Prostate cancer auxiliary diagnosis equipment based on microfluidic-calcium imaging technology

Abstract

The invention relates to prostate cancer auxiliary diagnosis equipment based on a microfluidic-calcium imaging technology, which comprises a calcium imaging detection module used for detecting neuron calcium signals, and a data processing and analyzing module used for processing and analyzing the calcium signals. And the data processing and analysis module comprises embedded computing equipment and analysis software, and is used for converting the acquired neuron calcium signals into a visual activity map, analyzing and comparing signal mode differences through an algorithm, and outputting a diagnosis result. The prostate cancer auxiliary diagnosis equipment is high in sensitivity, noninvasive and efficient, and the defects that traditional equipment is high in invasiveness and high in detection complexity are overcome.

Description

Technical Field

[0001] The present invention belongs to the technical fields of biomedical engineering and clinical diagnosis, and relates to a medical diagnostic device based on biological nerve signal detection. Specifically, it relates to a device for the auxiliary diagnosis of prostate cancer by utilizing the chemosensory nerve activity response of Caenorhabditis elegans, combining microfluidic technology and calcium imaging technology. More specifically, it relates to an auxiliary diagnostic device for prostate cancer based on microfluidic-calcium imaging technology. Background Art

[0002] Existing methods for diagnosing prostate cancer mainly rely on traditional means such as imaging examinations, blood tests, and digital rectal examinations. However, these methods often have certain limitations, especially in terms of early diagnosis, accuracy, patient acceptance, and cost, presenting technical bottlenecks.

[0003] A. Imaging Examinations (such as ultrasound, CT, etc.)

[0004] Existing imaging examinations mainly rely on ultrasound or computed tomography (CT) to image the prostate, and diagnose by observing the morphological changes of tumors. Although these methods can provide structural information of the prostate tissue, their sensitivity in the detection of early prostate cancer is relatively low, especially in the identification of small tumors or cancerous regions. Therefore, imaging examinations often cannot effectively conduct early diagnosis or precise positioning, and have a relatively high false negative rate.

[0005] Defect: The imaging examination technology is not sensitive enough for the early diagnosis of prostate cancer, and the detection of small changes in tumors is insufficient, posing a risk of misdiagnosis.

[0006] B. Blood Tests (such as prostate-specific antigen, PSA test)

[0007] PSA (prostate-specific antigen) test is one of the most commonly used means for prostate cancer screening. By detecting the PSA concentration in the blood to determine whether there is prostate cancer. However, the PSA test has problems of false positives and false negatives. Especially, some patients with benign prostatic hyperplasia (BPH) may also have an elevated PSA, leading to unnecessary further examinations. For the diagnosis of early prostate cancer, the sensitivity and specificity of PSA are poor, which may result in overdiagnosis and overtreatment.

[0008] Defect: The PSA test has relatively high false positive and false negative rates, affecting the accuracy, and cannot be used as the sole diagnostic tool for prostate cancer.

[0009] C. Digital Rectal Examination (DRE)

[0010] Digital rectal examination is a method where a doctor inserts a finger into the rectum to examine the size, shape of the prostate, and the presence of abnormal manifestations such as hard lumps. This examination method is convenient and does not require complex equipment. However, it mainly relies on the doctor's experience for judgment and is unable to effectively detect minute lesions inside the prostate. Its accuracy is relatively low, especially in the screening for early-stage cancer, where tumors are often difficult to detect.

[0011] Defects: This method is difficult to detect minute lesions in the prostate, has limited screening ability for early prostate cancer, and its accuracy highly depends on the doctor's operating experience.

[0012] D. Tissue biopsy

[0013] Biopsy is the gold standard method for diagnosing prostate cancer. It confirms the presence of cancer by extracting prostate tissue for pathological examination. Although its accuracy is relatively high, biopsy is somewhat invasive and places certain psychological pressure and physical burden on patients. In addition, biopsy is an invasive procedure that may have complications such as infection and bleeding, and it may not be able to collect tissue from the cancerous area, resulting in missed diagnosis.

[0014] Defects: As an invasive procedure, biopsy has certain risks and discomfort. At the same time, it cannot achieve early screening and places a relatively heavy physical and psychological burden on patients.

[0015] Analysis of problems in the prior art

[0016] The current diagnostic methods for prostate cancer generally have the following technical problems:

[0017] • Low sensitivity in early screening: Existing detection methods (such as imaging examinations and PSA tests) have relatively low sensitivity in screening for early prostate cancer, especially for minute cancerous areas, making it difficult to conduct effective early diagnosis.

[0018] • Insufficient accuracy: Existing detection methods (such as digital rectal examination, PSA test) are easily affected by false positives and false negatives, resulting in misdiagnosis or missed diagnosis.

[0019] • Highly invasive and large patient burden: Methods such as biopsy can provide relatively accurate diagnostic results, but due to their invasiveness and operation risks, they increase the physical and psychological burden on patients.

[0020] Therefore, there is still a need for auxiliary diagnostic equipment and methods for prostate cancer. Summary of the invention

[0021] In view of the technical problems existing in the prior art, the present invention proposes a method for detecting prostate cancer using nematode sensory nerve signals. By observing the response of nematodes to urine-prostatic fluid mixtures and combining calcium imaging technology, a non-invasive, highly sensitive, and low-cost auxiliary diagnostic device for prostate cancer is provided. This auxiliary diagnostic device can effectively solve the problems of low sensitivity, insufficient accuracy, and strong invasiveness in early screening in the prior art, and provides a new, bio-signal-guided diagnostic approach.

[0022] In addition, the present invention discloses an auxiliary diagnostic device based on nematode sensory nerve calcium signals, aiming to achieve efficient, accurate, and non-invasive auxiliary diagnosis of prostate cancer through highly sensitive calcium imaging technology and a microfluidic delivery system. The device combines automated microfluidic technology, a calcium imaging detection module, and a data processing and analysis module to provide an integrated solution from sample processing to result output.

[0023] The device of the present invention integrates a calcium imaging detection module, a microfluidic sample delivery system, and a data processing and analysis module, utilizes the chemosensory neuron response of Caenorhabditis elegans to collect and analyze the nerve signals of urine-prostatic fluid mixture samples, and aids in the diagnosis of the presence of prostate cancer. A highly sensitive, non-invasive, and efficient auxiliary diagnostic device for prostate cancer is realized, making up for the defects of strong invasiveness and high detection complexity of traditional devices.

[0024] The device of the present invention captures the specific signal peaks of neurons such as ASH and AWC through highly sensitive calcium imaging technology, compares them with the healthy control group, and forms a diagnostic conclusion. The diagnostic accuracy and sensitivity of the device are significantly improved, especially with high specificity for high-grade prostate cancer samples.

[0025] The device of the present invention supports users to manually perform preliminary processing of samples (such as filtering urine-prostatic fluid mixtures through a 0.22-micron filter membrane), and combines a standardized dilution method (dilution with 1:10 CTX buffer) to ensure the consistency and quality of samples. The device realizes high efficiency and standardization in the sample delivery and detection stages. It provides a user-friendly sample processing flow, supports highly consistent and high-quality detection of samples. It reduces sample waste, reduces background noise, and enhances the accuracy and repeatability of detection through the microfluidic delivery system.

[0026] The device of the present invention integrates a data processing and analysis module, automatically analyzes the signal pattern based on a preset diagnostic model by collecting the dynamic calcium signals of nematode neurons, and outputs a diagnostic result. It provides a fast and intuitive diagnostic report, supports batch analysis of multiple samples, and provides a scientific basis for clinicians.

[0027] The present invention uses a urine-prostatic fluid mixture as a detection sample, eliminating the need for puncture or invasive procedures, significantly enhancing the patient experience, and at the same time improving the sensitivity through calcium imaging technology.

[0028] The specific signal peak analysis of the present invention significantly reduces the false positive and false negative rates, and at the same time the equipment cost is lower than that of traditional diagnostic techniques, reducing the economic burden on patients.

[0029] The present invention innovatively uses a detection technology that combines a biosensor (nematode) with calcium imaging, providing a new way for cancer auxiliary diagnosis and expanding the application scenarios of biomedical devices.

[0030] Specifically, the present invention provides the following technical solutions.

[0031] On the one hand, the present invention provides a prostate cancer auxiliary diagnosis device, which includes a calcium imaging detection module for detecting neuronal calcium signals.

[0032] In some embodiments, the calcium imaging detection module includes a microscopic imaging device and nematodes expressing the calcium imaging fluorescent protein GCaMP and the indicator protein mCherry.

[0033] In some embodiments, the microscopic imaging device includes a spinning disk confocal microscope and an sCMOS single photon detector.

[0034] In some embodiments, the device further includes a data processing and analysis module, which includes an embedded computing device and analysis software for converting the collected neuronal calcium signals into a visual activity map, and analyzing and comparing the signal pattern differences through algorithms to output a diagnostic result.

[0035] In some embodiments, the analysis software uses Python scripts to perform visual processing on the extracted time series data to intuitively display the change trend of neuronal calcium signals.

[0036] In some embodiments, the analysis software stores the neuronal signal data extracted by algorithms in Excel format. The file contains the fluorescence signal intensity information of all neurons. The data is read using the Pandas library and plotted through Matplotlib. The X-axis in the figure represents the time points corresponding to different volume sequences, and the Y-axis represents the normalized fluorescence signal change, i.e., ΔF / F.

[0037] In some embodiments, based on the corrected signal and the baseline fluorescence intensity, the normalized fluorescence signal change ΔF / F is calculated. The methods for baseline calculation and bleaching correction are as follows: The average fluorescence intensity within the time window before sample stimulation is calculated as the baseline fluorescence intensity, and the exponential decay model is used to perform bleaching correction on the fluorescence signal. The bleaching correction is achieved by defining the exponential decay function where , and are fitting parameters. The fluorescence signal of each neuron is fitted using the curve_fit method in the Scipy library to obtain the corrected signal.

[0038] In some embodiments, when the sample is high-grade prostate cancer, the ΔF / F (normalized fluorescence signal) of ASH neurons is greater than 0.1; when the sample is a benign sample, the ΔF / F of AWC neurons is greater than 0.1.

[0039] In some embodiments, a heatmap of ΔF / F is plotted using Matplotlib, and red and green shaded regions are added to the time window through the axvspan method to respectively mark the benign stimulation interval and the high-grade prostate cancer stimulation interval, thereby realizing data visualization.

[0040] In some embodiments, the visualized data is saved as a PNG format image and stored in a specified path for further analysis, which is used for the auxiliary diagnosis of prostate cancer.

[0041] In some embodiments, the device further includes a microfluidic sample delivery module for fixing the nematode sample and precisely delivering the processed sample solution to be tested to the head region of the nematode.

[0042] In some embodiments, the microfluidic sample delivery module includes a multi-channel microfluidic chip, a liquid delivery pipeline, and a driving unit.

[0043] In some embodiments, the multi-channel microfluidic chip includes multiple holes to sequentially deliver different liquid samples to the experimental area, and at the same time, the excess liquid is removed through the waste liquid channel.

[0044] In some embodiments, the liquid delivery pipeline includes multiple channels, which are responsible for connecting the liquid storage bottle and the multi-channel microfluidic chip to ensure that the liquid is delivered to the experimental area in a predetermined order.

[0045] In some embodiments, the driving unit includes a gas pressure driving system, a valve controller, and a data acquisition and control module.

[0046] In some embodiments, the gas pressure driving unit pushes the liquid to flow through a stable air pressure and ensures the accuracy of liquid switching.

[0047] In some embodiments, the valve controller regulates the opening and closing of the liquid channel through computer instructions to achieve precise selection and switching of the liquid.

[0048] In some embodiments, the data acquisition and control module combines with a LabJack data acquisition device to ensure precise matching of the timing of valve switching signals, experimental data recording, and liquid delivery.

[0049] In some embodiments, the device further includes a sample processing module, and the sample processing module is used to perform preliminary filtration and dilution processing on the sample.

[0050] In some embodiments, the sample is a urine-prostatic fluid mixture.

[0051] On the other hand, the present invention provides the use of nematodes expressing the calcium imaging fluorescent protein GCaMP and the indicator protein mCherry in the preparation of a kit or device for the auxiliary diagnosis of prostate cancer.

[0052] On the other hand, the present invention provides a method for the auxiliary diagnosis of prostate cancer, and the method includes detecting the neuronal calcium signal of nematodes through the device as described above.

[0053] In some embodiments, the nematode is Caenorhabditis elegans.

[0054] In some embodiments, the neurons are ASH neurons and / or AWC neurons.

[0055] In some embodiments, when the sample is high-grade prostate cancer, the ΔF / F (normalized fluorescence signal) of ASH neurons is greater than 0.1; when the sample is a benign sample, the ΔF / F of AWC neurons is greater than 0.1.

[0056] In some embodiments, the method includes the following steps:

[0057] a. Sample collection and processing: Collect the urine-prostatic fluid mixture, and manually filter it through a 0.22-micron filter membrane and dilute it in proportion;

[0058] b. Microfluidic delivery and nematode fixation: The sample is delivered to the tip of the nematode fixed on the nematode chip through the microfluidic system;

[0059] c. Neuronal calcium signal acquisition: Start the calcium imaging detection module, record the calcium signal response of the nematode chemosensory neurons to the sample, and store the collected dynamic signals in the form of a map;

[0060] d. Data processing and analysis: Construct a differential pattern of neuronal signals, and finally output the prostate cancer diagnosis result.

[0061] In some embodiments, the calcium imaging protein is GCaMP8f, and its nucleotide sequence is as shown in SEQ ID NO: 1.

[0062] In some embodiments, the indicator protein is mCherry, and its nucleotide sequence is as shown in SEQ ID NO: 2.

[0063] In some embodiments, the calcium imaging reference protein is CyOFP, and its nucleotide sequence is as shown in SEQ ID NO: 4.

[0064] In some embodiments, the promoter of the calcium imaging protein is Posm-6, and its nucleotide sequence is as shown in SEQ ID NO: 3.

[0065] In some embodiments, the nuclear localization sequence of the calcium imaging protein is 3×SV40, and its nucleotide sequence is as shown in SEQ ID NO: 5.

[0066] Definitions

[0067] Calcium imaging: It is a method for measuring the flow of calcium in cells and directly observing the calcium signals of active neurons, which is widely used in fields such as brain research. When performing calcium imaging, it is necessary to observe with the help of a fluorescence microscope or a fluorescence plate reader. A protein or calcium fluorescence indicator that changes fluorescence intensity once bound to calcium ions is introduced into the cell interior, and the concentration change of calcium ions is detected according to the change of fluorescence intensity.

[0068] Spinning disk confocal microscope: Its working principle is based on a point light source illumination combined with a pinhole mechanism, which only allows fluorescence near the focus to pass through and filters out-of-focus plane fluorescence. The calcium indicator and the indicator protein are sequentially excited by lasers (488nm and 561nm). The excitation light is refracted by the objective lens and the optical path and then transmitted to the sCMOS single photon detector. The laser light sources are 488nm and 561nm lasers. The detector is a dual sCMOS single photon detector, which captures red and green fluorescence respectively. The calcium signals and the indicator protein signals of nematode neurons are collected through a dual camera to achieve synchronous imaging and dynamic monitoring.

[0069] ASH neuron: It is a bimodal sensory neuron in the head of nematodes, which can detect various harmful stimuli (such as high-concentration chemicals, mechanical pressure, and osmotic pressure changes) through ciliary structures and mediate avoidance behaviors. Its function depends on the glutamate signaling pathway and drives motor regulation by activating downstream interneurons (such as AVA). As a multimodal nociception model, ASH neurons have important application potential in analyzing the neural mechanism of pain, developing new analgesic drug targets, and designing bionic sensors (such as environmental toxicity detection).

[0070] AWC neurons: They are bilateral olfactory neurons that recognize volatile odor molecules (such as benzaldehyde) and regulate chemotaxis by expressing olfactory receptors (such as STR-2). Their subtype differentiation (AWCON / AWCOFF) and olfactory adaptability (dependent on the insulin signaling pathway) provide an ideal model for studying neuronal plasticity and olfactory coding mechanisms. AWC-related pathways (such as GPCR-cGMP signaling) have translational research value in the analysis of neurodegenerative disease mechanisms, the development of odor sensors, and artificial intelligence olfactory simulation technology.

[0071] High-grade prostate cancer: refers to the most malignant tumor type based on the prostate cancer histopathological grading system, which is defined as: Gleason score ≥ 8 points (scoring range 2-10), that is, the tumor cells show significant atypia under the microscope (such as Gleason pattern 4 or 5 is dominant, showing the absence of fusion glandular structure or diffuse single cell infiltration), indicating that the cells are extremely poorly differentiated and highly invasive; belonging to Group 4 (Gleason 4+4=8 points) or Group 5 (Gleason 9-10 points) in the International Society of Urological Pathology (ISUP) prognostic grade grouping, indicating a significantly increased risk of tumor progression, prone to local invasion or distant metastasis (such as bone metastasis), and a poor prognosis. This classification is the core basis for clinical formulation of radical treatment (such as prostatectomy, radiotherapy combined with androgen deprivation therapy) and evaluation of the applicability of new targeted therapies (such as PARP inhibitors, immune checkpoint inhibitors).

[0072] Microfluidics: It is a technology that precisely manipulates microfluids (nanoliter to microliter) in micrometer-scale channels or chambers (usually tens to hundreds of micrometers). Micropumps, microvalves, mixers and detection units are integrated on the chip through micromachining technology (such as photolithography and soft photolithography), and microscale fluid mechanics such as laminar flow effect, surface tension or electroosmotic flow are used to achieve directional transport, mixing, separation or reaction of fluids. This technology has low sample consumption, high integration and automated analysis capabilities, and is widely used in biomedical testing (such as gene sequencing, liquid biopsy), drug screening, organ-on-a-Chip and point-of-care (POCT) equipment development. It is a key technology platform for the next generation of portable diagnostic instruments and precision medical tools.

[0073] Benign Samples: Benign prostate lesions refer to the pathological state in which no canceration has occurred in the prostate tissue, mainly including benign prostatic hyperplasia (BPH) and chronic prostatitis. BPH is manifested as non-cancerous hyperplasia of prostate glands and stromal cells, resulting in an enlarged prostate volume, which is common in elderly men and clinically manifested as urethral compression symptoms (such as difficulty in urination, frequent urination); chronic prostatitis is characterized by inflammatory cell infiltration and fibrosis, without evidence of malignant transformation. In prostate cancer research, benign samples are often used as control groups. It should be noted that the Gleason index is not applicable to benign samples because the Gleason score is only used to evaluate the histological grade of prostate cancer (usually starting from Gleason 6, indicating low-grade canceration). Benign samples are urine-prostatic fluid from patients with benign prostate lesions.

[0074] Beneficial Effects

[0075] The present invention solves the problems of strong invasiveness and complex detection of existing devices through non-invasive sample collection and high-sensitivity calcium signal analysis technology.

[0076] Integrating microfluidics and data processing and analysis modules improves the detection efficiency and the standardization level of sample processing.

[0077] Innovatively utilizing the biological signals of nematode neurons to establish a reliable cancer auxiliary diagnosis method, improving the scientificity and accuracy of diagnosis.

[0078] The present invention adopts a multi-module integrated design, integrating functions such as sample processing, delivery, detection, and analysis, improving the operation convenience and efficiency.

[0079] The present invention achieves high-sensitivity detection. Combining with fluorescence calcium imaging technology, it significantly improves the resolution and specificity of detection signals.

[0080] The present invention realizes non-invasive diagnosis. Using urine-prostatic fluid samples as the main detection medium reduces the psychological and physiological burdens of patients.

[0081] The present invention realizes result visualization and data export, achieving intuitive result presentation and convenient data management functions.

[0082] In summary, the auxiliary diagnosis device of the present invention has significant technical advantages and practical value, providing an economical and efficient solution for the early detection and auxiliary diagnosis of prostate cancer. Description of the Drawings

[0083] Figure 1 It is a schematic structural diagram of the microfluidic sample delivery module.

[0084] Figure 2 It is a schematic structural diagram of the microfluidic chip.

[0085] Figure 3 Schematic diagram for introducing nematodes into a microfluidic chip.

[0086] Figure 4 Shows the signal changes of AWC neurons upon receiving signals from benign samples (red) and high-grade prostate cancer samples (green).

[0087] Figure 5 Shows the signal changes of ASH neurons upon receiving signals from benign samples (red) and high-grade prostate cancer samples (green).

[0088] Figure 6 Shows the signal changes of ASE neurons upon receiving signals from benign samples (red) and high-grade prostate cancer samples (green).

[0089] Figure 7 Schematic diagram of the connection mode of the device of the present invention. This figure shows the overall layout of the microfluidic calcium imaging experimental system. The system consists of multiple buffer and sample channels to be tested. The opening and closing of valves are adjusted by a controller to control the switching of liquid samples. The liquid flows through the chip on the displacement stage, enters the waste liquid collection area after flowing through the target area. The imaging system consists of a spinning disk confocal microscope, a 60×WI objective lens, an sCMOS camera, and lasers of different wavelengths (488 nm and 561 nm), and can accurately collect fluorescence signals and perform imaging analysis.

[0090] Figure 8 Shows the flowchart of the use of the device of the present invention. This figure shows the prostate cancer risk assessment process based on neuronal calcium signals. After the samples are collected, microfluidically transported, and nematodes are fixed, the neuronal calcium signals are recorded and data analysis is performed. When specific signal peaks are detected, the risk of prostate cancer is judged to be high (yes); if there are no obvious specific signals, the risk is low. Detailed implementation manners

[0091] To make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0092] Culturing and subculturing of nematodes

[0093] Nematodes are normally cultured in a 20°C biochemical incubator and propagated in NGM medium supplemented with Escherichia coli OP50. They are passaged every three or four days. If not used for a long time, they can be sealed with a sealing film and stored for more than half a month. When re-culturing is needed, cut a piece of NGM medium and place it on a new NGM medium. During passage, sterilize the platinum wire in the outer flame of an alcohol lamp, cool it in the air for a few seconds, and then dip a little OP50 as an attachment to pick the required nematodes. If the nematodes are contaminated, pick the adult worms into the rinsing and lysis solution, shake it, and after the worms are lysed, place it on a new NGM medium. After the eggs hatch into small worms, pick them onto a new NGM medium for culture.

[0094] The preparation of Nematode Growth Medium (NGM) requires two key stages to ensure the quality and sterility of the medium. First, before sterilization, add sodium chloride (3.0 g), agar powder (20.0 g), tryptone (2.5 g), and cholesterol (1.0 mL, 5 mg / mL ethanol solution) to ultrapure water in sequence, and make up the volume to 1.0 L. After fully mixing, transfer it to a conical flask for autoclaving. The sterilized medium needs to be cooled to an appropriate temperature in a laminar flow hood, and then, according to the formula of the components added after sterilization, add 1 M potassium phosphate buffer (pH 6.0, 25.0 mL), 1 M sterile calcium chloride solution (1.0 mL), 1 M sterile magnesium sulfate solution (1.0 mL), and nystatin (1.0 mL, 10 mg / mL ethanol solution) in sequence. Gently shake the medium to make all components fully mixed, and then use a peristaltic pump to dispense the medium into culture dishes and disinfect it under an ultraviolet lamp. Finally, let the medium stand in the laminar flow hood for 12 hours to completely solidify. The prepared medium can be stored at room temperature for 7 days. If the storage time needs to be extended, it can be placed in a refrigerated environment to maintain its physical and chemical properties and culture effect.

[0095] The equipment of the present invention

[0096] The equipment of the present invention mainly includes the following modules:

[0097] 1. Sample processing module

[0098] The sample processing module is used to perform preliminary filtration and dilution on the urine-prostatic fluid mixture sample. After the sample is manually filtered through a 0.22-micron filter membrane, it is diluted with CTX buffer at a ratio of 1:10 to ensure the purity of the sample and the stability of the concentration of the active ingredients.

[0099] CTX buffer is used for microfluidic-calcium imaging experiments to dilute the urine or prostatic fluid sample to be tested and form a laminar flow structure in the microfluidic chip. Its preparation method is as follows:

[0100] 1. Prepare a 5 mM potassium dihydrogen phosphate / dipotassium hydrogen phosphate buffer (KH2PO4 / K2HPO4) (5 mM potassium dihydrogen phosphate / dipotassium hydrogen phosphate buffer means the total concentration of potassium dihydrogen phosphate (KH2PO4) and dipotassium hydrogen phosphate (K2HPO4) is 5 mM), and adjust the pH to 6.0.

[0101] 2. Add 1 mM calcium chloride (CaCl2), 1 mM magnesium sulfate (MgSO4), 50 mM sodium chloride (NaCl), and 235 mM D-sorbitol.

[0102] 3. Make up the volume to 1 L with ultrapure water (ddH2O).

[0103] 4. Transfer it to a heat-resistant glass bottle and autoclave at 121 °C for 20 minutes.

[0104] 5. After sterilization, store it at 4 °C, and the validity period is 6 months.

[0105] 2. Microfluidic sample delivery module

[0106] The microfluidic sample delivery module includes a multi-channel microfluidic chip, a liquid delivery pipeline, and a driving unit. This module fixes the nematode sample through the multi-channel microfluidic chip and precisely delivers the processed sample solution to be tested to the head region of the nematode. Due to the low Reynolds Number of the fluid in the microfluidic chip, all liquid flows maintain a laminar flow state. The microfluidic chip is designed to precisely control the flow direction and flow rate of the fluid, ensuring the uniformity of the nematode's contact with the liquid and the repeatability of the experiment.

[0107] Each module of the microfluidic sample delivery module cooperates with each other to achieve precise control of the experimental liquid sample. The multi-channel microfluidic chip is the core component of the entire module, responsible for sequentially delivering different liquid samples to the experimental area, and at the same time removing excess liquid through the waste liquid channel. The microfluidic chip is usually bonded by PDMS and glass materials, with good transparency and biocompatibility, suitable for microscopic imaging and experimental observation.

[0108] The liquid delivery pipeline is responsible for connecting the liquid storage bottle and the microfluidic chip, ensuring that the liquid is delivered to the experimental area in a predetermined order. This pipeline adopts a multi-channel independent design, enabling the system to quickly switch different liquids, avoiding cross-contamination, and maintaining the stability of the fluid environment at the same time. By precisely controlling the opening and closing of the valves, the liquid can be stably delivered according to the set time and order, providing a reliable fluid microenvironment for the experiment.

[0109] The drive unit includes a gas pressure drive system, a valve controller, and a data acquisition and control module. The gas pressure drive unit pushes the liquid to flow through a stable air pressure and ensures the accuracy of liquid switching. The valve controller regulates the opening and closing of the liquid channels through computer instructions to achieve precise selection and switching of liquids. At the same time, the data acquisition and control module combines with the LabJack data acquisition device to ensure that the valve switching signals, experimental data records, and the timing of liquid delivery are precisely matched. The computer control software presets the liquid switching scheme and records all parameters during the experiment, making the entire system efficient in data storage, reading, and analysis.

[0110] The operation process of the entire microfluidic system includes four key steps. First, the sample liquid is stored in an independent liquid storage bottle and enters the liquid delivery pipeline through gas pressure drive. Subsequently, the target sample is selected through the valve controller and delivered to specific holes in the microfluidic chip. Then, the liquid acts on the experimental area inside the microfluidic chip, and the unused sample is discharged through the waste liquid channel. Finally, the multifunctional data acquisition and control module records the liquid switching time, the moment of stimulus application, and related experimental data to ensure the accuracy and repeatability of the experiment.

[0111] The microfluidic sample delivery module relies on precise liquid control, a stable fluid environment, and efficient data acquisition to ensure high stability and repeatability of the experimental process. Its main advantages include high-efficient liquid switching ability, which can quickly switch between different samples; stable fluid control, effectively avoiding mixing between samples and improving the reliability of the experiment; precise signal synchronization, ensuring strict alignment between liquid delivery and data acquisition, thereby improving the quality of experimental data. This system provides a high-precision and high-throughput solution for microfluidic experiments and has broad application value in fields such as neuroscience research, biosensing, and drug screening.

[0112] The microfluidic chip contains 7 holes, and the functions and distributions of each hole are as Figure 2 shown:

[0113] Hole 1 and Hole 5: Hole 1 and Hole 5 are control channels, used to control the opening and closing of liquid flow respectively to achieve precise delivery of liquid sample stimuli.

[0114] Holes 2 - 3: Liquid sample channels, used to transport liquid samples.

[0115] Hole 4: Buffer channel, used to provide buffer solution, which plays a role in dilution and cleaning.

[0116] Hole 6: Nematode channel, through which nematodes are injected into the fixed chamber of the microfluidic chip to ensure accurate position and reduce interference with experimental operations.

[0117] Hole 7: Waste liquid channel, which is used to discharge excess liquid to maintain the dynamic balance of the fluid in the system. All the liquid entering the microfluidic chip finally discharges through the waste liquid channel, avoiding the influence of fluid accumulation or overflow on the experimental results.

[0118] During the experiment, three fluids are always present: a liquid sample channel (one of Hole 2 - 3), a buffer solution channel (Hole 4), and a control channel (Hole 1 or Hole 5).

[0119] 3. Calcium imaging detection module

[0120] The calcium imaging detection module includes:

[0121] (1) High - sensitivity microscopic imaging equipment: including a spinning disk confocal microscope and an sCMOS single - photon detector. Fluorescent excitation light sources: including lasers of 488 nm and 561 nm, which are used to excite the calcium indicator (GCaMP) and the indicator protein (mCherry) respectively.

[0122] (2) A nematode strain expressing the calcium imaging fluorescent protein GCaMP and the indicator protein mCherry

[0123] GCaMP is a genetically encoded calcium indicator, which is formed by fusing the green fluorescent protein (GFP), the peptide sequence of myosin light chain kinase (M13) and calmodulin (CaM). When there is no calcium, the GFP chromophore is exposed to water, and the protonated state results in the lowest fluorescence intensity. After binding calcium ions, the conformational change of the CaM domain binds to M13, the chromophore is de - protonated, transformed into an anionic form, and emits bright green fluorescence. The peak excitation wavelength is 488 nm. The peak emission wavelength is 510 nm. The excitation light source is a 488 - nm laser. GCaMP can be specifically expressed in neurons by inserting it under a specific promoter.

[0124] mCherry is a red fluorescent protein modified from DsRed, which has high photostability and is suitable for simultaneous imaging with GCaMP. The peak excitation wavelength is 561 nm. The peak emission wavelength is 610 nm. mCherry can be used as a marker protein for specific neurons and provide a fluorescence signal reference for GCaMP.

[0125] The method for constructing the transgenic nematode strain adopts the general method (reference can also be made to patent application CN117467703A).

[0126] The commonly used expression vector for Caenorhabditis elegans is modified from the pUC18 vector. We inserted the sequence of unc-54 3'UTR+polyA (for transcriptional termination) in the downstream of the multiple cloning site. This is the template of the commonly used expression vector for C. elegans. We only need to insert the required promoter and the target protein upstream of unc-54 3'UTR+polyA. In the invention, we ligated the Posm-6 promoter, the calcium imaging protein (GCaMP8f), and the reference protein (CyOFP) in sequence and inserted them into the multiple cloning site of the commonly used expression vector for C. elegans, namely Posm-6::GCaMP8f::CyOFP, and the nuclear localization sequence is 3×SV40. Posm-6:: 3×SV40::GCaMP8f::CyOFP is inserted between the promoter and the calcium imaging protein. mCherry is used as a reference protein, and its fluorescence intensity does not change, and it is used for the localization of neurons. GCaMP and mCherry are constructed on the same vector.

[0127] The calcium imaging protein is used to monitor the calcium activity of C. elegans neurons. The reference protein is used for calibration to adapt to the distortion or deformation of neurons caused by the movement of C. elegans. CyOFP is a blue light-excited fluorescent protein, but its emission spectrum is red-shifted, which is significantly different from the emission spectrum of the calcium imaging protein, facilitating us to distinguish the fluorescence emitted by the fluorescent protein CyOFP and the calcium imaging protein through different cameras or image separators.

[0128] Taking the experiment in Caenorhabditis elegans as an example, the construction of transgenic C. elegans includes the following steps:

[0129] 1. Construct the plasmid of the calcium imaging protein and the reference fluorescent protein (specific promoter - calcium imaging protein - CyOFP), send it to Sangon Biotech Co., Ltd. for sequencing to confirm that the sequence is correct.

[0130] The plasmid extraction is carried out using the FastPure Plasmid Mini Kit of Nanjing Novoprotein Scientific Inc., with the product number (DC201-01).

[0131] 2. Inject the plasmid to construct transgenic C. elegans WEN0070 wenEX0070 (Posm-6::SV40(3XNLS)::Gcamp8f::CyOFP).

[0132] 3. Screen the progeny C. elegans expressing the marker protein by fluorescence microscopy 72 hours after injection.

[0133] Injecting the plasmid into C. elegans includes the following steps:

[0134] First, prepare the agarose fixation pad required for microinjection: Weigh 2 g of electrophoresis-grade agarose, add it to 100 mL of ultrapure water, and heat it in a microwave until completely dissolved. Drop the molten agarose solution onto the center of a 40×60 mm coverslip, add 100 μL of liquid to each coverslip, quickly cover it with another coverslip, press to form a uniform film, separate the coverslips after curing at room temperature, and obtain a fixation pad with a thickness of 200±20 μm. Store it at 25°C in dry conditions, and the validity period is 14 days. Secondly, select experimental nematodes: Select young adults (nematodes on the second day after adulthood), which have the best egg-laying ability, a moderate body wall thickness, and a high survival rate after injection. Transfer L4-stage nematodes to a fresh OP50 culture plate 24 hours in advance, and culture them at 22°C until the early adult stage (body length 1.2 - 1.5 mm, 8 to 12 oocytes), and wash them 3 times with M9 buffer before injection to remove bacterial contamination on the body surface.

[0135] The setup of the microinjection system includes using a P-97 puller to make injection needles (parameters: Heat = 600, Pull = 100, Velocity = 60), obtaining borosilicate glass needles with a tip diameter of 0.5 - 0.9 μm, and equipping with a FemtoJet 4i microinjection pump (injection pressure 80 - 120 hPa, compensation pressure 20 hPa). The injection solution is configured as a 10 μL plasmid mixture system, with the target plasmid concentration of 50 - 100 ng / μL (the target plasmid simultaneously expresses the calcium imaging protein and mCherry protein), add 0.5 μL GeneRuler™ DNA Ladder (SM0311, Thermo Scientific, this DNA Ladder is beneficial for free DNA to be absorbed and expressed by nematodes), centrifuge at 14,800×g for 10 minutes and collect the supernatant, and store it at 4°C for no more than one week. During the microinjection operation, fix the nematodes on the agarose pad, with the body axis at a 45° angle to the horizontal plane, expose the gonad region in the center of the field of view, use a 40× objective lens (NA = 0.75) to locate the distal end of the gonad, insert the injection needle into the genital cavity at an angle less than 30°, inject 50 - 100 nL of the injection solution in a pulsed manner, observe the change in refractive index in the gonad cavity to confirm the completion of injection, and resuscitate the nematodes with NGM buffer and transfer them to a pre-equilibrated OP50 culture plate after injection. To prevent contamination, soak the eyebrow picker in medical alcohol and sterilize it with ultraviolet light 1 - 3 hours after injection, and transfer the nematodes with good recovery to a new NGM plate for culture. The screening of transgenic lines is carried out in the F1 generation, and the progeny nematodes expressing the marker protein are screened by a fluorescence microscope 72 hours after injection.

[0136] 4. Data Processing and Analysis Module

[0137] The data processing and analysis module includes an embedded computing device and analysis software (Python code) for converting the collected neuronal calcium signals into a visualized activity map, analyzing and comparing the signal pattern differences through algorithms, and outputting a diagnostic result.

[0138] Data Visualization and Analysis Method

[0139] To visually display the calcium signal change trend of neurons, this paper uses Python scripts to perform visualization processing on the extracted time series data. The neuronal signal data after algorithm extraction is stored in Excel format, and the file contains the fluorescence signal intensity information of all neurons. The Pandas library is used to read the data, and Matplotlib is used for plotting. The X-axis in the figure represents the time points, corresponding to different volume sequences; the Y-axis represents the normalized fluorescence signal change (ΔF / F). To more clearly mark the changes in stimulus-induced neural activities, shaded areas (red and green respectively) are added to the image, and these areas mark different stimulus time windows. Each stimulus time period corresponds to different external signal inputs, enabling the visualization results to intuitively reflect the response characteristics of neurons. Finally, the visualization images of all neurons are saved to a specified folder for subsequent analysis.

[0140] Python Code Implementation Steps

[0141] 1. Data reading and preprocessing: Use the Pandas library to read the Excel file and extract the time series data of the fluorescence intensity of neurons.

[0142] 2. Baseline calculation and bleach correction: Calculate the average fluorescence intensity within the pre-stimulus time window as the baseline fluorescence intensity, and use an exponential decay model to perform bleach correction on the fluorescence signal. The bleach correction is achieved by defining an exponential decay function where , and are fitting parameters. The fluorescence signal of each neuron is fitted using the curve_fit method in the Scipy library to obtain the corrected signal.

[0143] Calculation of normalized fluorescence signal: Calculate the normalized fluorescence signal change ΔF / F based on the corrected signal and the baseline fluorescence intensity.

[0144] 1. Data visualization: Use Matplotlib to plot a ΔF / F heatmap, and add red and green shaded areas in specific time windows through the axvspan method to mark the benign stimulus interval and the high-grade cancer stimulus interval respectively.

[0145] 2. Result saving: Save the generated heatmap as a PNG format image and store it in the specified path for further analysis.

[0146] The algorithm model (CeNDeR) constructs an auxiliary diagnostic model based on specific neuron signal features such as ASH / AWC, using statistical analysis and machine learning methods, and outputs the diagnostic result.

[0147] Example: Sample detection and analysis

[0148] 1. Sample preparation: Take out the pre-filtered and aliquoted urine-prostatic fluid mixture sample from the -80°C refrigerator and allow it to thaw completely at room temperature. The research has obtained the ethical review approval for the collection of urine-prostatic fluid mixture samples from patients with clinically suspected prostate cancer (Ethics Committee of the First Affiliated Hospital of the University of Science and Technology of China, Approval number: 2023KY-324).

[0149] All patients who need to collect samples should meet the following criteria:

[0150] (1) Serum PSA ≥ 4 ng / ml;

[0151] (2) Complete prostate magnetic resonance examination;

[0152] (3) Scheduled for prostate biopsy, prostate hyperplasia surgery or radical prostatectomy, and can obtain a clear pathological diagnosis result;

[0153] (4) No history of other malignant tumors in the urinary system;

[0154] (5) No urinary system stones;

[0155] (6) No contraindications to prostate massage.

[0156] When collecting samples, instruct the patient to assume the chest-knee position, and alternately and regularly massage the bilateral lobes of the patient's prostate with the fingertips of the index finger, gently squeeze the midline of the prostate, with a total duration of 2-3 minutes. When the patient feels secretions in the urethra, instruct the patient to urinate and collect about 30 ml of the first-pass urine, which is aliquoted into 2 pre-treated 15-ml centrifuge tubes and stored at -4°C and -80°C for later use. When collecting samples, it is necessary to record in detail the collection date, the patient's age, height, weight, family history, serum PSA, prostate volume, IPSS score, magnetic resonance PI-RADS score and other clinical data.

[0157] 2. Sample dilution and labeling: Dilute the sample to be tested with CTX buffer in a ratio of 1:10 and transfer it to a sterile 50-mL centrifuge tube for later use. At the same time, attach clear labels to distinguish different samples.

[0158] 3. Hardware connection:

[0159] • Connect the liquid pipeline to the centrifuge tube.

[0160] • Connect the liquid storage bottle to the liquid sample delivery device and dock the liquid sample delivery device with the microfluidic chip.

[0161] • Connect the computer controller to the valve control system and ensure stable power connection.

[0162] 4. Software initialization and chip connection:

[0163] • Start the SignalFlow Control software.

[0164] • Open the liquid storage bottle and ensure that all channels of the microfluidic chip are unblocked.

[0165] • Open the valves in sequence. After the liquid in the capillary reaches the tip, insert the capillary into the corresponding flow port of the microfluidic chip to reduce the generation of bubbles.

[0166] 5. Nematode introduction (see Figure 3 )

[0167] • Connect a syringe to the capillary and wash the Caenorhabditis elegans to remove surface OP50 bacteria.

[0168] • Place the washed nematodes in CTX buffer to swim and suck up the nematodes using a syringe.

[0169] • Insert the capillary into the nematode flow channel entrance of the microfluidic chip and apply pressure to the syringe (the syringe is also filled with CTX buffer) to push the nematodes into the flow channel and fix them.

[0170] 6. Reduce nematode peristalsis interference with nerve signal acquisition:

[0171] • Remove the CTX buffer at the end of the syringe and replace it with CTX buffer containing 50 mM levamisole.

[0172] • Slowly introduce the anesthetic levamisole solution until the nematodes are completely stationary.

[0173] Nematode anesthetic (50 mM levamisole solution)

[0174] This solution is used for microfluidic calcium imaging experiments, aiming to reduce the movement of nematodes in the channels of the microfluidic chip, thereby avoiding interference with the acquisition of neural signals. The preparation method is as follows: Take an appropriate amount of sterilized CTX buffer as the solvent, weigh levamisole to a final concentration of 50 mM, and completely dissolve it in the CTX buffer. After preparation, store it in the dark at 4°C, with a shelf life of 1 month. It needs to be fully mixed before use. After the nematodes are introduced into the chip, inject the anesthetic into the nematode flow channel through a syringe to inhibit the nematode peristalsis and ensure stable acquisition of neural signals during the experiment.

[0175] 7. Remove air bubbles:

[0176] • Air bubbles may form during the introduction of nematodes.

[0177] • At this time, block the waste liquid flow channel and open the control water / buffer / control odor valves.

[0178] • Due to the air permeability of the PDMS material, air bubbles can be effectively removed by liquid pressurization.

[0179] 8. Calcium imaging experiment:

[0180] • Set the protocol for buffer supply and different sample stimulations in the Signal Flow Control software.

[0181] • Synchronously trigger the Andor Zyla 4.2 sCMOS camera (99 fps) and the valve control system.

[0182] • Record the valve signals and the nematode neural activity signals.

[0183] 9. Expel nematodes:

[0184] • After the experiment, replace with new nematodes for the next round of data acquisition.

[0185] • Expel the nematodes in the flow channel by pressurizing the waste liquid flow channel.

[0186] 10. Repeat the experiment:

[0187] • Follow the above steps to repeat the experimental process for all samples to be tested.

[0188] • Measure at least two nematodes for each sample to be tested, and each nematode receives three repeated stimulations.

[0189] 11. Equipment cleaning:

[0190] • Drain all the liquid in the system.

[0191] • Clean once with a diluted sodium hypochlorite (NaClO) solution.

[0192] • Pressurize and clean the pipeline three times with ultrapure water.

[0193] • Seal and store all used pipelines, and label them for distinction.

[0194] 12. Data storage:

[0195] • Upload the collected data to the server for subsequent data processing and analysis.

[0196] 13. Data analysis method:

[0197] Utilize the existing Caenorhabditis elegans neuron detection and recognition system (CeNDeR) (Reference: Wu Y, Wu S, Wang X, Lang C, Zhang Q, Wen Q, et al. (2022) Rapid detection and recognition of whole - brain activity in a freely behaving Caenorhabditis elegans. PLoS Comput Biol 18(10): e1010594. https: / / doi.org / 10.1371 / journal.pcbi.1010594) to identify fluorescently labeled C. elegans neurons and extract neuron signals.

[0198] Use Python scripts to visualize the extracted time - series data. First, the experimental data is stored in Excel format, and the file contains the fluorescence signal intensity information of all neurons. Use the Pandas library to read this data and plot it through Matplotlib. The X - axis in the figure represents time points corresponding to different volume sequences; the Y - axis represents the normalized change in fluorescence signal.

[0199] Experimental results and analysis:

[0200] The horizontal axis represents time, with the unit being seconds. Red and green respectively represent two different samples, which are alternately stimulated. Each sample is stimulated for 10 seconds each time until each sample is exposed to the nematode's nose tip three times, ensuring rigor and excluding specific signals in nematode neurons caused accidentally by other external reasons rather than sample stimulation. During the experiment, the laser parameters and the opening and closing times of the microfluidic valves are precisely controlled to ensure the stability of alternating stimulation and nerve signal recording. Parameters are set in the computer, and the opening and closing times of the valves of each liquid pipeline can be set in the SignalFlow Control software, so that the exposure time of each sample at the nematode's nose tip can be accurately controlled. The laser parameters can be directly set on the computer by a commercial software. For the specific working principle of the calcium imaging device, reference can be made to patent application CN117467703A.

[0201] Blue is to pass the buffer solution at the nematode's nose tip for 20 seconds each time. At this time, the nerve activity brought by the previous sample stimulation is washed away, making the nematode's sensory neurons ready to receive the next sample stimulation.

[0202] In the face of exposure to high-grade prostate cancer, the ΔF / F (normalized fluorescence signal) of the ASH neuron is greater than 0.1, indicating that ASH will be significantly activated by the high-grade prostate cancer sample stimulation. Figure 5 The shaded part represents the time period when stimulation is given. In the green section, the calcium signal is significantly enhanced, but in the red area, that is, the section of exposure to the benign sample, the calcium signal of the ASH neuron shows no obvious change. Different samples are alternately given, and the experimental results are stable and consistent.

[0203] After the AWC neuron is exposed to the benign sample and then rinsed with CTX buffer solution, it will be significantly activated, and the ΔF / F (normalized fluorescence signal) is greater than 0.1, indicating that AWC will be significantly activated by the benign sample stimulation. Figure 4 The shaded part represents the time period when stimulation is given. In the green section, the calcium signal shows no significant change, but after the end of the red area, that is, after the section of exposure to the benign sample, the calcium signal of the AWC neuron is significantly enhanced. Different samples are alternately given, and the experimental results are stable and consistent.

[0204] Control neuron ASE:

[0205] The ASE neuron is a pair of olfactory sensory neurons in Caenorhabditis elegans, located in the amphid sensilla at the head of the nematode. The ASE neuron is divided into ASEL (left side) and ASER (right side), which are respectively responsible for perceiving different chemical concentration gradients in the environment, especially water-soluble chemicals (such as Na + 、Cl - 、pH value, etc.). ASEL mainly perceives cations (such as Na +), while ASER mainly senses anions (such as Cl - ). These pairs of neurons help the nematode find food (such as bacteria) or avoid harmful substances by regulating the chemotaxis behavior of the nematode. The shaded part represents the time period when the stimulus is given. There are no significant changes in the calcium signal in the green and red sections. Different samples are given alternately, and the experimental results are stable and consistent.

[0206] Sequence

[0207] SEQ ID NO:1 Nucleotide sequence of the calcium imaging protein GCaMP8f

[0208]

[0209] SEQ ID NO:2 indicates the nucleotide sequence of the protein mCherry

[0210] Gtgagcaagggcgaggaggataacatggccatcatcaaggagttcatgcgcttcaaggtgcacatggagggctccgtgaacggccacgagttcgagatcgagggcgagggcgagggccgcccctacgagggcacccagaccgccaagctgaaggtgaccaagggtggccccctgcccttcgcctgggacatcctgtcccctcagttcatgtacggctccaaggcctacgtgaagcaccccgccgacatccccgactacttgaagctgtccttccccgagggcttcaagtgggagcgcgtgatgaacttcgaggacggcggcgtggtgaccgtgacccaggactcctccctgcaggacggcgagttcatctacaaggtgaagctgcgcggcaccaacttcccctccgacggccccgtaatgcagaagaagaccatgggctgggaggcctcctccgagcggatgtaccccgaggacggcgccctgaagggcgagatcaagcagaggctgaagctgaaggacggcggccactacgacgctgaggtcaagaccacctacaaggccaagaagcccgtgcagctgcccggcgcctacaacgtcaacatcaagttggacatcacctcccacaacgaggactacaccatcgtggaacagtacgaacgcgccgagggccgccactccaccggcggcatggacgagctgtacaagtaa

[0211] SEQ ID NO:3 Posm-6 promoter nucleotide sequence

[0212]

[0213] Nucleotide sequence of reference protein CyOFP with SEQ ID NO:4

[0214] ATGGTGTCAAAAGGAGAAGAGCTTATTAAGGAGAATATGCGTTCCAAGCTCTACCTCGAGGGATCCGTCAACGGACACCAATTCAAGTGCACCCACGAGGGAGAGGGAAAGCCATACGAGGGAAAGCAAACCAACCGTATCAAGGTCGTCGAGGGAGGACCACTCCCATTCGCCTTCGACATCCTCGCCACCCACTTCATGTACGGATCCAAGgtaagtttaaacatatatatactaactaaccctgattatttaaattttcagGTCTTCATCAAGTACCCAGCCGACCTCCCAGACTACTTCAAGCAATCCTTCCCAGAGGGATTCACCTGGGAGCGTGTCATGGTCTTCGAGGACGGAGGAGTCCTCACCGCCACCCAAGACACCTCCCTCCAAGACGGAGAGCTCATCTACAACGTCAAGGTCCGTGGAGTCAACTTCCCAGCCAACGGACCAGTCATGCAAAAGAAGACCCTCGGATGGGAGCCATCCACCGAGACCATGTACCCAGCCGACGGAGGACTCGAGGGACGTTGCGACAAGgtaagtttaaacatgattttactaactaactaatctgatttaaattttcagGCCCTCAAGCTCGTCGGAGGAGGACACCTCCACGTCAACTTCAAGACCACCTACAAGTCCAAGAAGCCAGTCAAGATGCCAGGAGTCCACTACGTCGACCGTCGTCTCGAGCGTATCAAGGAGGCCGACAACGAGACCTACGTCGAGCAATACGAGCACGCCGTCGCCCGTTACTCCAACCTCGGAGGAGGAATGGACGAGCTCTACAAG

[0215] Nucleotide sequence of the nuclear localization sequence of calcium imaging protein GCaMP8f with 3×SV40

[0216] ccaaagaagaaacgcaaagtaccgagctcagaaaaaatgacggcacctaaaaagaaacgcaaagtaccggtcgccgagaagacagccccaaagaagaagcgtaaggtcggaatccacggagtcccagccgcc

[0217] The specific embodiments described above further elaborate on the objective, technical solution, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A prostate cancer auxiliary diagnosis device, characterized in that: The device comprises a calcium imaging detection module, which is used to detect neuronal calcium signals. Optionally, the calcium imaging detection module comprises a microscopic imaging device and a nematode expressing a calcium imaging fluorescent protein GCaMP and an indicator protein mCherry. Optionally, the microscopic imaging device comprises a spinning disk confocal microscope and a sCMOS single-photon detector.

2. The device according to claim 1, characterized in that The device also includes a data processing and analysis module, which includes an embedded computing device and analysis software, and is used to convert the collected neuronal calcium signals into a visual activity map, and compare the signal pattern differences through algorithm analysis to output a diagnosis result.

3. The device according to claim 2, characterized in that The analysis software uses Python scripts to visualize the extracted time series data to intuitively display the changing trend of neuronal calcium signals.

4. The device according to claim 2 or 3, characterized in that The analysis software stores the neuronal signal data extracted by the algorithm in Excel format. The file contains the fluorescence signal intensity information of all neurons. The data is read using the Pandas library and plotted using Matplotlib. The X-axis in the figure represents the time point, corresponding to different volume sequences, and the Y-axis represents the normalized fluorescence signal change, i.e., ΔF / F. Optionally, the normalized fluorescence signal change ΔF / F is calculated based on the corrected signal and the baseline fluorescence intensity. The method for baseline calculation and bleaching correction is as follows: the average fluorescence intensity in the time window before sample stimulation is calculated as the baseline fluorescence intensity, and the fluorescence signal is bleached using an exponential decay model. The bleaching correction is performed by defining an exponential decay function. Implementation, where , and To fit the parameters, the fluorescence signal of each neuron was fitted by the curve_fit method in the Scipy library to obtain the corrected signal. Optionally, a ΔF / F heat map was plotted using Matplotlib, and red and green shaded areas were added to the time window by the axvspan method to mark the benign stimulation interval and the high-grade prostate cancer stimulation interval, respectively, so as to achieve data visualization. Optionally, the visualized data was saved as a PNG format image and stored in a specified path for further analysis for auxiliary diagnosis of prostate cancer.

5. The device according to claim 4, characterized in that When the sample is high-grade prostate cancer, the ASH neuron ΔF / F (normalized fluorescence signal) is greater than 0.1; when the sample is a benign sample, the AWC neuron ΔF / F is greater than 0.

1.

6. The device according to any one of claims 1 to 5, characterized in that The device also includes a microfluidic sample delivery module for fixing the nematode sample and accurately delivering the processed test liquid sample to the nematode head area. Optionally, the microfluidic sample delivery module includes a multi-channel microfluidic chip, a liquid delivery pipeline and a drive unit. Optionally, the multi-channel microfluidic chip includes a plurality of holes to deliver different liquid samples to the experimental area in sequence, and remove excess liquid through the waste liquid channel. Optionally, the liquid delivery pipeline includes a plurality of channels, which are responsible for connecting the liquid storage bottle with the multi-channel microfluidic chip to ensure that the liquid is delivered to the experimental area in a predetermined order. Optionally, the drive unit includes a gas pressure drive system, a valve controller and a data acquisition and control module. Optionally, the gas pressure drive unit drives the liquid flow through stable gas pressure and ensures the accuracy of liquid switching. Optionally, the valve controller regulates the opening and closing of the liquid channel through computer instructions to achieve accurate selection and switching of the liquid. Optionally, the data acquisition and control module is combined with a LabJack data acquisition device to ensure accurate matching of the timing of valve switching signals, experimental data records and liquid delivery.

7. The device according to any one of claims 1 to 6, characterized in that The device also includes a sample processing module, which is used to perform preliminary filtering and dilution processing on the sample.

8. The device according to any one of claims 1 to 7, characterized in that The sample is a urine-prostatic fluid mixture.

9. Use of nematodes expressing the calcium imaging fluorescent protein GCaMP and the indicator protein mCherry in the preparation of a kit or device for auxiliary diagnosis of prostate cancer, optionally, the calcium imaging protein is GCaMP8f, whose nucleotide sequence is shown in SEQ ID NO: 1, optionally, the indicator protein mCherry, whose nucleotide sequence is shown in SEQ ID NO: 2, optionally, the calcium imaging reference protein is CyOFP, whose nucleotide sequence is shown in SEQ ID NO: 4, optionally, the promoter of the calcium imaging protein is Posm-6, whose nucleotide sequence is shown in SEQ ID NO: 3, optionally, the nuclear import sequence of the calcium imaging protein is 3×SV40, whose nucleotide sequence is shown in SEQ ID NO:

5.

10. The device according to any one of claims 1 to 8 or the use according to claim 9, characterized in that The nematode is Caenorhabditis elegans, and optionally, the neuron is an ASH neuron and / or an AWC neuron.

Images