CN-122017154-A - Automatic anti-sugar biological molecule activity detection method and system

CN122017154ACN 122017154 ACN122017154 ACN 122017154ACN-122017154-A

Abstract

The invention discloses an automatic anti-sugar biomolecule activity detection method and system, which relate to the field of automatic anti-sugar biomolecule activity detection and are used for realizing the improvement of the reliability of detection results, and comprise the steps of acquiring initial state characteristic data of biomolecules in a sample and transportation and processing process information of the sample; the transportation and processing process information comprises the collection time of a sample and a temperature change curve in the transportation process, the activity state of biomolecules in the sample is estimated based on the initial state characteristic data and the transportation and processing process information, a biomolecule activity detection strategy is adjusted according to the activity state of the biomolecules in the sample, and the adjusted biomolecule activity detection strategy is executed and a biomolecule activity detection result is output.

Inventors

CONG FENGSONG
LIU QINGHUA
LI XINGHUA

Assignees

不老莓生命技术(上海)有限公司

Dates

Publication Date: 20260512
Application Date: 20260331

Claims (10)

1. An automated anti-glycobiomolecule activity assay method comprising: Acquiring initial state characteristic data of biomolecules in a sample and transportation and processing process information of the sample, wherein the transportation and processing process information comprises acquisition time of the sample and a temperature change curve in a transportation process; Evaluating the activity status of biomolecules in the sample based on the initial status feature data and the transportation and handling process information; adjusting a biomolecule activity detection strategy according to the activity state of the biomolecules in the sample; Executing the adjusted biological molecule activity detection strategy and outputting a biological molecule activity detection result.
2. The automated anti-glycobiomolecule activity detection method of claim 1, wherein the assessing the activity status of the biomolecules in the sample based on the initial status feature data and the transportation and handling process information comprises: Dividing the sample into a first and a second sub-sample; Carrying out sensor scanning on the first sub-sample to generate first characteristic data; injecting a chemical reagent into the second sub-sample, and scanning the sensor to generate second characteristic data; determining interfering substances and corresponding contributions thereof according to the first characteristic data and the second characteristic data; Stripping the influence of the interfering substance from the initial state characteristic data according to the interfering substance and the corresponding contribution thereof, and reducing the real signal of the target anti-glycobiomolecule; Based on the actual signal of the target anti-glycobiomolecule and the transport and handling process information, the active status of the biomolecule in the sample is assessed.
3. The automated anti-glycobiomolecule activity detection method of claim 2, wherein the injecting the chemical reagent into the second sub-sample and scanning the sensor to generate second characteristic data comprises: Dividing the second sub-sample injected with the chemical reagent into two micro-sub-samples to obtain a first micro-sub-sample and a second micro-sub-sample; carrying out sensor scanning on the first trace sample to generate processed biomolecule state characteristic data; performing target anti-glycobiomolecule removal treatment on the second trace sample, and performing sensor scanning to generate chemical reagent influence characteristic data; and subtracting the characteristic data of the influence of the chemical reagent from the characteristic data of the state of the processed biological molecule to obtain the second characteristic data.
4. An automated anti-glycobiomolecule activity detection method according to claim 3, wherein the performing a target anti-glycobiomolecule removal treatment on the second trace sample and performing a sensor scan generates chemical reagent influence characteristic data comprising: the micro physical separation module is integrated with a microfluidic channel of a nano-pore membrane, the pore diameter of the nano-pore membrane is preset to be smaller than the hydrodynamic diameter of the target anti-sugar biomolecules, and the pore diameter of the nano-pore membrane is preset to be larger than the hydrodynamic diameters of the chemical reagent and the interfering substances, so that the target anti-sugar biomolecules are selectively filtered and removed from the second micro-molecular sample; Detecting the conductivity change rate of the effluent liquid through a conductivity sensor inside the miniature physical separation module; And when the conductivity change rate is smaller than a preset threshold value, performing sensor scanning on the filtered second trace sub-sample to generate the chemical reagent influence characteristic data.
5. The automated anti-glycobiomolecule activity detection method of claim 4, further comprising: detecting the optical density, pH, and concentration of a particular ion of the second sample of micro-ions prior to filtering the second sample of micro-ions; and dynamically adjusting the preset threshold according to the optical density, the pH value and the concentration of the specific ions.
6. The automated anti-glycobiomolecule activity detection method of claim 4, further comprising: when the conductivity change rate is greater than or equal to the preset threshold, judging that the target anti-sugar biomolecules are not sufficiently removed; After the insufficient removal of the target anti-sugar biomolecules is judged, a self-checking program is started, wherein the self-checking program comprises the steps of detecting the working state of the conductivity sensor, and detecting the delay and the packet loss rate of a communication link, wherein the working state comprises a calibration parameter and response time; Generating a system state report based on the result of the self-checking program; when any parameter in the system state report exceeds a system health threshold, adjusting internal parameters to carry out self-adaptive correction, wherein the internal parameters comprise driving voltage or pulse duration of a micro piezoelectric pump, the micro piezoelectric pump is used for periodically generating fluid pulses so as to prevent the nanopore membrane from being blocked and promote the passage of the target anti-glucose biomolecules, and the parameters in the system state report comprise the working state of a conductivity sensor, delay of a communication link and packet loss rate.
7. The automated anti-glycobiomolecule activity detection method of claim 6, further comprising: Acquiring a preset initial system health threshold; Acquiring historical performance data of an automatic anti-sugar biomolecule activity detection system, wherein the historical performance data comprises performance drift trend, performance data at different environmental temperatures and response characteristics when different sample matrixes are processed; acquiring current environment information, wherein the environment information comprises temperature and humidity information; And adjusting an initial system health threshold according to the historical performance data and the current environment information to obtain the system health threshold.
8. An automated anti-glycobiomolecule activity detection method according to claim 2, wherein the assessing the status of the activity of the biomolecules in the sample based on the actual signal of the target anti-glycobiomolecule and the transportation and handling process information comprises: Determining fingerprint deviation degree according to Euclidean distance between the real signal of the target anti-glycobiomolecule and pre-stored reference data; determining a logistics influence assessment index according to the transportation and treatment process information, wherein the logistics influence assessment index is used for assessing the influence of the transportation and treatment process information on the activity state of the biological molecules; and evaluating the activity state of the biological molecules in the sample according to the fingerprint deviation degree and the logistics influence evaluation index.
9. The automated anti-glycobiomolecule activity detection method of claim 8, wherein the assessing the status of the activity of the biomolecules in the sample based on the fingerprint bias and the logistic impact assessment index comprises: carrying out weighted summation on the fingerprint deviation degree and the logistics influence evaluation index to obtain an activity state score; and evaluating the activity state of the biomolecules in the sample according to the activity state scores and the activity mapping relation, wherein the activity mapping relation comprises the corresponding relation between different activity state scores and different activity states.
10. An automated anti-glycobiomolecule activity detection system, the system comprising: the system comprises an initial state characteristic data acquisition module, a transport and processing process information acquisition module and a storage module, wherein the initial state characteristic data acquisition module is used for acquiring initial state characteristic data of biomolecules in a sample and transport and processing process information of the sample, and the transport and processing process information comprises acquisition time of the sample and a temperature change curve in the transport process; An activity state assessment module for assessing the activity state of biomolecules in the sample based on the initial state characteristic data and the transportation and processing process information; The detection strategy adjustment module is used for adjusting a biological molecule activity detection strategy according to the activity state of biological molecules in the sample; and the detection execution and result output module is used for executing the adjusted biomolecule activity detection strategy and outputting the biomolecule activity detection result.

Description

Automatic anti-sugar biological molecule activity detection method and system Technical Field The invention relates to the field of automatic anti-sugar biological molecule activity detection, in particular to an automatic anti-sugar biological molecule activity detection method and system. Background Traditional existing automatic anti-glycobiomolecule activity detection systems often face challenges of loss of activity or structural change of the biomolecules to be detected during sample collection, transportation, storage and internal processing of the systems. At the same time, the reagents on which the system depends may also gradually decay during use. Existing automated systems often lack the ability to sense and adaptively adjust these biochemical changes in real time, resulting in an affected accuracy of the test results and clinical guidance value. Disclosure of Invention The application discloses an automatic anti-sugar biomolecule activity detection method and system, and aims to solve the technical problems that the accuracy of detection results and clinical guidance value are affected due to the loss of biomolecule activity or structural change, attenuation of reaction reagents and the like in the processes of sample collection, transportation, storage and internal processing of the existing automatic anti-sugar biomolecule activity detection system. In a first aspect, the application discloses an automated anti-glycobiomolecule activity detection method comprising the steps of: The method comprises the steps of obtaining initial state characteristic data of biomolecules in a sample and transportation and processing process information of the sample, wherein the transportation and processing process information comprises the collection time of the sample and a temperature change curve in the transportation process, evaluating the activity state of the biomolecules in the sample based on the initial state characteristic data and the transportation and processing process information, adjusting a biomolecule activity detection strategy according to the activity state of the biomolecules in the sample, executing the adjusted biomolecule activity detection strategy, and outputting a biomolecule activity detection result. Optionally, evaluating the activity status of the biomolecules in the sample based on the initial status feature data and the transportation and handling process information, comprising: dividing the sample into a first sub-sample and a second sub-sample; Carrying out sensor scanning on a first part of sub-samples to generate first characteristic data; Injecting a chemical reagent into the second sub-sample, and scanning the sensor to generate second characteristic data; Determining interfering substances and corresponding contributions thereof according to the first characteristic data and the second characteristic data; Stripping the influence of the interfering substances from the initial state characteristic data according to the interfering substances and the corresponding contributions thereof, and reducing the real signal of the target anti-glycobiomolecule; Based on the actual signal and the transport and handling process information of the target anti-glycobiomolecules, the activity status of the biomolecules in the sample is assessed. Optionally, injecting a chemical reagent into the second sub-sample and scanning the sensor to generate second characteristic data, including: Dividing the second sub-sample injected with the chemical reagent into two micro-sub-samples to obtain a first micro-sub-sample and a second micro-sub-sample; carrying out sensor scanning on the first trace sample to generate processed biomolecule state characteristic data; Performing target anti-sugar biomolecule removal treatment on the second trace sample, and performing sensor scanning to generate chemical reagent influence characteristic data; And subtracting the characteristic data of the influence of the chemical reagent from the characteristic data of the state of the processed biomolecules to obtain second characteristic data. Optionally, performing a target anti-glycobiomolecule removal process on the second trace sample and performing a sensor scan to generate chemical agent influence characteristic data, including: The micro physical separation module is integrated with a micro-fluidic channel of a nano-pore membrane, the pore diameter of the nano-pore membrane is preset to be smaller than the hydrodynamic diameter of the target anti-sugar biological molecules, and the pore diameter of the nano-pore membrane is preset to be larger than the hydrodynamic diameters of the chemical reagent and the interfering substances, so that the target anti-sugar biological molecules are selectively filtered and removed from the second micro-molecular sample; detecting the conductivity change rate of the effluent liquid through a conductivity sensor inside the miniature physical separation module; and when