CN-121534800-B - Non-targeting detection device, system and detection method based on nano holes

Abstract

The invention provides a non-targeting detection device, a system and a detection method based on nano holes, which are used for performing non-targeting detection on complex matrixes through the nano holes, extracting characteristics of a nano hole detection map, realizing classification of samples through constructing a model, the detection method does not predefine the target to be detected, but acquires various molecular information existing in serum by a net capturing method, realizes non-targeted capturing and overall state analysis of various molecules in serum, and provides a new quick and portable way for disease screening. By combining the nanopore technology and machine learning, the method breaks through the limitation of traditional single marker detection, and is hopeful to promote the development of accurate medical treatment to a more efficient and comprehensive direction.

Inventors

• TANG LONGHUA
• YANG YUXIN
• XU HONGXIA
• BAI HEXIANG
• Ma Haozhong
• WU JIAN

Assignees

• 浙江大学

Dates

Publication Date

20260512

Application Date

20260119

Claims (4)

1. 1. The non-targeting detection system based on the nanopores is characterized by comprising a detection module and an analysis module, wherein the detection module is used for detecting a sample by adopting a non-targeting detection device, the non-targeting detection device comprises the nanopores and a micro-channel sample pool, the micro-channel sample pool is used for collecting the sample and comprises a glass tube, the nanopores are arranged in the glass tube for detecting the sample, the aperture of the nanopores is 20-50 nm, the micro-channel sample pool comprises a glass tube with the inner diameter of 1.5 mm-2.5 mm and a support frame thereof, and the detection module is used for detecting the sample by adopting a positive and negative potential alternating method; The analysis module is used for analyzing the nanopore detection map obtained by the detection module, and realizing classification of the sample by extracting the characteristics and constructing a model, wherein the classification of the sample comprises any one or more of disease and health differentiation, differentiation of different disease types, pathogen identification and cancer typing.
2. 2. The non-targeted detection system of claim 1, wherein the support frame tilts the glass tube by an angle of 10-30 degrees, and further comprising an electrical control module comprising a working electrode, a reference electrode, a patch clamp amplifier, and a digital-to-analog converter.
3. 3. The non-targeted detection system of claim 1, further comprising a dilution of the sample, the dilution comprising any one or more of KCl, naCl, liCl, TE buffer, tris-HCl buffer, HEPES buffer, phosphate buffer.
4. 4. The non-targeted detection system of claim 1, wherein the features comprise four dimensional extracted feature parameters of time domain, frequency domain, time-frequency domain, and non-linear domain, and the sample comprises any one or more of serum, urine, tears, bile, cerebrospinal fluid, saliva, and body fluid.

Description

Non-targeting detection device, system and detection method based on nano holes Technical Field The invention relates to the technical field of biomedical detection, in particular to a non-targeting detection device and system based on nanopores and a detection method thereof. Background The generation and development of most diseases are accompanied by the appearance or concentration change of certain specific molecular markers, and detection of the disease-related molecular markers in complex body fluid matrixes such as serum is an effective method for early disease diagnosis. However, the concentration of molecular markers associated with early stages of disease is generally at very low levels, and the currently known partial markers are not highly specific (i.e., many molecular marker changes occur not only in a particular disease but may occur in a variety of diseases, even in normal physiological conditions). Although the detection accuracy can be greatly improved by combining multiple molecular markers for diagnosis, there are still multiple molecular markers which have not yet been clearly identified as having high specificity and high sensitivity, thereby directly affecting early diagnosis, accurate typing and effective treatment of diseases. The serum contains abundant disease related molecular information, including proteins, nucleic acids, metabolic small molecules and the like, and the comprehensive analysis of the serum has great significance for early screening, diagnosis and typing of diseases. At present, the detection of serum markers in clinic and laboratory mainly depends on the known specificity of specific molecular markers related to a certain disease to related diseases, and the specificity detection of one or more molecular markers related to the disease is respectively applicable to the detection of nucleic acid and protein molecular markers, for example, the traditional PCR and ELISA technologies are respectively applicable to the detection of the nucleic acid and protein molecular markers, the technology based on non-targeted histology adopts a full spectrum analysis strategy, and the composition and content changes of various molecular markers in different samples are represented by the difference of histology spectrums or spectrums, so that the rapid classification is realized by combining a machine learning algorithm. However, the method has the remarkable limitation that the PCR and ELISA of the specific detection molecular marker highly depend on the pre-definition and specific probe of the target, the single index detection of 'fishing type' can be only carried out, the unbiased global capture of the molecular population of the molecular marker with low specificity or undefined in serum can not be carried out, and important unexpected marker information is easily omitted. Even some emerging nanopore sequencing technologies focus on nucleic acid sequence analysis, and are difficult to directly apply to serum environments with complex components and high-salt, high-protein and other interference substances, and the molecular state spectrum of serum cannot be characterized on the whole. Therefore, the application of the method for respectively carrying out quantitative detection on the nucleic acid and protein molecular markers based on PCR and ELISA is limited to disease diagnosis of known markers, the detection sensitivity and flux are insufficient, and the method is often ineffective for disease detection scenes with undefined markers. The method of simultaneously detecting multiple types of molecular markers based on nanopores improves detection sensitivity and detection throughput, but is still limited by predictability of marker information. The method based on non-targeted histology combined with machine learning classification is an innovation of the traditional detection concept based on specific markers, and provides more comprehensive description of the overall state of the sample by incorporating other molecular information except for the known markers into an analysis model, however, histology technology often involves more complex sample marking and sample pretreatment, has long analysis flow, is relatively high in cost, and simultaneously has the problem of insufficient detection sensitivity. It is highly desirable to find a more portable, rapid and accurate method for non-targeted detection of complex samples, which can truly realize rapid and comprehensive molecular information capture of complex biological samples without predefining targets, and can perform effective qualitative analysis on the overall state. Disclosure of Invention Aiming at the problems in the prior art, the invention provides a non-targeting detection device, a system and a detection method based on a nanopore, wherein the system is based on a solid quartz nanopore device with a certain pore size and is used for detecting electrical signals of a complex human serum matrix. The detection t