18 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 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 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 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 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 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 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.

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.