57 results about "Disease mechanisms" patented technology

The invention relates to the technical field of biology, and discloses a construction method of a gastric cancer organoid culture system, which comprises the following steps: preparation of a conditioned medium: culturing L-WRN cells and collecting the conditioned medium; preparing a gastric cancer organoid culture medium, and mixing the conditioned culture medium, the basic culture medium, a plurality of growth factors and additives; and extraction and culture of organoid: separating cells from gastric cancer tissues, mixing the cells with matrigel, and culturing by using the prepared culture medium. According to the method, the repeatability and the stability of the organoid model are improved, the response consistency of the organoid in drug screening is improved, and the reliability of the model in disease mechanism research and personalized medical application is guaranteed.

The invention provides an ovarian cancer monitoring system based on iron metabolism related protein, comprising: an information monitoring module for monitoring iron metabolism protein index data and ovarian cancer core biomarker index data of a user; the abnormality determination module is used for comparing the iron metabolism protein index data and the ovarian cancer core biomarker index data with historical personal baselines of the current ovarian cancer development stage of the user, determining the variation amplitude, and triggering the ovarian cancer analysis module to perform analysis when the variation amplitude meets preset requirements; and the ovarian cancer analysis module is used for updating the ovarian cancer risk index grade based on the iron metabolism protein index data of the user and the ovarian cancer core biomarker data. According to the invention, the iron metabolism protein index is combined with the ovarian cancer core biomarker, and the biological characteristic of iron-dependent proliferation of the ovarian cancer cells is utilized, so that an index basis which is more suitable for a disease mechanism is provided for monitoring, and the possibility of early abnormality capture is improved.

This invention belongs to the field of vertebrate technology, specifically relating to a method for constructing a complex inflammatory animal model in middle-aged and elderly individuals and its related applications. The method includes: selecting adult animals for adaptive feeding, daily subcutaneous injection of D-galactose to establish a susceptibility to aging and oxidative stress, and administering sodium dextran sulfate (DSS) solution within a specific time window to induce intestinal inflammation, forming a complex inflammatory state through gut-hepatic axis interactions. The constructed animal model simultaneously exhibits intestinal inflammatory damage, abnormal hepatic oxidative stress, and aging-related characteristics, realistically simulating the pathological process of gut-hepatic axis dysfunction in middle-aged and elderly individuals. This model is suitable for screening and evaluating drugs, medical nutrition products, and functional foods that improve gut-hepatic axis dysfunction, providing a reliable technical platform for research on related disease mechanisms and the development of interventional substances.

The invention relates to the technical field of medical education and biological information visualization, in particular to a disease mechanism-associated protein structure and function visualization teaching virtual simulation system, which comprises a data storage module, a structure calling visualization module, a function-disease association module, an interactive operation module and a teaching evaluation module, all the modules interact through data interfaces. According to the protein structure and function visual teaching virtual simulation system associated with the disease mechanism, deep association of a protein three-dimensional structure, a function mechanism and a disease case is realized for the first time, the knowledge splitting barrier of traditional teaching is broken, and students are helped to construct a complete cognitive chain; autonomous operation and mutation simulation are supported, an abstract structure function relation is converted into an interactive visual model, the learning difficulty is remarkably reduced, and the knowledge absorption rate is increased; an experiment task and evaluation system is built in, a teaching closed loop of preview-operation-assessment-feedback is achieved, and the requirement for large-scale medical talent training is met.

The invention relates to the technical field of molecular immunology and biology, in particular to a sicca syndrome model mouse B cell immune repertoire sequencing and subpopulation analysis method. The method comprises the following steps: S1, sample preparation: preparing a single-cell suspension from a target autoimmune disease animal model and a preset tissue of a control animal, and carrying out B cell enrichment treatment on the single-cell suspension to obtain a B cell sample; s2, multi-dimensional data parallel analysis: analyzing the B cell sample, and performing parallel construction of the multi-dimensional data; and S3, integrated correlation analysis: carrying out correlation analysis on the immune group library data, the cell subset data and the signal channel data obtained in the step S2 to establish a correlation relationship among specific B cell cloning characteristics, specific B cell subset changes and specific signal channel activity, and carrying out multilevel analysis and generating a B cell immune response mechanism of the autoimmune disease. The efficiency and accuracy of disease mechanism research and drug action mechanism evaluation are remarkably improved.

The invention relates to the technical field of molecular biology and precision medical treatment, and relates to a molecular marker for predicting FOLFOX chemosensitivity and application thereof. A patient-derived colorectal cancer organoid biological sample library is constructed, the heterogeneity of in-vitro drug reaction is analyzed and evaluated through transcriptome, clinical groups sensitive to FOLFOX chemotherapy can be accurately recognized, a molecular marker prediction system containing 11 genes is obtained through further screening, and the molecular marker prediction system is used for predicting the FOLFOX chemotherapy. The method effectively overcomes the technical defect of lack of accurate prediction of colorectal cancer chemosensitivity at present, and has important value in the aspects of revealing disease mechanisms and guiding personalized treatment.

The system according to this embodiment aims to analyze gene expression data, predict disease mechanisms, and generate new research hypotheses. [Solution] The system according to the embodiment comprises an acquisition unit, an analysis unit, a prediction unit, a hypothesis generation unit, a treatment method proposal unit, and a report generation unit. The acquisition unit acquires gene expression data. The analysis unit analyzes the gene expression data acquired by the acquisition unit. The prediction unit predicts the disease mechanism based on the data analyzed by the analysis unit. The hypothesis generation unit generates a new research hypothesis based on the prediction results obtained by the prediction unit. The treatment method proposal unit proposes the optimal treatment method based on the hypothesis generated by the hypothesis generation unit. The report generation unit generates an experimental result as a report based on the treatment method proposed by the treatment method proposal unit.

The separation and detection method comprises the following steps: rinsing placenta or villus tissues in a PBS (Phosphate Buffer Solution) added with a 1% penicillin-streptomycin double antibody solution, digesting the placenta or villus tissues into single cells by using a 1640 culture medium containing I-type and IV-type collagenase after the placenta or villus tissues are rinsed sufficiently to obtain a cell suspension, and culturing the cell suspension for later use; diluting and neutralizing collagenase digestive juice by using a 1640 culture medium containing high-temperature heat-inactivated fetal calf serum according to 5 times of volume; repeatedly discarding the precipitate, recovering the supernatant, and centrifuging to obtain a coarse migration body; and establishing a density gradient by using Optiprep as a density medium, washing the precipitate with PBS, and centrifuging to obtain the trophoblast cell-derived transporter. The invention provides a group of placenta villus trophoblast cell source migration body specific expression membrane proteins for the first time, and provides a method for specifically capturing the placenta trophoblast source migration body on the basis of the placenta villus trophoblast cell source migration body specific expression membrane proteins, so that a new direction for researching a trophoblast dysfunction related disease mechanism can be enriched.

This invention relates to a method for disease therapeutic target discovery and drug prediction based on multi-omics networks and deep learning models, belonging to the interdisciplinary field of bioinformatics and artificial intelligence drug discovery. The method includes: integrating genomic expression profiles and common molecular interaction data from disease and control groups to construct a candidate whole-genome network; refining the network based on expression profile data through systematic modeling and the AIC criterion to obtain the real molecular interaction network; extracting the core network using the master network projection method and identifying key targets through pathway analysis; predicting candidate drugs interacting with the targets using a pre-trained deep neural network model; and finally screening potential therapeutic drugs based on multi-dimensional criteria such as regulatory ability, sensitivity, and toxicity. This invention achieves a complete integration from disease mechanism analysis to drug prediction, and is particularly suitable for complex diseases such as atopic dermatitis. It can systematically discover precise targets and efficiently predict repositionable drugs, significantly improving R&D efficiency.

The invention discloses a state recognition method of an adaptive gene editing laboratory mouse, and aims to solve the problem of insufficient state recognition specificity of the gene editing laboratory mouse in the prior art. The method comprises the following steps: acquiring genotypes, disease model types and experimental environment parameters of laboratory mice; optimizing detection and optical flow analysis parameters, generating a time sequence behavior track map and segmenting a key area; extracting general and pathological specific composite features and standardizing the general and pathological specific composite features; calling a genotype pathological feature association database to calibrate a weight and a threshold value, and inputting a random forest classifier recognition state of transfer learning optimization; scores are calculated through a weighted scoring model, the state is judged, and credibility is calculated through a multi-dimensional confidence evaluation model. The method is suitable for various gene editing laboratory mice and experimental environments, the accuracy and suitability of state recognition are improved, and powerful support is provided for gene therapy research and development and disease mechanism research.

The application discloses a virtual cell analysis platform based on cell disturbance data. The platform comprises three parts: a large language model data preprocessing system, a database and an online analysis platform, and a direction matching algorithm. The large language model data preprocessing system comprises an automatic data information extraction and retrieval tool, an automatic data file download tool, a large language model analysis engine and a gene expression data acquisition and feature extraction tool. The application can automatically preprocess the original data by applying the large language model data preprocessing system to the target scientific problem, and then store the data in the database. The characteristic direction matching algorithm is combined to output the drugs and key targets related to the target data set. The efficiency of target point and drug screening is improved. The application is suitable for large-scale omics data mining and disturbance analysis, accelerates the drug research and development, disease mechanism and translational medicine research process, and reduces the research and development cost.

The invention provides a biological sample system for clinical tests. Comprising a sample identification and tracking end, a sample acquisition and processing planning end and a sample storage and inventory management end. The biological sample system plays an important role in a clinical test, and the biological sample system for the clinical test ensures the quality and traceability of a sample and the reliability of data. According to the biological sample system for the clinical test, by effectively managing biological samples, researchers can obtain accurate test results, better understand disease mechanisms, evaluate drug curative effects, find new biomarkers and the like. In addition, the biological sample system should follow ethical specifications and supervision requirements, and rights and interests and privacy of test participants are protected.

The application discloses a virtual cell analysis platform based on cell disturbance data. The platform comprises three parts: a large language model data preprocessing system, a database and an online analysis platform, and a direction matching algorithm. The large language model data preprocessing system comprises an automatic data information extraction and retrieval tool, an automatic data file download tool, a large language model analysis engine and a gene expression data acquisition and feature extraction tool. The application can automatically preprocess the original data by applying the large language model data preprocessing system to the target scientific problem, and then store the data in the database. The characteristic direction matching algorithm is combined to output the drugs and key targets related to the target data set. The efficiency of target point and drug screening is improved. The application is suitable for large-scale omics data mining and disturbance analysis, accelerates the drug research and development, disease mechanism and translational medicine research process, and reduces the research and development cost.

The invention discloses application of double-mutant zebrafish in preparation of a mast cell function defect animal model. The double-mutant zebra fish disclosed by the invention is cpa1- / -cpa5- / -double-mutant zebra fish, and is obtained by further knocking out a cpa1 gene on the basis of a cpa5- / -zebra fish mutant. According to the method, potential compensation effects of two key carboxypeptidases are eliminated at the same time, and the storage and release capacity of mast cell protease is remarkably weakened from the genetics level, so that the zebrafish animal model with the mast cell function defect, which is clear in phenotype and stable in function, is obtained. The animal model can be used for mast cell function mechanism research, related disease mechanism exploration and drug screening and evaluation, and has a good application prospect.

This invention relates to a method for constructing a polycystic kidney disease (PCD) model and its applications. The method involves overexpressing the MYCN gene in a target animal to obtain a PCD model that leads to PCD-related phenotypes. The method includes the following steps: obtaining a first strain of mice with Rosa26 knock-in overexpressing the CAG-LSL-HA tag-MYCN-IRES-BFP-Wpre-polyA gene; obtaining a second strain of mice by inserting Cre-WPRE-polyA into the start codon of the Pax8 gene; and crossing the first and second strains of mice to obtain a MYCN-overexpressing PCD model. This invention employs various experimental methods for validation, including histopathological analysis, immunohistochemical staining, and Western blotting. The model provided by this invention overcomes the limitations of existing in vitro cell models, organoids, and existing animal models in terms of limited phenotypes. The established MYCN-overexpressing PCD animal model exhibits stable disease progression and a short disease cycle, which not only helps to elucidate the disease mechanism but also serves as an ideal platform for drug screening and efficacy evaluation.

This invention relates to an in vitro method for mapping the spatiotemporal electrophysiological dynamics and spatial transcriptional profiles of cells in a functional neuronal cell ensemble. This in vitro method includes simultaneously recording and analyzing spatial data of molecular activity and electrical network activity at the level down to individual cells using high-density electrobiosensors, spatial transcriptomics, optical imaging, and advanced computational strategies. The invention also relates to: methods for identifying the composition of a functional neuronal ensemble; methods for monitoring the spatiotemporal electrophysiological dynamics and transcriptional profiles of cells in a functional neuronal cell ensemble; methods for monitoring the cellular composition of a functional neuronal ensemble; methods for identifying compounds that influence spatial electrophysiological and transcriptional dynamics; and / or methods for identifying the cellular composition of a functional neuronal cell ensemble based on detected dynamics; and devices thereof. This invention allows for a better understanding of disease mechanisms, the identification of therapeutic targets, and the development of new drugs and treatment regimens.

The invention discloses a lung tissue organoid culture method. The method comprises the following steps: firstly, carrying out three-dimensional differentiation culture on matrigel by utilizing lung basal cells in vitro to construct an organoid with alveolar epithelium characteristics; then, the organ is transplanted into the spleen of a recipient animal subjected to ectopic surgery (shifted to subcutaneous tissues). The rich blood vessel network and the unique microenvironment of the spleen greatly promote rapid vascularization, structural remodeling and functional maturation of organoids, and lung tissue highly simulating natural alveolus is formed. The invention overcomes the defects of insufficient vascularization and immature function of the existing organ-like model, provides an excellent in-vivo platform for researching lung development and disease mechanisms and carrying out drug screening and toxicological evaluation, and has important application value in the field of regenerative medicine.

This invention discloses a monoclonal antibody against Oit3 protein in mouse hepatic sinusoidal endothelial cells or its antigen-binding fragment and its applications, belonging to the fields of biotechnology and medical immunology. The monoclonal antibody or its antigen-binding fragment comprises a heavy chain variable region and a light chain variable region. The heavy chain variable region contains HCDR1, HCDR2, and HCDR3 with amino acid sequences as shown in SEQ ID NO. 3~SEQ ID NO. 5; the light chain variable region contains LCDR1, LCDR2, and LCDR3 with amino acid sequences as shown in SEQ ID NO. 8~SEQ ID NO. 10. This monoclonal antibody and the recombinant fluorescent antibody exhibit high affinity and high specificity, and can be effectively applied to enzyme-linked immunosorbent assay (ELISA), Western blotting, and immunofluorescence detection. They can serve as important antibody tools for basic research on mouse hepatic sinusoidal endothelial cells and for exploring the mechanisms of liver diseases. Based on its variable region sequence, a recombinant fluorescent antibody, Oit3-scFv-GFP, was also constructed. This recombinant fluorescent antibody enables one-step direct immunofluorescence staining, providing a convenient tool for in situ visualization of mouse hepatic sinusoidal endothelial cells.

The application provides an animal brain metabolite identification method based on mass spectrometry imaging technology and application, and establishes a mouse brain tissue slice endogenous metabolite DESI-MSI analysis method based on mass spectrometry imaging technology, which comprises the following steps: after preparing metabolite control sample imaging samples and brain tissue slice imaging samples, multiple animal brain tissues are attached to the same glass slide, mass spectrometry imaging condition optimization is carried out by using the control sample imaging samples, and mass spectrometry imaging analysis is carried out by using the brain tissue slice imaging samples; the image of the biological sample is divided into multiple structure regions in combination with tissue morphological characteristics; for the structure regions, multivariate statistical analysis is carried out to obtain different metabolites in different structure regions; metabolite identification is carried out based on parent ions and characteristic daughter ion profiles; and the method is used for disease mechanism research and drug intervention effect evaluation on diseases.

The invention discloses a functional phosphorylation modification site screening method based on base editing, which is used for accurately identifying functional phosphorylation modification sites. According to the method, a cell line (such as human gastric cancer cells AGS / HGC27) for stably expressing ABE is constructed, an sgRNA library (containing 39 and 689 sites) covering phosphorylation sites of a whole genome is designed, screening is carried out under the conditions of oxaliplatin and the like, and the technical problem that more than 95% of phosphorylation sites are unknown in function is solved. According to the method, key sites (such as WEE1 S53) related to gastric cancer chemotherapy drug resistance are successfully recognized, the synergistic effect of oxaliplatin and WEE1 inhibitor combination is verified through experiments, and an innovative platform is provided for disease mechanism research and drug development.

The invention discloses a biomarker for diagnosing Alzheimer's disease as well as a screening method and application thereof, relates to the technical field of biomarkers for Alzheimer's disease, and aims to solve the technical problems that the Alzheimer's disease lacks dynamic pathological monitoring indexes and stereoisomeric modification is difficult to systematically detect. According to the invention, the stereoisomeric modification level of peptide fragments KLDLSNVQSK and AKTDHGAEIVYK is used as the core biomarker for the first time, the modification level is remarkably related to the Braak staging of AD, and a detection method and a combined diagnosis model containing the marker are provided. A novel molecular target with high correlation and dynamic monitoring potential is provided for AD, the model diagnosis precision is remarkably improved, and a brand new solution is provided for disease mechanism research and drug development.

The application provides a method for synchronously detecting multiple cell death modes in a tissue slice based on multiplex immunofluorescence, and belongs to the technical field of biological detection. The application realizes the synchronous labeling and visualization of multiple cell death modes in a single tissue slice, significantly improves the detection efficiency and saves precious samples; by integrating key biomarkers covering main cell death modes in the same detection system, a self-defined interpretation scheme based on multi-marker expression combination is constructed, effectively reducing the error caused by non-specific expression of a single marker, improving the reliability and rationality of the death mode classification, and providing a general solution for rapid screening of complex cell death networks. The application is suitable for anticancer drug efficacy evaluation, combination drug regimen screening and disease mechanism research, and has important scientific research value and clinical conversion prospect.

The invention discloses a rat parotitis model construction method based on general anesthesia and parotid gland directional injection, which belongs to the technical field of biology and comprises the steps of animal preparation, anesthesia, disinfection incision exposure, LPS injection and postoperative care. The method has the advantages that the parotid gland is directly exposed by adopting a longitudinal incision of the cheek, 2mg / mL LPS (0.2 mL and depth of 2mm) is injected, microscope positioning is not needed, the operation is simple and convenient, inflammation is limited to the parotid gland, pathological characteristics (alveolar injury, inflammatory infiltration and saliva reduction) are consistent with those of clinical application, the success rate is greater than or equal to 90%, and compared with an existing catheter injection method, the method is high in repeatability, less in interference and suitable for disease mechanism research and drug screening.

The invention discloses a method for researching the action mechanism of saikoside D on paclitaxel-induced peripheral neuropathy, and relates to the technical field of disease mechanism research and drug development. Comprising the following steps: performing continuous administration through intraperitoneal injection of paclitaxel, and establishing a paclitaxel-induced peripheral neuropathy animal model; a von Frey cellosilk experiment and a cold and hot plate experiment are adopted for behavioral detection, and mechanical pain threshold and cold and hot pain sense changes are evaluated; the morphological structure change of the sciatic nerve myelin sheath is observed through Luxol Fast Blue staining; and the expression level of the myelin sheath basic protein in the sciatic nerve is detected by using immunofluorescence staining and Western blotting technologies. According to the invention, a closed-loop research system is formed from animal model construction to molecular mechanism verification; based on behavioral detection, histological analysis and multiple dimensions of a molecular biological technology, the data reliability is ensured, and the curative effect of saikoside D can be comprehensively evaluated.

The invention relates to the technical field of gene editing, in particular to a method for synchronously constructing a mouse model with the point mutation (Knockin, KI) of a Clcn3 gene p.T570I and the knockout (Knockout, KO) of the Clcn3 gene by utilizing a CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats-associated protein 9) system and application of the mouse model. By optimizing a gRNA targeting site and a donor oligonucleotide sequence, efficient introduction of Clcn3 gene p.T570I point mutation is achieved, and the mutation efficiency is improved by 30% or above compared with a traditional method; the constructed Clcn3 gene p.T570I KI and KO mouse models can be used for stably inheriting target mutation. The method is short in period, low in cost and suitable for large-scale gene editing animal model construction, the first Clcn3 gene p.T570I KI mouse model carrying the human pathogenic mutation site in the world is constructed, and an ideal and reliable genetic tool is provided for deep analysis of the physiological function of the CLCN3 gene and related disease mechanisms.

The invention provides a road disease detection method based on a Bayesian network, and the method comprises the steps: firstly collecting environment, traffic and structure multi-source data, recognizing key risk factors affecting road diseases, and constructing a causal dependency graph between events; on this basis, a static Bayesian network structure is constructed, risk factors are mapped into bottom layer nodes, disease mechanisms are mapped into intermediate nodes, disease'super-threshold state 'is set as top layer nodes, and conditional probability parameter learning is completed through maximum likelihood estimation and Bayesian estimation methods. Furthermore, a dynamic Bayesian network is constructed, a time slice and cross-time sequence dependency relationship is introduced, and recursive modeling of a disease evolution process is realized through a dynamic transition probability table. In the model reasoning stage, a variable elimination method is adopted for probability calculation, missing information is processed in combination with a data credibility weight mechanism, and key influence factors are identified through sensitivity analysis. The method can be widely applied to risk prediction and intervention simulation of multiple disease types such as ruts and cracks, and provides decision support for road maintenance management.

This invention provides a method for predicting protein methylation sites that integrates quantum and region-aware technologies, comprising the following steps: Step 1, obtaining protein sequences as data sources and constructing training and independent test sets respectively; Step 2, constructing multimodal features for each protein sequence using a three-way nested scattering network, fusing the multimodal features to obtain an optimized fused feature tensor; Step 3, inputting the optimized fused feature tensor into a RaQMeNet network model to perform methylation site prediction. This invention not only significantly outperforms existing technologies in terms of performance indicators but also possesses stronger adaptability, stability, and interpretability. It can be widely applied in multiple bioinformatics and biomedical fields such as protein functional annotation, disease mechanism research, and drug target discovery, demonstrating promising application prospects and commercial value.

The application belongs to the technical field of regenerative medicine, and discloses a kind of organoid culture method derived from human and non-human primate subventricular zone neural stem cells. By optimizing the medium formula and regulating transcription factors, the organoid is successfully induced to differentiate into CRABP1-expressing neuronal precursors. These cells express TAC3, and the application overcomes the limitations of existing technologies in simulating primate-specific neural lineages and complex brain structures, providing a breakthrough in vitro model for studying neural development, neurological diseases and drug development. The established system not only provides a new tool for studying the development of primate nervous system and disease mechanism, but also provides a reliable experimental platform and transplantable cell source for developing targeted drugs, constructing advanced disease models and conducting cell replacement therapy.

The invention discloses a method for detecting metabolite containing phosphate radicals, which is characterized in that a mass spectrum label with stable and characteristic chlorine isotope distribution is introduced through a chlorination reagent derivatization strategy, so that a derivatization product can be subjected to rapid and high-specificity preliminary identification based on primary mass spectrum data. By combining with an automatic data mining program specially developed for this purpose, high-throughput and accurate screening and locking of potential phosphate radical-containing metabolites from massive and complex non-targeted metabonomics original data are realized, and the data analysis efficiency and reliability are greatly improved. The method is successfully applied to analysis of actual biological samples such as cholestasis disease models, efficient identification and accurate quantification of various key metabolites such as nucleotide and sugar phosphoric acid are achieved, disturbance of related metabolic pathways is disclosed, and a powerful innovative analysis tool is provided for disease mechanism research and biomarker discovery.

The application provides a cancer gene key regulation module identification method, system, device and storage medium, comprising: collecting tissue sample data of a patient; performing transcriptome sequencing on the collected tissue samples respectively, and performing data processing on the obtained raw sequencing data to generate a gene node set; constructing a cancer gene regulation network based on the gene node set, and constructing a simplex network by introducing a high-order topological modeling method; performing cluster centrality evaluation on the high-order clusters of the simplex network based on a set high-order random walk centrality index, and dynamically removing redundant clusters from the modules based on a dynamic redundancy removal strategy, to output a key regulation module ranking result. The application can significantly improve the identification ability of the key regulation module, thereby effectively evaluating the importance of each regulation module in the cancer network, and providing solid data support for disease mechanism analysis and network intervention strategy design.