65 results about "Disease phenotype" patented technology

The invention relates to a drug-disease association prediction method and model based on NMF and GT. A drug-disease association prediction method based on NMF and GT comprises the steps of (1) obtaining a comprehensive similarity matrix of drugs and diseases according to drug fingerprint similarity, disease phenotype similarity and Gaussian kernel similarity of the drugs and the diseases; (2) extracting features of the comprehensive similarity matrix of the medicines and the diseases through non-negative matrix factorization to obtain characteristics of the medicines and the diseases; capturing a high-order structure relationship through a graph Transform to obtain similarity features of drugs and diseases; (3) respectively carrying out interactive fusion on the drug characteristics and the drug similarity characteristics and the disease characteristics and the disease similarity characteristics to obtain final drug and disease characteristic representations; and (4) carrying out association prediction according to the final characteristic representation of the medicine and the disease. The NMF and GT-based drug-disease association prediction method and model provided by the invention have good potential in the aspect of accurately predicting potential drugs.

The invention discloses a human NLRP7 mutation decidua type organ and application thereof, and belongs to the technical field of construction of type organs. The human NLRP7 mutant decidua organ is preserved in the China Center for Type Culture Collection, and is named as the human NLRP7 mutant decidua organ N7LLY (Homo sapiens), the preservation number is CCTCC (China Center for Type Culture Collection) NO: C2024375, and the preservation date is November 06, 2024. The human NLRP7 mutant decidua-like organ is applied to construction of a model for simulating an in-vivo NLRP7 mutant embryo decidua-like organ, and is applied to screening of drugs with prevention or treatment effects on grape embryo or embryo implantation failure. The human NLRP7 mutant decidua-like organ provided by the invention has endometrial epithelial cells and interstitial cells at the same time, expresses receptivity-related markers, and can retain pathological mutation and disease phenotypes of patients in vitro.

The invention provides a drug recommendation method for drug effect prediction and / or personalized medication guidance. The drug recommendation method is based on a multi-dimensional differential expression map reference database. According to the invention, the association between the gene and a drug action mechanism or a disease phenotype is inferred through multi-dimensional information of the gene and functional modules including a GO function, a signal channel, transcriptional regulation, protein-protein interaction and the like; and meanwhile, a model integrated statistical method is benefited, and more accurate drug effect prediction and personalized medication guidance are finally realized compared with similar work. The method has a wide application prospect.

The invention relates to a double-gene rare variation and disease relevance prediction model and an establishment method and application thereof, and belongs to the technical field of biological medicines.The establishment method of the double-gene rare variation and disease relevance prediction model comprises the following steps that S1, a sample library is screened; s2, performing quality control on whole exome sequencing data (WES); s3, performing phenotype screening; s4, performing grouping design; s5, carrying out PheWAS logistic regression analysis; s6, performing Firth logistic regression analysis and verification; and S7, carrying out double-gene feature analysis and double-gene pathogenicity relevance prediction. The method for analyzing the correlation between the rare double-gene variation and all disease phenotypes is designed for the first time, and a new method is provided for screening hereditary pathogenic factors of various diseases.

The invention relates to the technical field of drugs, in particular to a drug relocation method for integrating multi-source biological data based on a meta-path, which comprises the following steps: acquiring an original data set; constructing a fusion heterogeneous network, and fusing the incidence matrixes of every two combinations of drugs, diseases and proteins and the respective similarity matrixes to obtain a heterogeneous graph; designing a multi-level association path based on meta-path and similarity negative sampling, fusing similarity information of same-level networks in the heterogeneous network based on a similarity principle, and selecting a negative link sample; extracting drug characteristics; constructing an SMS-MPF module, carrying out migration on the meta-paths through a heterogeneous network, extracting and fusing features among different meta-paths, and obtaining associated features of drugs and diseases; and inputting the disease phenotype similarity matrix, the drug characteristics and the associated characteristics of the drugs and the diseases into an associated prediction module to obtain final node representation. The method solves the problem that an existing method has significant defects in selection of positive and negative samples.

The invention discloses a construction method and application of a Prpf6 gene mutation induced single dose insufficient RP mouse model, and belongs to the technical field of molecular biology and biomedicine. The mouse model constructed by using the method provides a convenient, reliable and economic means for researching the relationship between PRPF6 gene mutation and retinitis pigmentosa diseases and the pathogenesis of the PRPF6 gene mutation, and provides an effective research model capable of stably inheriting in the research on the aspects of RP pathogenesis, treatment methods, drug screening and the like. The animal model is subjected to transcriptome and a series of phenotype detection, wherein a transcriptome result shows that Prpf6 gene knockout mouse retina has occurred a certain degree of metabolic abnormality, electrophysiological detection, fundus examination and Hamp; e staining results show that the shapes and functions of the retinal cell layer and the retina of the mouse are damaged, and the disease phenotype of RP is met.

The invention belongs to the technical field of medicine, and particularly relates to application of a small molecule compound R406 in preparation of a product for preventing and treating Parkinson's disease, screening based on small molecules and microarrays is carried out, the compound R406 can reduce the alpha-syn protein level in an autophagy-dependent mode, and in addition, the compound R406 can be used for preparing a product for preventing and treating Parkinson's disease. The R406 also reduces the level of alpha-syn phosphorylated serine 129 in a fiber-induced cell model pre-formed by alpha-syn, and prevents neuronal degeneration. In addition, experiments confirm that the R406 can relieve PD-related disease phenotypes in a human alpha-syn preformed fiber-induced cell model and a PD patient-derived organ-like model, and a new thought is provided for treatment of the Parkinson's disease.

To provide a method, a system and software for training a model for phenotyping subjects with respect to a medical condition.SOLUTION: A method includes generating a plurality of labeling functions with respect to a medical condition. Each of labeling function within the plurality of labeling functions includes comprises a corresponding set of one or more criteria that, when satisfied, indicate presence or absence of the medical condition. The method also includes assigning, to each medical record in a first plurality of medical records, a corresponding label indicating a status of the medical condition by evaluating first information from the respective medical record using an ensemble model comprising the plurality of labeling functions to obtain as output from the ensemble model prediction for the status of the medical condition, wherein the evaluating comprises natural language processing of at least a portion of each medical record.SELECTED DRAWING: Figure 2E

The application discloses a method for constructing a RP mouse model caused by Prpf6 gene mutation and haploinsufficiency and application thereof, and belongs to the field of molecular biology and biomedical technology. The mouse model constructed by the method provides a convenient, reliable and economical means for studying the relationship between the PRPF6 gene mutation and the retinal pigment degeneration disease and the pathogenic mechanism thereof, and provides a stable hereditary effective research model in the research of the pathogenic mechanism, treatment method and drug screening of RP. The animal model is subjected to transcriptome and a series of type detection, wherein the transcriptome result shows that the retina of the Prpf6 gene knockout mouse has a certain degree of metabolic abnormality, and the results of the electro-physiological detection, fundus examination and H&E staining show that the cell layer of the mouse retina and the shape and function of the retina are damaged, which is consistent with the disease phenotype of RP.

This invention discloses a method, medium, and device for identifying DRG over-compensation based on invoice reverse engineering and causal imprinting. The method includes: acquiring detailed medical billing data from the medical records to be audited; extracting features of treatment items and mapping them to a medical knowledge graph to obtain a set of feature atoms; inputting the feature atom set into a large language model, outputting real disease phenotypes as pseudo-labels, and performing semantic comparison with the reported primary diagnosis to identify over-compensation of the primary diagnosis; classifying the sensitivity of other reported diagnoses by score, screening high-value complication entities, and verifying their resource consumption matching degree through a clinical pathway constraint library to identify fictitious complications; extracting the main billing items and their low-value billing imprint rule library, and identifying falsely inflated primary intervention items through counterfactual causal comparison; finally, calculating a comprehensive anomaly index based on deviation, matching degree, and divergence, and outputting an audit report. This invention automatically identifies DRG over-compensation anomalies from multiple dimensions, improving the accuracy and comprehensiveness of audits.

The invention relates to a screening method of anti-breast cancer key targets of a traditional Chinese medicine composition for treating triple-negative breast cancer pulmonary metastasis, which sequentially comprises the following steps: component-target preliminary screening, two sample Mendel randomization, SMR and co-localization, full phenotype association and side effect evaluation, pathway enrichment, clinical expression verification, molecular docking verification and the like. After Mendel randomization (MR) and SMR are placed in network pharmacology, population genetic variation is used as a natural randomization tool, evidence of causal relationship between exposure (target level) and outcome (breast cancer risk) is provided on a public GWAS level, traditional association analysis mixing and reverse causal risk are reduced, and the false positive rate of network pharmacology prediction is greatly reduced; pheWAS-MR is introduced to perform system identification on phenotypes of various diseases, so that a potential off-target effect can be identified in advance, the multiple effects and possible adverse reactions of potential treatment targets in traditional Chinese medicine compound targets can be evaluated, powerful data support is provided for subsequent clinical test design and drug alert strategies, and the risk of later failure of research and development is effectively reduced.

A method for identifying cell subpopulations associated with disease phenotypes, belonging to the biomedical field. To identify cell subpopulations associated with disease phenotypes, this invention collects single-cell RNA sequencing data of the disease to obtain a single-cell expression matrix, collects the bulk expression matrix of the disease and corresponding phenotypic tags, and downloads human protein-protein interaction data to construct a protein-protein interaction network; extracts gene signature features of cells and samples and maps them to the protein-protein interaction network to form corresponding cell modules and sample modules; calculates the distance between each cell module and each sample module, and determines a set of multiple sample modules as the sample module set of the disease phenotype; calculates the distance between cell modules and the sample module set of the disease phenotype; creates a background distance distribution to evaluate the statistical significance of the distance between cell modules and the sample module set of the disease phenotype, and identifies cells whose distance to the sample module set of the disease phenotype is significantly smaller than the background distance distribution.

The invention relates to an osteoarthritis AI (osteoarthritis) prediction method based on NETs (neutrophile granulocyte extracellular traps) related key genes, and aims to develop a model universally applicable to gene diagnosis or molecular diagnosis by analyzing and disclosing a large sample data set through an advanced algorithm by utilizing ML (makeup language) to reveal genetic regulation of neutrophile granulocyte extracellular traps (NETs) in joint tissues. Therefore, the optimal algorithm needs to be compared and screened by using multiple algorithms during modeling, the gene (molecule) diagnosis efficiency is improved by combining the algorithms on the basis, key genes which can best reflect OA characteristics and are driven by NETs (key gene characteristics related to the NETs) are selected, and the disease-related genes and the relationship between the disease-related genes and disease phenotypes are identified, so that the disease-related genes are identified. Therefore, understanding of interaction of biological components is deepened, and diagnosis and treatment strategies are improved.

The invention belongs to the technical field of gene engineering, and particularly relates to a construction method of a ribosomal disease zebrafish model. The invention provides a construction method of a ribosomal disease zebrafish model, which comprises the following steps: directionally mutating a pno1 gene in a wild zebrafish embryo to obtain F0-generation zebrafish; mating the F0-generation zebrafish with wild type zebrafish, and screening out positive heterozygote F1-generation zebrafish from birth zebrafish as the ribosomal disease zebrafish model. The zebrafish mutant is constructed through the targeted ribosomal factor gene, multi-system phenotypes of hematopoietic system defects, skeletal insufficiency and digestive system dysplasia can be reproduced at the same time, the problem that in the prior art, disease phenotypes are incomplete is solved, and the zebrafish mutant can be widely applied to pathogenesis research and drug screening of ribosomal diseases and has a wide application prospect. An important platform is provided for developing a novel treatment means.

The present application relates to a kind of difficult culture pathogen resistance identification method and its application, belong to the field of agriculture and forestry science, step 1: the culture screening of toxic source plant, plant to be identified and indicator plant;Step 2: grafting transmission, the toxic source plant screened only with difficult culture pathogen, the plant to be identified without difficult culture pathogen and indicator plant are arranged in position, and transmission is carried out using grafting method;Step 3: observation and detection, according to the disease cycle of difficult culture pathogen, the disease phenotype of plant to be identified and indicator plant in step 2 is observed, and the colonization, propagation of difficult culture pathogen is detected by PCR method;Step 4: disease resistance and pathogen running speed evaluation.Effectively solve the problem that the identification result is inaccurate due to the low inoculation rate of difficult culture pathogen using transmission medium, the inconsistency of inoculation source pathogen and other reasons, the error is larger in resistance identification work, etc.

The invention discloses a construction method and application of a mouse model for testicular development disorder caused by Map3k1 gene mutation. The method comprises the following steps: designing and constructing sgRNA and a homologous recombinant vector capable of specifically recognizing a Map3k1 gene on the basis of a CRISPR / Cas9 system, injecting the sgRNA and the homologous recombinant vector into a mouse fertilized egg, screening out an F0-generation mouse with Map3k1 gene mutation from a mouse produced after the fertilized egg is transplanted, and hybridizing the F0-generation mouse with a wild type mouse to obtain a stably inherited Map3k1 gene mutation mouse model. The phenotype detection result of the mouse model shows that the fertility of the mouse model is remarkably reduced, and testis dysplasia conforms to the disease phenotype of testis dysplasia. The mouse model provides a convenient, reliable and economic means for researching the relationship between Map3k1 gene mutation and testicular dysplasia and the pathogenesis of the Map3k1 gene mutation and testicular dysplasia, and can be used for researching the pathogenesis of testicular dysplasia, a treatment method, drug screening and the like.

The application relates to methods for identifying putative regulatory elements that regulates a gene, comprising: obtaining a measure of intrinsic activity of a plurality of genomic elements; obtaining a measure of proximity between each of the genomic elements and the gene; scoring a predicted impact of each of the genomic elements on the gene as a function of the measure of intrinsic activity and the measure of proximity, wherein a plurality of predicted impacts scored are ranked to identify at least one genomic element as a putative regulatory element that regulates the gene; and optionally, training, optimizing, and / or validating the scoring of predicted impact using experimental or computational data describing functional interactions between the genomic elements and the gene. The application also relates to methods for identification of transcriptional enhancers and repressors regulating a gene associated with an agricultural trait of interest in plants or a disease phenotype in mammalians.

The application provides a method and system for optimizing SNP interaction selection precision based on an ant colony algorithm, and the method comprises the following steps: each artificial ant selects an SNP interaction in a search space, all artificial ants are divided into several populations, and an adaptive function is allocated to each population, and the adaptive function is used to evaluate the correlation between the SNP interaction and a disease phenotype; an information matrix is updated by using any pheromone updating strategy; in each iteration process of the ant colony algorithm, a self-learning mechanism is set by taking the maximum cumulative reward of the ants as a target, and the pheromone updating strategy is changed through the self-learning mechanism. Based on the method, a system for optimizing SNP interaction selection precision based on the ant colony algorithm is also provided. The application is used for accurately selecting SNP interactions related to a disease phenotype, several different path selection strategies are designed, and the path selection strategy which can bring the maximum selection ability to the algorithm is adaptively selected in the search process of the algorithm based on reinforcement learning.

The application discloses application of forskolin and / or isoforskolin in preparation of a medicine for preventing and / or treating colitis, and belongs to the technical field of medicines.The medicine can significantly improve the disease phenotype of colitis, including relieving weight loss, reducing disease activity index score, improving colon length shortening and histopathological damage.The mechanism of action involves multiple targets: repairing intestinal mucosal barrier function, reducing local inflammation of the colon, and regulating intestinal flora balance, restoring the abundance of beneficial bacteria and inhibiting the proliferation of pathogenic bacteria.The application provides a candidate drug with anti-inflammatory, barrier repair and flora regulation functions for the treatment of colitis, and expands the medical use of forskolin or isoforskolin.

The invention relates to the technical field of animal models, and particularly discloses a construction method and application of a mouse model with fat dystrophy complicated with atherosclerosis, and the construction method comprises the following steps: mating MED1flox / flox mice with Adipoq-CreERT2 mice to obtain F1-generation mice; the F1-generation mice and MED1flox / flox mice are subjected to backcross, the mice with the genotype being MED1fl / flAdipoq-Cre < + / -> are screened, tamoxifen is injected to induce fat cell specific Cre recombinase expression, and fat cell specific MED1 gene knockout mice are obtained; and performing caudal vein injection of AAV8-PCSK9 virus and feeding with a high-cholesterol and high-fat feed to obtain the fat dystrophy complicated with atherosclerosis mouse model. According to the method provided by the invention, the mouse model with fat dystrophy complicated with atherosclerosis is successfully constructed and obtained, and collaborative simulation and regulation of phenotypes of two diseases are realized.

The present invention provides a method for targeting a maternal UBE3A allele to establish an animal model of Angelman syndrome and use thereof. By means of extensive and in-depth research and screening of the sequences of primate genome UBE3A genes, a target suitable for genetic engineering is obtained: an intron upstream of and / or an intron downstream of exon 5 of a maternal UBE3A gene. An animal model of Angelman syndrome can be obtained by performing downregulation targeting the target. The animal model has a stable and controllable state and a typical disease phenotype, which is conducive to observation.

The invention belongs to the technical field of medicines, and particularly relates to application of LLDT-8 in preparation of a medicine for treating polymyositis, LLDT-8 reduces expression levels of MHC-I and NLRC5 in muscular tissues and inhibits activation of CD8 + T cells through targeted regulation of an NLRC5 / MHC-I pathway, so that infiltration of the CD8 + T cells in the muscular tissues is reduced, muscular inflammation is remarkably inhibited, and phenotypes of polymyositis diseases are improved.

The application discloses an ncRNA gene mutation interpretation method, a storage medium and a terminal, and relates to the field of ncRNA gene mutation interpretation.The ncRNA gene mutation interpretation method comprises the following steps: constructing an ncRNA gene pathogenic mutation standard dataset, an ncRNA gene benign variation standard dataset and an ncRNA gene variation harmfulness standard dataset for experimental verification; constructing a scoring model for training ncRNA gene variation harmfulness and an ncRNA gene related disease phenotype similarity scoring model by using the aforementioned datasets; performing logistic regression modeling on harmfulness scoring files and ncRNA gene disease phenotype similarity scoring files containing the same number of pathogenic and benign ncRNA gene variation sites by using data mining software; obtaining an algorithm model for screening and identifying specific evaluation of ncRNA gene pathogenic mutations; training the algorithm model; and interpreting and reporting ncRNA gene mutations by using the trained algorithm model.The ncRNA gene mutation interpretation method can realize standardized, automatic, intelligent and high-throughput clinical interpretation reports for ncRNA gene mutations, greatly improves the interpretation efficiency and the accuracy of the interpretation.

The present invention provides methods of profiling gene and protein expression of a plurality of nuclei from a single cell type and comparing the profiles to determine variability among cell populations, samples from different subjects, and cells expressing a disease phenotype.

The present disclosure relates to systems, methods and computer program products for drug development using in silico techniques. An aspect of the disclosure is directed to an in silico method for determining drug activity of a plurality of drug targets by determining biomarker stratifier effects, calculating a biomarker stratifier score for a chosen disease phenotype; and calculating a pharmacomimetic genetic score using molecular biomarker stratifier data.

This specification relates to the field of medical technology, and in particular to a disease phenotype term matching method, device, computer equipment and medium. The method includes: inputting disease-related text in a diagnostic text into a phenotype information prediction model to obtain phenotype information output by the phenotype information prediction model, wherein the phenotype information prediction model is obtained by training an initial large language model with phenotype labels and training sample data; converting the phenotype information into a corresponding vector representation; selecting the term with the highest matching degree with the vector representation from the HPO standard term library based on the vector representation of the phenotype information; and determining the term as the final term of the diagnostic text. This specification uses a large language model combined with sentence embedding technology to more accurately identify phenotypic information in clinical texts. When processing clinical records with complex semantics or irregular expressions, the possibility of misidentification is reduced, and the recognition accuracy of complex and rare phenotypes is improved.

The present application provides a method for constructing a rat model of mucopolysaccharidosis type IVA, characterized by comprising the following steps: obtaining rats with a GALNS p.M320R heterozygous mutation and a GALNS p.M320R homozygous mutation; and mating male GALNS p.M320R heterozygous mutation rats with female GALNS p.M320R homozygous mutation rats to construct the rat model of mucopolysaccharidosis type IVA. By simulating the GALNS p.M318R mutation, a common clinical patient, the rat model has a high survival rate and exhibits mild mucopolysaccharidosis type IVA. Furthermore, the rat model constructed in the present application exhibits a clear skeletal phenotype at 3 to 4 weeks of age, which is closer to the clinical onset of mucopolysaccharidosis type IVA. Furthermore, the present application enables the regulation of the severity of the disease phenotype.

Herein disclosed is a method of preparing a model to detect health and ill-health related characteristics in complete blood counts (CBC) data. The method comprises receiving CBC data from one or more data sources, where the CBC data comprise raw and rich data; encoding CBC data using one or more machine-learning algorithms; training classifier for biological traits based on the encoded CBC data, where the biological traits comprise disease phenotypes; and outputting the model comprising the trained classifier.

The invention provides an application of a liver Sdhaf4 gene in preparation of a retinopathy model. The inventor is devoted to research on retinopathy for a long time, through deep research tests, a brand-new retinopathy-causing gene target of peripheral tissues related to retinopathy, namely the Sdhaf4 gene is disclosed, and through reasonable design, the Sdhaf4 gene can be used for preparing a new retinopathy-causing gene target. The retinopathy animal model under the condition of good blood glucose control can be obtained by targeting the target and implementing down-regulation. The animal model is stable and controllable in state, typical in disease phenotype and easy to observe.

The present disclosure relates to systems, methods, and computer program products for drug development using in silico techniques. One aspect of the disclosure relates to an in silico method for determining drug activity for multiple drug targets by determining biomarker stratification factor effects, calculating biomarker stratification factor scores for a selected disease phenotype, and calculating pharmacomimetic gene scores using molecular biomarker stratification factor data.