately 35 seconds ● Magnet ○ Upper magnet - 0.2mm coil gauge copper coil electromagnet. Connects to a 3.23V DC power supply. ○ 5 cycles of upper magnet operation (each cycle consists of a 2-second magnet on time followed by a 5-second magnet off time) ●Device setup ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - Upper magnet □Intermediate component - sample □Lower component - Sensor ○All components were aligned vertically, passing through the center of each component. ● For each biomarker analyte concentration tested ○ 1 μL of magnetizable particles - Nanocs superparamagnetic beads (2 mg / mL) ○ 0.75 ng anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○ Human albumin recombinant protein at different concentrations, generated by serial dilution (from the DY1455 ELISA kit). ○ All components mixed and sensed in a test volume of 10 μL

[0353] 2.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0354] In this way, the sensor output corresponding to the magnet on phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best fit line, R 2 The value was derived.

[0355] 3. Quantitative detection of biomarker analytes The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes. In this example, 30 nm superparamagnetic particles were used. [Table 3]

[0356] The results in Table 3 are from R 2 The value is 0.94.

[0357] 3.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles ○Nanocs MP25-AV-0.5 (30nm) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ● Magnetic sensor ○Honeywell HMC2003 magnetometer ● Amplifier ○Honeywell HMC2003 built-in amplifier ●Data acquisition ○Silent SDS1204X-E Oscilloscope ○ Sampling rate of 10,000 samples per second ○Total execution time on the device: approximately 35 seconds ● Magnet ○ Upper magnet - 0.2mm coil gauge copper coil electromagnet. Connects to a 3.33V DC power supply. ○Lower magnet - 25mm diameter DC cylindrical electromagnet. Disconnect from power supply. ○ 5 cycles of upper magnet operation (each cycle consists of a 2-second magnet on time followed by a 5-second magnet off time) ○The lower magnet did not activate, or did not receive power. ●Device setup ○Place the sample between the sensor and the magnet as follows: □ Upper component - Upper magnet □Intermediate component - sample □Intermediate component - Sensor (placed below the sample) □Lower component - Lower magnet ●All components were aligned vertically, passing through the center of each component. ● For each biomarker analyte concentration tested ○ 1 μL of magnetizable particles - Nanocs superparamagnetic beads (2 mg / mL) ○ 1 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○ Human albumin recombinant protein at different concentrations, generated by serial dilution (from the DY1455 ELISA kit). ○ All components mixed and sensed in a test volume of 10 μL

[0358] 3.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0359] In this way, the sensor output corresponding to the magnet on-phase was averaged for each cycle, then averaged over all 5 cycles, fitted to the best-fit line, and the R2 value was derived.

[0360] The objective of this experiment is to demonstrate quantitative detection using different biomarker analytes with the MED detection method and 30 nm superparamagnetic particles. [Table 4]

[0361] The results in Table 4 are from R 2 The value is 0.94.

[0362] 3.3 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles ○Nanocs MP25-AV-0.5 (30nm) streptavidin-coated superparamagnetic particles ○Functionalization of the biotinylation "detection" antibody in the DY2586 ELISA kit (anti-feline TNF-α). ● Magnetic sensor ○Honeywell HMC2003 magnetometer ● Amplifier ○Honeywell HMC2003 built-in amplifier ●Data acquisition ○Silent SDS1204X-E Oscilloscope ○ Sampling rate of 10,000 samples per second ○Total execution time on the device: approximately 35 seconds ● Magnet ○ Upper magnet - 0.2mm coil gauge copper coil electromagnet. Connects to a 0.5V DC power supply. ○Lower magnet - 25mm diameter DC cylindrical electromagnet. Disconnect from power supply. ○ 5 cycles of upper magnet operation (each cycle consists of a 2-second magnet on time followed by a 5-second magnet off time) ○The lower magnet did not activate, or did not receive power. ●Device setup ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - Upper magnet □Intermediate component - sample □Intermediate component - Sensor (placed below the sample) □Lower component - Magnet □All components were aligned vertically, passing through the center of each component. ● For each biomarker analyte concentration tested ○ 1 μL of magnetizable particles - Nanocs superparamagnetic beads (2 mg / mL) ○1 ng of anti-TNF-α antibody - DY2586 ELISA kit for biotinylation detection. ○Various concentrations of feline TNF-α recombinant protein produced by serial dilution (from the DY2584 ELISA kit). ○ All components mixed and sensed in a test volume of 10 μL

[0363] 3.4 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0364] In this way, the sensor output corresponding to the magnet on phase is averaged for each cycle, then averaged over all 5 cycles, and fitted to the best fit line, R 2 The value was derived.

[0365] 4. Experiment 1 The objective of this experiment is to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30 nm superparamagnetic particles with an even lower binder-to-bead ratio (0.5:1). [Table 5]

[0366] The results in Table 2 are from R 2 The value is 0.91.

[0367] 4.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles ○Nanocs MP25-AV-0.5 (30nm) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ● Magnetic sensor ○Honeywell HMC2003 magnetometer ● Amplifier ○Honeywell HMC2003 built-in amplifier ●Data acquisition ○Silent SDS1204X-E Oscilloscope ○ Sampling rate of 10,000 samples per second ○Total execution time on the device: approximately 35 seconds ● Magnet ○ Upper magnet - 0.2mm coil gauge copper coil electromagnet. Connects to a 3.23V DC power supply. ○ 5 cycles of upper magnet operation (each cycle consists of a 2-second magnet on time followed by a 5-second magnet off time) ●Device setup ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - Upper magnet □Intermediate component - sample □Lower component - Sensor □All components were aligned vertically, passing through the center of each component. ● For each biomarker analyte concentration tested ○ 1 μL of magnetizable particles - Nanocs superparamagnetic beads (2 mg / mL) ○ 0.5 ng anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○ Human albumin recombinant protein at different concentrations, generated by serial dilution (from the DY1455 ELISA kit). ○ All components mixed and sensed in a test volume of 10 μL

[0368] 4.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0369] In this way, the sensor output corresponding to the magnet on phase is averaged for each cycle, then averaged over all 5 cycles, and fitted to the best fit line, R 2 The value was derived.

[0370] 5. Experiment 2 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 6]

[0371] R of the results in Table 6 2 The value is 0.99.

[0372] 5.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○ Upper magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 0.63 V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of upper magnet operation (each cycle consists of a 2-second magnet on time followed by a 5-second magnet off time) ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - Upper magnet □Intermediate component - sample □Lower component - Sensor ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (2x dilution from 100 pg / ml to 3.125 pg / ml). ○All components (0.5 μg of beads per sample) mixed and sensed in a 5 microliter test volume.

[0373] 5.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0374] The sensor output corresponding to the magnet on-phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best-fit line, R 2 The value was derived.

[0375] 6. Experiment 3 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 7]

[0376] R of the results in Table 7 2 The value was 0.98.

[0377] 6.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○ Upper magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 0.63 V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of operation for the upper magnet (each cycle consists of a 2-second magnet-on time followed by a 5-second magnet-off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - Upper magnet □Intermediate component - sample □Lower component - Sensor ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (4-fold dilution from 100 pg / ml to 0.098 pg / ml). All components (0.5 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0378] 6.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0379] The sensor output corresponding to the magnet on-phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best-fit line, R 2The value was derived.

[0380] 7. Experiment 4 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 8]

[0381] R of the results in Table 8 2 The value was 0.99.

[0382] 7.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○ Upper magnet - Rectangular copper coil electromagnet with a coil gauge of -0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Both magnets are connected in a Helmholtz configuration to a 0.63V DC power supply with programmable execution via the RIGOL DP832. ○ 5 cycles of operation for the upper magnet (each cycle consists of a 2-second magnet-on time followed by a 5-second magnet-off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - Upper magnet □Intermediate component - sample □ Subsequent components - sensors □Lower component - Lower magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution from 10,000 pg / ml to 0.1 pg / ml). ○All components (0.5 μg of beads per sample) mixed and sensed in a 5 microliter test volume.

[0383] 7.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0384] The sensor output corresponding to the magnet on-phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best-fit line, R 2 The value was derived.

[0385] 8. Experiment 5 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 9]

[0386] R of the results in Table 9 2 The value was 0.91.

[0387] 8.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 0.63 V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of operation for the upper magnet (each cycle consists of a 2-second magnet-on time followed by a 5-second magnet-off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Lower magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution from 10,000 pg / ml to 0.1 pg / ml). ○All components (0.5 μg of beads per sample) mixed and sensed in a 5 microliter test volume.

[0388] 8.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0389] The sensor output corresponding to the magnet on-phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best-fit line, R 2 The value was derived.

[0390] 9. Experiment 6 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using an MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 10]

[0391] R of the results in Table 10 2 The value was 0.90.

[0392] 9.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 0.63 V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of upper magnet operation (each cycle consists of a 2-second magnet on time followed by a 5-second magnet off time) ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Lower magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution from 10,000 pg / ml to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0393] 9.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0394] Therefore, the sensor output corresponding to the magnet on phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best fit line, R 2 The value was derived.

[0395] 10. Experiment 7 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 11]

[0396] R of the results in Table 11 2 The value was 0.96.

[0397] 10.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 0.9V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of operation for the upper magnet (each cycle consists of a 2-second magnet-on time followed by a 5-second magnet-off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Lower magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution from 10,000 pg / ml to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0398] 10.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0399] Therefore, the sensor output corresponding to the magnet on phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best fit line, R 2 The value was derived.

[0400] 11. Experiment 8 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 12]

[0401] R of the results in Table 12 2 The value was 1.00.

[0402] 11.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 0.9V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of operation for the upper magnet (each cycle consists of a 2-second magnet-on time followed by a 5-second magnet-off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Lower magnet □All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution from 10,000 pg / ml to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0403] 11.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0404] Therefore, the sensor output corresponding to the magnet on phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best fit line, R 2 The value was derived.

[0405] 12. Experiment 9 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 13]

[0406] R of the results in Table 13 2 The value is 0.98.

[0407] 12.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 0.6V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of operation for the upper magnet (each cycle consists of a 2-second magnet-on time followed by a 5-second magnet-off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Lower magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution from 10,000 pg / ml to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0408] 12.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0409] Therefore, the sensor output corresponding to the magnet on phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best fit line, R 2 The value was derived.

[0410] 13. Experiment 10 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 14]

[0411] R of the results in Table 14 2 The value was 0.99.

[0412] 13.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 0.5V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of operation for the upper magnet (each cycle consists of a 2-second magnet-on time followed by a 5-second magnet-off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Lower magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution from 10,000 pg / ml to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0413] 13.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0414] Therefore, the sensor output corresponding to the magnet on phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best fit line, R 2 The value was derived.

[0415] 14. Experiment 11 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 15]

[0416] R of the results in Table 15 2 The value was 0.96.

[0417] 14.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 0.5V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of operation for the upper magnet (each cycle consists of a 3-second magnet on time followed by a 5-second magnet off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Lower magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (2x dilution from 10,000 pg / ml to 312.5 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0418] 14.2 Data Processing During the 3-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of powering on or off the magnet were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0419] Therefore, the sensor output corresponding to the magnet on phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best fit line, R 2 The value was derived.

[0420] 15. Experiment 12 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using an MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 16]

[0421] R of the results in Table 16 2 The value was 0.99.

[0422] 15.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 0.5V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of upper magnet operation (each cycle consists of a 3-second magnet on time followed by a 5-second magnet off time) ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Lower magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (2x dilution from 10,000 pg / ml to 312.5 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0423] 15.2 Data Processing During the 3-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of powering on or off the magnet were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0424] Therefore, the sensor output corresponding to the magnet on phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best fit line, R 2 The value was derived.

[0425] 16. Experiment 13 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 17]

[0426] R of the results in Table 17 2 The value was 0.91.

[0427] 16.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: Rectangular copper coil electromagnet with lower magnet - 0.2 mm coil gauge. Rectangular copper coil electromagnet with lower magnet - 0.2 mm coil gauge (dimensions 36 x 33.5 mm, thickness 5.3 mm). Connects to a 0.3V DC power supply for programmable operation by RIGOL DP832. ○ 5 cycles of upper magnet operation (each cycle consists of a 3-second magnet on time followed by a 5-second magnet off time) ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Lower magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (2x dilution from 10,000 pg / ml to 312.5 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0428] 16.2 Data Processing During the 3-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of powering on or off the magnet were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0429] Therefore, the sensor output corresponding to the magnet on phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best fit line, R 2 The value was derived.

[0430] 17. Experiment 14 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 18]

[0431] R of the results in Table 18 2 The value was 0.96.

[0432] 17.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.2 mm (dimensions 36 x 33.5 mm, thickness 5.3 mm). Connects to a 0.3V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of upper magnet operation (each cycle consists of a 3-second magnet on time followed by a 5-second magnet off time) ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Lower magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution from 10,000 pg / ml to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0433] 17.2 Data Processing During the 3-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of powering on or off the magnet were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0434] Therefore, the sensor output corresponding to the magnet on phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best fit line, R 2 The value was derived.

[0435] 18. Experiment 15 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 19]

[0436] R of the results in Table 19 2 The value is 0.92.

[0437] 18.1 Description of the experiment The experimental design parameters are set as follows: ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 0.5V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of upper magnet operation (each cycle consists of a 3-second magnet on time followed by a 5-second magnet off time) ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Lower magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution from 10,000 pg / ml to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0438] 18.2 Data Processing During the 3-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of powering on or off the magnet were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0439] Therefore, the sensor output corresponding to the magnet on phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best fit line, R 2 The value was derived.

[0440] 19. Experiment 16 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 50-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 20]

[0441] R of the results in Table 20 2 The value was 1.00.

[0442] In this embodiment and subsequent embodiments, the harmonics correspond to the operating cycles of the magnet. For example, the fifth and first harmonics correspond to the fifth and first magnet operating cycles, as may be described in the following experimental description. In this experiment, the fifth harmonic is divided by the first harmonic.

[0443] 19.1 Description of the experiment The experimental design parameters are set as follows: ●Magnetizable particles: ○SuperMag streptavidin beads, 50nm (Product ID: SV0050) ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.2 mm (dimensions 36 x 33.5 mm, thickness 5.3 mm). Connects to a DC power supply with programmable operation via RIGOL DP832. ○ 5 cycles of lower magnet operation (each cycle consists of a 1-second magnet-on time where the step voltage fluctuates up and down every 1 second by 0.2V). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech SuperMag streptavidin beads ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution from 10,000 pg / ml to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0444] 19.2 Data Processing The sensor output, including the magnet's on / off phase which is linked to the magnet's power on / off, was considered as part of the entire dataset. Next, the data was processed through an automated FFT (Fast Fourier Transform) tool, and each processed output was manually checked.

[0445] Therefore, the Fast Fourier Transform was used to process the sensor output corresponding to the magnet on and off phase cycles. Fast Fourier Transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, to reflect the correlation between concentration and harmonics, and the correlation between magnitude and ratio, these magnitudes and ratios were applied to obtain the correlation coefficient (R) across the indicated concentrations. 2 The value is determined quantitatively.

[0446] 20. Experiment 17 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 50-nanometer superparamagnetic particles. The binder-to-particle ratio (0.75:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 21]

[0447] R of the results in Table 20 2 The value was 0.99.

[0448] 20.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SuperMag streptavidin beads, 50nm (Product ID: SV0050) ○Functionalization of the DY2586 ELISA kit with a biotinylation "detection" antibody (anti-feline TNF-α). ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.2 mm (dimensions 36 x 33.5 mm, thickness 5.3 mm). Connects to a DC power supply with programmable operation via RIGOL DP832. ○ 5 cycles of lower magnet operation (each cycle consists of a 1-second magnet-on time where the step voltage fluctuates up and down every 1 second by 0.2V). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech SuperMag streptavidin beads (1 mg / ml) ○ 0.75 nanogram anti-TNFα antibody - Biotinylated "detection" antibody in the DY2586 ELISA kit ○ Various concentrations of feline TNF-α recombinant protein (from the DY2586 ELISA kit) were generated by serial dilution (10-fold dilution from 10,000 pg / ml to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0449] 20.2 Data Processing The sensor output, including the magnet's on / off phase which is linked to the magnet's power on / off, was considered as part of the entire dataset. Next, the data was processed through an automated FFT (Fast Fourier Transform) tool, and each processed output was manually checked.

[0450] Therefore, the Fast Fourier Transform was used to process the sensor output corresponding to the magnet on and off phase cycles. Fast Fourier Transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, to reflect the correlation between concentration and harmonics, and the correlation between magnitude and ratio, these magnitudes and ratios were applied to obtain the correlation coefficient (R) across the indicated concentrations. 2 The value is determined quantitatively.

[0451] 21. Experiment 18 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 50-nanometer superparamagnetic particles. The binder-to-particle ratio (1.5:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 22]

[0452] R of the results in Table 21 2 The value was 0.94.

[0453] 21.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SuperMag streptavidin beads, 50nm (Product ID: SV0050) ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.2 mm (dimensions 36 x 33.5 mm, thickness 5.3 mm). Connects to a 0.4V DC power supply and is programmable by a RIGOL DP832. ○ 30 cycles of operation of the lower magnet (each cycle consists of a 1-second magnet on time and a 1-second magnet off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech SuperMag streptavidin beads (1 mg / ml) ○ 1.5 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○ Human serum albumin recombinant protein at various concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution starting from 10,000 pg / ml down to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0454] 21.2 Data Processing The sensor output, including the magnet's on / off phase which is linked to the magnet's power on / off, was considered as part of the entire dataset. Next, the data was processed through an automated FFT (Fast Fourier Transform) tool, and each processed output was manually checked.

[0455] Therefore, the Fast Fourier Transform was used to process the sensor output corresponding to the magnet on and off phase cycles. Fast Fourier Transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, to reflect the correlation between concentration and harmonics, and the correlation between magnitude and ratio, these magnitudes and ratios were applied to obtain the correlation coefficient (R) across the indicated concentrations. 2 The value is determined quantitatively.

[0456] 22. Experiment 19 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 50-nanometer superparamagnetic particles. The binder-to-particle ratio (1.5:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 23]

[0457] R of the results in Table 22 2 The value was 0.99.

[0458] 22.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SuperMag streptavidin beads, 50nm (Product ID: SV0050) ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○ST sensor (LIS2MDL) ● Amplifier: ○ST sensor built-in amplifier ●Magnets: ○Lower magnet - Elliptical copper coil electromagnet with a coil gauge of 0.2 mm (dimensions 43.8 x 33.5 mm, thickness 5.3 mm). Connects to a 0.4V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of operation for the lower magnet (each cycle consists of 2 seconds of magnet on and 1 second of magnet off) ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech SuperMag streptavidin beads (1 mg / ml) ○ 1.5 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○ Human serum albumin recombinant protein at various concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution starting from 100,000 pg / ml down to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0459] 22.2 Data Processing The sensor output, including the magnet's on / off phase which is linked to the magnet's power on / off, was considered as part of the entire dataset. Next, the data was processed through an automated FFT (Fast Fourier Transform) tool, and each processed output was manually checked.

[0460] Therefore, the Fast Fourier Transform was used to process the sensor output corresponding to the magnet on and off phase cycles. Fast Fourier Transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, to reflect the correlation between concentration and harmonics, and the correlation between magnitude and ratio, these magnitudes and ratios were applied to obtain the correlation coefficient (R) across the indicated concentrations. 2 The value is determined quantitatively.

[0461] 23. Experiment 20 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 50-nanometer superparamagnetic particles. The binder-to-particle ratio (1.5:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 24]

[0462] R of the results in Table 23 2 The value was 0.91.

[0463] 23.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SuperMag streptavidin beads, 50nm (Product ID: SV0050) ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○ST sensor (LIS2MDL) ● Amplifier: ○ST sensor built-in amplifier ●Magnets: ○Lower magnet - Elliptical copper coil electromagnet with a coil gauge of 0.2 mm (dimensions 43.8 x 33.5 mm, thickness 5.3 mm). Connects to a 1V DC power supply that runs programmably by RIGOL DP832. ○ 25 cycles of operation of the lower magnet (each cycle consists of a 1-second magnet on time and a 1-second magnet off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech SuperMag streptavidin beads (1 mg / ml) ○ 1.5 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○ Human serum albumin recombinant protein at various concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution starting from 100,000 pg / ml down to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0464] 23.2 Data Processing The sensor output, including the magnet's on / off phase which is linked to the magnet's power on / off, was considered as part of the entire dataset. Next, the data was processed through an automated FFT (Fast Fourier Transform) tool, and each processed output was manually checked.

[0465] Therefore, the Fast Fourier Transform was used to process the sensor output corresponding to the magnet on and off phase cycles. Fast Fourier Transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, to reflect the correlation between concentration and harmonics, and the correlation between magnitude and ratio, these magnitudes and ratios were applied to obtain the correlation coefficient (R) across the indicated concentrations. 2 The value is determined quantitatively.

[0466] 24. Experiment 21 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 50-nanometer superparamagnetic particles. The binder-to-particle ratio (1.5:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 25]

[0467] R of the results in Table 24 2 The value was 0.92.

[0468] 24.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SuperMag streptavidin beads, 50nm (Product ID: SV0050) ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○ST sensor (LIS2MDL) ● Amplifier: ○ST sensor built-in amplifier ●Magnets: ○ Upper magnet - Circular planar base EM coil (pancake coil) design including a 0.9mm coil gauge (dimensions: radius 20.6mm, thickness 1.8mm). Connects to a 0.3V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of operation for the lower magnet (each cycle consists of 2 seconds of magnet on and 1 second of magnet off) ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - Magnet □Intermediate component - sample □Lower component - Sensor ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech SuperMag streptavidin beads (1 mg / ml) ○ 1.5 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○ Human serum albumin recombinant protein at various concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution starting from 100,000 pg / ml down to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0469] 24.2 Data Processing The sensor output, including the magnet's on / off phase which is linked to the magnet's power on / off, was considered as part of the entire dataset. Next, the data was processed through an automated FFT (Fast Fourier Transform) tool, and each processed output was manually checked.

[0470] Therefore, the Fast Fourier Transform was used to process the sensor output corresponding to the magnet on and off phase cycles. Fast Fourier Transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, to reflect the correlation between concentration and harmonics, and the correlation between magnitude and ratio, these magnitudes and ratios were applied to obtain the correlation coefficient (R) across the indicated concentrations. 2 The value is determined quantitatively.

[0471] 25. Experiment 22 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 50-nanometer superparamagnetic particles. The binder-to-particle ratio (1.5:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 26]

[0472] R of the results in Table 25 2 The value was 0.95.

[0473] 25.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SuperMag streptavidin beads, 50nm (Product ID: SV0050) ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○ST sensor (LIS2MDL) ● Amplifier: ○ST sensor built-in amplifier ●Magnets: ○Lower magnet - Elliptical copper coil electromagnet with a coil gauge of 0.2 mm (dimensions 43.8 x 33.5 mm, thickness 5.3 mm). Programmable by RIGOL DP832, time-controlled execution via an 80-duty cycle SSR switch connected to a 1V DC power supply. ○ The lower magnet operates for 10 cycles (each cycle consists of a 1-second magnet on time and a 1-second magnet off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech SuperMag streptavidin beads (1 mg / ml) ○ 1.5 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○ Human serum albumin recombinant protein at various concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution starting from 100,000 pg / ml down to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0474] 25.2 Data Processing The sensor output, including the magnet's on / off phase which is linked to the magnet's power on / off, was considered as part of the entire dataset. Next, the data was processed through an automated FFT (Fast Fourier Transform) tool, and each processed output was manually checked.

[0475] Therefore, the Fast Fourier Transform was used to process the sensor output corresponding to the magnet on and off phase cycles. Fast Fourier Transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, to reflect the correlation between concentration and harmonics, and the correlation between magnitude and ratio, these magnitudes and ratios were applied to obtain the correlation coefficient (R) across the indicated concentrations. 2 The value is determined quantitatively.

[0476] 26. Experiment 23 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using an MED detection method and 50-nanometer superparamagnetic particles. The binder-to-particle ratio (1.5:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 27]

[0477] R of the results in Table 26 2 The value was 0.93.

[0478] 26.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SuperMag streptavidin beads, 50nm (Product ID: SV0050) ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○ST sensor (LIS2MDL) ● Amplifier: ○ST sensor built-in amplifier ●Magnets: ○Lower magnet - Elliptical copper coil electromagnet with a coil gauge of 0.2 mm (dimensions 43.8 x 33.5 mm, thickness 5.3 mm). Programmable by RIGOL DP832, time-controlled execution via an 80-duty cycle SSR switch connected to a 1V DC power supply. ○ 5 cycles of operation of the lower magnet (each cycle consists of a 1-second magnet on time and a 1-second magnet off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech SuperMag streptavidin beads (1 mg / ml) ○ 1.5 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○ Human serum albumin recombinant protein at various concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution starting from 100,000 pg / ml down to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0479] 26.2 Data Processing The sensor output, including the magnet's on / off phase which is linked to the magnet's power on / off, was considered as part of the entire dataset. Next, the data was processed through an automated FFT (Fast Fourier Transform) tool, and each processed output was manually checked.

[0480] Therefore, the Fast Fourier Transform was used to process the sensor output corresponding to the magnet on and off phase cycles. Fast Fourier Transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, to reflect the correlation between concentration and harmonics, and the correlation between magnitude and ratio, these magnitudes and ratios were applied to obtain the correlation coefficient (R) across the indicated concentrations. 2 The value is determined quantitatively.

[0481] 27. Experiment 24 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 2.1 μm ferromagnetic particles. The binder-to-particle ratio (10:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 28]

[0482] R of the results in Table 27 2 The value was 0.95.

[0483] 27.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○ SpheroTech 2.1um ferromagnetic beads coated with streptavidin (SVFM20-5). ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○ST sensor (LIS2MDL) ● Amplifier: ○ST sensor built-in amplifier ●Magnets: ○Lower magnet - Elliptical copper coil electromagnet with a coil gauge of 0.2 mm (dimensions 43.8 x 33.5 mm, thickness 5.3 mm). Programmable by RIGOL DP832, time-controlled execution via an 80-duty cycle SSR switch connected to a 1V DC power supply. ○ 5 cycles of operation of the lower magnet (each cycle consists of a 1-second magnet on time and a 1-second magnet off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - SpheroTech 2.1 μm ferromagnetic beads (1% w / v) ○ 10 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○ Human serum albumin recombinant protein at various concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution starting from 100,000 pg / ml down to 0.1 pg / ml). ○All components (0.5 μg of beads per sample) mixed and sensed in a 5 microliter test volume.

[0484] 27.2 Data Processing Sensor data related to the period from the very beginning of EM coil saturation (evidence from the increase in the sensed magnetic field) to maximum coil saturation (for a given / set power level) were selected so that the total measurement period for Em-on reaching equilibrium was 0.05 seconds. Although the total period of EM-on equilibrium per cycle was approximately 1.0 second, the next focus was a mirror image of the time window and data position described above. That is, here, we collected the aggregated data (a concatenated dataset of these two data windows) (as described above) by capturing the 0.05 seconds from the beginning before the start of EM coil desaturation until the EM coil returns to the desaturation level. These focus on a total time of approximately 0.10 seconds per EM coil power modulation cycle.

[0485] The concatenated data was processed using an automated calculation tool for FFT (Fast Fourier Transform), and the output of each data processing was manually checked.

[0486] Therefore, the sensor output corresponding to the magnet-on period (the period from the start of EM coil saturation to equilibrium, and the connected period from the last moment of the coil's equilibrium state through the start of EM coil desaturation to the complete desaturation of the EM coil) represents the entire dataset in this data processing design. Fast Fourier transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, to reflect the correlation between concentration and harmonics, and the correlation between magnitude and ratio, these magnitudes and ratios were applied to obtain a correlation coefficient (R) over the indicated concentration. 2 The value is determined quantitatively.

[0487] 28. Experiment 25 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 2.1 μm ferromagnetic particles. The binder-to-particle ratio (10:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 29]

[0488] R of the results in Table 28 2 The value was 0.97.

[0489] 28.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○ SpheroTech 2.1um ferromagnetic beads coated with streptavidin (SVFM20-5). ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○ST sensor (LIS2MDL) ● Amplifier: ○ST sensor built-in amplifier ●Magnets: ○Lower magnet - Elliptical copper coil electromagnet with a coil gauge of 0.2 mm (dimensions 43.8 x 33.5 mm, thickness 5.3 mm). Programmable by RIGOL DP832, time-controlled execution via an 80-duty cycle SSR switch connected to a 1V DC power supply. ○ 5 cycles of operation of the lower magnet (each cycle consists of a 1-second magnet on time and a 1-second magnet off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - SpheroTech 2.1 μm ferromagnetic beads (1% w / v) ○ 10 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○ Human serum albumin recombinant protein at various concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution starting from 100,000 pg / ml down to 0.1 pg / ml). ○All components (0.5 μg of beads per sample) mixed and sensed in a 5 microliter test volume.

[0490] 28.2 Data Processing Sensor data related to the period from the very beginning of EM coil saturation (evidence from the increase in the sensed magnetic field) to maximum coil saturation (for a given / set power level) were selected so that the total measurement period for Em-on reaching equilibrium was 0.05 seconds. The total duration of EM-on equilibrium per cycle was approximately 1.0 seconds, while the next focus was on the mirror image of the time windows and data positions described above. That is, here, a concatenated dataset of these two data windows (as described above) was used to capture the 0.05 seconds from before the start of EM coil desaturation until the EM coil returned to its desaturation level, and the focus was on a total period of approximately 0.10 seconds per EM coil power modulation, only for the intermediate third cycle.

[0491] The concatenated data was processed using an automated calculation tool for FFT (Fast Fourier Transform), and the output of each data processing was manually checked.

[0492] Therefore, the sensor output corresponding to the magnet-on period of the third cycle (the continuous period from the start of EM coil saturation to equilibrium, and from the last moment the coil is in equilibrium, through the start of EM coil desaturation, until the EM coil is completely desaturated) represents the entire dataset in this data processing design. Fast Fourier transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, to reflect the correlation between concentration and harmonics, and the correlation between magnitude and ratio, these magnitudes and ratios were applied to obtain a correlation coefficient (R) over the indicated concentration. 2 The value is determined quantitatively.

[0493] 29. Experiment 26 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 2.1 μm ferromagnetic particles. The binder-to-particle ratio (10:1) was tested to determine whether such a ratio affected particle-to-particle interactions in the absence of the analyte. [Table 30]

[0494] R of the results in Table 29 2 The value was 0.97.

[0495] 29.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○ SpheroTech 2.1um ferromagnetic beads coated with streptavidin (SVFM20-5). ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○ST sensor (LIS2MDL) ● Amplifier: ○ST sensor built-in amplifier ●Magnets: ○Lower magnet - Elliptical copper coil electromagnet with a coil gauge of 0.2 mm (dimensions 43.8 x 33.5 mm, thickness 5.3 mm). Programmable by RIGOL DP832, time-controlled execution via an 80-duty cycle SSR switch connected to a 1V DC power supply. ○ 5 cycles of operation of the lower magnet (each cycle consists of a 1-second magnet on time and a 1-second magnet off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - SpheroTech 2.1 μm ferromagnetic beads (1% w / v) ○ 10 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○ Human serum albumin recombinant protein at various concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution starting from 100,000 pg / ml down to 0.1 pg / ml). ○All components (0.5 μg of beads per sample) mixed and sensed in a 5 microliter test volume.

[0496] 29.2 Data Processing Sensor data related to the period from the very beginning of EM coil saturation (evidence from the increase in the sensed magnetic field) to maximum coil saturation (for a given / set power level) were selected so that the total measurement period for Em-on reaching equilibrium was 0.05 seconds. The total duration of EM-on equilibrium per cycle was approximately 1.0 seconds, while the next focus was on the mirror image of the time windows and data positions described above. That is, here, a concatenated dataset of these two data windows (as described above) was used to capture the 0.05 seconds from before the start of EM coil desaturation until the EM coil returned to its desaturation level, and the focus was on a total period of approximately 0.10 seconds per EM coil power modulation, only for the intermediate third cycle.

[0497] The concatenated data was processed using an automated calculation tool for FFT (Fast Fourier Transform), and the output of each data processing was manually checked.

[0498] Therefore, the sensor output corresponding to the magnet-on period of the third cycle (the continuous period from the start of EM coil saturation to equilibrium, and from the last moment the coil is in equilibrium, through the start of EM coil desaturation, until the EM coil is completely desaturated) represents the entire dataset in this data processing design. Fast Fourier transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, to reflect the correlation between concentration and harmonics, and the correlation between magnitude and ratio, these magnitudes and ratios were applied to obtain a correlation coefficient (R) over the indicated concentration. 2 The value is determined quantitatively.

[0499] 30. Experiment 27 The objective of this experiment was to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. Different binder-to-particle ratios (0.75:1) were tested to determine whether such ratios affect particle-to-particle interactions in the absence of the analyte. [Table 31]

[0500] R of the results in Table 30 2 The value was 0.88.

[0501] 30.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○ Upper magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 0.63 V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of upper magnet operation (each cycle consists of a 2-second magnet on time followed by a 5-second magnet off time) ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - Upper magnet □Intermediate component - sample □Lower component - Sensor ●All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (4-fold dilution from 100 pg / ml to 0.098 pg / ml). ○All components (0.5 μg of beads per sample) mixed and sensed in a 5 microliter test volume.

[0502] 30.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0503] The sensor output corresponding to the magnet on-phase was averaged for each cycle, and then averaged over all 5 cycles. This was then fitted to the best-fit line, R 2 The value was derived.

[0504] 31. Experiment 27a The purpose of this experiment is to determine when FFT is used to process the sensor value output obtained in Experiment 27, R 2 The key is to observe the differences in values. [Table 32]

[0505] R of the results in Table 31 2 The value was 0.97.

[0506] When FFT is used to process the sensor value output obtained in Experiment 27, R 2 An increase in the value is observed.

[0507] 31.1 Data Processing The sensor output, including the magnet's on / off phase which is linked to the magnet's power on / off, was considered as part of the entire dataset. Next, the data was processed through an automated FFT (Fast Fourier Transform) tool, and each processed output was manually checked.

[0508] Therefore, the Fast Fourier Transform was used to process the sensor output corresponding to the magnet on and off phase cycles. Fast Fourier Transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, these magnitudes and ratios were applied to quantitatively determine the correlation coefficient (R² value) across the indicated concentrations, reflecting the correlation between concentration and harmonics, and the correlation between magnitude and ratio.

[0509] 32. Experiment 28 The objective of this experiment is to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The inventors tested different binder-to-particle ratios (0.75:1) to determine whether such ratios could affect the interaction between particles in the absence of the analyte. [Table 33]

[0510] R of the results in Table 32 2 The value was 0.89.

[0511] 32.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 1V DC power supply that runs programmably by RIGOL DP832. ○ 5 cycles of operation for the upper magnet (each cycle consists of a 2-second magnet-on time followed by a 5-second magnet-off time). ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Lower magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (10-fold dilution from 10,000 pg / ml to 0.1 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0512] 32.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0513] The sensor output corresponding to the magnet's on-phase was averaged for each cycle, and then averaged over all five cycles. This was then fitted to the best-fit line to derive the R² value.

[0514] 33. Experiment 28a The purpose of this experiment is to determine when FFT is used to process the sensor value output obtained in Experiment 28, R 2 The key is to observe the differences in values. [Table 34]

[0515] R of the results in Table 33 2 The value was 0.95.

[0516] When FFT is used to process the sensor value output obtained in Experiment 28, R 2 An increase in the value is observed.

[0517] 33.1 Data Processing The sensor output, including the magnet's on / off phase which is linked to the magnet's power on / off, was considered as part of the entire dataset. Next, the data was processed through an automated FFT (Fast Fourier Transform) tool, and each processed output was manually checked.

[0518] Therefore, the Fast Fourier Transform was used to process the sensor output corresponding to the magnet on and off phase cycles. Fast Fourier Transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, these magnitudes and ratios were applied to quantitatively determine the correlation coefficient (R² value) across the indicated concentrations, reflecting the correlation between concentration and harmonics, and the correlation between magnitude and ratio.

[0519] 34. Experiment 29 The objective of this experiment is to demonstrate the quantitative detection of biomarker analytes using the MED detection method and 30-nanometer superparamagnetic particles. The inventors tested different binder-to-particle ratios (0.75:1) to determine whether such ratios could affect the interaction between particles in the absence of the analyte. [Table 35]

[0520] R of the results in Table 34 2 The value was 0.84.

[0521] 34.1 Description of the experiment The experimental design parameters are shown below. ●Magnetizable particles: ○Ocean NanoTech SHS30-01 (30 nanometer) streptavidin-coated superparamagnetic particles ○Functionalization using the biotinylation "detection" antibody (anti-human serum albumin) of the DY1455 ELISA kit. ●Magnetic sensor: ○Honeywell HMC1041z magnetometer ● Amplifier: ○Texas Instruments INA819 Amplifier ●Magnets: ○Lower magnet - Rectangular copper coil electromagnet with a coil gauge of 0.1 mm (dimensions 22 x 25 mm, thickness 3.5 mm). Connects to a 0.5V DC power supply and is programmable by a RIGOL DP832. ○ 5 cycles of upper magnet operation (each cycle consists of a 2-second magnet on time followed by a 5-second magnet off time) ●Setting up the equipment: ○The sample is positioned between the sensor and the magnet as follows: □ Upper component - sample □Intermediate component - Sensor □Lower component - Lower magnet ○All components were aligned vertically, passing through the center of each component. ●Regarding the concentrations of each biomarker analyte tested: ○ 1 microliter of magnetizable particles - Ocean NanoTech superparamagnetic beads (1 mg / mL) ○ 0.75 nanogram anti-albumin antibody - Biotinylated "detection" antibody in the DY1455 ELISA kit ○Human albumin recombinant protein at different concentrations (from the DY1455 ELISA kit) generated by serial dilution (2x dilution from 10,000 pg / ml to 312.5 pg / ml). ○All components (2 μg of beads per sample) were mixed and sensed in a 5 microliter test volume.

[0522] 34.2 Data Processing During the 2-second magnet-on phase of each cycle, the sensor output was processed to exclude data points corresponding to the magnet's operation (either on or off), and the effects of the magnet's power-on or power-off were not considered. For this data processing, an automated tool was created, and each processed output was manually checked.

[0523] Therefore, the sensor output corresponding to the magnet on-phase was averaged for each cycle, and then averaged over all five cycles. This was then fitted to the best-fit line to derive the R² value.

[0524] 35. Experiment 29 The purpose of this experiment is to determine when FFT is used to process the sensor value output obtained in Experiment 29, R 2 The key is to observe the differences in values. [Table 36]

[0525] R of the results in Table 35 2 The value was 0.94.

[0526] When FFT is used to process the sensor value output obtained in Experiment 29, R 2 An increase in the value is observed.

[0527] 35.1 Data Processing The sensor output, including the magnet's on / off phase which is linked to the magnet's power on / off, was considered as part of the entire dataset. Next, the data was processed through an automated FFT (Fast Fourier Transform) tool, and each processed output was manually checked.

[0528] Therefore, the Fast Fourier Transform was used to process the sensor output corresponding to the magnet on and off phase cycles. Fast Fourier Transform analysis was used to obtain the magnitude of the detected fundamental frequency and the magnitude of the associated harmonics for each concentration. Next, these magnitudes and ratios were applied to quantitatively determine the correlation coefficient (R² value) across the indicated concentrations, reflecting the correlation between concentration and harmonics, and the correlation between magnitude and ratio.

Claims

1. A method for detecting a target analyte in a sample, wherein the method is a) providing an amount of magnetizable particles having a reference magnetic signal known or measured before or after the addition of the sample, wherein the particles are coated with a binding molecule complementary to the target analyte, and further, the method b) Contacting the sample containing the target analyte with the magnetizable particles to generate bound and unbound binder composites, c) Applying a magnetic field to the sample for a certain period of time, d) obtaining a magnetic signal, wherein the magnetic signal is the magnetic signal of the bonded and unbonded binder composite in the presence of the magnetic field, and further, the method e) Removing the magnetic field for a certain period of time. f) The method comprising comparing the reference magnetic signal with the magnetic signal, wherein the difference between the reference magnetic signal and the magnetic signal correlates with the presence and / or amount of the target analyte in the sample.

2. The method according to claim 1, wherein the reference magnetic signal is determined by measuring the magnetic signal of the amount of magnetizable particles in the absence of the target analyte.

3. The method according to claim 2, wherein the reference magnetic signal is measured at any point between step b) and step e).

4. The method according to any one of claims 1 to 3, wherein the magnetic field is generated using an electromagnet.

5. The method according to any one of claims 1 to 4, wherein the magnetic signal is acquired after the electromagnetic coil of the electromagnet has reached saturation.

6. The method according to any one of claims 1 to 3, wherein the magnetic field is generated using a permanent magnet.

7. The method according to any one of claims 1 to 6, wherein the quantitative determination of the target analyte in the sample is determined by correlating the measured change in magnetic signal with the reference / predetermined magnetic signal.

8. moreover, To generate a baseline dataset based on known values ​​of the amount of analytes, The method according to any one of claims 1 to 7, comprising comparing a value obtained from the difference between the reference magnetic signal and the magnetic signal with the reference dataset to determine the amount of the analyte in the sample.

9. The method according to any one of claims 1 to 8, wherein the magnetic field is applied for a predetermined time.

10. The method according to claim 9, wherein the magnetic field is applied for approximately 0.1 to approximately 5 seconds.

11. The method according to any one of claims 1 to 10, wherein the magnetic field is removed for a predetermined time.

12. The method according to claim 11, wherein the magnetic field is removed for about 0.1 to about 5 seconds.

13. The method according to any one of claims 1 to 12, wherein the magnetic field is applied and removed for substantially equal periods of time.

14. The method according to claim 13, wherein the magnetic field is applied and removed for approximately 1 second.

15. The method according to any one of claims 1 to 14, wherein steps c) to e) are repeated two or more times.

16. The method according to any one of claims 1 to 15, wherein the magnetizable particles are superparamagnetic or ferromagnetic nanoparticles.

17. The method according to any one of claims 1 to 16, wherein the average particle size of the magnetizable particles is about 20 nm to about 60 nm.

18. The method according to any one of claims 1 to 17, wherein the average particle size of the magnetizable particles is about 30 nm.

19. The method according to any one of claims 1 to 18, further comprising magnetically shielding the sample from an ambient magnetic field.

20. The method according to any one of claims 1 to 19, further comprising measuring the ambient magnetic field and adjusting the reference magnetic signal and the magnetic signal based on the ambient magnetic field.

21. The method according to any one of claims 1 to 20, wherein the magnetic signal is measured at a sampling rate of at least about 10,000 samples / second.

22. The method according to any one of claims 1 to 21, wherein the sample is incubated at a temperature of approximately 20°C.

23. The method according to any one of claims 1 to 22, wherein the magnetic signal is the magnetic field strength.

24. ● Sample well or sample reservoir, ● A magnet placed at the top or bottom of the sample well or sample reservoir, and The method according to any one of claims 1 to 23, performed using a sample testing device that includes a magnetic field sensor for measuring the change over time of the magnetic signal in the sample well or sample reservoir.

25. The method according to any one of claims 1 to 24, wherein the magnetizable particles are functionalized with molecules that specifically bind to the target analyte.

26. The method according to any one of claims 1 to 25, wherein the sample and magnetizable particles are processed by a microfluidic device.

27. The method according to any one of claims 1 to 26, wherein the microfluidic device facilitates the coupling of the magnetizable particles and the analyte.

28. The method according to any one of claims 1 to 27, wherein one or more magnets generate a magnetic field that changes over time.

29. The method according to any one of claims 1 to 28, wherein one or more magnets can generate a continuity of size.

30. The method according to any one of claims 1 to 29, wherein one or more magnets can alternately switch the magnetic field on and off.

31. The method according to claim 24, wherein the magnetic field sensor measures over time the change in magnetic field strength generated by the magnetizable particles.

32. The method according to any one of claims 24 to 31, wherein the signal output from the magnetic field sensor is amplified by a signal amplifier.

33. The method according to any one of claims 24 to 32, wherein the signal output from the magnetic field sensor is a reading of a voltage proportional to the magnetic signal measured by the magnetic field sensor.

34. The method according to claim 32, wherein the amplified signal is converted from a voltage reading to a digital bitstream and recorded and / or analyzed by a computer.

35. The method according to claim 34, wherein the conversion is performed by an analog-to-digital converter.

36. The method described above is a) Generate a magnetic signal within 15 seconds sufficient to detect and / or quantify the target analyte in the sample, or b) The limit of detection (LOD) is at least about 0.05 pg / mL, or c) The limit of quantification (LOQ) is at least about 0.1 pg / mL, or d) The method according to any one of claims 1 to 35, wherein one or more of (a) to (c).

37. The method according to any one of claims 1 to 36, wherein the magnetic signal is processed using a fast Fourier transform (FFT).

38. The method according to claim 37, wherein the magnetic signal is preprocessed by truncating and / or concatenating the magnetic signal in one or more dimensions before processing it using FFT.

39. The method according to claim 37 or claim 38, wherein the magnetic signal is windowed before the FFT processing.

40. A device for detecting analytes in a sample, ● Sample wells that are separate from or integrated with microfluidic devices, ●Magnets for generating a magnetic field, The device includes a magnetic field sensor configured to measure the magnetic signal of magnetizable particles in the sample well in the presence of the magnetic field, wherein the magnetic signal is detected from an overall magnetic response proportional to the size of the aggregate.

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