Construction method of neural probe and array culture chip, and neural electrophysiological toxicity evaluation method and device

Abstract

The application relates to a construction method of a neural probe and array culture chip and a neural electrophysiological toxicity evaluation method and device, the construction method comprising the following steps: acquiring a base material, a probe material and a chip circuit layout; and processing the base material, the probe material and the chip circuit layout by adopting a traditional micro-electro-mechanical system manufacturing stripping process and a micro-pattern stamping technology to construct a chip base with an array neural probe; and constructing a multi-channel neural cell culture chamber corresponding to the array neural probe on the chip base to obtain a multi-channel chip with the neural probe and array culture. The construction method integrates an ultrathin neural probe array and an array culture chamber layer to form a complete multi-channel chip, the multi-channel chip can realize high-throughput neural electrophysiological toxicity detection, full-process automation and high-throughput of neural cell culture to toxicity detection can be realized on the multi-channel chip, and then test cost, time and complexity can be significantly reduced.

Description

Methods for constructing neural probes and array culture chips, and methods and equipment for assessing neurophysiological toxicity. Technical Field

[0001] This application relates to the field of chip technology, and in particular to a method for constructing a neural probe and an array culture chip, as well as a method and device for evaluating neurophysiological toxicity. Background Technology

[0002] Currently, the models used for external neurotoxicity testing mainly include three categories: mammalian models, non-mammalian models, and in vitro cell models. Mammalian models are expensive, time-consuming, and difficult to construct, and are not suitable for high-throughput testing. Non-mammalian models, such as zebrafish and fruit fly models, have short cycles and low costs, but the accuracy of the evaluation results is limited and difficult to replicate. In vitro cell models mostly rely on the biological behavior of nerve cells for evaluation, and the results are relatively simple and limited, making it difficult to detect the toxic effects of chemical substances on the neurophysiological signals of the brain. Summary of the Invention

[0003] This application provides a method for constructing neural probes and array culture chips, as well as a method and device for evaluating neurophysiological toxicity, to solve the technical problems of existing neurotoxicity testing models, such as high cost, long time consumption, and complex construction.

[0004] To achieve the above objectives, this application provides the following technical solution:

[0005] On the one hand, a method for constructing a neural probe-based culture chip array is provided, including the following steps:

[0006] The substrate material, probe material, and chip circuit layout are obtained. Based on the substrate material, probe material, and chip circuit layout, the traditional microelectromechanical system (MEMS) manufacturing stripping process and micropattern stamping technology are used to construct a chip substrate with arrayed neural probes.

[0007] A multi-channel neural cell culture chamber corresponding to the array of neural probes is constructed on the chip substrate to obtain a multi-channel chip with neural probes and array culture; the multi-channel neural cell culture chamber is connected to the electrodes of the chip substrate;

[0008] The construction of a multi-channel neural cell culture chamber corresponding to the array neural probes on the chip substrate includes: processing the chip substrate using the conventional microelectromechanical system (MEMS) manufacturing stripping process to obtain the multi-channel neural cell culture chamber; the multi-channel neural cell culture chamber includes an inlet / outlet, a cell seeding layer, a gradient layer, and multiple culture chamber layers corresponding to the array neural probes; the inlet / outlet is connected to the gradient layer; the cell seeding layer is disposed above each culture chamber layer; the gradient layer is disposed below all the culture chamber layers; and the gradient layer is connected to the electrodes of the chip substrate.

[0009] Preferably, the chip substrate with arrayed neural probes is constructed by processing the substrate material, the probe material, and the chip circuit layout using conventional microelectromechanical systems (MEMS) manufacturing stripping processes and micropattern stamping techniques.

[0010] Based on the chip circuit layout, an n×n array electrode circuit layout is fabricated on the substrate material using a conventional microelectromechanical system (MEMS) fabrication stripping process to obtain a substrate with neural probe assembly positions; and the probe material is synthesized using a solution method to obtain the neural probe.

[0011] The substrate to be modified is obtained by modifying the substrate with a silanizing coupling agent to obtain the substrate to be printed;

[0012] The micropattern stamping technology is used to print the neural probes at each assembly position of the neural probes on the substrate to be printed, thereby obtaining a chip substrate with an array of neural probes.

[0013] Preferably, the cell seeding layer is used for seeding cells and defining the range of the culture solution; and / or, the inlet / outlet is used for introducing chemical molecules into the gradient layer; the gradient layer is used to diffuse the introduced chemical molecules to construct a horizontal gradient in the XY plane, so as to provide a gradually decreasing concentration of the input chemical molecules to each culture chamber layer.

[0014] Preferably, the culture chamber layer is made of a scaffold or hydrogel material, and the thickness of the culture chamber layer is 250µm; and / or, the thickness of the gradient layer is 400µm.

[0015] On another front, a method for assessing neurophysiological toxicity based on neural probes and array culture chips is provided, comprising the following steps:

[0016] Obtain the multichannel chip constructed using the above-described method based on neural probes and array culture chips;

[0017] A gradient target compound is constructed within the multi-channel chip. Neurophysiological signals generated by a neural probe at different gradient exposure concentrations of the gradient target compound are collected and classified to obtain collected data. The neurophysiological signals include action potential signals and local field potential signals.

[0018] Obtain neurotoxicity standards, analyze the collected data based on the neurotoxicity standards, and obtain the toxicity level and neuroelectrophysiological toxicity assessment standards corresponding to the gradient target compounds.

[0019] Preferably, constructing the gradient target compound within the multi-channel chip includes:

[0020] An array neural network is established within the multi-channel chip;

[0021] The test compound and setting parameters for different gradient exposure concentrations are obtained, and the test compound is input into the array neural network according to the setting parameters to obtain the gradient target compound;

[0022] The process of establishing an array neural network within the multi-channel chip includes: adding at least 80,000 neurons to a cell seeding layer for seeding; the cells in the cell seeding layer falling into the multi-channel independent culture chamber layer by gravity; and obtaining the array neural network after at least 3 weeks of cell seeding / induction in the culture chamber layer.

[0023] Preferably, the compound to be tested includes the heavy metal lead, nitric oxide and / or neurotoxic chemical molecules of tetrodotoxin.

[0024] Preferably, the neurophysiological signals generated by the neural probe for different gradient exposure concentrations of the target compound are collected and classified to obtain the collected data, including:

[0025] The acquired neurophysiological signals are amplified and bandpass filtered to obtain processed data;

[0026] The EM algorithm is used to perform spike sorting on the action potential signals of the processed data to obtain sorted signal data;

[0027] Obtain a signal classification standard, and perform spike classification on the signal data according to the signal classification standard to obtain classification data;

[0028] Electrophysiological features are extracted from each type of peak in the classified data to obtain the collected data consisting of the electrophysiological features of all peak classifications.

[0029] Preferably, the signal classification criteria include the peak value, rise duration, and fall duration of the spike; and / or, the electrophysiological characteristics include frequency, amplitude, resonance, duration, rise time, decay time, peak-to-peak interval, peak energy, signal center frequency, and information entropy.

[0030] On the other hand, a terminal device is provided, including a processor and a memory;

[0031] The memory is used to store program code and transmit the program code to the processor;

[0032] The processor is configured to execute the aforementioned neurophysiological toxicity assessment method based on neural probes and array culture chips according to the instructions in the program code.

[0033] This invention discloses a method for constructing a neural probe-based array culture chip and a method and device for evaluating neurophysiological toxicity. The method includes acquiring a substrate material, probe material, and chip circuit layout; processing the substrate material, probe material, and chip circuit layout using traditional microelectromechanical systems (MEMS) fabrication stripping technology and micropattern stamping to construct a chip substrate with array neural probes; constructing multi-channel neural cell culture chambers corresponding to the array neural probes on the chip substrate to obtain a multi-channel chip with neural probes and array culture; and connecting the multi-channel neural cell culture chambers to the electrodes of the chip substrate. The construction of the multi-channel neural cell culture chambers corresponding to the array neural probes on the chip substrate includes: processing the chip substrate using traditional MEMS fabrication stripping technology to obtain the multi-channel neural cell culture chambers; the multi-channel neural cell culture chambers include an inlet / outlet, a cell seeding layer, a gradient layer, and multiple culture chamber layers corresponding to the array neural probes; the inlet / outlet is connected to the gradient layer; the cell seeding layer is positioned above each culture chamber layer; the gradient layer is positioned below all culture chamber layers; and the gradient layer is connected to the electrodes of the chip substrate.

[0034] As can be seen from the above technical solutions, this application has the following advantages: The construction method based on neural probes and array culture chips integrates an ultra-thin neural probe array with an array-type culture chamber layer by constructing a multi-channel neural cell culture chamber on a chip substrate composed of array neural probes, thus forming a complete multi-channel chip. This multi-channel chip can realize high-throughput detection of neurophysiological toxicity. The entire process from neural cell culture to toxicity detection can be automated and high-throughput on the multi-channel chip, thereby significantly reducing testing costs, time and complexity, and solving the technical problems of high cost, long time consumption and complex construction of existing neurotoxicity testing models.

[0035] This neurophysiological toxicity assessment method based on neural probes and array culture chips uses array neural probes and array culture chambers on a multi-channel chip to construct gradient target compounds for the test compounds, reducing experimental material consumption and animal use, and lowering testing costs. The method collects neurophysiological signals from different gradient exposure concentrations of the test compounds output by the array neural probes on the multi-channel chip, and analyzes the collected data to achieve rapid assessment of the neurotoxicity of a large number of compounds, improving testing efficiency and shortening the testing cycle. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 is a flowchart of the construction method based on neural probes and array culture chips according to an embodiment of this application;

[0038] Figure 2 is a schematic diagram of the structure of the multi-channel neural cell culture chamber in the construction method based on neural probes and array culture chips described in the embodiments of this application;

[0039] Figure 3 is a schematic diagram of the neurotoxicity test performed on a multi-channel chip in the construction method based on neural probes and array culture chips described in the embodiments of this application;

[0040] Figure 4 is a schematic diagram of the structure of the chip substrate with arrayed neural probes in the construction method based on neural probes and array culture chips described in the embodiments of this application;

[0041] Figure 5 is a schematic diagram of the neural probe acquiring signals in the construction method based on neural probes and array culture chips described in the embodiments of this application;

[0042] Figure 6 is a schematic diagram of the neural probe acquiring signals in the construction method based on neural probes and array culture chips described in the embodiments of this application;

[0043] Figure 7 is a flowchart of the steps of the neurophysiological toxicity assessment method based on neural probes and array culture chips described in the embodiments of this application;

[0044] Figure 8 is a flowchart of the neurophysiological toxicity assessment method based on neural probes and array culture chips described in the embodiments of this application;

[0045] Figure 9 is a schematic diagram of the array neural network construction in the neurophysiological toxicity assessment method based on neural probes and array culture chips described in the embodiments of this application;

[0046] Figure 10 is a schematic diagram showing the ultrasensitivity and specificity of the neurophysiological response in the neurophysiological toxicity assessment method based on neural probes and array culture chips described in the embodiments of this application.

[0047] Figure 11 is a schematic diagram of the terminal device described in an embodiment of this application. Detailed Implementation

[0048] To make the inventive objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0049] In the description of the embodiments of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0050] In the embodiments of this application, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of this application according to the specific circumstances.

[0051] Currently, methods for testing external neurotoxicity are mainly based on three categories: mammalian models, non-mammalian models, and in vitro cell models.

[0052] Mammalian models are the current standard models for assessing the neurotoxicity of chemicals, enjoying high and widespread acceptance. Standards include traditional neurodevelopmental toxicity testing methods based on experimental animals (such as OPPTS 870.6300) and TG426 issued by the OECD. These standards generally require the use of live mammals for neurotoxicity assessment, such as mice, rabbits, dogs, and monkeys. However, neurotoxicity assessments based on mammalian models suffer from drawbacks such as long experimental cycles, high costs, and low throughput, making it difficult to meet the needs of large-scale, high-throughput detection of compound neurotoxicity.

[0053] Due to the limitations of mammalian experimental models, various alternative non-mammalian models have emerged in recent years, such as zebrafish and fruit fly models. One of the most significant advantages of non-mammalian models is their rapid development, short development cycle, and small size, which can significantly shorten the neurotoxicity assessment cycle and reduce costs. However, neurotoxicity assessment based on non-mammalian models also has some drawbacks, such as short time windows, limited accuracy and difficulty in reproducibility of assessment results, and difficulty in observing samples, which restricts the development of related detection and assessment technologies.

[0054] Compared to other models, in vitro cell models offer advantages such as simplicity, efficiency, and ease of operation. They can be used to model and assess key events in neural development, including the toxic effects of compounds on early neural cell proliferation and metabolism, neural differentiation, cell migration, axonal dendrite growth and synapsis, glial cell differentiation, and myelination. Appropriate selection of cell models not only allows for the evaluation of the neurotoxic mechanisms of compounds from different perspectives but also simplifies the assessment process, reducing costs and enabling high throughput. Therefore, for drug synthesis and large-scale neurotoxicity screening, cell experimental models are a good candidate due to their low cost, ease of observation, and diverse modeling types, making them suitable for developing high-throughput array technologies. However, in vitro cell models only reflect local physiological functional characteristics of the nervous system and cannot reflect the overall toxicity level of the compound on the nervous system.

[0055] Current neurotoxicity assessment techniques generally use the biological behavior of the nervous system as the benchmark for toxicity evaluation. However, these assessments suffer from limitations such as single parameters and insufficient sensitivity of toxicity results. Electrophysiological signals of nerve cells, as functional characteristics of the brain's neural network, are extremely sensitive to environmental and cellular states and can be used to assess the overall health of the nervous system. Several neurotoxic substances have been found to affect the electrophysiological signals of the nervous system. For example, beta-amyloid protein can cause changes in neurophysiological signals, including the number, frequency, amplitude, and phase of neural action potentials, and can be toxic to the brain's neural network system. However, current technologies primarily focus on exploring the toxic mechanisms of compounds, lacking research on neurotoxicity assessment based on the corresponding characteristics of neurophysiological signals. Furthermore, while neurophysiological signals, as terminal functional signals of the brain's neural network, are sensitive and reliable to environmental changes, effective detection techniques and evaluation standards are lacking due to limitations in related technologies. Overall, current neurotoxicity detection technologies, due to difficulties in high-throughput quantification and limited evaluation parameters, are insufficient to meet the needs of large-scale neurotoxicity detection of new compounds and preclinical neurotoxicity safety assessments.

[0056] In recent years, due to the rapid development of micro / nanofabrication and microelectronics technologies, various probe systems have been designed to detect neurophysiological signals. Currently, the most common neural probe technology uses metal / silicon materials as electrodes to record physiological electrical activities in the extracellular environment. However, these electrodes still suffer from problems such as susceptibility to interference, poor selectivity, poor sensitivity, and complex signal separation and processing. Therefore, novel ultrathin neural probe technologies based on two-dimensional monolayer molecular materials have been developed, enabling the amplification of neurotransmitter responses and the transmission and recording of parameters such as the frequency, amplitude, waveform of cellular action potentials, and the speed of signal propagation between cell networks. A novel "neural probe system" has been developed by combining novel probe materials and field-effect transistor technology. This neural probe technology has advantages such as small size, high throughput, low detection limit, good biocompatibility, and convenient synthesis, making it suitable for developing novel neurotoxicity detection chips. In high-throughput neural cell culture technology, most current research utilizes microfluidic technology to construct multi-channel culture chambers, which can precisely control, monitor, and manipulate the extracellular microenvironment.

[0057] In this field, a multi-channel neural chemotaxis research chip platform can simultaneously detect the chemotaxis of thousands of 3D neural network microsystems, enabling high-throughput assessment of the effects of compounds on the nervous system.

[0058] Therefore, neuroelectrophysiological characteristics are the final assessment standard for the functional health of the nervous system, but the assessment results are based on a single parameter and lack sensitivity. For chemical neurotoxicity that is difficult to detect using conventional detection methods, only by analyzing its electrical characteristic parameters through specialized electrophysiological detection techniques can its neurotoxicity be discovered, but currently there are still no readily available relevant assessment techniques.

[0059] Multielectrode array (MEA) technology is an advanced method for recording and analyzing the electrophysiological activity of neurons or neural networks. This technology integrates multiple tiny electrodes on a culture dish or chip, enabling simultaneous monitoring of electrical signals at multiple sites, including action potentials (APs) and local field potentials (LFPs). Its advantage lies in its ability to simultaneously record a group of cells and support observations for several days without the need for micromanipulation or other auxiliary equipment. Because neuronal networks cultured on MEA arrays can survive for months, and because MEA arrays are non-invasive, they can be used to study acute and chronic toxicities, as well as developmental neurotoxicities. Another advantage of MEA arrays is their applicability to routine industrial-scale screening. In fact, with advancements in high-throughput MEA array technology, it is now possible to place microelectrode arrays at the bottom of each well in a multi-well plate, making it possible to evaluate 200 drugs per day. In 2018, Jenna D. Strickland et al. evaluated the effects of 1055 chemicals in the EPAI phase ToxCast library on neural function and cellular health to demonstrate the practicality of MEA-based methods as a rapid neurotoxicity screening tool. The results indicate that large-scale functional screening using neural networks on multi-electrode arrays (MEAs) can fill a critical gap in assessing potential neurotoxicity in ToxCast assays. The popularity of multi-electrode arrays (MEAs) has grown rapidly over the past decade. MEA devices are now widely used to measure the activity of neuronal cultures, primarily derived from rodents. Rodent neuron cultures on MEAs have been used to study physiological mechanisms, investigate the role of chemicals in neurotoxicity screening, and simulate the electrophysiological phenotypes of neuronal networks under different pathological conditions.

[0060] Patent terminology:

[0061] MEMS manufacturing processes mainly include surface micromachining, bulk micromachining, and LIGA technology. Surface micromachining utilizes methods such as thin film deposition, photolithography, and etching to construct microstructures by adding material layer by layer onto a substrate and finally removing the sacrificial layer.

[0062] Micro-pattern stamping technology is a technique that uses flexible stamping to transfer micro-graphics from the surface of a stamp onto a flat substrate. This technology typically uses a flexible stamp with surface adhesion, which transfers the pattern onto the target substrate through the micro-graphics on its surface. Flexible stamps are usually composed of a thin layer of silicone and encapsulated on the back with quartz glass of low coefficient of thermal expansion to provide rigid support.

[0063] The EM algorithm is an optimization algorithm based on the theory of Maximum Likelihood Estimation (MLE). Given mutually independent observation data and a probability model containing latent variables and parameters, according to MLE theory, the optimal single-point estimate of the parameters is given when the likelihood of the probability model reaches its maximum value.

[0064] Peak-to-peak interval refers to the time elapsed between the maximum value of a peak and the maximum value of the next peak.

[0065] Crest energy refers to the energy integral from the left extreme point to the right extreme point of the wave crest.

[0066] SEM images are images acquired using a scanning electron microscope (SEM).

[0067] Titanium aluminum carbide (Ti3AlC2) is a ceramic material belonging to the MAX phase (M represents a metallic element, A represents a main group element, and X represents carbon or nitrogen).

[0068] This application provides a method for constructing a neural probe and an array culture chip, as well as a method and device for evaluating neurophysiological toxicity, which solves the technical problems of high cost, long time consumption, and complex construction of existing neurotoxicity testing models.

[0069] Example 1:

[0070] Figure 1 is a flowchart of the construction method based on neural probes and array culture chips according to an embodiment of this application.

[0071] As shown in Figure 1, this application provides a method for constructing a neural probe and an array culture chip, including the following steps:

[0072] S1. Obtain the substrate material, probe material, and chip circuit layout. Based on the substrate material, probe material, and chip circuit layout, use traditional microelectromechanical system (MEMS) manufacturing stripping process and micropattern stamping technology to construct a chip substrate with arrayed neural probes.

[0073] It should be noted that in step S1, materials for fabricating neural probes and array culture chips are first obtained. Then, traditional microelectromechanical systems (MEMS) fabrication lift-off processes and micropatterning techniques are used to fabricate the obtained materials to obtain a chip substrate with array neural probes. In this embodiment, the substrate material can be glass, silicon wafers, etc. The probe material can be MXene, a two-dimensional semiconductor material with a wide bandgap, high sensitivity, and good biocompatibility.

[0074] Figure 2 is a schematic diagram of the structure of the multi-channel neural cell culture chamber in the construction method based on neural probes and array culture chips described in the embodiments of this application.

[0075] S2. Construct a multi-channel neural cell culture chamber corresponding to the array neural probes on the chip substrate to obtain a multi-channel chip with neural probes and array culture; the multi-channel neural cell culture chamber is connected to the electrodes of the chip substrate. As shown in Figure 2, the construction of the multi-channel neural cell culture chamber corresponding to the array neural probes on the chip substrate includes: processing the chip substrate using a traditional microelectromechanical system (MEMS) fabrication stripping process to obtain the multi-channel neural cell culture chamber; the multi-channel neural cell culture chamber includes an inlet / outlet (INLET / DRAIN), a cell seeding layer (SOURCE), a gradient layer (STEPNESS), and multiple culture chamber cells corresponding to the array neural probes. The inlet / outlet (INLET / DRAIN) is connected to the gradient layer (STEPNESS). The cell seeding layer (SOURCE) is located above each culture chamber cell, and the gradient layer (STEPNESS) is located below all culture chamber cells. The gradient layer (STEPNESS) is connected to the electrodes of the chip substrate.

[0076] It should be noted that in step S2, a multi-channel neural cell culture chamber is constructed on the chip substrate built in step S1. This integrates an ultra-thin neural probe array with an array-type culture chamber layer, forming a complete multi-channel chip. This multi-channel chip can achieve high-throughput detection of neurophysiological toxicity. The entire process from neural cell culture to toxicity detection can be automated and achieved with high throughput on this multi-channel chip. Compared with existing neurotoxicity testing technologies, which are expensive, time-consuming, and complex to construct, this method based on neural probes and array culture chips significantly reduces testing costs, time, and complexity by using a constructed multi-channel chip for high-throughput detection of neurophysiological toxicity.

[0077] Figure 3 is a schematic diagram of the multi-channel chip used for neurotoxicity testing in the construction method based on neural probes and array culture chips described in the embodiments of this application. In Figure 3a, it refers to the construction of a high-throughput concentration gradient of the compound to be tested; in Figure 3b, it refers to the high-throughput determination of the compound's influence on neural migration, neural axon dendrites, and other properties.

[0078] As shown in Figure 2, in this embodiment, the cell seeding layer (SOURCE) is used to seed cells and define the range of the culture solution; and / or, the inlet / outlet (INLET / DRAIN) is used to introduce chemical molecules into the gradient layer (STEPNESS); the gradient layer (STEPNESS) is used to diffuse the introduced chemical molecules to construct a horizontal gradient in the XY plane, so as to provide a gradually decreasing concentration of input chemical molecules to each culture chamber cell. The culture chamber cells are made of scaffold or hydrogel material, and the thickness of the culture chamber cells is 250 µm; and / or, the thickness of the gradient layer (STEPNESS) is 400 µm.

[0079] It should be noted that the multichannel neural cell culture chamber includes an array of cell culture chamber layers corresponding to the array of neural probes, a gradient layer of target chemicals (STEPNESS), a cell seeding layer (SOURCE), and an inlet / outlet (INLET / DRAIN). Each layer of the multichannel neural cell culture chamber is fabricated into a specific dimethylsiloxane (PDMS) structure using microelectromechanical systems (MEMS) technology. The multichannel neural cell culture chamber is then assembled onto a chip substrate with an array of neural probes, completing the construction of an electrophysiological array chip (such as a multichannel chip) for a multichannel independent neural microsystem. In this embodiment, as shown in Figure 3, an n×n (e.g., 8×8) matrix of culture chamber layers (CELL) is designed first, based on the reserved positions of the ultrathin neural probes in the chip substrate. The array of culture chamber layers (CELL) consists of 64 hollow cylinders with a diameter of 2000µm. The PDMS structure is replicated from a micropatterned SU-8 (Microchem) layer group on the chip substrate (such as a silicon wafer). A cell seeding layer (SOUCE) is then constructed on the culture chamber layers (CELL) for planting cells and defining the range of the culture solution. The bottom gradient layer, STEPNESS, sets the inlet / outlet for introducing chemical molecules. With a height of approximately 400µm, the STEPNESS ensures that molecules establish a horizontal gradient in the XY plane only through diffusion, providing a gradually decreasing input concentration within each culture chamber cell. This multi-channel chip, through its multi-channel neural cell culture chambers, can test dozens of different gradient steepnesses (along the X-axis) and multiple repetitions (along the Y-axis), significantly improving the detection efficiency of compound toxicity using multi-channel chips. This high-throughput capability of the multi-channel chip is crucial for screening a wide range of compound neurotoxicities, overcoming the limitations of traditional MEA technology, which, while capable of multi-channel recording, often suffers from limited drug concentration settings and inconvenient gradient concentration settings. This method of constructing a neural probe and array culture chip uses materials such as three-dimensional scaffolds or hydrogels to fabricate the culture chamber cells, allowing them to simulate the in vivo neuronal growth environment and promote the formation of more complex network structures. This enhances the physiological relevance of the detection results for compound toxicity testing using this multi-channel chip.

[0080] This application provides a method for constructing a chip based on neural probes and an array culture chip, including obtaining a substrate material, probe material, and chip circuit layout; processing the substrate material, probe material, and chip circuit layout using a traditional microelectromechanical system (MEMS) fabrication stripping process and micropattern stamping technology to construct a chip substrate with array neural probes; constructing multi-channel neural cell culture chambers corresponding to the array neural probes on the chip substrate to obtain a multi-channel chip with neural probes and array culture; connecting the multi-channel neural cell culture chambers to the electrodes of the chip substrate; wherein, constructing the multi-channel neural cell culture chambers corresponding to the array neural probes on the chip substrate includes: processing the chip substrate using a traditional MEMS fabrication stripping process to obtain the multi-channel neural cell culture chambers; the multi-channel neural cell culture chambers include an inlet / outlet, a cell seeding layer, a gradient layer, and multiple culture chamber layers corresponding to the array neural probes, the inlet / outlet being connected to the gradient layer, the cell seeding layer being positioned above each culture chamber layer, the gradient layer being positioned below all culture chamber layers, and the gradient layer being connected to the electrodes of the chip substrate. This method for constructing a neural probe and array culture chip integrates an ultrathin neural probe array with an array-shaped culture chamber layer by building a multi-channel neural cell culture chamber on a chip substrate composed of arrayed neural probes. This results in a complete multi-channel chip that enables high-throughput detection of neurophysiological toxicity. The multi-channel chip achieves full automation and high throughput from neural cell culture to toxicity detection, thereby significantly reducing testing costs, time, and complexity. It also solves the technical problems of existing neurotoxicity testing models, such as high cost, long time consumption, and complex construction.

[0081] Figure 4 is a schematic diagram of the chip substrate with arrayed neural probes in the construction method based on neural probes and arrayed culture chips according to an embodiment of this application. Figure 5 is a schematic diagram of the neural probe signal acquisition in the construction method based on neural probes and arrayed culture chips according to an embodiment of this application. Figure 6 is a schematic diagram of the neural probe signal acquisition in the construction method based on neural probes and arrayed culture chips according to an embodiment of this application. In Figure 4, a refers to the SEM image of the multilayer MXene structure; b refers to the XRD pattern of the titanium Ti transition from 3AlC2 to Ti3C2Tx; c refers to a schematic diagram of the biosensing device based on MXene field-effect transistors. In Figure 5, a refers to a schematic diagram of the working principle of using MXene-FET field-effect devices to detect action potentials; the left image of b refers to the fluorescence image of neurons stained with βIII-tubulin immunostaining; the right image of b refers to the combined image of bright field and fluorescence channels, showing good compatibility between neuronal cells and MXene micromodes. Scale bar, 100 μm; c indicates that the arrayed neural probes on the chip substrate have higher temporal resolution compared with traditional calcium imaging technology.

[0082] As shown in Figures 4 to 6, in one embodiment of this application, a chip substrate with an array of neural probes is constructed by processing the substrate material, probe material, and chip circuit layout using a conventional microelectromechanical system (MEMS) fabrication stripping process and micropattern stamping technology.

[0083] Based on the chip circuit layout, an n×n array electrode circuit layout is fabricated on the substrate material using a traditional microelectromechanical system (MEMS) fabrication stripping process to obtain a substrate with neural probe assembly positions; and a solution method is used to synthesize the probe material to obtain the neural probe.

[0084] The substrate to be modified is obtained by using a silanizing coupling agent;

[0085] By employing micropattern stamping technology, neural probes are printed at each assembly position of the neural probes on the substrate to be printed, resulting in a chip substrate with an array of neural probes.

[0086] It should be noted that the chip circuit layout employs a traditional micro-electro-mechanical system (MEMS) lift-off process. Two-dimensional semiconductor material MXene was prepared using solution methods (HF and HCl+LiF etching) to synthesize the probe body. The MXene samples were characterized using scanning electron microscopy (SEM) and X-ray diffraction (XRD), as shown in Figures 4a and 4b. Neural probe fabrication first required modification of the substrate with a silanizing coupling agent, followed by micropatterning to print the neural probe array onto the substrate, completing the array neural probe construction. An MXene-based field-effect transistor device was used to monitor spike activity in cultured primary hippocampal neurons in real time, as shown in Figure 5a. After action potential excitation, neurotransmitters are released and subsequently bind to the MXene surface to induce electrical signal fluctuations. Due to the ultrathin thickness (≈5nm) of the MXene micropatterns, the device is almost transparent, as shown in Figure 5b, thus unaffected by conventional microscopic observation. This multichannel chip exhibits excellent temporal resolution via neural probes because it captures spikes that are unobservable in calcium imaging due to the slow dynamics (approximately one hundred milliseconds) of calcium signal transduction in neuronal cells, as shown in Figure 5c. In this embodiment, the multichannel chip constructed using this neural probe and array culture chip construction method further enhances the chip's sensitivity by employing a field-effect transistor-based neural probe design. n is a non-zero natural number.

[0087] As shown in Figure 6, in the embodiments of this application, the construction method based on neural probes and array culture chips can select appropriate substrate materials (such as glass or silicon wafers) according to the optical requirements of detection and the performance requirements of field-effect transistors. The microelectrode circuit layout of an n×n (e.g., 8×8) array is completed using traditional MEMS lift-off technology, with approximately 300×300μm of space reserved for neural probe assembly. After surface hydroxyl modification of the substrate to be modified, 3-aminopropyltriethoxysilane (APTES) modification is immediately performed. The substrate to be printed is designed and microfabricated using photolithography, and a dimethylsiloxane (PDMS) circuit stamp is molded. An MXene field-effect transistor probe matrix is ​​then printed on the modified substrate using MXene micro-stamping technology, as shown in Figure 6.

[0088] It should be noted that this method for constructing neural probes and array culture chips significantly improves the detection sensitivity of multi-channel chips for neurophysiological signal detection by using ultrathin neural probes with field-effect transistor (FET) designs and combining them with the two-dimensional semiconductor material MXene. This enables the capture of even weaker and more subtle changes in neural signals. The method utilizes the high conductivity and small size of carbon nanotubes, a two-dimensional semiconductor material, to fabricate ultrathin neural probes, further enhancing the spatial resolution and signal sensitivity of multi-channel chip detection. Combining this multi-channel chip with optical and / or electrical detection technologies allows for the monitoring of neural activity using optical signals transmitted via fiber optics.

[0089] Example 2:

[0090] Figure 7 is a flowchart of the steps of the neurophysiological toxicity assessment method based on neural probes and array culture chips according to an embodiment of this application, and Figure 8 is a flowchart of the neurophysiological toxicity assessment method based on neural probes and array culture chips according to an embodiment of this application.

[0091] As shown in Figures 7 and 8, embodiments of this application provide a method for assessing neurophysiological toxicity based on neural probes and array culture chips, including the following steps:

[0092] S01. Obtain the multi-channel chip constructed using the above-described method based on neural probes and array culture chips.

[0093] It should be noted that the construction method based on neural probes and array culture chips has been described in Example 1, and will not be repeated in this example. In step S01, the first step is to obtain a multi-channel chip constructed using the neural probe and array culture chip construction method. The multi-channel chip includes an array of neural probes and a multi-channel neural cell culture chamber. Assembling the array of neural probes and the multi-channel neural cell culture chamber completes the construction of a multi-channel high-throughput neurophysiological toxicity detection chip, providing a detection hardware platform for subsequent toxicity detection of the target compound. This toxicity detection hardware platform is easy to construct and operate, simplifying the experimental procedure for neurotoxicity testing.

[0094] S02. Construct gradient target compounds within a multi-channel chip, and collect and classify the neurophysiological signals generated by neural probes for different gradient exposure concentrations of the gradient target compounds to obtain the collected data; the neurophysiological signals include action potential signals and local field potential signals.

[0095] It should be noted that in step S02, a gradient target compound is constructed within the multi-channel chip built in step S01. For example, the gradient curve of the target compound is used to acquire high-throughput data such as the frequency, amplitude, and phase resonance of the action potential of the nerve signal through the gradient curve of the target compound. This achieves high-throughput acquisition of the neurophysiological signal of the target compound, providing data for subsequent analysis of the toxicity level of the acquired data and the neurophysiological toxicity assessment criteria. The acquired data is based on changes in neurophysiological signals, which improves the accuracy of data for comprehensively assessing the impact of the neurotoxicity of the test compound on the nervous system function, and improves the sensitivity and accuracy of the assessment.

[0096] S03. Obtain neurotoxicity standards, analyze the collected data according to the neurotoxicity standards, and obtain the toxicity level and neuroelectrophysiological toxicity assessment standards corresponding to the gradient target compounds.

[0097] It should be noted that in step S03, firstly, neurotoxicity standards are obtained, such as traditional neurodevelopmental toxicity testing methods based on experimental animals (e.g., OPPTS 870.6300) and TG426 issued by the OECD. Secondly, neurotoxicity thresholds and their grading systems are defined according to the neurotoxicity standards, that is, clarifying what level of electrophysiological abnormality can serve as an indicator of a chemical substance's neurotoxicity, and establishing standards to quantify its toxicity severity. Next, based on determining the minimum toxicity exposure concentration at which common neurotoxic substances induce toxic effects, and further investigating the changing patterns of neurotoxicity levels at different concentrations by collecting data from different gradient exposure concentrations in step S02, toxicity levels and neuroelectrophysiological toxicity assessment standards corresponding to the gradient target compounds are obtained. In this embodiment, neurotoxic substances with known neurotoxicity standards are mainly graded for toxicity based on their minimum toxic dose or lethal dose, and electrophysiological toxicity is calibrated based on their electrophysiological response characteristics, thereby constructing a novel electrophysiological toxicity assessment standard and its toxicity grading. For example, by constructing different gradient exposure concentrations of a target compound within a single multichannel chip, high-throughput acquisition and evaluation of neurophysiological responses at different exposure concentrations can be performed in real time. The toxicity level of the substance can be determined based on the grade range of electrophysiological impairment / changes falling within different gradient exposure concentrations. Simultaneously, based on the analysis of the constructed concentration gradient curves, the minimum toxic exposure concentration of the compound and the degree of neurotoxicity produced at different concentrations can be determined. Here, gradient exposure concentration refers to the concentration of the chemical molecule of the test compound introduced into the culture chamber cell. Exposure concentration parameters include the type and concentration of the compound.

[0098] In this embodiment, the neurophysiological toxicity assessment method based on neural probes and array culture chips explores and records the relationship between different levels of toxic chemicals and neurophysiological responses by referencing and rating known neurotoxic substances, and extracts and constructs novel neurophysiological toxicity assessment and toxicity grading standards. This method uses the neurophysiological signals output by the neural probes of a multi-channel chip as terminal functional signals of the brain's neural network. By monitoring and analyzing parameters such as the frequency, amplitude, and phase resonance of the neural action potentials in the neurophysiological signals, it provides a basis for neurotoxicity assessment, enabling qualitative and quantitative assessment of the neurotoxicity of the test compound, and improving the sensitivity and accuracy of the assessment.

[0099] It should be noted that this neurophysiological toxicity assessment method based on neural probes and array culture chips uses array neural probes and array culture chambers of multi-channel chips to construct gradient target compounds of the test compounds, reducing experimental material consumption and animal use, and lowering testing costs. By collecting neurophysiological signals of test compounds with different gradient exposure concentrations output by array neural probes of multi-channel chips, the neurophysiological signals of test compounds are collected, and the collected data are analyzed to achieve rapid assessment of the neurotoxicity of a large number of compounds, improving testing efficiency and shortening the testing cycle.

[0100] Figure 9 is a schematic diagram of the array neural network construction in the neuroelectrophysiological toxicity assessment method based on neural probes and array culture chips described in the embodiments of this application. In Figure 9, a refers to primary hippocampal neural cell culture; b refers to neural network culture induced by neuroblastoma; and cf refers to the constructed neural microsystems that have been shown to possess active neuroelectrophysiological signals.

[0101] As shown in Figure 9, in one embodiment of this application, constructing a gradient target compound within a multichannel chip includes:

[0102] Establish an array neural network within a multi-channel chip;

[0103] The test compound and the set parameters for different gradient exposure concentrations are obtained. The test compound is then input into the array neural network according to the set parameters to obtain the gradient target compound.

[0104] The process of establishing an array neural network within a multi-channel chip includes: adding at least 80,000 neurons to a cell seeding layer for seeding; cells from the gravity-driven cell seeding layer falling into independent multi-channel culture chambers; and obtaining the array neural network after at least 3 weeks of cell seeding / induction in the culture chambers.

[0105] It should be noted that, due to the requirements of multi-channel chips for the electrophysiological characteristics of the nervous system, the neurotoxicity detection subject is a neural system with mature neurophysiological characteristics. This embodiment uses two test schemes as examples. Scheme A uses a primary hippocampal neural network as the array neural network, as shown in Figure 9a; Scheme B uses a neural network with electrophysiological characteristics induced from neuroblastoma as the array neural network, as shown in Figure 9b. Scheme A uses primary neural cells, preserving the biological characteristics of the original in vivo tissue, but the modeling cost is higher; Scheme B has the advantage of relatively low cost, but the neurotoxicity detection effect needs further verification in experiments. The constructed neural microsystem possesses active neurophysiological signals and can rapidly generate a large number of responses to the test compound, as shown in Figure 9cf. Scheme A is based on the hippocampus of fetal rats dissected from E18 Sprague Dawley rats under sterile conditions. The hippocampus is first washed, minced, digested with papain for 15 minutes, filtered through a 200-mesh filter, and cultured for three weeks. Primary neural cells are constructed using calcium imaging technology, and their neurophysiological activity is verified through primary neural cell testing. Option B involves inducing neuroblastoma cells in Brainphys medium with the addition of retinoic acid (RA) for three weeks, followed by calcium imaging to obtain a neural cell network, and then detecting neurophysiological activity through this network. The array neural network construction process can be understood as follows: 80,000 neurons are added to a cell seeding layer (SOURCE) and seeded into a culture chamber layer (CELL) containing suspended cells. Due to gravity, the cells from the SOURCE fall into multiple (e.g., 64) independent culture chamber layers. Three weeks after cell seeding / induction in the culture chamber layers, neurophysiological signals generated by gradient exposure to target compounds at different concentrations can be collected via neural probes.

[0106] In the embodiments of this application, obtaining the setting parameters for different gradient exposure concentrations of the test compound includes: adding the test compound to the NLET / DRAIN at the inlet / outlet and calculating the gradient exposure concentration of each channel according to the canonical diffusion equation. The setting parameters include the gradient exposure concentration of the gradient layer and the gradient exposure concentration of each culture chamber layer.

[0107] It should be noted that the test compounds include heavy metals such as lead, nitric oxide, and / or neurotoxic molecules such as tetrodotoxin. The canonical diffusion equation is based on the molecular diffusion coefficient, and the diffusion time and distance are calculated using the canonical diffusion equation to determine the gradient exposure concentration of each channel (e.g., each culture chamber layer). Calculating the gradient exposure concentration of each channel allows determination of the compound concentration exposed to cells in each channel, thereby enabling neurotoxicity assessment of different compound concentrations and identifying the minimum toxic dose or lethal dose. In this embodiment, a gradient layer STEPNESS is used to construct multiple channels with different set parameters, and the electrophysiological response characteristics of different concentrations of neurotoxicity in these channels are collected and analyzed. Specifically: After the array neural network is constructed, the test compound is added to the array neural network, and the gradient concentration of each channel is calculated according to the canonical diffusion equation. In the simulation of the 3D diffusion process, the 3D diffusion is simplified to two 1D models with the following assumptions: there is no magnetic flux along the Y direction in the bottom horizontal plane (source layer); the concentration change in the XY plane of the hydrogel cylindrical culture chamber layer is ignored; therefore, only flux along the Z direction exists in each cylindrical culture chamber layer. The culture chamber layer (drainage layer) is large enough that the total concentration in the chamber is unaffected by diffusion and remains close to zero during the experiment.

[0108] In this embodiment, diffusion in the bottom layer (gradient layer) is controlled by a conventional diffusion equation, which is:

[0109]

[0110] Diffusion within the cylindrical culture chamber is governed by a canonical diffusion equation, which is:

[0111]

[0112] In the formula, x is the distance of the analyte compound from the inlet of the multichannel chip, z is the distance of the analyte compound from the bottom of the culture chamber, D0 is the diffusion coefficient of the analyte compound in a low-viscosity solution (e.g., culture medium), n is the number of the culture chamber, and C... n C represents the gradient exposure concentration of the nth culture chamber layer. bottom The gradient exposure concentration is the gradient layer.

[0113] In one embodiment of this application, the neuroelectrophysiological signals generated by a neural probe at different gradient exposure concentrations of the target compound are collected and classified to obtain the collected data, including:

[0114] The acquired neurophysiological signals are amplified and bandpass filtered to obtain processed data;

[0115] The EM algorithm is used to perform spike sorting on the action potential signals of the processed data to obtain sorted signal data.

[0116] Obtain signal classification criteria, perform spike classification on signal data according to the signal classification criteria, and obtain classified data;

[0117] Electrophysiological features are extracted from each type of peak in the classification data to obtain the collected data consisting of the electrophysiological features of all peak classifications.

[0118] It should be noted that the signal classification criteria include the peak value, rise duration, and fall duration; and / or, electrophysiological characteristics include frequency, amplitude, resonance, duration, rise time, decay time, peak-to-peak interval, peak energy, signal center frequency, and information entropy. The neurophysiological signals from each channel of the multi-channel chip are amplified in situ by neural probes in each culture chamber layer, initially improving the signal-to-noise ratio of neural detection. The front-end amplification, filtering, and recording of the electrical signals rely on a commercial multi-channel neurophysiological signal acquisition system (Blackrock Microsystems Inc., Salt Lake City, UT) for processing. The acquired offline data is analyzed using neural signal waveform analysis and processing software. For example, real-time monitoring of action potential signals (APs) and local field potential signals (LFPs) in various channels of a multi-channel chip yields neurophysiological signals. These signals are amplified and bandpass filtered (1-5000Hz) by the corresponding channel's preamplifier. The action potential signals (APs) are spike-sorted using the t-dist EM algorithm of the Offline Sorter (Plexon, Inc.) built into the multi-channel chip, resulting in sorted signal data. The sorted LFP signals are then classified using a 250Hz offline digitization filter to obtain categorized data. Further offline analysis of the categorized data reveals various electrophysiological characteristics of the signals.

[0119] Figure 10 is a schematic diagram illustrating the ultrasensitivity and specificity of the neurophysiological response in the neurophysiological toxicity assessment method based on neural probes and array culture chips described in this application. In Figure 10, ad refers to the difference in action potential frequency of the nervous system under different conditions; df refers to the different gamma oscillation energies of neural networks under different neural conditions.

[0120] In this embodiment, the neurophysiological toxicity assessment method based on neural probes and array culture chips first involves planting cells in the cell seeding layer (SOURCE) of a multi-channel chip and recording their neurophysiological signals after three weeks of culture. Graded neurotoxins, such as lead, nitric oxide, and tetrodotoxin, are selected as test compounds. The neurotoxic chemical molecules of the test compounds are introduced into the gradient layer (STEPNESS) via the inlet (INLET) to set the exposure concentration parameters. The neurophysiological signals of each channel are acquired, and the response signals at different exposure concentrations in each channel are analyzed and compared with background signals from healthy nerves to determine the toxicity level. The neurophysiological toxicity threshold of the neurotoxicity standard is determined based on the magnitude of electrophysiological response damage or change at the minimum toxic dose of the neurotoxin (referencing the safe standard concentration of the substance), and serves as the assessment threshold for defining whether neurotoxicity exists. The minimum exposure concentration of the unknown toxic compound is determined by locating the minimum concentration in each channel where the change in electrophysiological response exceeds the toxicity threshold.

[0121] Example 3:

[0122] Figure 11 is a schematic diagram of the terminal device described in an embodiment of this application.

[0123] As shown in Figure 11, this application embodiment provides a terminal device, including a processor and a memory;

[0124] Memory is used to store program code and transfer the program code to the processor;

[0125] The processor is used to execute the above-described neurophysiological toxicity assessment method based on neural probes and array culture chips according to the instructions in the program code.

[0126] It should be noted that the processor is used to execute the steps in the above-described embodiment of a neurophysiological toxicity assessment method based on neural probes and array culture chips, according to the instructions in the program code. Alternatively, the processor executes the computer program to implement the functions of each module / unit in the above-described system / device embodiments.

[0127] For example, a computer program can be divided into one or more modules / units, one or more of which are stored in memory and executed by a processor to complete this application. One or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0128] Terminal devices can be computing devices such as desktop computers, laptops, handheld computers, and cloud servers. Terminal devices may include, but are not limited to, processors and memory. Those skilled in the art will understand that this does not constitute a limitation on the terminal device, which may include more or fewer components than illustrated, or combinations of certain components, or different components. For example, a terminal device may also include input / output devices, network access devices, buses, etc.

[0129] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (dSICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor, etc.

[0130] Memory can be an internal storage unit of a terminal device, such as a hard drive or RAM. Memory can also be an external storage device, such as a plug-in hard drive, smart memory card (SMC), secure digital card (SD) card, or flash card. Furthermore, memory can include both internal and external storage units. Memory is used to store computer programs and other programs and data required by the terminal device. Memory can also be used to temporarily store data that has been output or will be output.

[0131] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0132] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0133] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0134] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0135] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0136] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for constructing a neural probe and an array culture chip, characterized in that, The process includes the following steps: obtaining a substrate material, probe material, and chip circuit layout; processing the substrate material, probe material, and chip circuit layout using a traditional microelectromechanical system (MEMS) fabrication stripping process and micropattern stamping technology to construct a chip substrate with an array of neural probes; the probe material is a two-dimensional semiconductor material MXene; constructing a multi-channel neural cell culture chamber corresponding to the array of neural probes on the chip substrate to obtain a multi-channel chip with neural probes and array culture; the multi-channel neural cell culture chamber is connected to the electrodes of the chip substrate; wherein, constructing the multi-channel neural cell culture chamber corresponding to the array of neural probes on the chip substrate includes: processing the chip substrate using the traditional MEMS fabrication stripping process to obtain the multi-channel neural cell culture chamber; the multi-channel neural cell culture chamber includes an inlet / outlet, a cell seeding layer, a gradient layer, and an electrode connected to the array of neural probes. The multi-channel neural cell culture chamber comprises multiple culture chamber layers corresponding to the probes, with the inlet and outlet connected to the gradient layer. The cell seeding layer is positioned above each culture chamber layer, and the gradient layer is positioned below all culture chamber layers. The gradient layer is connected to the electrodes of the chip substrate. Each layer of the multi-channel neural cell culture chamber is fabricated into a specific dimethylsiloxane (PDMS) structure using microelectromechanical systems (MEMS) technology. The multi-channel neural cell culture chamber is then assembled onto the chip substrate with an array of neural probes, completing the construction of the multi-channel chip of the multi-channel independent neural microsystem. The cell seeding layer is used for seeding cells and defining the range of the culture solution. And / or, the inlet and outlet are used to introduce chemical molecules into the gradient layer. The gradient layer is used to diffuse the introduced chemical molecules to construct a horizontal gradient in the XY plane, thereby providing a gradually decreasing concentration of the input chemical molecules within each culture chamber layer.

2. The construction method based on neural probes and array culture chips according to claim 1, characterized in that, The process of constructing a chip substrate with an array of neural probes by using conventional microelectromechanical systems (MEMS) fabrication stripping technology and micropatterning technology on the substrate material, the probe material, and the chip circuit layout includes: fabricating an n×n array of electrode circuit traces on the substrate material using conventional MEMS fabrication stripping technology according to the chip circuit layout, to obtain a substrate to be modified with neural probe assembly positions; synthesizing the probe material using a solution method to obtain neural probes; modifying the substrate to be modified with a silanizing coupling agent to obtain a substrate to be printed; and printing the neural probes at each neural probe assembly position on the substrate to be printed using the micropatterning technology to obtain a chip substrate with an array of neural probes.

3. The construction method based on neural probes and array culture chips according to claim 1 or 2, characterized in that, The culture chamber layer is made of a scaffold or hydrogel material, and the thickness of the culture chamber layer is 250µm; and / or, the thickness of the gradient layer is 400µm.

4. A method for assessing neurophysiological toxicity based on neural probes and array culture chips, characterized in that, Includes the following steps: A multi-channel chip is constructed using the method described in any one of claims 1-3, based on neural probes and array culture chips. A gradient target compound is constructed within the multi-channel chip. Neurophysiological signals generated by the neural probe at different gradient exposure concentrations of the gradient target compound are collected and classified to obtain collected data. The neurophysiological signals include action potential signals and local field potential signals. A neurotoxicity standard is obtained, and the collected data is analyzed according to the neurotoxicity standard to obtain the toxicity level and neurophysiological toxicity assessment standard corresponding to the gradient target compound.

5. The method for assessing neurophysiological toxicity based on neural probes and array culture chips according to claim 4, characterized in that, Constructing a gradient target compound within the multi-channel chip includes: establishing an array neural network within the multi-channel chip; acquiring set parameters for the test compound and different gradient exposure concentrations; inputting the test compound into the array neural network according to the set parameters to obtain the gradient target compound; wherein, establishing the array neural network within the multi-channel chip includes: adding at least 80,000 neurons to a cell seeding layer for seeding; the cells in the cell seeding layer will fall into multi-channel independent culture chamber layers by gravity; and obtaining the array neural network after at least 3 weeks of cell seeding / induction in the culture chamber layers.

6. The method for assessing neurophysiological toxicity based on neural probes and array culture chips according to claim 5, characterized in that, The test compounds include heavy metal lead, nitric oxide and / or neurotoxic chemical molecules such as tetrodotoxin.

7. The method for assessing neurophysiological toxicity based on neural probes and array culture chips according to claim 4, characterized in that, The process involves collecting and classifying neurophysiological signals generated by a neural probe at different exposure concentrations of the target compound. The collected data includes: amplifying and bandpass filtering the collected neurophysiological signals to obtain processed data; using the EM algorithm to sort the action potential signals of the processed data into peaks to obtain sorted signal data; acquiring signal classification criteria and classifying the signal data into peaks according to the criteria to obtain classified data; and extracting electrophysiological features from each type of peak in the classified data to obtain collected data consisting of the electrophysiological features of all peak classifications.

8. The method for assessing neurophysiological toxicity based on neural probes and array culture chips according to claim 7, characterized in that, The signal classification criteria include the peak value of the spike, the rise duration, and the fall duration; And / or, the electrophysiological characteristics include frequency, amplitude, resonance, duration, rise time, decay time, peak-to-peak interval, peak energy, signal center frequency, and information entropy.

9. A terminal device, characterized in that, It includes a processor and a memory; the memory is used to store program code and transmit the program code to the processor; the processor is used to execute the neurophysiological toxicity assessment method based on neural probes and array culture chips as described in any one of claims 4-8 according to the instructions in the program code.

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