2732 results about "RNA" patented technology

The invention belongs to the technical field of RNA biological prevention and treatment, and particularly relates to dsRNA for preventing and treating crop anthracnose and application of the dsRNA. The dsRNA is targeted inositol phosphatidylceramide (IPC) synthetase coding gene dsRNA, and is obtained by transcription of a part of sequence (SEQ ID No.1) of an inositol phosphatidylceramide (IPC) synthetase coding gene CaAUR1, the gene segment is a segment of a target gene for preventing and treating crop anthracnose, and the dsRNA obtained by transcription can obviously reduce pathogenicity of mango anthracnose bacteria, and has the effects of keeping mango fresh, preventing and treating anthracnose. And the compound can be used for preventing and treating the crop anthracnose or preparing products for preventing and treating the crop anthracnose.

The invention discloses an intestinal cancer metastasis prediction method and device based on spatial omics, a medium and equipment, and the method comprises the steps: collecting original multi-omics data, and carrying out modal alignment and quality control processing to obtain pre-processed multi-omics data comprising second spatial transcriptome data, second single-cell RNA sequencing data and second pathological image data; performing cross-modal semantic embedding on the second spatial transcriptome data based on the second single-cell RNA sequencing data to generate a spatial enhanced expression profile; performing multi-scale graph construction on the second spatial transcriptome data and the second pathological image data, and extracting spatial heterogeneity features; inputting the spatial enhancement expression spectrum and the spatial heterogeneity features into a pre-trained metastasis risk prediction model, and outputting a liver metastasis probability spatial heat map and a key driving feature list; and finally generating a clinical prediction report containing high-risk area positioning. According to the method, through dynamic optimization of spatial resolution and multi-scale feature collaborative modeling, the sensitivity of early transfer detection is remarkably improved.

The present invention relates to the field of tissue-derived cell identification, in particular to a method for identifying tissue-derived cells in the body fluid based on single-cell sequencing technology. In the present invention, on the basis of high-throughput single-cell RNA sequencing data of cell samples obtained from body fluids, by means of reference component analysis (RCA), expression of known tissue-related marker genes, and a tissue-derived cell prediction model constructed based on logistic regression, the specific identification of tissue-derived cells in body fluids is achieved.

The present invention discloses an interfering RNA for inhibiting PCSK9 gene and use thereof. The interfering RNA comprises a nucleotide sequence set forth in any one or two or more of SEQ ID NOs: 1-40, 73-96. The interfering RNA of the present invention can better target and silence hepatic PCSK9 mRNA, reduce the protein level of PCSK9, enhance LDL-C metabolism, and reduce serum cholesterol, providing a solid technical foundation for the development of siRNA medicaments for the prevention, treatment, and symptom alleviation of PCSK9 gene-mediated diseases.

Systems and methods for computer modeling in medicine. A sort of period table of medical models is described for personalized diagnostics, prognostics and therapeutics, including at least 80 major categories of medical models. Generative artificial intelligence and geometric deep learning techniques, and algorithms including 2D and 3D graph machine learning and GenAI algorithms, are described, tailored and applied to diagnostic disease description, prognostic prediction and therapeutic development and management, including generation of novel synthetic drugs. The AI and machine learning techniques and algorithms are applied to understand each individual's genetic, RNA and protein anomalies that represent the source of many unique patient diseases. AI-enabled software agents assist physicians and researchers in building patient medical models. Several personalized medicine applications of individualized medical modeling include cardiovascular disease, cancer, neurological disorders, immune system disorders and genetic diseases.

The invention discloses an interfering RNA (Ribonucleic Acid) for inhibiting a PCSK9 gene and application of the interfering RNA. The interfering RNA comprises any one or more than two nucleotide sequences as shown in SEQ ID NO: 1-40 and SEQ ID NO: 73-96. The interfering RNA can better target and silence mRNA of the liver PCSK9, reduce the protein level of the PCSK9, enhance LDL-C metabolism and reduce serum cholesterol, and a solid technical basis is provided for research and development of siRNA drugs for prevention and treatment of PCSK9 gene mediated diseases and symptom relief.

The technology described herein relates to 5'-modified nucleosides, nucleotides, oligonucleotides and double-stranded RNAs, e.g., siRNAs, and kits comprising them and methods of their use for inhibiting target genes.

Provided are variant Cas12f4 polypeptides, fusion proteins containing variant Cas12f4 polypeptides, nucleic acids encoding variant Cas12f4 polypeptides and fusion proteins, compositions and methods related to those variant Cas12f4 polypeptides and fusion proteins, and modified host cells comprising the variant Cas12f4 polypeptides and / or encoding nucleic acids. The variant Cas12f4 polypeptides disclosed herein exhibit improved functionality, stability, and / or other desirable properties and may be used in combination with guide Cas12f4 RNAs that can be used in a variety of applications ex vivo, in vitro, and in vivo.

The invention discloses an animal single cell data cell type annotation method, which is characterized by comprising the following steps: collecting Bulk RNA-seq data of purified cell types in various tissues and organs of a specific animal, and integrating the Bulk RNA-seq data into a reference data set after preprocessing; the method comprises the following steps: acquiring single-cell RNA-seq original data, screening the single-cell RNA-seq original data to obtain high-quality cells, screening high-variation genes from the high-quality cells, processing the high-variation genes, extracting principal components, performing dimensionality reduction on the principal components, and performing cell clustering based on a dimensionality reduction result to obtain cell clusters; and calculating expression similarity between the cell clusters and the reference data set based on the high-variation genes, determining initial cell types of the cell clusters according to a similarity result, and carrying out iterative tuning on the initial cell types with similar scores to obtain a final cell type annotation result. The method provides efficient and accurate technical support for animal single cell research.

The invention relates to a method for inhibiting in-vitro infection of a porcine epidemic diarrhea virus by using JPH203 and application. The JPH203 can be used for preparing an antiviral drug for inhibiting infection of the porcine epidemic diarrhea virus. JPH203 with the concentration of 5 [mu] M is added in the process that Vero cells are infected with PEDV, compared with a control group without JPH203, the virus infection condition, the protein expression quantity, the RNA content and the virus titer of the PEDV in a treatment group with JPH203 are all remarkably reduced, and it is indicated that JPH203 can be used for inhibiting in-vitro infection of the porcine epidemic diarrhea virus.

The invention provides a full-length gene sequence modeling method and system based on a neural network, and the method comprises the steps: constructing a first expression matrix for initial single-cell RNA sequencing data, and carrying out the quality control transformation of the first expression matrix to obtain a second expression matrix; inputting the second expression matrix into a preset binning embedding module to obtain a binning embedding matrix; maintaining and loading a gene pathway set through a knowledge base and a mapping module to obtain a binary mask matrix, and performing mask processing on the binning embedded matrix based on the binary mask matrix to obtain a pathway mask matrix; the path mask matrix is input into a preset attention state space model, the attention state space model comprises an encoder module, a jump connection module and a decoder module which are arranged in sequence, and a reconstruction tensor is output through the decoder module. According to the scheme, an efficient and extensible whole-gene annotation method is provided, and whole-gene expression input can be processed while the calculation efficiency is kept.

The invention provides application of TRMT61A and its inhibitor tetramethylthiuram disulfide in tumor immunotherapy, and relates to the technical field of biological medicine, clinical research proves that RNA m1A methyltransferase TRMT61A is highly expressed in tumor tissues and is related to poor prognosis of tumor patients, and can be used as one of tumor therapy targets. Meanwhile, high expression of the TRMT61A is related to poor prognosis of a tumor patient receiving anti-PD-1 immunotherapy, and after anti-PD-1 antibody immunotherapy is carried out on the patient with low TRMT61A expression level in the tumor of the patient, pathological complete relief is easier. Tetramethylthiuram disulfide inhibits TRMT61A, inhibits m1A modification regulation of TRMT61A on PD-L1 mRNA, increases PD-L1 protein expression, and is combined with a PD-1 antibody drug to significantly enhance the immunotherapy effect of the anti-PD-1 immune checkpoint drug in treating malignant tumors.

The invention provides a spatial omics data completion method and system based on a variational graph auto-encoder, and relates to the technical field of bioinformatics. Extracting partial common genes in the data pair to obtain a feature matrix; based on the spatial position information, obtaining a first sub-adjacency matrix of cells in the spatial transcriptomics sequencing data; respectively obtaining a second sub-adjacency matrix of the cells in the single-cell RNA sequencing data and a third sub-adjacency matrix of the cells in the data pair based on gene expression similarity; combining the first sub-adjacency matrix, the second sub-adjacency matrix and the third sub-adjacency matrix to obtain a final adjacency matrix; and inputting the feature matrix and the final adjacent matrix into a pre-trained variational graph auto-encoder network to complete the deletion gene of the space transcriptomics. According to the method, the position information and gene expression characteristics between idle data cells can be effectively utilized, errors can be reduced, and meanwhile, the similarity between complementation genes and true values can be improved.

The invention discloses an m5U modification site prediction method and device based on feature fusion, and the method comprises the steps: constructing an m5U-Hybrid Net model, integrating an RNA pre-training large model used for deep semantic feature extraction with features derived from a convolutional neural network after one-hot coding, inputting the integrated model into a layer of a full-connection neural network, and carrying out the prediction of the m5U modification site. And obtaining a m5U modification site prediction result. According to the method, the m5U modification site can be accurately predicted, and stable performance is shown in various verification scenes.

The invention discloses a system for detecting viral nucleic acid on the basis of a CRISPR (clustered regularly spaced short palindromic repeat) technology and an FET (field effect transistor) chip and application of the system, and relates to a method for detecting the viral nucleic acid on the basis of clustered CRISPR (clustered regularly spaced short palindromic repeat) and related proteins (Cas) and a field effect transistor (FET). The CRISPR-FET (clustered regularly interspaced short palindromic repeats-field effect transistor) detection system comprises a non-amplified CRISPR system, a reporter RNA (ribonucleic acid) and gold nanoparticles (AuNPs) connection system, a separation system and a field effect transistor chip detection system. The CRISPR-FET detection method provided by the invention has high sensitivity and high specificity on virus nucleic acid detection, and the lower limit of detection reaches a single copy (100 copies / [mu] L).

The present disclosure provides systems and methods for separating and characterizing oligonucleotides. Fixed dose combinations of small interfering RNAs can be subjected to denaturing ion pairing reverse phase liquid chromatography using optimal conditions to separate single RNA strands for purity analysis.

The invention belongs to the technical field of molecular diagnosis, and particularly discloses a high-risk HPV16 rapid detection system based on RPA-CRISPR / Cas12a, which is prepared by the following steps: (1) mixing a nucleic acid lysis solution containing Tris (pH = 8.0), NaHCO3, polyvinylpyrrolidone and Tween-20 with Proteinase K to treat a sample, and performing pyrolysis at room temperature for 5 minutes to obtain a nucleic acid template; (2) an RPA reaction system contains an RNA inhibitor, a reverse transcriptase and an RPA reaction essential enzyme, and after the template and the starting agent in the step (1) are added, RPA amplification is carried out at 37 DEG C; (3) dropping the reaction liquid on a colloidal gold test strip subjected to position exchange and transformation of a sample pad and a water absorption pad, and carrying out result interpretation; and (4) adding the RPA product into a CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) reaction system containing the LbCas12a protein, the specific gRNA and the probe. According to the scheme, a rapid, high-sensitivity and cross-reaction-free detection system of the HPV16 is realized by optimizing a nucleic acid lysis solution formula, designing a specific primer and gRNA and modifying a test strip for detection.

The invention provides a nucleotide mutation site prediction model construction and disease-related point mutation identification method. Specifically, the invention provides a deep learning model-fused nucleotide mutation site prediction model construction method and a disease-related point mutation identification method. According to the method, DNA point mutation and RNA point mutation can be recognized from transcriptome sequencing data in a high-sensitivity and high-specificity mode, and basic data is provided for explaining mutation generation mechanisms and functions on the whole transcriptome and genome level.

The present invention relates to modulators that can regulate, for example, inhibit the expression and / or activity of an inhibin subunit βE (INHBE), such as double-stranded RNA (dsRNA) active agents or antisense polynucleotide formulations. The present invention also relates to a method for inhibiting the expression and / or activity of INHBE by using such modulators, and a method for preventing and treating INHBE-related diseases in subjects (such as metabolic disorders or obesity or cardiovascular diseases, such as metabolic syndrome).

The invention discloses a single-cell data deep clustering method and device based on double auto-encoders and a medium, and relates to the technical field of single-cell RNA sequencing. The method comprises the following steps: acquiring original gene data of a single cell; an scDAEC model is constructed; the scDAEC model comprises a dynamic combination multi-head attention mechanism, a denoising auto-encoder and a graph auto-encoder; the de-noising auto-encoder is constructed based on zero-expansion negative binomial distribution loss adjusted by a zero-expansion proportion adaptive weight; the graph self-encoder is constructed based on a graph convolutional network; and inputting the original gene data into the scDAEC model for clustering processing to obtain a single cell data clustering result. The framework constructed by the method disclosed by the invention has very strong generalization ability and high fault tolerance.

The invention discloses chiral ionizable lipid nanoparticles and a preparation method thereof, and belongs to the technical field of biomedical materials. The chiral ionizable lipid nanoparticle comprises chiral amino acid derived lipid, ionizable lipid, auxiliary lipid, cholesterol, a phospholipid polyethylene glycol derivative and an RNA (Ribonucleic Acid) drug, the preparation method comprises the following steps: dissolving chiral amino acid derived lipid in methanol, respectively dissolving ionizable lipid, auxiliary lipid, cholesterol and phospholipid polyethylene glycol derivative in ethanol, and mixing to obtain a total lipid organic phase; dissolving an RNA drug in DEPC water to obtain an RNA aqueous solution, and mixing the RNA aqueous solution with an acidic buffer solution to obtain an RNA aqueous phase; quickly mixing the total lipid organic phase and the RNA water phase, and standing and incubating; adding the mixed solution into a 3500 Da dialysis bag, taking 1 * phosphate buffer solution (PBS, pH = 7.4) as an external water phase, and dialyzing to obtain the chiral ionizable lipid nanoparticles. The lipid nanoparticles provided by the invention can enhance the RNA uptake efficiency, and have good application prospects in the treatment of systemic inflammation and other diseases.

The invention relates to a high-throughput cis-acting element screening carrier and a screening method. Specifically, the invention provides a plasmid vector system containing bar codes, each bar code in the system is in one-to-one correspondence with a candidate cis-acting element, and the activation multiple of the candidate cis-acting element can be obtained by measuring the abundance of the bar codes; in order to eliminate the influence of a bar code on the vector on a detection result, an exogenous intron which can be cut off during transcription is inserted into a coding region in the vector and is used for distinguishing vector DNA and RNA obtained by transcription. The screening method of the biological cis-acting element has high efficiency, wide applicability and high throughput, and has outstanding application value in biological research and breeding.

Disclosed herein include methods, compositions, and kits suitable for use in e.g., nucleic acid delivery. Provided are compositions (e.g., nucleic acid compositions) comprising polynucleotide(s) encoding a fusion protein, a dimerization fusion protein, a soluble RBP, an adapter fusion protein, and / or a cell fusion protein. The compositions also comprise one or more polynucleotides comprising one or more RNA cargo molecules. The fusion protein, dimerization fusion protein, and / or adapter fusion protein can comprise an endosomal sorting complex required for transport (ESCRT)-recruiting domain (ERD). Recruitment of one or more ESCRT proteins results in secretion of enveloped nanoparticles (ENPs) from a cell in which at least one of a fusion protein, a dimerization fusion protein, and / or an adapter fusion protein are expressed. The ENPs can comprise the one or more RNA cargo molecules. There are also provided populations of ENPs in some embodiments.

The present disclosure, among other things, provides machine-learning technologies for identifying and localizing particular genomic elements (e.g., gene elements and / or regulatory elements) within nucleotide sequences, such as DNA and / or RNA sequences. In certain embodiments, similar to the manner in which image processing methods can be used to localize particular objects in images at pixel level resolution, referred to as “segmentation,” systems and methods of the present disclosure predict presence and locations of certain genomic elements within nucleotide sequences, thereby “segmenting” nucleotide sequences. Accordingly, genomic element segmentation technologies described herein may be used to generate annotations that identify and label portions of nucleotide sequences according to their predicted (e.g., via machine learning models described herein) function—e.g., as protein-coding genes, untranslated regions, splice sites, promotors, enhancers, etc. Among other things, these genomic annotations may be used to inform underlying biological processes driving diseases and facilitate development of new therapies.

A protein interface prediction method based on three-track coding comprises the following steps: combining a fine-tuned protein language model SiteT5 with evolutionary, geometric and statistical features extracted from a sequence, sending the combined features into a three-track coding network, and integrating a cyclic gating module, a multi-resolution aggregation module and a long sequence deformation module to obtain a protein interface prediction model SiteT5; the method comprises the following steps: respectively capturing a time sequence relation, a local mode and long-range dependence among residues, respectively mapping the three codes into different weights, carrying out point multiplication on the three codes, and carrying out aggregation through a multi-view cross attention module; then the protein residues are sent to a three-layer hierarchical interactive learning module, local structure and global dependency are cooperatively mined through an eight-head gating self-attention module and a position-by-position feedforward module, and finally the probability that each protein residue is an interface is obtained through a classifier. According to the invention, a protein-DNA interface, a protein-RNA interface, a protein-protein interface and an antibody-antigen interface can be effectively captured. And the robustness is ensured, and meanwhile, relatively high prediction precision is also shown.

The invention discloses an environment RNA (Ribonucleic Acid)-based double-saw eye spot fish detection method and a primer combination thereof, and solves the technical problems of lack of molecular markers, insufficient detection specificity and difficulty in reflecting physiological status in application of an existing environment RNA detection technology to benthic fishes. The primer pair aiming at the Ptger4b gene is designed on the basis of an environment RNA (eRNA) technology, and rapid and sensitive detection of the gemphus ocellatus in an independent feeding system is realized in combination with a fluorescent quantitative PCR (qPCR) technology. The method is easy and convenient to operate, high in sensitivity, small in interference to the ecological environment and suitable for detection and quantitative verification of target species in an independent feeding system, and has the potential of being expanded to natural sea areas in the future and used for fish population monitoring, fishery resource evaluation and species protection.

The invention discloses a VdNOB1 gene as well as an anti-pathogenic bacterium target gene segment, an interference vector and disease-resistant application thereof. According to the invention, the VdNOB1 gene is subjected to knockout mutation, so that the infection pathogenicity of verticillium dahliae to host plants can be obviously reduced. The invention further provides a verticillium dahliae VdNOB1 gene anti-pathogenic bacterium target gene segment, the nucleotide sequence of the verticillium dahliae VdNOB1 gene anti-pathogenic bacterium target gene segment is shown as SEQ ID No.4, and the pathogenicity of verticillium dahliae to host plants can be remarkably reduced after plants are transformed by an RNA interference vector constructed by the verticillium dahliae VdNOB1 gene anti-pathogenic bacterium target gene segment. The invention further provides an RNA (Ribonucleic Acid) interference vector containing the VdNOB1 gene or an anti-pathogenic bacterium target gene fragment thereof. The verticillium dahliae VdNOB1 gene or the anti-pathogenic-bacterium target gene segment and the RNA interference vector thereof have application prospects in the aspects of improving the resistance of crops to diseases caused by verticillium dahliae, cultivating new varieties of verticillium dahliae-resistant plants and the like.

The invention discloses a double-stranded RNA (Ribonucleic Acid) aiming at hemiptera insects as well as a pesticide composition and application of the double-stranded RNA. The dsRNA provided by the invention is used as a biopesticide, has the characteristics of high efficiency, specificity, fast degradation and no residue, realizes the prevention and control of brown planthopper through an RNAi mechanism, and is beneficial to reducing the use of chemical pesticides. The invention provides a brand new brown planthopper target gene as a target of RNA interference. The survival rate result shows that the genes play an important role in the survival process of the brown planthopper, are effective targets for preventing and treating the brown planthopper by using a gene silencing means, and have a wide application prospect. Correspondingly, the invention provides a plurality of dsRNA sequences aiming at the targets, and part of the sequences show unprecedented brown planthopper control efficiency.

The invention discloses a double-stranded RNA (Ribonucleic Acid) aiming at hemiptera insects as well as a pesticide composition and application of the double-stranded RNA. The dsRNA provided by the invention is used as a biopesticide, has the characteristics of high efficiency, specificity, fast degradation and no residue, realizes the prevention and control of brown planthopper through an RNAi mechanism, and is beneficial to reducing the use of chemical pesticides. The invention provides a brand new brown planthopper target gene as a target of RNA interference. The survival rate result shows that the genes play an important role in the survival process of the brown planthopper, are effective targets for preventing and treating the brown planthopper by using a gene silencing means, and have a wide application prospect. Correspondingly, the invention provides a plurality of dsRNA sequences aiming at the targets, and part of the sequences show unprecedented brown planthopper control efficiency.

The disclosure relates to compositions and methods for treating a disease or condition associated with a TDP-pathology or a decline in TDP-43 functionality in neuronal cells in a subject, and for identifying candidate agents to restore expression of a normal full-length or protein coding STMN2 RNA.