41 results about "Mirna expression" patented technology

The invention discloses a miRNA and disease relation prediction system and method based on causal feature selection. According to the system, the accuracy of miRNA and disease relation prediction is improved through a plurality of modules such as data acquisition, negative sample selection, feature selection and causal analysis, model training and evaluation and the like. The data acquisition module is used for acquiring miRNA expression data and disease characteristics from a biomedical database; the negative sample selection module is used for grouping unknown miRNA-disease relationships through k-means clustering and randomly selecting negative samples; the feature selection module adopts a causal feature selection algorithm to construct a Markov blanket so as to screen out miRNA features directly related to disease states, and redundancy is reduced; the model training module uses a single machine learning algorithm for training, and optimizes the model performance through cross validation; and finally, the evaluation module evaluates the model effect through indexes such as AUROC and AUPR. According to the method, the accuracy of miRNA and disease relation prediction is remarkably improved, and important support is provided for medical research.

The invention belongs to the technical field of biological medicine, and particularly relates to an extracellular vesicle drug delivery system, a preparation method thereof and application of the extracellular vesicle drug delivery system in treatment of Alzheimer's disease. According to the invention, one or more of stilbene glucoside, emodin, kaempferol, resveratrol and quercetin are used for regulating and controlling the expression of miRNA (micro Ribonucleic Acid) related to the disease progress in the extracellular vesicles, and the result shows that one or more of miR-let-7c-5p, miR-486-5p, miR-132-3p, miR-160b and miR-129-5p is remarkably up-regulated, and one or more of miR-342-3p, miR-16-5p and miR-125b-5p is remarkably down-regulated. The regulated extracellular vesicles can be used for treating Alzheimer's disease, relieving Tau protein abnormal phosphorylation, reducing amyloid protein beta deposition, inhibiting microglial cell activation, protecting neuronal cells and relieving memory deficits.

The invention provides an application technology for screening lung cancer high-risk groups, early auxiliary diagnosis and postoperative treatment effect monitoring of lung cancer patients through model and computing power, and belongs to the fields of molecular biotechnology, medical diagnosis and treatment and massive health. The method comprises the following steps: collecting samples of human body liquid, exosomes and the like, detecting the DNA methylation level, miRNA expression quantity, protein level and the quantity of molecular markers such as autoantibodies, exosomes, kits and the like related to the lung cancer by virtue of a modern detection technology, and obtaining individual precision medical treatment and clinical application by virtue of a model and computing power (including a software algorithm, a DeepSeek large model, intelligent agent application and an artificial intelligence method). The problems of lung cancer high-risk group screening, early auxiliary diagnosis, pathological typing, clinical staging, metastatic state, postoperative curative effect evaluation and poor accuracy of national approved kits are solved. The non-destructive detection technology can prevent and treat lung cancer in time, is precise in medical treatment and good in health prevention, and has wide social benefits and popularization and use values. The traditional Chinese medicine composition also has a popularization effect on other non-lung cancers.

The invention provides a patient serum miRNA expression level detection method and system, and relates to the field of biomedical detection.The method comprises the steps that on the basis of synchronously collecting multi-channel fluorescence signals, a common time-space change mode of all channels is extracted through statistical analysis, and a time-space change mode of all the channels is obtained; then systematic common mode interference signals are separated by means of adaptive filtering or curved surface fitting and the like, interference is accurately deducted for physical coordinates of each reaction channel, a real reaction process is reconstructed, then amplitude standardization and time axis nonlinear alignment are performed on a reconstruction curve, signal scales and dynamic references are unified, and the real reaction process is reconstructed. And finally extracting characteristic parameters and quantifying the expression level of the target miRNA with high precision in combination with a standard curve model. The problems of reaction kinetics heterogeneity caused by a serum matrix effect and difficulty in stripping systematic noise caused by instrument drifting are solved at the same time, and the accuracy, the reliability and the repeatability of multi-sample parallel detection are greatly improved.

The present invention discloses a method for enriching small fragment cDNA of single cell sequencing for identifying miRNA expression in single cell transcriptome, using SPRISlect magnetic beads to sort library fragments, adding PEG10000, isopropanol and trichlorohexammine cobalt complex to the magnetic bead binding solution to improve the enrichment of small fragments of 100 to 300 bp. The present invention innovatively integrates DNA linear amplification and magnetic bead small fragment sorting technology with 10xGenomics single cell library construction method, solving the problem of small fragment PrimRNA data loss caused by insufficient small fragment enrichment ability in the single cell sequencing process in the prior art. The present invention has broad application prospects.

The invention provides a cancer diagnosis model development method. The cancer diagnosis model development method comprises the steps of constructing a training set and establishing a diagnosis model on the training set. The training set includes miRNA expression profiles from non-cancer subjects and cancer patients having two or more cancer types, and establishing the diagnostic model includes calculating a diagnostic index based on a selected miRNA biomarker set, the selected miRNA biomarker set being obtained from a miRNA ranking in a differential expression analysis of the miRNA expression profiles in the training set. Methods of detecting a target cancer by means of the diagnostic model so developed are also provided. A 4-miRNA-based diagnostic model shows high performance in a verification set, and can realize the sensitivity greater than or equal to 0.98 while maintaining the specificity of 0.99 when detecting various cancers including lung cancer, gastric cancer, biliary tract cancer, bladder cancer, prostate cancer and glioma.

The present invention provides a method of determining endometrial status using a sample (e.g., a plasma sample) from a subject, comprising: (a) performing an assay on a blood sample from a subject to determine a miRNA expression profile wherein the miRNA expression profile comprises a plurality of expression levels of miRNAs, and (b) analyzing the miRNA expression profile using a computer-based machine learning model to obtain a predicted score.

The disclosure relates to methods for determining an endometrial status using a sample, for example, a blood plasma sample, from a subject, comprising: (a) performing an assay on the blood sample from the subject to determine a miRNA expression profile, wherein the miRNA expression profile comprises expression levels of a plurality of miRNA and (b) analyzing the miRNA expression profile to obtain a predictive score using a computer-based machine-learning model.

The invention provides a computing power device application technology for screening of liver cancer high-risk groups, early auxiliary diagnosis and postoperative treatment monitoring of patients, and belongs to the fields of biotechnology, medical diagnosis and treatment and massive health. By collecting samples of human body liquid such as peripheral blood, plasma, serum, saliva and the like and using biological and medical detection technologies, molecular markers (nationally approved that each kit is equal to the molecular marker) of a target gene methylation level, miRNA expression quantity and protein level or immune index quantity are detected; the problems of low sensitivity and poor accuracy in liver cancer high-risk group screening, early auxiliary diagnosis and patient postoperative treatment monitoring (including kits) are solved by using a computing power device application technology according to the detection result of any combination of the molecular markers, the precision can be greatly improved to prevent excessive medical treatment, and the purposes of precise medical treatment and clinical application are achieved. The method has important practical significance on screening of high-risk groups of liver cancer, early auxiliary diagnosis and postoperative treatment monitoring of patients, and has wide social benefits and use values.

The disclosure relates to methods for determining an endometrial status using a sample, for example, a blood plasma sample, from a subject, comprising: (a) performing an assay on the blood sample from the subject to determine a miRNA expression profile, wherein the miRNA expression profile comprises expression levels of a plurality of miRNA and (b) analyzing the miRNA expression profile to obtain a predictive score using a computer-based machine-learning model.

This invention discloses a method and kit for quantitative detection of circularized rolling circle amplified miRNAs. The method utilizes T4 RNA ligase to ligate the 3'-OH and 5'-phosphate ends of the target miRNA to form a circular miRNA. Using the circularized miRNA as a template, isothermal rolling circle amplification is performed using phi29 DNA polymerase to generate a large number of single-stranded DNA sequences with repetitive sequences. A universal molecular beacon is used to monitor the fluorescence signal of the amplification products in real time, achieving highly sensitive quantitative detection of miRNAs. This method has advantages such as high sensitivity, high specificity, and a wide linear detection range. It eliminates the need to design specific reverse transcription primers for each miRNA, can be extended to multiplex detection, and is suitable for clinical applications such as early tumor diagnosis, drug efficacy evaluation, and single-cell miRNA expression profiling.

A system for generating a hepatocellular carcinoma (HCC) report for a subject based on blood-based molecular profiling is provided. The system includes a sample preparation module configured to process a blood sample by isolating both plasma and serum fractions. A nucleic acid extraction module extracts a microRNA (miRNA) profile from the plasma fraction, and a real-time PCR module detects and quantifies the expression levels of a predefined panel of miRNAs, including miR-361-5p, miR-130a-3p, miR-27a-3p, miR-30d-5p, and miR-193a-5p. The expression levels of the predefined panel of miRNAs are used by a trained machine learning classifier to generate a HCC risk classification categorizing the subject into one of HCC risk levels. An alpha-fetoprotein (AFP) level detected and quantified from the serum fraction may also be used in combination with the miRNA expression levels in the HCC risk classification for enhanced prediction accuracy.

The invention belongs to the technical field of medicines, and discloses an application of rhynchophylline in preparation of a medicine for reversing organ injuries, and the organ injuries are heart injuries and liver injuries induced by ketamine. According to the invention, ketamine is used for inducing miRNA expression of mouse heart, liver and PBMCs to be up-regulated / down-regulated, and then rhynchophylline is used for intervention, and the miRNA expression is correspondingly changed (down-regulated / up-regulated), so that a gene intervention regulation mechanism of ketamine addiction to occurrence and development of changes of heart, liver and peripheral blood immune functions and the like can be further known; moreover, the rhynchophylline can act on miRNA change caused by ketamine addiction in a multi-target manner, and heart injury, liver injury and PBMCs (peripheral blood mononuclear cells) related immunologic function abnormality caused by ketamine abuse can be effectively intervened.

The invention discloses miRNA (micro Ribonucleic Acid), a miRNA simulant and application of the miRNA simulant to prevention and control of spodoptera frugiperda. According to the invention, a miRNA, namely novel-miR-111, is found in spodoptera frugiperda, and a miRNA simulant capable of promoting the expression of the miRNA is used for feeding the spodoptera frugiperda, so that the expression of immune-related genes in the spodoptera frugiperda can be inhibited and the defense of the spodoptera frugiperda can be reduced by promoting the expression of the miRNA. In addition, by promoting the expression of the miRNA, the proliferation of the AcMNPV virus in the spodoptera frugiperda can be promoted, and the death rate of the spodoptera frugiperda infected by the AcMNPV virus is increased. Therefore, the invention provides the reagent for promoting the expression of the novel-miR-111 and the application of the AcMNPV virus in the aspect of preventing and treating the spodoptera frugiperda. The method is beneficial to prevention and control of the spodoptera frugiperda, and harm of the spodoptera frugiperda to agriculture

The invention provides a breast cancer risk assessment model construction method based on miRNA and a genetic algorithm and a model, and relates to the technical field of model construction based on the genetic algorithm, and the method comprises the steps: obtaining miRNA expression data of a breast cancer patient and a healthy control to obtain a training sample set, taking the training sample set as training data, carrying out cleaning and standardization treatment; setting genetic algorithm parameters, and defining a chromosome coding scheme; based on a predefined fitness function, performing iterative evolution on the population through a genetic algorithm to search for an optimal chromosome; and determining a final feature set according to the optimal chromosome, and training based on the feature set and all the training data to obtain a final risk assessment model. The evaluation model constructed by the method not only can more comprehensively reflect the complex biological basis of the disease, but also can effectively reduce the dependence on initial feature selection, and improves the ability of the model to resist data noise.

The invention provides an application technology for enabling screening, early auxiliary diagnosis and postoperative curative effect evaluation of gynecological cancer high-risk groups through an artificial intelligence algorithm, and belongs to the field of molecular biology, medical diagnosis and treatment and disease prevention. The method comprises the following steps: collecting samples of human body liquid, exosomes and the like, detecting the DNA methylation level, miRNA expression quantity, protein level and the quantity of molecular markers such as autoantibodies, exosomes, kits and the like of the gynecological cancer by virtue of a modern detection technology, and obtaining individual precision medical treatment by virtue of a model and computing power (including a software algorithm, a large model, intelligent agent application and an artificial intelligence method). The problems of screening of gynecological cancer high-risk groups, early auxiliary diagnosis, pathological typing, clinical staging, metastatic state, postoperative curative effect evaluation and poor accuracy of national approved kits are solved, and the non-destructive detection technology can be used for timely prevention, precise medical treatment and cancer development tendency analysis, and has wide social benefits and popularization and use values. And the traditional Chinese medicine also has a popularization effect on non-gynecological cancers and other cancers.

The present disclosure relates to a tissue-specific promoter system for expressing microRNA (miRNA) for RNA interference-based methods of gene therapy. In these systems, the miRNA will inhibit gene expression or replace natural miRNA expression using microRNA.

In general terms present invention proposes a method for multi-cancer management in a subject. The method comprises obtaining a miRNA expression profiling raw data; selecting a quality miRNA expression profiling raw data from amongst the obtained miRNA expression profiling raw data; converting the quality miRNA expression profiling raw data into a formatted data; and subjecting the formatted data to an artificial intelligence-based pipeline, for multi-cancer early detection and diagnosis in the subject. The present invention also proposes a system for multi-cancer management in a subject. The system comprises a processor configured to perform steps of the aforementioned method.

The invention discloses a free miRNA (micro Ribonucleic Acid) extraction lysis buffer and an extraction method, the miRNA extraction lysis buffer comprises the following components: 0.1 mol / L to 0.5 mol / L of Tris-HCl, 3 mol / L to 6 mol / L of guanidine isothiocyanate, 0.15 mol / L to 0.30 mol / L of potassium chloride and 2.00 mol / L to 5.30 mol / L of N, N-dimethylacetamide. The N, N-dimethylacetamide is added into the miRNA extraction lysis buffer based on guanidinium isothiocyanate, so that the yield of miRNA can be improved, the sensitivity of a clinical sample miRNA detection reagent is improved, the miRNA extraction stability is remarkably improved, miRNA expression quantity deviation caused by a nucleic acid extraction link is reduced, and finally the quantitative accuracy of sample miRNA is improved.

The invention relates to an S12micro model for cancer auxiliary diagnosis and prognosis evaluation and application of the S12micro model. According to the method, miRNA expression profiles of more than 20000 cases of samples of 8 common data sets are analyzed, 113 combinations of 12 machine learning algorithms are adopted for modeling and verification, 12 key miRNAs are screened out, and an S12micro model is constructed. The average AUC of the model in a large-scale verification queue is up to 0.987 and is obviously superior to that of the existing 42 serum miRNA marker combinations, and the excellent performance of the serum miRNA marker combination is further verified through clinical samples. The S12micro model is based on a serum sample, does not need invasive operation, has the detection cost lower than that of imaging examination, has the advantages of high sensitivity, high specificity and noninvasiveness, is suitable for early screening and auxiliary diagnosis of various cancers, is higher in universality, can effectively fill the blank of accurate diagnosis and prognosis evaluation of the cancers, and has a wide application prospect. And the method has important practical significance, and has extremely high social value and market application prospect.

The embodiment of the specification provides a disease-related miRNA prediction method and system based on a deep autoencoder, wherein the method comprises the following steps: obtaining miRNA expression profile data of samples from a TCGA database, and performing standardization processing on the obtained miRNA expression profile data respectively; the samples comprise disease samples and normal samples; filling zero values in the miRNA expression profile data after the standardization processing by using a matrix decomposition method, and training a deep autoencoder model by using the filled miRNA expression profile data; training a reverse encoder based on the deep autoencoder model, obtaining the miRNA expression profile data of the disease samples and the disease correlation size according to the reverse encoder, and obtaining miRNAs with high disease correlation. The application can discover new disease-related miRNAs, and promote the diagnosis and treatment of diseases.

The invention belongs to the technical field of molecular diagnosis, and discloses a molecular diagnosis kit related to cardiovascular diseases. The molecular diagnosis kit related to cardiovascular diseases comprises a multiple gene mutation detection module, a high-sensitivity marker detection module, a miRNA expression level detection module, a high-sensitivity rare mutation detection module, an automatic sample treatment and analysis module, a gene-protein integration analysis module and a pharmacogenomics guidance module. Through the application of the kit, the diagnosis efficiency and accuracy of a hospital are remarkably improved, namely, a doctor can comprehensively know the molecular state of a patient through multi-dimensional detection, and deeper disease assessment is provided for multi-level information from genes, RNA (Ribonucleic Acid) to protein. High-sensitivity detection enables hospitals to detect low-abundance biomarkers through digital PCR and immunocapture technologies, diseases can be found in the early stage, and the success rate of early intervention is increased.

The application discloses a kind of upstream cell-miRNA-downstream cell network construction method. By identifying primary miRNA in single cell nucleus transcriptome data and its expression data in mRNA cell cluster, upstream cell and miRNA relationship pair can be obtained; by correlating exosome miRNA expression data, single cell mRNA expression data, miRNA and downstream cell type gene / mRNA relationship pair can be obtained; finally, based on the results of the first two methods and single cell transcriptome cell communication data, a complete upstream cell-miRNA-downstream cell functional interaction regulation network can be constructed, which provides data support for identifying specific miRNA source cell type and downstream regulatory cell type, and clarifying the interaction and regulation between different cell types. The complete technical solution of exosome miRNA sequencing analysis and single cell nucleus sequencing analysis from experiment to bioinformatics analysis is realized. The application also discloses a system for realizing the above method and application of the method.

The present invention relates to donor cells engineered for use in general donor cell therapy, for allogeneic, ready-to-use administration, and with greater persistence in the immune system of a host. The invention also relates to the use of miRNA expression constructs in such engineered donor cells.

The invention provides application of a reagent for regulating and controlling miRNA expression of extracellular vesicles in relieving cognitive impairment, and researches find that the extracellular vesicles released by intestinal epithelial cells of inflammatory bowel disease and aging mice are rich in miRNA-16-5p, and the miRNA-16-5p can be transferred into hippocampal neural stem cells. The miRNA-16-5p is used for delaying hippocampal neurogenesis by targeting CDK1 protein, so that inflammatory bowel diseases and age-related cognitive impairment are induced. In addition, the invention also finds that the skatole generated by the bacteroides promotes cognitive impairment by up-regulating miRNA-16-5p in individuals suffering from inflammatory bowel diseases and aging. Compared with the prior art, another intestinal bacterial metabolite vitamin B12 can down-regulate miRNA-16-5p, so that the development of IBD and senescence individual cognitive impairment is relieved.

The invention discloses a decoupling comparison multi-view clustering cancer subtype recognition method, belongs to the technical field of biological information, and relates to a cancer subtype recognition method. The method aims at solving the problems that in an existing multi-omics data cancer subtype recognition method, the relation between groups is difficult to effectively capture, most methods depend on random sampling in the negative sample pair construction process, false negative samples are likely to be caused, and therefore the recognition accuracy is affected. The method comprises the following steps: S1, acquiring a cancer data set, wherein each kind of cancer data in the cancer data set comprises mRNA expression data, DNA methylation data and miRNA expression data; s2, the preprocessed mRNA feature data, DNA methylation feature data and miRNA feature data are obtained; s3, a trained DCMC model is obtained; s4, obtaining mRNA expression data, DNA methylation data or miRNA expression data to be detected; and realizing subtype clustering of the data based on the trained DCMC model.

The invention relates to the technical field of breeding of disease-resistant varieties of plants, in particular to application of miRNA (micro Ribonucleic Acid) of Chinese roses in gray mold resistance, the miRNA is novel-miR103, a mature sequence of the miRNA is shown as SEQ ID NO.1, and a precursor sequence of the miRNA is shown as SEQ ID NO.2; an interference vector containing SEQ ID NO.3 is constructed through a short tandem target simulation method and transferred into Chinese roses, the gray mold resistance of the Chinese roses can be remarkably improved by down-regulating the expression of the miRNA, the resistance can be reduced by up-regulating the expression of the overexpression vector constructed through an artificial microRNA method and transferred into the Chinese roses, and the invention further discloses application of the miRNA interference preparation and application of the miRNA interference preparation in gray mold resistance breeding of the Chinese roses. According to the application of the Chinese rose miRNA in gray mold resistance, the problems of cost, pollution and pathogenic bacterium drug resistance of chemical prevention and treatment can be solved, a clear molecular target and a technical path are provided, an important foundation is laid for improvement of Chinese rose disease resistance breeding, and the application prospect in the aspect of Chinese rose gray mold prevention and treatment is good.

The invention discloses an exosome efficient loading miRNA expression vector as well as preparation and application thereof, and belongs to the technical field of miRNA expression vectors. According to the present invention, the expression vector for efficiently loading the miRNA on the exosome is provided, the expression vector is formed by compounding the modified pre-miR-423'skeleton and the pcDNA6.2-EmGFP-mir9 vector, and the expression vector can effectively improve the efficiency of the miR-423 entering the exosome; the expression sequence of miR-423 in the expression vector can be replaced by the expression sequences of other miRNAs, so that compared with the existing general miRNA expression vector, the effect of remarkably improving the exosome entering efficiency of other exogenous miRNAs can be achieved; according to the provided exosome efficient loading miRNA expression vector, the method for loading the exogenous miRNA is simple and easy to operate, and the exosome efficient loading miRNA expression vector is expected to be used for improving the loading efficiency of therapeutic miRNA in the exosome and improving the therapeutic effect of exosome mediated targeted drug delivery.

The invention discloses an exosome miRNAs biomarker for evaluating the radiation exposure dose of a human body and application of the exosome miRNAs biomarker, the radiation exposure dose is calculated according to the dose effect relationship between the expression quantity of the exosome miRNAs and the radiation exposure dose, and the exosome miRNAs comprise miR-664b-3p, miR-551b-3p, miR-181b-5p, miR-125b-5p, miR-27a-3p, miR-18a-5p, miR-29a-3p and let-7i-5p. The method has the advantages of being convenient and minimally invasive in sampling, easy and convenient to operate and high in flux, the problems that in the prior art, the process is tedious, and consumed time is long can be solved, and the requirement for dose evaluation on large-scale crowds in nuclear and radiation emergencies is met.

The present invention relates to a method and system for constructing a sepsis miRNA biomarker model based on an evolutionary algorithm, belonging to the field of bioinformatics. First, dimensionality reduction processing is performed on the miRNA expression matrix. Then, a search objective function is constructed, with maximizing the training model performance and eliminating the multicollinearity among miRNA screening results as the optimization objectives. Next, an improved genetic algorithm search strategy is adopted to decompose the search objective into multiple sub-problems for solution. For example, a three-classification problem is decomposed into three binary-classification problems to separately search for the optimal miRNA combinations for identifying healthy patients, identifying critically ill but non-sepsis patients, and identifying sepsis patients. Finally, through parameter tuning, the best miRNA biomarkers are obtained and a sepsis miRNA biomarker model is constructed, such as using machine learning algorithms like random forest or support vector machine. The present invention provides an efficient and accurate method for mining sepsis miRNA biomarkers.