262 results about "Differential expression" patented technology

A spatial omics multi-modal fusion method under a single cell level comprises the following steps: extracting spatial morphological characteristics of differential expression genes and cell nucleuses from spatial transcriptome data, single cell sequencing data and histological images, and realizing field adaptation among different platforms by using a conditional variation auto-encoder. And based on a probability inference model, fusing spatial transcriptome expression, unicellular omics and morphological characteristics, and jointly inferring the type and gene expression level of each cell. A spatial cell network is constructed through a graph attention mechanism, and spatial diffusion and recognition of cell types in a full slice range are realized. In combination with a multi-omics enhancement module, undetected gene and protein expression is completed based on expression similarity, and prediction consistency is improved through spatial correction. According to the method, high-resolution reconstruction of single-cell multi-omics information in a three-dimensional space is realized, the information coverage and spatial resolution of spatial omics data are improved, and an efficient and low-cost solution is provided for spatial biology and precise medical research.

The invention provides a glycolipid metabolism related gene-based endometrial cancer prognosis prediction model construction method, which comprises the following steps of 1, acquiring data containing gene expression and clinical information, and preprocessing the data; 2, differential expression and prognosis gene screening; 3, constructing a prognosis model; 4, analyzing model gene enrichment; 5, evaluating the immunocompetence of the two GLRG related dangerous groups; and step 6, statistical analysis. According to the technical scheme, more accurate and reliable prognosis evaluation is provided for endometrial cancer by comprehensively analyzing multi-dimensional information such as gene expression, immune characteristics, mutation characteristics and drug sensitivity.

The invention belongs to the technical field of biological medicine and molecular biology, and particularly relates to application of circ0005704 and related biological elements thereof in diagnosis and treatment of recurrent spontaneous abortion with unknown reasons. Researches find that differential expression and autophagy level of ULK1 in trophoblast cells of URSA patients are increased. High-throughput transcriptome sequencing is combined with bioinformatics analysis, and it is found that miR-26a-5p is down-regulated in URSA patients, is responsible for up-regulation of ULK1 and promotes autophagy of trophoblast cells, so that occurrence of URSA is increased. Through a high-throughput transcriptional set screening strategy and dual luciferase reporter gene analysis, it is found that circ0005704 enhances the expression of ULK1 through miR-26a-5p. In a word, the research of the invention shows that the circ0005704 / miR-26a-5p / ULK1 signal axis participates in the pathogenesis of URSA by adjusting the migration of the trophoblast cells, and a new target and scientific evidence are provided for the clinical treatment of URSA.

The invention discloses a rapid detection method for traumatic brain injury by fusing genetic engineering and quantum dots, and relates to the technical field of traumatic brain injury detection. The method comprises the following steps: acquiring a suspected patient biological sample, extracting biomolecule components, and comparing the biomolecule components with a healthy population biomolecule database to obtain related differential expression molecules. A specifically recognizable recombinant antibody is constructed by genetic engineering, and is connected with a quantum dot through a coupling reaction to prepare a detection probe. The probe and a biological sample are mixed and reacted, and the intensity of a fluorescence signal generated by combination is collected by a fluorescence detection device. A standardized signal value is obtained through signal processing algorithm noise reduction and feature extraction, and a preliminary detection result is determined by combining a bioinformatics database evaluation sample. And finally, according to the differential expression molecule, the standardized signal value and the preliminary result, analyzing a data change trend in a preset time window by using a multivariable statistical model, and generating a diagnosis report. According to the method, various technologies are fused, and a new path is provided for traumatic brain injury detection.

The invention discloses a screening method of a protein marker combination, which is used for risk prediction of abdominal aortic aneurysm or ruptured abdominal aortic aneurysm, and optimizes the stability of a protein expression profile by constructing an initial protein expression profile; screening differential expression proteins by adopting statistical analysis, and preliminarily locking candidate proteins remarkably associated with a disease endpoint based on survival analysis or a risk regression model; performing cross validation by combining a sparse constraint algorithm and a nonlinear feature selection algorithm, and extracting a robust core marker; the independent contribution degree of each marker is evaluated through the standardized weight, and finally the optimal protein combination for disease prediction or diagnosis is determined. According to the method, six core proteins obtained through multi-algorithm cross screening can be detected in serum, multivariable logistic regression and external verification set performance both show good robustness, and an aorta protein fingerprint feature set which can be popularized and explained is formed.

The invention discloses a rape grain weight regulation gene NGAL3 based on whole genome screening and a breeding application thereof, based on the seed size and grain weight phenotypic value of a cabbage type rape germplasm resource, a candidate gene interval is positioned by using GWAS; the method comprises the following steps: selecting large-grain-weight and small-grain-weight extreme phenotypic materials, performing transcriptome sequencing in a critical period of seed development, and screening differential expression genes; and performing cross comparison on the GWAS candidate gene and the differential expression gene to obtain a key gene for jointly regulating and controlling the size and the grain weight of the seed, and performing functional verification on the key gene. The thousand seed weights of the created homozygous three mutant strains L1-sg1-1-4-5 and L2-sg1-4-8-16 are obviously increased by 46% and 29% compared with those of the wild type strains. The invention provides a new target for high-yield rape breeding, and non-transgenic high-grain-weight germplasm can be created through gene editing or beneficial allelic variation of NGAL3 is selected and enriched under the assistance of molecular markers.

The invention discloses a gastric cancer biomarker composition as well as a screening method and application thereof, and belongs to the technical field of bioinformatics. The screening method of the gastric cancer biomarker composition comprises the following steps: firstly, collecting blood specimens of a gastric cancer patient and a healthy control, carrying out high-throughput plasma proteomics detection, and screening out differential expression proteins; and verifying the candidate protein markers by using a prospective queue in the British biological sample library, and finally determining 17 core proteins to obtain the gastric cancer biomarker composition. A gastric cancer risk prediction model is constructed by combining clinical risk factors and protein expression levels of gastric cancer biomarkers. The gastric cancer risk prediction model constructed by the invention can realize accurate layering of gastric cancer risks, decision curve analysis shows that the net benefit of the model is obviously superior to that of a traditional screening method, and an efficient tool is provided for early warning and personalized intervention of gastric cancer.

The invention relates to a deep feature fusion-based fabricated component surface defect multi-task detection method. The method comprises the following steps of: constructing a multi-view camera array and an illumination feedback regulation and control module at a data acquisition end; on the algorithm level, feature cross-layer propagation and information compensation are realized through an improved lightweight convolutional network and a multi-scale residual diffusion module; a dynamic feature fusion module is introduced, and a self-adaptive fusion weight is generated based on channel statistical features, so that feature sharing and differential expression are realized among different tasks; meanwhile, a defect perception attention mechanism and cross-task consistency constraint are adopted, and the problem that semantic space distribution is inconsistent in the multi-task detection process is solved; in the detection post-processing stage, a three-dimensional quantitative evaluation system based on the geometric dimension, the texture roughness and the depth volume is constructed, and unified grade evaluation of the surface defects of the component is achieved through the multi-feature fusion quality index. The problems of low detection efficiency, unstable precision, difficulty in collaborative recognition of multiple types of defects and the like in existing component delivery detection are solved.

The invention relates to the technical field of biology, and provides a genetic marker for children nephrotic syndrome genetic risk assessment. The invention relates to genetic detection and application of hormone sensitive nephrotic syndrome (pSSNS) of children. Nine risk sites, including new sites of 1q23.1, 1p36.13, 5p13.2, 10q21.3, 10q24.1 and the like, highly related to diseases are found by integrating whole genome association research (GWAS) data, combining Meta analysis and a conjugate false discovery rate (conjFDR) method and taking genetic information of IgA nephropathy as assistance. Research results show that genes near the loci have differential expression in pSSNS and IgAN patients, which prompts that the genes play an important role in the occurrence and development of diseases. The invention provides a molecular detection method based on the risk site, which can be used for risk assessment, auxiliary diagnosis and prognosis prediction of children's nephropathy. Meanwhile, the invention provides potential application values of the loci and related genes thereof in individualized medication and targeted therapy.

The invention discloses an adversity high-photosynthetic-efficiency transcription factor screening method based on deep learning, and relates to the technical field of biological information analys.The method comprises the steps that rice multi-modal stress response data is obtained and preprocessed, and preprocessed gene expression data is obtained; carrying out differential expression gene screening and co-expression network analysis on the preprocessed gene expression data, extracting multi-modal features, and fusing the multi-modal features to generate a multi-modal input feature matrix; constructing a double-layer deep learning model, training the double-layer deep learning model by using the multi-modal input feature matrix, and respectively outputting a regulation and control relationship matrix of transcription factors and target genes and a regulation and control relationship matrix of transcription factors and target pathways; and according to an output result, calculating a comprehensive score of each transcription factor through a multi-dimensional scoring system, and screening out the stress high-photosynthetic-efficiency transcription factor according to a predetermined screening standard.

The invention discloses application of MNDA in diagnosis of multiple sclerosis. According to the application, the gene MNDA presenting significant differential expression in multiple sclerosis is screened out by analyzing database data, and verification is further carried out by sequencing data and collecting clinical samples, so that the MNDA presents significant up-regulation in multiple sclerosis patients and has relatively high diagnosis efficiency; a new direction is provided for diagnosing and treating multiple sclerosis, and the application prospect is wide.

The circulating snoRNA biomarker comprises the following six specific snoRNAs: SNORA7B, SNORD41, SNORA74A, SNORA79B, SNORD83A and SNORD94, the differential expression of the circulating snoRNA biomarker in plasma is remarkable, and the circulating snoRNA biomarker is suitable for early screening, diagnosis and prognosis evaluation of gastric cancer. The circulating snoRNA is applied to a detection reagent for gastric cancer diagnosis, and has the advantages of non-invasiveness and convenience in detection.

The invention discloses an application of a reagent for detecting AP3S2 in preparation of a diagnostic reagent for neoadjuvant immunochemotherapy resistance of gastric cancer in a local progression stage, which comprises the following steps: screening differential expression proteins in neoadjuvant immunochemotherapy resistance tissues of gastric cancer in the local progression stage through proteomics; a new marker is provided for diagnosis of the local progression stage gastric cancer immunochemotherapy drug resistance, and a basis is also provided for development and future development of a local progression stage gastric cancer immunochemotherapy drug resistance diagnosis method.

The application discloses a marker for determining the severity of IgAN kidney tissue lesions and application thereof, and inventors find that ACTN4, ACADS and COL1A1 are significantly differentially expressed proteins in kidney tissues. The significant down-regulation of ACTN4 may cause the change of actin cytoskeleton of IgAN glomerular podocytes; the significant down-regulation of ACAD may indirectly participate in the occurrence process of abnormal structure and function of IgAN renal tubular epithelial cells by affecting fatty acid metabolism in the cells; and the significant up-regulation of COL1A1 may participate in the accumulation of extracellular matrix in the renal interstitium of IgAN, and play a certain role in promoting the renal interstitial fibrosis. The combination of ACTN4, ACADS and COL1A1 has good prediction efficiency for the diagnosis of the severity of IgAN kidney tissue lesions, and the area under the ROC curve is 0.815, P 0.043. In addition, the immunohistochemical results also confirm the expression trend of the three proteins ACTN4, ACADS and COL1A1 in the corresponding kidney tissue substructures in proteomics.

The invention relates to application of an ILF3 gene in diagnosis or treatment of sepsis, and belongs to the technical field of biological medicines. It is found for the first time that the ILF3 gene is a macrophage-related differential expression gene of sepsis, the expression level of the ILF3 gene in plasma and alveolar lavage fluid of sepsis patients is obviously higher than that of healthy people, a primer pair capable of specifically recognizing and detecting the ILF3 gene is designed, a mouse with the ILF3 gene in macrophage being specifically knocked out is constructed, and the ILF3 gene in the macrophage is specifically knocked out. The invention also designs si-ILF3 capable of specifically interfering with the expression level of the ILF3 gene. The ILF3 gene is used as a sepsis diagnosis marker and a sepsis treatment target, the application of the ILF3 gene detection reagent in preparation of sepsis diagnosis products and the application of si-ILF3 in preparation of sepsis treatment drugs are provided, and the si-ILF3 gene detection reagent is used for further diagnosis and treatment of sepsis patients.

The invention discloses a method for researching influence on hemolytic activity of marine microalgae based on a transcriptome technology, and relates to the field of hemolytic activity analys.The method comprises the steps that pretreatment is conducted on the marine microalgae based on culture requirements, and cystic morphological cell density and hemolytic activity of the marine microalgae are measured according to experimental design rules after pretreatment is completed; carrying out transcriptome sample collection operation by utilizing the marine microalgae subjected to pretreatment, constructing a library according to a transcriptome sample collection result, and obtaining a gene function annotation and a differential expression gene result; the growth conditions of the marine microalgae under different temperature conditions are analyzed according to cystic morphological cell density and hemolytic activity, and the regulatory gene influencing the hemolytic activity of the marine microalgae is obtained by combining gene function annotation and differential expression gene results. According to the method, the hemolytic activity of the marine microalgae cultured under different temperature conditions is extracted, so that the aim of researching related metabolic pathways possibly participating in toxin synthesis and hemolytic activity regulation is fulfilled.

The invention discloses application of an mRNAs marker in early diagnosis of lung signet-ring cell carcinoma and a kit. The marker is a combination of C1QA, CRISPLD2, ROBO4, SPARCL1, SFTPB, LAMC3, FN1, EMP1, CD68, THBS1, PRG4, ICAM1, PODXL, KDM6B, ENPP2, KLF10 and THBD (tetrahydrofuran). According to the invention, FFPE cancer tissue of a patient with primary pulmonary signet ring cell carcinoma diagnosed by an existing detection means in clinic is used as a sample, para-carcinoma tissue is used as a control sample, mRNA expression profiles of the cancer tissue and the control tissue are detected by adopting an RNA sealing technology, and 17 differentially expressed mRNA markers are found by applying statistics and a machine learning method. Based on the 17 found markers, a risk scoring model with high sensitivity and specificity is constructed, and the sensitivity gt of the model to early-stage lung signet-ring cell carcinoma diagnosis; the specificity is gt; 89%.

The invention provides a spatial transcriptome tissue specific expression gene identification method and system based on a multi-dimensional statistical index, and belongs to the technical field of gene identification, the method comprises the following steps: obtaining gene expression data corresponding to a plurality of genes in different cells, different cells belonging to different types of tissues; the gene expression data is data processed based on a space transcriptome; for each gene, determining a basic statistical feature and a differential expression feature corresponding to the gene based on the gene expression data corresponding to the gene in different cells; determining specific index characteristics of the gene based on the basic statistical characteristics of the gene; and determining a tissue specific expression gene from the plurality of genes based on the basic statistical characteristics, the differential expression characteristics and the specific index characteristics corresponding to each gene. According to the invention, the accuracy of tissue specific expression gene recognition can be improved.

The invention discloses an epigenetics method for improving the cryopreservation efficiency of sheep semen. The method comprises the following steps: extracting seminal fluid of Donflilien and Hu sheep hybrid F1-generation sheep, dividing the seminal fluid into a fresh group and a frozen group, carrying out somatic cell removal and small non-coding RNA extraction, screening out differentially expressed microRNAs by utilizing a Pandorah sequencing technology, analyzing a target gene and a signal channel of the microRNAs, and determining the seminal fluid of the Donflilien and Hu sheep hybrid F1-generation sheep. The small non-coding RNA related to sperm cryopreservation is found to mainly relate to key biological processes such as oxidative stress response and cell surface receptor signal channels. The screened differentially expressed small non-coding RNA is added into the frozen semen through methods such as in vitro chemical synthesis, so that the artificial fertilization conception rate of the frozen semen is remarkably increased.

According to the invention, 23 key miRNAs are identified in patients with liver injury caused by taking antituberculous drugs. Compared with patients who cannot cause liver injury by taking antituberculous drugs, the miRNAs are obviously differentially expressed in the patients who cannot cause liver injury by taking antituberculous drugs. Furthermore, five miRNAs are selected from the key miRNAs to construct a diagnosis model for drug-induced liver injury caused by tuberculosis and antituberculosis drugs. The model can accurately diagnose tuberculosis, and also can accurately diagnose drug-induced liver injury caused by antituberculosis drugs.

Applicants have discovered differential expression and activity of various miRNAs in neurodegenerative diseases. These miRNAs can serve as therapeutic targets for prevention and treatment of neurodegenerative diseases. Accordingly, embodiments of the invention include formulations and methods for treating neurodegenerative diseases such as dementia and Alzheimer's disease. The formulations and methods can include five microRNAs and two small molecule therapeutics. In aspects, the miRNAs are MIR-145-3p, let-7c-3p, MIR-383-5p, MIR-548aj-3p and MIR-548x-3p. In aspects, the small molecule therapeutics are GATC-49, fucosterol and fucoidan. In aspects, the compounds work synergistically with one another.

The invention discloses a marker combination, a kit thereof and application of the marker combination to prediction of diabetic peripheral neuropathy, the marker combination comprises human angiotensin (ANG), human vascular endothelial cell adhesion molecule 1 (VCAM1) and human mannan binding lectin serine peptide 1 (MASP1), TMT quantitative proteomics and PRM targeted proteomics are adopted, and the marker combination is used for detecting diabetic peripheral neuropathy. A technology combination strategy of an ELISA experiment is adopted, and key differential expression proteins such as MASP1, VCAM1 and ANG in serum exosomes of patients with diabetic peripheral neuropathy are systematically screened and verified. By establishing a multi-model machine learning diagnosis system based on logistic regression, a support vector machine and a naive Bayes algorithm, simple and rapid identification of diabetic peripheral neuropathy patients is realized, and a new experimental basis is provided for clarification of a molecular regulation network of diabetic peripheral neuropathy; more importantly, a rapid screening tool with clinical application potential is developed.

The application discloses biomarkers for early diagnosis of lung adenocarcinoma and / or classification of unknown lung nodules and application thereof, and relates to the technical field of biological medicine.The biomarkers are piR-hsa-8429916 or piR-hsa-8393202.Two core biomarkers, piR-hsa-8393202 and piR-hsa-8429916, are successfully identified by screening and verifying piRNAs differentially expressed in lung adenocarcinoma tissues and serum, and the expression levels of the biomarkers are significantly positively correlated with tumor load.The diagnostic value of piR-hsa-8393202 and piR-hsa-8429916 in early diagnosis of lung adenocarcinoma and classification of lung nodules is significantly better than that of a traditional CEA marker.The application provides an innovative solution for early diagnosis of lung adenocarcinoma and risk stratification of lung nodules.

The invention discloses application of a zanthoxylum bungeanum ZaMYC2 gene in resistance of zanthoxylum bungeanum rust, and belongs to the technical field of plant breeding. According to a transcriptome sequencing result, differential expression of the Zanthoxylum bungeanum ZaMYC2 gene is found. In order to further clarify the function of the ZaMYC2 gene, the invention verifies the function of ZaMYC2 in pepper rust resistance through an expression technology and an RNAi technology. Experimental results show that green spots appear on the backs of the bunge pricklyash leaves in the overexpression treatment group, and compared with a control group, the symptom is obviously relieved; the disease symptom of the zanthoxylum bungeanum in the silence treatment group is the most serious, and orange spore piles cover the whole leaf backs. The results show that the ZaMYC2 gene plays an important role in the rust disease resistance process of zanthoxylum armatum. Therefore, the invention provides a basis for further breeding of resistant varieties, in-depth study on the disease-resistant mechanism of the pepper rust and research and development of a new strategy for continuously and effectively preventing and treating the forest rust.

The application belongs to the field of plant biotechnology, and particularly relates to a cucumber CsODO1 gene and application thereof, and is a MYB transcription factor capable of being combined with a CsCSE1 promoter, which is screened through a yeast single hybridization. It is proved through EMSA and tobacco transient expression analysis that the CsODO1 gene directly and specifically combines with a "CAACCA" sequence in the CsCSE1 promoter, and inhibits the expression of the CsCSE1 gene. The CsODO1 gene can be induced to express by a powdery mildew fungus, and is differentially expressed in the cucumber infected by the powdery mildew fungus. It is found through a cucumber cotyledon transient transformation system mediated by an agrobacterium that the CsODO1 gene negatively regulates the biosynthesis of lignin and the resistance of the cucumber to the powdery mildew fungus. The application provides a new reference gene resource for the cultivation of a cucumber disease-resistant variety, and provides a new thought for the research on the molecular mechanism of the plant immunity mediated by the lignin pathway.

The invention provides an acute pancreatitis intestinal micro-ecological marker and application thereof, and belongs to the technical field of disease diagnosis. According to the method, 20 intestinal microbe markers with differential expression are screened based on samples of acute pancreatitis patients and healthy people, an acute pancreatitis prediction model is constructed by adopting a random forest model, and results show that the method has relatively high prediction accuracy, and the AUC value is 0.98. The acute pancreatitis intestinal micro-ecological marker and the constructed prediction model thereof can be used for early diagnosis of clinical acute pancreatitis.

The invention provides a feature gene selection method and system based on deep learning attribution analysis and beam combination optimization, and relates to the technical field of signal analysis, and the method comprises the following steps: obtaining single cell RNA sequencing data and batch RNA sequencing data; the method comprises the following steps: based on single-cell RNA sequencing data, obtaining an initial gene pool aiming at a plurality of disease subtypes through a consensus screening strategy fusing XGBoost multi-dimensional importance measurement and deep learning SHAP attribution analysis; performing first-stage optimization on the gene list of each subtype by taking the initial gene pool as a starting point and adopting beam combination search and based on a global discrimination objective function to obtain a first-stage optimized gene set; integrating the first-stage optimized gene set with the differential expression gene set of the batch RNA sequencing data, and carrying out second-stage optimization by adopting bundle combination search again to obtain a second-stage optimized gene set; and performing cross validation integration on the second-stage optimized gene set, and outputting a final feature gene set.

The application discloses a kind of based on multi-omics deep learning colorectal cancer liver metastasis detection method and system, comprising: extracting the feature gene group with CRC transfer-metabolic dual function, and construct CRC transfer risk prediction model foundation, based on analysis CRC transfer risk probability to screen the molecular marker with CRC transfer nature and CRLM specific characteristics as initial candidate biomarker;Meanwhile, from the metabolome to obtain the differential expression metabolite corresponding to CRLM patient sample and LCRC patient sample metabolome, and the enrichment pathway analysis of transcriptome and metabolome is combined to construct CRLM multi-layer core metabolic network, for the screening core biomarker of colorectal cancer liver metastasis accurate detection in accordance with, entire method can effectively screen the biomarker for detecting colorectal cancer liver metastasis.

The invention relates to the technical field of methylation detection site detection, and particularly provides an early gastric cancer lymph node metastasis risk prediction method, system, application and medium, and the method comprises the following steps: obtaining a gastric cancer public data set containing a DNA methylation chip data set and an RNA sequencing data set, and carrying out sample screening, quality control and grouping processing to obtain eight quality control grouping samples; carrying out methylation and RNA difference analysis on the quality control grouped samples to obtain a related gene set of differential methylation sites and differential methylation regions and an RNA differential expression gene set; a gene set of differential methylation sites and an RNA differential expression gene set are integrated and screened to obtain eight target genes. The system comprises a sample acquisition module, a gene analysis module and a gene screening module. Target genes are analyzed and screened on the basis of database biological information, and methylation detection sites for histopathological specimens are screened in combination with lymph node metastasis positive and negative early gastric cancer histological sample verification.

The invention discloses application of a reagent for detecting RGS12 in preparation of a diagnostic reagent for neoadjuvant immunochemotherapy resistance of local advanced esophageal squamous carcinoma. Differential expression proteins in neoadjuvant immunochemotherapy resistance tissues of local advanced esophageal squamous carcinoma are screened out through proteomics; a new marker is provided for diagnosis of local advanced esophageal squamous cell carcinoma immunochemotherapy drug resistance, and a basis is also provided for development and future development of a local advanced esophageal squamous cell carcinoma immunochemotherapy drug resistance diagnosis method.