28 results about "Mirna expression" patented technology

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 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 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 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.

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 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 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 invention relates to a data processing method and device based on multi-modal contrast fusion and a graph neural network, and a medium. The method comprises the following steps: collecting multi-modal biomedical data set samples of mRNA expression data, DNA methylation data and miRNA expression data; embedded matrixes of three modes are obtained through an independent feedforward neural network encoder; adopting a contrast learning mechanism based on NT-Xent to carry out unsupervised contrast alignment on the embedded matrixes of different modalities, and generating aligned embedded matrixes of three modalities; embedding and stacking the aligned modalities into a sequence, and inputting the sequence into a multi-layer Transform encoder to obtain a unified fusion representation; normalizing the fusion representation, and constructing a sample similarity graph structure; and based on the graph structure and the fusion representation, node high-order adjacency features are extracted through a three-layer graph convolutional network, sample classification is completed in combination with two full-connection layers, and a sample classification result is output. Compared with the prior art, the method has the advantages of cross-modal data fusion optimization, medical data discrimination enhancement, high efficiency and the like.

The present invention relates to miRNA expression constructs, which are useful e.g. in gene and gene-modified cell therapies. In particular, the present invention relates to multiplexed miRNA expression constructs with improved efficiency, wherein multiple miRNA hairpins are expressed from within an intron.

This invention provides a method and system for detecting serum miRNA expression levels in patients, relating to the field of biomedical detection. The method includes: simultaneously acquiring multi-channel fluorescence signals; firstly, extracting common temporal-spatial variation patterns across channels through statistical analysis; then, separating systematic common pattern interference signals using adaptive filtering or surface fitting techniques; and precisely subtracting this interference from the physical coordinates of each reaction channel to reconstruct the true reaction process. Subsequently, the reconstructed curves are normalized in amplitude and nonlinearly aligned with the time axis to unify the signal scale and kinetic benchmark. Finally, feature parameters are extracted and combined with a standard curve model to quantify the target miRNA expression level with high precision. This invention simultaneously solves the problems of reaction kinetic heterogeneity caused by serum matrix effects and the difficulty in removing systematic noise caused by instrument drift, significantly improving the accuracy, reliability, and repeatability of multi-sample parallel detection.

The invention belongs to the technical field of gene technology and biomedicine, and provides a construction method of a colorectal cancer prognosis model based on M7G modification, which comprises the following steps: firstly, acquiring and downloading the miRNA expression quantity of METTL1 and cofactors WDR4 thereof of 539 tumor samples and 9 normal samples from a TCGA database, and then analyzing differential genes between the tumor samples and the normal samples by using an edgeR packet, then selecting 20 miRNAs before the top according to a difference multiple, and drawing a heat map and a volcano map by using a pheatmap and a gplo2 packet so as to present different expression modes of the 20 genes; the colorectal cancer prognosis model consisting of 13 M7G modification related miRNAs is established, can be used as a prognosis evaluation index, and has potential values of helping patients to layer and formulate personalized treatment strategies; and meanwhile, the M7G modification has potential influence on immune cell subset infiltration and immune function in the tumor microenvironment, which is possibly beneficial to deepening the understanding of people on the colorectal cancer tumor microenvironment and brings new hope for the development of immunotherapy intervention in the future.

The invention discloses a DNA molecule calculation method and system for parallel detection of various miRNA expression profile abnormalities, and relates to the technical field of biomolecule calculation, and the method comprises the following steps: determining weight parameters of target miRNA; designing a DNA enzyme detection probe and an inactivated DNA enzyme detection probe for the target miRNA, setting a first substrate chain for the DNA enzyme detection probe of the target miRNA with a positive weight parameter, and setting a second substrate chain, a reference DNA chain, a reference DNA enzyme detection probe and a third substrate chain for the DNA enzyme detection probe of the target miRNA with a negative weight parameter to obtain a detection reaction system; adding a biological sample to be detected into the detection reaction system for hybridization reaction to obtain a fluorescence spectrum signal generated by a fluorescence reporter group in the detection reaction system; and performing correction by using the linear correction model, and comparing a correction result with a preset discrimination threshold to obtain a target expression profile data classification result.

The invention relates to application of a combined miRNA expression quantity detection agent in preparation of an endometriosis diagnostic agent and an endometriosis diagnostic kit. The expression quantity of the combined miRNA in the serum exosome is used as a diagnostic marker of endometriosis, the sensitivity is 0.846, the specificity is 0.898, the false positive rate is 0.102, and the ROC curve AUC value is 0.921. Therefore, both the sensitivity and the specificity of the combined miRNA are very high, and the combined miRNA has a relatively good diagnostic value.

The present invention relates to a method for determining the state of the endometrium using a sample from a subject, for example, a plasma sample, and includes: (a) obtaining a sample from a subject or using a sample obtained from a subject, where the miRNA expression profile includes the expression levels of multiple miRNAs; and (b) analyzing the miRNA expression profile using a computer-based machine learning model to obtain a predictive score.