45 results about "Immune gene" patented technology

The invention discloses an aquaculture organism health state monitoring system based on multi-dimensional feature association, and belongs to the technical field of aquaculture, and the system comprises a visual feature collection layer which is composed of an image collection module, an image preprocessing module, a target analysis module and a feature extraction module; the molecular biology verification layer is composed of an immune gene monitoring module and a metabolic gene monitoring module; the data association prediction layer is composed of a standardization module, a feature screening module, a deep learning module and an evaluation output module; a self-adaptive optimization mechanism, a fault-tolerant mechanism and an environment adaptability adjustment mechanism. According to the aquaculture organism health state monitoring system based on multi-dimensional feature association, intelligent monitoring of the health state of aquaculture organisms is achieved by integrating a computer vision technology and a molecular biology detection method, and a scientific basis is provided for aquaculture production management.

The invention discloses an interpretable deep learning-based innate immune gene expression prediction method, which comprises the following steps of: 1, collecting and preprocessing a DNA (Deoxyribose Nucleic Acid) promoter sequence and epigenetic modification data, and dividing a preprocessed data set into a training set and an independent test set so as to verify the prediction performance of a model; 2, constructing a human innate immune gene expression prediction network based on residual connection, a convolutional neural network and an attention mechanism; 3, performing model training on a plurality of cell lines to obtain an optimal human innate immune gene expression prediction model, and evaluating the prediction effect of the model on the independent test set; and 4, carrying out post interpretability analysis on the model through an integral gradient method, and identifying a key motif which is most likely to influence gene expression. According to the method, DNA sequence information and epigenetic modification information are extracted more effectively, and a new tool is provided for deeply understanding a regulation mechanism of an innate immune gene and developing individualized medical treatment.

The invention discloses tobacco bacterial wilt biocontrol burkholderia and application thereof, relates to the technical field of agricultural microorganisms, and is technically characterized in that the burkholderia S8288 is preserved in China General Microbiological Culture Collection Center (CGMCC) in October 2024, the preservation number of the burkholderia S8288 is CGMCC NO.32293, the preservation number of the burkholderia S8288 is CGMCC NO.32293, and the preservation number of the burkholderia S8288 is CGMCC NO.32293. The 16S rRNA (ribosomal Ribonucleic Acid) gene sequence of the Burkholderia sp. S8288 strain is as shown in SEQ ID No. 1. The strain has a good inhibition effect on pathogenic fine diseases and oomycetes such as Coreiella solani causing tobacco bacterial wilt and phytophthora nicotianae causing tobacco black shank, and the prevention effect on the tobacco bacterial wilt reaches 50%. The strain can induce death of plant cells and stimulate expression of plant-related immune genes. Besides, the Burkholderia sp. S8288 can decompose potassium, hydrolyze inorganic phosphorus and organic phosphorus and produce protease and NH3, and has potential capabilities of improving soil nutrition and promoting crop growth, and greenhouse tests show that the strain can significantly promote tobacco growth and development.

The present disclosure relates to predicting genomic instability status in biological samples using machine learning techniques with comprehensive genomic and immune profiling (CGIP) data. Particularly, aspects are directed towards performing a genomic instability test on a biological sample. Then, multi-omics data for the subject are obtained by DNA sequencing and RNA sequencing assays, including genomic alteration data for a first set of genes and expression data for a second set of immune genes. The multi-omics data are input into a machine learning model having a tree-based architecture, which is configured to analyze features by traversing paths from root nodes to terminal nodes in each tree based on values generated from the data. The model predicts a genomic instability status, which is then provided via a user interface notification or as part of a testing report.

The invention discloses a macrobrachium rosenbergii probiotic biofloc technology (BFT) culture system construction method based on an SBOS-FOS composite carbon source, and belongs to the technical field of aquaculture. The total ratio of SBOS (soybean oligosaccharide) and FOS (fructo-oligosaccharide) in the composite carbon source is 2%-10%, and the balance is glucose; and adding the composite carbon source into a macrobrachium rosenbergii culture system according to the C / N ratio of (10: 1)-(20: 1) according to the feed protein content in the culture water body. Through a specific ratio of SBOS to FOS, the content of functional probiotics in a culture water body is specifically increased, stable control of ammonia nitrogen and nitrite nitrogen and directional optimization of a carbon source-flora-host three-level regulation and control network in a BFT system are realized, the weight gain rate (WG), the specific growth rate (SGR) and digestive enzyme activity (trypsin and amylase) of macrobrachium rosenbergii are increased, and the survival rate of the macrobrachium rosenbergii is increased. The abundance of probiotics in the water body and the immune gene expression of the macrobrachium rosenbergii are obviously improved.

The invention discloses a hepatocellular carcinoma prognosis and immune response prediction method based on multi-omics machine learning, and relates to the technical field of biomedicine and artificial intelligence crossing, and the method comprises the following steps: S1, constructing a multi-omics data set for model training and verification; s2, performing feature integration and clustering analysis on the multi-omics data to obtain corresponding hepatocellular carcinoma molecular subtype distribution; s3, constructing a hepatocellular carcinoma prognosis model based on Cox regression combined with a random survival forest, identifying 11 core immune genes and corresponding weight coefficients by training the model, and constructing an immunotherapy response index IMLIRI score; and S4, carrying out clinical application on the IMLIRI score. According to the method, through multi-omics data integration and multi-queue external verification, the influence of data deviation and queue heterogeneity on the model performance is reduced, so that the method shows stable prediction performance in hepatocellular carcinoma queues with different sources and different pathogenesis backgrounds, and the reliability and generalizability of the model in clinical application are improved.

The present invention discloses a system for monitoring the health of aquaculture organisms based on multidimensional feature association, belonging to the field of aquaculture technology. The system comprises a visual feature acquisition layer, comprising an image acquisition module, an image preprocessing module, a target analysis module, and a feature extraction module; a molecular biology verification layer, comprising an immune gene monitoring module and a metabolic gene monitoring module; a data association prediction layer, comprising a standardization module, a feature screening module, a deep learning module, and an evaluation output module; and an adaptive optimization mechanism, a fault tolerance mechanism, and an environmental adaptability adjustment mechanism. The system provides a system for monitoring the health of aquaculture organisms based on multidimensional feature association, integrating computer vision technology and molecular biology detection methods to achieve intelligent monitoring of the health of aquaculture organisms, providing a scientific basis for aquaculture production management.

The application discloses application of sodium butyrate in preparation of a medicine for preventing and treating grass carp hemorrhagic disease, wherein a structural formula of the sodium butyate is molecular formula C4H7NaO2, and a CAS number is 156-54-7; and the application further provides a medicine composition which comprises an effective dose of the sodium butyrate as an active ingredient, and further comprises a pharmaceutically acceptable carrier or excipient, and the dosage form comprises tablets, granules, powders, powders, suspensions, oral liquids, and the concentration of the sodium butyrate is 0.1-20 mM. Through a cell experiment, it is found that the sodium butyrate can significantly inhibit replication of grass carp reovirus in grass carp kidney cells, and improve expression of immune genes of the grass carp kidney cells, and it is proved that the sodium butyrate has a high efficient inhibiting effect on infection of the grass carp reovirus, and has the advantages of high safety and wide application prospect for preparing the medicine for preventing and treating the grass carp hemorrhagic disease caused by the grass carp reovirus.

The invention relates to application of an epiinhibitor EED226 in preparation of a cynoglossus semilaevis LPS-induced inflammation resisting medicine, and belongs to the field of epigenetics, and the epiinhibitor EED226 reduces LPS-induced inflammation response in a cynoglossus semilaevis body by regulating and controlling expression of downstream immune genes. And the inhibited genes comprise clec4c, ltbr, mcp-1b, tnfrsf13b, tnfsf6 and tnfsf14. The invention further discloses a method for preparing the recombinant protein.

The invention discloses a vaccine immune gene expression prediction method based on a multi-scale time sequence mode, and the method comprises the steps: S1, carrying out the structural representation and data preprocessing of vaccine post-gene expression data, and constructing a multivariate time sequence tensor and a corresponding effective observation mask tensor; s2, constructing a multi-time-scale learnable time sequence mode dictionary, carrying out end-to-end model training, and automatically learning and capturing multi-scale immune dynamic characteristics with the most information content for a prediction task; s3, performing time sequence mode matching and feature extraction based on distance measurement to obtain a distance spectrum feature vector of the input gene expression sequence after the single vaccine; s4, constructing a dynamic prediction model based on the distance spectrum feature vector; and based on a loss function of a mean square error, jointly optimizing parameters of the time sequence mode dictionary and the weight of the dynamic prediction model, and carrying out end-to-end training.

The present invention includes compositions and methods comprising viral vector systems for multiplexed activation of endogenous genes as immunotherapy and viral-based immune-gene therapy.

The invention discloses siRNA for inhibiting expression of a large yellow croaker SOCS1 gene and application of the siRNA. The target gene cDNA sequence of the siRNA is as shown in SEQ ID NO.1. By transfecting siRNA (siSOCS1-237) into a large yellow croaker head kidney cell strain, the expression of SOCS1 in the cell can be specifically inhibited, and the expression of an anti-virus immune gene of the large yellow croaker is promoted, so that the anti-virus immune response of the large yellow croaker is enhanced. The invention proves that the siRNA is expected to be developed into a novel pseudosciaena crocea antiviral drug, and lays a foundation for preventing and controlling marine fish virus diseases.

The present invention relates to the field of biological immunity, and discloses a method and system for analyzing and evaluating immunotoxicity, the method comprising: culturing immune cells and non-immune cells, constructing an immune microenvironment of immune cell tissue, and constructing an in vitro immune system model of the human body; inputting exogenous substances into the in vitro immune system model, and detecting the cellular immune parameters of the experimental in vitro immune system model; extracting the mouse genome of mice, constructing the gRNA-Cas9 complex of the target immune gene, implanting the gRNA-Cas9 complex into a preset mouse fertilized egg, cultivating the target gene fertilized egg into a target gene mouse, inputting exogenous substances into the body of the target gene mouse, and analyzing the humoral immune parameters of the blood sample; detecting the organ parameters of the immune organ, calculating the organ coefficient of the immune organ, and analyzing the immune organ status of the immune organ; analyzing the immunotoxicity evaluation report of the exogenous substance on the human immune system. The present invention can improve the accuracy of immunotoxicity analysis.

The present application relates to the technical field of biological medicines, and particularly relates to a polypeptide for specifically blocking the interaction between PD-L1 and endogenous double-stranded RNA and a medicine. The present application provides a polypeptide for specifically binding to endogenous double-stranded RNA, which has a strong effect on the activation of innate immune genes. The polypeptide fused with a cell-penetrating peptide can competitively bind to endogenous double-stranded RNA in cells and inhibit the A-to-I editing of endogenous double-stranded RNA, thereby improving the sensitivity of tumor cells to drugs. The present application provides a new strategy for the immunotherapy of tumor patients and has a wide application prospect.

The application discloses a vaccine immune gene expression prediction method based on a multi-scale time sequence mode, which comprises the following steps: S1, structural representation and data preprocessing of gene expression data after vaccination, construction of a multivariate time sequence tensor and a corresponding effective observation mask tensor; S2, construction of a multi-time scale learnable time sequence mode dictionary, and end-to-end model training to automatically learn and capture multi-scale immune dynamic characteristics with the most information quantity for a prediction task; S3, time sequence mode matching and feature extraction based on distance measurement to obtain a distance spectrum feature vector of an input single-vaccine post-gene expression sequence; S4, construction of a dynamic prediction model based on the distance spectrum feature vector; and joint optimization of parameters of the time sequence mode dictionary and weights of the dynamic prediction model based on a mean square error loss function, and end-to-end training.

The present invention relates to bacterial probiotics useful in aquaculture. Specifically, it discloses a selection of non-hemolytic, proteolytic, stress-tolerant bacterial strains with enhanced quorum- quenching capabilities. Moreover, the method allows detection of novel species of bacteria whose probiotic attributes could be massive for aquaculture. From the isolated bacteria, selected species were tested for their probiotic efficacy in Nile tilapia (Oreochromis niloticus), a key fish species in global finfish aquaculture. The species demonstrated significant efficacy in improving the health and growth performance of Nile tilapia juveniles. Specific growth rates and weight gain, and improved feed conversion ratios without adverse effects on fish health were observed. The gut microbiome was positively influenced by promoting beneficial bacteria while reducing harmful (opportunistic) species, leading to improved immune modulation. Survival rates were significantly boosted during a pathogenic challenge, and key immune genes were upregulated, indicating stronger local immune defenses. These findings show that the selected probiotic species offer substantial benefits for growth, feed efficiency, and disease resistance, emphasizing their potential for widespread application as probiotics in aquaculture.

The invention relates to the technical field of synthetic biology and immunotherapy, in particular to an immune gene combination fragment responding to a tumor microenvironment, a recombinant plasmid, probiotics and application of the immune gene combination fragment, the recombinant plasmid and the probiotics. The preparation method comprises the following steps: selecting phytobacterium plantarum, casei casei, casei paracasei, streptococcus thermophilus and lactococcus lactis as a probiotic chassis, further designing and assembling an immune gene combination fragment of immune checkpoint inhibitors (PD-L1 and CTLA-4), and uploading the immune gene combination fragment to the bacterial strain to construct customized probiotics, so as to prepare the immune checkpoint inhibitors (PD-L1 and CTLA-4). The in-vitro expression condition is researched; it is found that in a mouse tumor model, the customized probiotics can release PD-L1 and CTLA-4 nano antibodies at the tumor site, the tumor microenvironment is reversed, the immune system is mobilized, and the anti-tumor effect is enhanced. The research is expected to provide a safe and efficient anti-tumor strategy for tumor treatment, and new hope is brought to tumor patients.

The present disclosure generally relates to a method (1) for typing genes, preferably immune genes and allelic variants thereof. The present disclosure also relates to a kit for use in the method and to a set of target primers for use in the method.

The invention discloses a queen bee breeding value evaluation and core population selection method based on multi-omics data, and relates to the technical field of bee genetic breeding and multi-omics data application, and the method comprises the steps: obtaining candidate queen bee genome, intestinal microbiome and host transcriptome data; analyzing data and screening disease-resistant related core microbial markers, immune genes and bacterium-gene interaction network characteristics; by taking the characteristics as input, constructing a machine learning model to calculate a disease-resistant genome-microbiome combined breeding value; combining the breeding value, a core group genetic coefficient and an intestinal flora diversity index to construct a comprehensive selection index; according to the method, accurate evaluation of disease-resistant breeding values is achieved through multi-omics fusion and machine learning, genetic relationship and flora diversity optimization selection are combined, the disease resistance and genetic diversity of the core populations are improved, and a scientific basis is provided for queen bee breeding.

The present invention is directed to humanized CD37-CAR comprising humanized CD37 scFv of the present invention. The present invention is also directed to a bispecific CD19-humanized CD37 CAR, comprising: (i) CD19 VL, (ii) Humanized CD37 ScFv, (iii) CD19 VH, (iv) a transmembrane domain, (v) at least one co-stimulatory domains, and (vi) an activating domain. The CARs of the present invention are useful in the field of adoptive immunity gene therapy for hematological cancers.

The invention relates to a hot rolling process optimization method based on a multi-objective optimization immune algorithm, and belongs to the technical field of steel rolling intellectualization. The method comprises the steps that a wire and bar production data set is acquired and preprocessed; an initialized antibody group is generated by adopting an orthogonal test design, and uniform discretization is realized; the solution space search range expansion is realized by adopting immune cloning operation; the antibody population diversity is optimized through gene recombination and clone variation by adopting immune gene operation; predicting the mechanical property corresponding to the antibody by adopting a mechanical property prediction model; dividing antibodies into dominated antibodies and non-dominated antibodies by adopting clone selection operation through dynamically adjusting relaxation parameters, dividing a non-dominated antibody group, properly screening non-dominated solutions, rejecting dense non-dominated solutions, and screening a Pareto optimal solution set; and S7, adopting an antibody population updating operation, calculating the fitness between the antibodies, and deleting the antibodies corresponding to the places with dense antibody populations. The production cost is reduced while the product quality is improved.

The invention discloses a molecular marker closely linked with a wheat spontaneous immune gene WAI-B2 and application of the molecular marker. The invention belongs to the technical field of biology, and particularly relates to a molecular marker closely linked with a wheat spontaneous immune gene WAI-B2 and application of the molecular marker. The substance for detecting the polymorphism or genotype of the SNP site in the wheat genome can be applied to any one of the following aspects: identifying or assisting in identifying the wheat activated spontaneous immune response performance; and screening or breeding a wheat single plant or strain or strain or variety which activates the spontaneous immune response or inhibits the spontaneous immune response. The specific primer composition developed by the invention can be applied to wheat breeding, and the breeding efficiency is improved.

The invention discloses a construction method and application of a transgenic mouse model for in-vivo autoimmune gene screening, belongs to the technical field of animal model construction, and aims to solve the problems that in-vitro screening targets are not real, the repeatability is poor, the operation is complicated, the application range is narrow, and in-vivo screening tools for multiple autoimmune genes are lacked. The method comprises the following steps: designing sgRNA (SEQ ID NO: 1-150) of 140 autoimmune genes and 10 control genes, and constructing 150mer library plasmids step by step; after microinjection, the mouse copulates with Cas9 and UBC-CreERT2 mice to obtain a Sanyang mouse, tamoxifen induction is carried out, autoimmune related genes are screened by combining a tumor model, flow sorting and NGS analysis screening targets, 150 autoimmune related genes can be covered, the screening is real, the repeatability is high, the operation is simple and convenient, the application is wide, and a key tool is provided for autoimmune research and target development.

The application discloses a wheat spontaneous immunity gene WAI-5, related biological materials and application thereof, and belongs to the technical field of biotechnology.The amino acid sequence of the protein coded by the aforementioned spontaneous immunity gene WAI-5 is SEQ ID NO:1, and the application also provides biological materials related to the aforementioned protein.The application proves through experiments that the wheat spontaneous immunity gene WAI-5 can be widely applied in the fields of wheat genetic breeding, germplasm resource improvement, genome editing breeding and plant cultivation of WAI-5 gene transformation, and has an important role in improving and improving the germplasm resources of crops such as wheat.

The invention belongs to the technical field of biology, and particularly relates to a method for enhancing pathogenic bacterium resistance by activating plant immune genes. A method for activating a plant immune gene to enhance pathogenic bacteria resistance is characterized by comprising the step of applying nano-silica particles to a plant to improve expression of a plant gene PR1 and a gene PR1A1. After the plant is treated by the SiO2NPs, the SAR-related immune genes PR1 and PR1A1 in the plant are highly expressed, so that the SAR of the plant is activated, and the pathogenic bacterium resistance of the plant is improved.

The invention provides application of soybean rust fungus elicitor PpE1 protein in inducing plant immune response and / or improving plant resistance, and belongs to the technical field of elicitor protein application. The amino acid sequence of the soybean rust fungus elicitor PpE1 protein is as shown in SEQ ID NO. 2. The invention discovers the application of the soybean rust fungus protein elicitor PpE1 in inducing plant immune response and improving plant resistance for the first time. The PpE1 can cause the hypersensitive reaction of the nicotiana benthamiana and induce active oxygen in the nicotiana benthamiana to burst out; the protein can induce immune response of soybeans, including burst of active oxygen, activation of MAPK and expression of immune genes, and promote resistance of the soybeans to rust fungi; the heterologous expression of the PpE1 can also improve the resistance of the soybean to rust fungi. The invention provides a new way for improving the disease resistance of plants, and has a wide application prospect in agricultural production.

The invention relates to an immune gene prognosis model system based on K-ras and TP53 co-mutation colon cancer patients and a construction method of the immune gene prognosis model system. The prognosis model system comprises the following seven genes: DUOX2, BST2, CCL28, APOBEC3C, CD79B, GUCA2A and TNFRSF13C, and an evaluation formula of the prognosis model system is as follows: a risk score = (DUOX2 gene expression quantity *-0.004321) + (BST2 gene expression quantity * + 0.00168) + (CCL28 gene expression quantity *-0.01796) + (APOBEC3C gene expression quantity * + 0.000145) + (CD79B gene expression quantity * + 0.05418) + (GUCA2A gene expression quantity *-0.00528) + (TNFRSF13C gene expression quantity * + 0.12786). According to the invention, by analyzing the difference between genes of a K-ras and TP53 co-mutation patient and a co-wild type patient and combining with gene intersection in an immunological database, a more reliable related gene capable of better reflecting an immune microenvironment is obtained, a prognosis model is constructed based on the gene, and meanwhile, the prognosis model has a good application prospect. The value of the model in the tumor immune microenvironment is evaluated by analyzing the risk score in the model and immune cell infiltration in the tumor microenvironment, and a method is provided for clinical related prognosis analysis.

The invention belongs to the technical field of gene engineering, and relates to application of an apple pattern recognition receptor gene MdRE02 in regulation and control of plant disease resistance. The nucleotide sequence of the apple pattern recognition receptor gene MdRE02 is as shown in SEQ ID NO.1, the MdRE02 gene is silenced in apples, the expression of an immune gene induced by a pathogen-related molecular pattern VmE02 is remarkably reduced, and the disease resistance to valsa mali of apple trees is remarkably weakened. Through overexpression of the MdRE02 gene in the tobacco mutant re02, cell necrosis and active oxygen bursting induced by the VmE02 can be recovered, which indicates that the MdRE02 is a pattern recognition receptor for recognizing the VmE02. By overexpressing the MdRE02 gene in tobacco mutants re02 and oilseed rape, the resistance of the MdRE02 gene to sclerotinia sclerotiorum can be remarkably improved. The results show that the MdRE02 gene can be used for disease-resistant breeding and disease prevention and control of valsa ceratosperma and sclerotinia sclerotiorum of apple trees.

The present invention discloses a method for constructing a prognostic prediction model for PD-L1 inhibitor targeted therapy. This method constructs an expression data matrix of immune genes based on the RNA expression levels of immune genes, applies an immune gene expression sequence algorithm to screen immune gene pairs most relevant to the clinical response of treating tumors with PD-L1 inhibitors, constructs an immune gene expression sequence matrix, and obtains a prognostic prediction model for PD-L1 inhibitor targeted therapy of tumors through training. The present invention constructs a prognostic prediction model for PD-L1 inhibitor targeted therapy based on the paired immune gene expression levels, and predicts the possible response of tumor patients, especially urothelial carcinoma patients, to PD-L1 inhibitor therapy by deeply analyzing the expression levels of relevant immune genes in tumor samples after PD-L1 inhibitor treatment, greatly improving the prognostic prediction accuracy of PD-L1 inhibitor treatment response, helping to achieve personalized treatment plans, and improving the treatment success rate.

The invention discloses a monochamus alternatus hope adenosine triphosphate enzyme gene V-ATPase H and application thereof. The monochamus alternatus hope adenosine triphosphate enzyme gene V-ATPase H comprises a V-ATPase H superfamily conserved domain, and the base sequence is shown as SEQ ID NO.1. The monochamus alternatus hope adenosine triphosphate enzyme gene V-ATPase H encodes V-ATPase protein, and the amino acid sequence of the monochamus alternatus hope adenosine triphosphate enzyme gene V-ATPase protein is shown as SEQ ID NO.2. The invention also discloses an application of the triphosadenase gene V-ATPase H of the monochamus alternatus hope as an RNAi target gene in prevention and treatment of the monochamus alternatus hope. The dsRNA is designed and synthesized by taking the monochamus alternatus hope adenosine triphosphate enzyme gene V-ATPase H as a template, then the dsRNA is used for interfering expression of monochamus alternatus hope immune genes Dome, Tube and TAB2, and experimental results show that the dsRNA designed and synthesized by utilizing the monochamus alternatus hope adenosine triphosphate enzyme gene V-ATPase H can effectively inhibit expression of monochamus alternatus hope immune related genes, so that the dsRNA has good development and utilization prospects.