29 results about "Cellular development" patented technology

The invention provides a cell development process dynamic modeling method and device based on time sequence single cell transcriptome data and a medium, and relates to the crossing field of bioinformatics and computational biology. The method comprises the following steps: constructing a Shenchang differential equation learning framework; adjusting parameters of the single cell development state change model based on the Shenxuan differential equation learning framework so as to construct a population cell development state change model; obtaining a cell specific gene regulation network and a population cell gene regulation network based on the population cell development state change model so as to predict occurrence opportunity of cell lineage differentiation and a molecular decision mechanism of cell differentiation; therefore, the problems of incomplete modeling mechanism, insufficient noise processing and lack of energy principle in the existing cell development process are solved.

A multi-cell barrier tissue model of a bionic sequential development mechanism has a multi-layer multi-cell structure simulating a physiological barrier, related cells of different barriers are distributed in different layers according to the physiological structure, and the development time and sequence of the cells of different layers are regulated and controlled according to natural barrier multi-cell development physiological characteristics; the multi-cell three-dimensional structure of in-vivo barrier tissue can be simulated, regulation and control of cell development behaviors are achieved by regulating and controlling the matrix environment, and meanwhile, the model has enough overall mechanical support through the soft / hard chimeric structural design so as to adapt to perfusion culture and operation requirements; the model can realize functional bionics of natural barrier tissues at the same time in the spatial structure dimension and the time development dimension so as to realize application in the aspects of disease modeling, drug screening and the like.

The invention belongs to the technical field of biotechnology, and discloses a peanut peptide for promoting cell development, which is characterized in that the sequence of the peanut peptide is Met Ala Ser Val Thr Gly Pro Ser Ser Ala Leu Ala Asp Ser Ile Gly, through the accurately designed amino acid sequence, the peanut peptide constructs a molecular level adaptation mechanism with a cell surface receptor, triggers a cascade reaction of a key signal channel of phosphatidylinositol-3 kinase PI3K, and can promote cell development. The activation effect not only accelerates the process of a cell cycle and increases the proportion of DNA synthetic cells in an S phase by 40% or more, but also directionally induces the mesenchymal stem cells to differentiate into functional cells such as muscle cells and nerve cells by up-regulating transcription factors MyoD and NeuroD1, in a three-dimensional cell culture model, the cell migration rate of an experimental group added with 200 [mu] g / mL peanut peptide is increased by 58% compared with a control group, and the cell migration rate of the experimental group added with 200 [mu] g / mL peanut peptide is increased by 30% or more compared with that of the control group. The branch density of the formed vascular-like network is increased by 3 times, and meanwhile, the test further proves that the peanut peptide has the function of promoting cell development and shows remarkable optimization capability on a tissue regeneration microenvironment.

The invention relates to a computer-implemented method for detecting oesophageal squamous cell dysplasia (OSCD) or oesophageal squamous cell cancer (OSCC) in a cell sample from a subject. This invention also relates to a computer-implemented method for generating a trained model to detect OSCD or OSCC. This invention also relates to a computer-readable storage medium or a computer program comprising instructions which when executed by a computer, are capable of causing the computer to perform the method. This invention also relates to a kit comprising the computer program or computer-readable storage medium and a non-endoscopic cell collection device. The invention also relates to an apparatus for performing the method. The invention further relates to the use of genome wide instability scores (GWIS) as a diagnostic marker for cancer, wherein GWIS is a measure of the CNV across a plurality of autosomal arms in a cell sample from a subject.

Natural killer (NK) cells are a critical first line of defense against viral infections. Rare mutations in a small subset of transcription factors can result in decreased NK cell numbers and function in humans, with an associated increased susceptibility to viral infections. Utilizing a non-viral CRISPR-Cas9 knockout screen targeting 31 transcription factors differentially expressed during human NK cell development, we identified myocyte enhancer factor 2C (MEF2C) as a master regulator of human NK cell functionality ex vivo. MEF2C haploinsufficient (MCHS) patients and mice displayed profound defects in NK cell development and effector function, with an increased susceptibility to viral infection. Mechanistically, MEF2C was required for IL-2 and IL-15-mediated increase in lipid content through regulation of the SREBP pathways. Supplementation with oleic acid restored MEF2C-deficient and MCHS patient NK cell cytotoxic function.

The utility model discloses a positive and negative pressure rotary biological culture device, which belongs to the technical field of biological sample experimental equipment and comprises a control host, an environment adjusting system and a rotary culture system arranged in the environment adjusting system. The spherical bottom culture bottle is arranged on the rotating mechanism, so that the spherical bottom culture bottle is driven by the rotating mechanism to rotate. By adopting the positive and negative pressure rotary biological culture device, a stable culture environment is provided for biological sample development required by different environments, different culture environment selections are provided for biological culture research, meanwhile, the nutrient exchange rate of biological cells can be increased, and the phenomena of slow development or death of the biological sample cells are reduced.

The application discloses a bone marrow morphology acute event identification early warning system and relates to the technical field of intelligent medical treatment, and the technical solution points are as follows: acquiring bone marrow cell image data, pre-processing, obtaining pre-processed image data; inputting the pre-processed image data into a trained AI model, and outputting a classification prediction result. The application can more accurately identify and classify bone marrow cells by applying a visual Transformer and a visual Mamba model, can identify different cell development stages, and can diagnose various blood diseases through an AI model standardized analysis process, reduce professional barriers in the field of bone marrow morphology, reduce absolute dependence on expert experience, and enable areas with insufficient medical conditions to also obtain high-quality preliminary diagnosis.

A method for simultaneously deducing single-cell pseudo time, velocity field and gene interaction comprises the following steps: preprocessing a single-cell RNA sequencing data set of cell development with multiple branches, clustering different cell types, constructing a piecewise linear model, optimizing the piecewise linear model by adopting an expectation maximization algorithm, and calculating the single-cell pseudo time, velocity field and gene interaction. Deduced pseudo time of each cell, a gene interaction matrix of the dynamic network and single cell velocity field visualization on a pseudo time chart are obtained. According to the method, a segmented ordinary differential equation model is introduced to reconstruct an RNA velocity field and pseudo time of a cell and an interaction network between genes. By iteratively optimizing a connection matrix between genes and pseudo time of the cells, the prediction precision of dynamic change of the cells can be remarkably improved, cell state transition can be accurately deduced, and a key gene regulation and control relationship can be accurately detected.

The present application belongs to the field of functional substance research, and particularly relates to a kind of nutritional composition for regulating immunity and purposes thereof.The nutritional composition provided by the present application comprises essential active ingredients shown in (I) and (II) as follows: (I) lysophosphatidyl ethanolamine; (II) 2'-FL; and in the nutritional composition, the mass ratio of the essential active ingredients shown in (I) to the essential active ingredients shown in (II) is 1:(1-2000). Lysophosphatidyl ethanolamine and 2'-FL are compounded, which can take T cell development activation as core, promote the overall construction and functional regulation of adaptive immune and innate immune system.

The application discloses a cell suction and release detection method based on microtube air pressure change, relates to the technical field of cell operation, and comprises the following steps: S1: suction and release of cells are carried out through a microtube, and a cell suction model is established; S2: in-situ pressure of the microtube before and after suction and release of cells is modeled based on the Clapeyron equation; and S3: based on the modeling result, the suction and release of cells are detected through microtube air pressure change detection; the application obtains the air pressure change trend of the microtube in the suction and release process through air pressure modeling of the cells in the suction and release process, and realizes the detection of the suction and release operation of the cells based on the air pressure change; experimental results show that the cell suction and release detection has a high success rate, and the development ability of the cells after the operation is not affected, and the application has wide applicability; the application is free of dependence on microscopic vision for the cell suction and release detection, and significantly promotes the popularization and application of the cell operation technology in the above-mentioned occasions.

The invention discloses an AI-based human germ cell development and culture system evaluation method, which comprises the following steps: step 1, constructing a standardized reference map, step 2, establishing a germ cell development stage prediction model which comprises a transfer learning-based single cell annotation variation inference prediction module, a united prediction module combining single cell annotation variation inference with k nearest neighbor and a cell type classification module for feature selection optimization realize collaborative decision through a three-level confidence system; and step 3, in-vitro culture system evaluation, including construction of double indexes for quantitative evaluation and analysis of evaluation results. According to the method, a whole-process solution from single cell reference map construction, development stage prediction to culture system evaluation is realized, and the problems of reference data fragmentation, inaccurate development stage annotation and lack of quantitative standards of culture system data in the current germ cell research field are solved.

The invention belongs to the field of bioinformatics, and relates to a high-precision elastic network transcription factor targeting relationship prediction method. The method comprises the following steps: firstly, acquiring single cell transcriptome sequencing data, and extracting a gene expression matrix and potential transcription factor information; secondly, constructing a high-resolution latent time grid, and performing fine-grained division on a single cell cycle; secondly, introducing an elastic network hybrid regularization mechanism, performing sparsification on the gene expression model by using L1 regularization, and meanwhile, retaining core transcription factor characteristics with a collaborative regulation effect by using L2 regularization; then, carrying out iterative optimization based on an RNA kinetic equation, and calculating a regulation weight of a transcription factor on a target gene and a cytodynamic rate; and finally, outputting a high-confidence-coefficient gene regulatory network atlas. According to the method, high-precision, high-robustness and anti-noise targeting relation prediction is realized, and an important calculation and analysis tool is provided for revealing a gene regulation and control mechanism of a cell development bottom layer and accurately searching key disease targets.

This invention discloses the role of the POFUT1 gene in determining the function of tissue-infiltrating CD4+ T cells and the application of related biomarkers in diseases, belonging to the field of biomedical technology. This invention discovers that POFUT1 is a decisive gene regulating the development of CXCR5+CD4 T cells; simultaneously, CXCR5+ and SLAMF1+CD4 T cells, as tissue-infiltrating source cells, possess the function of carrying out CD4 T cell-mediated antigen-specific killing and tissue destruction, leading to the pathogenesis of autoimmune diseases. Related applications include: using the POFUT1 gene, CXCR5+, and SLAMF1+CD4 T cells as biomarkers for the clinical diagnosis and treatment of diseases caused by tissue-infiltrating CD4 T cells, such as autoimmune diseases and xenotransplant rejection. The killing function of CXCR5+ and SLAMF1+CD4 T cells as tissue-infiltrating source cells can also be used to treat tumors.

A method of gene targeting utilizing outer membrane vesicle is disclosed. As described herein outer membrane vesicles (OMVs) have the ability to modulate the expression of NRG1 intracellularly, which affects intracellular NRG1 mediated functions in addition to autocrine and paracrine signaling that support cell development, differentiation and growth. The OMVs are useful in modifying the expression of NRG1 and the expression of genes other than NRG1. The Pg OMVs also function as a gene therapy vector, as it is up taken by mammalian cells and crosses both the placental and blood brain barrier.

Described herein is a microphysiological system for models of disease. Specifically, induced pluripotent stem cells (iPSCs) and iPSC-derived cells, including those obtained from disease patients, are seeded onto microfluidic “chip” devices to study cellular development and disease pathogenesis. Herein, neurodegenerative disease modeling, including Parkinson's Disease (PD) is shown to reproduce key PD pathology in a vascularized human model that contains neurons relating to PD pathology. Such compositions and methods are used for research for PD biomarkers, patient screening for PD risk assessment, and therapeutic discovery and testing. A panel of biomarkers are generated through analysis of living PD-chips by neural activity, whole transcriptomic, proteomic, and metabolomic analysis, and functional enzyme tests of media and tissue. Introducing therapeutics through a vasculature channel, coupled with blood brain barrier penetration studies can be assessed for efficacy in the human neural cells present in the PD-Chip.

The invention discloses an intervention system for Chinese yam tuber cells based on different development stages, and particularly relates to the technical field of Chinese yam planting.The intervention system comprises the steps that smashed corn straw and dormant-state degrading bacteria are premixed and regulated to the high carbon-nitrogen ratio, a delayed degradation matrix is constructed, vertical backfilling is conducted along planting ditches to form a loose columnar structure, and the loose columnar structure is formed; in the early growth stage, matrix rigidity is used for resisting soil settlement to guarantee vertical guiding. When a tuber expansion critical period is entered, high-nitrogen activation liquid is poured into the root side, inoculant dormancy is instantly relieved, an explosive degradation reaction is started, and straw skeletons are promoted to be softened and collapsed and are converted into a porous biochemical buffer layer rich in metabolites in situ. The layer utilizes mesh pores to reduce mechanical resistance and utilizes organic acid to induce acid relaxation of cortical cell walls to synergistically drive maximized amplification of cells, so that the problems of cortical cell development hindering and tuber malformation caused by soil compaction of Chinese yams are solved.

The invention discloses an application of 24-Epi brassinolide in promoting the development of female germline stem cells. Belongs to the technical field of reproductive biology. Female germline stem cells (FGSCs) are important cell models for studying the development of germ cells, however, the regulation and control mechanism of natural products on the development of the FGSCs still needs to be deeply explored. The invention aims at disclosing the regulation and control effect of 24-Epi brassinolide (24-Epibrassinolide, EBR) on FGSCs development and a molecular mechanism of the 24-Epi brassinolide on the FGSCs development by utilizing an FGSCs in-vitro development system and combining LongRNA-seq and RIC-seq technologies, and a new strategy is provided for treatment of infertility and optimization of a clinical treatment scheme.

Disclosed herein are methods of treating or preventing a metabolic disease in a subject. The methods include administering to the subject a composition comprising Candida dubliniensis in an amount effective to treat or prevent or reduce a metabolic disease. Methods of treating diabetes or promoting or enhancing proliferation of beta cell development or beta cell regeneration are also provided.

This invention discloses an AI-based method for evaluating human germ cell development and culture systems, comprising: Step 1, constructing a standardized reference atlas; Step 2, establishing a germ cell development stage prediction model, including a single-cell annotation variational inference prediction module based on transfer learning, a joint prediction module combining single-cell annotation variational inference with k-nearest neighbors, and a cell type classification module optimized by feature selection. These three modules achieve collaborative decision-making through a three-level confidence system; Step 3, evaluating the in vitro culture system, including constructing dual indicators for quantitative evaluation and analyzing the evaluation results. This invention provides a complete solution from single-cell reference atlas construction and development stage prediction to culture system evaluation, solving three key technical bottlenecks in current germ cell research: fragmented reference data, inaccurate developmental stage annotation, and lack of quantitative standards for culture system data.

The invention provides a single-cell multi-omics sequencing data integration method and system based on comparative learning, and the method comprises the steps: single omics feature extraction: employing an intra-omics comparative learning method to capture a local and global potential interaction relationship in single omics data; performing multi-omics feature fusion, realizing inter-omics information alignment by using a cross-modal attention algorithm, retaining feature heterogeneity of each omics, creating positive and negative sample pairs based on a multi-omics pairing relationship, and designing inter-omics comparison loss and inter-omics matching loss to mine an inter-omics correlation relationship; downstream tasks are achieved, and cell type clustering, cell subtype analysis, cell type re-labeling and cell development trajectory prediction are achieved based on cell fusion representation. The influence of high noise, high sparsity and high dimension difference of single-cell multi-omics sequencing data on multi-omics data fusion is relieved, the quality of cell fusion characterization is effectively improved, and help is provided for cell type clustering, cell subtype analysis and cell development trajectory reasoning.

A system for mimicking cellular microenvironment is provided and includes a chip, a hydrogel, and cells in contact with the hydrogel. The chip includes a first carrier having a pore and a second carrier coupled to the first carrier. The hydrogel is disposed in the pore and includes extracellular matrix. Also provided is a method for evaluating cell development, including providing the system for mimicking cellular microenvironment; providing a stimulation to a responsive hydrogel; and evaluating the cell development. Further provided is a method for evaluating drug therapy effectiveness, including providing the system for mimicking cellular microenvironment; administering the drug to the cells; and evaluating drug therapy effectiveness.

The invention discloses a pseudo time sequence inference method for a single-cell Hi-C map and a related device. The method comprises the following steps: extracting a single-cell Hi-C contact matrix from an original sequencing library; performing interpolation and feature enhancement on the extracted single cell Hi-C contact matrix to generate an enhanced contact matrix; based on the enhanced contact matrix, extracting multi-order chromatin structural features of the single cells, and embedding each single cell into a low-dimensional space for representation; from the low-dimensional cell representation, multiple discrete pseudo-timings of the cells under multiple k values are calculated, and a continuous development pseudo-timing of each cell is estimated based on these discrete pseudo-timings. The development path of the cells is estimated by adopting the shortest Hamiltonian path, and the final cell development pseudo-timing sequence is estimated based on the discrete pseudo-timing sequence under multiple k values, so that a pseudo-timing sequence inference result is insensitive to the number of cell clusters, and the accuracy is higher.

The invention provides an identification method and system for multi-omics analysis of lung cancer brain metastasis driving genes. The method comprises the following steps: data quality control: acquiring single-cell RNA sequencing data from a public data source, carrying out initial cell screening after standardization processing, removing low-quality data and ensuring the reliability of the data; a batch effect removing algorithm is adopted, technical deviation between batches is eliminated, and data consistency is ensured; the cells are grouped, the cells are divided into different subgroups through dimensionality reduction and clustering analysis, and the heterogeneity and diversity of the cells in the tumor microenvironment are revealed; inferring copy number variation, and inferring genome instability and possible canceration characteristics of the cells by analyzing the copy number variation in the single cell data; performing quasi-time sequence analysis, reconstructing a cell development or transformation process by utilizing the quasi-time sequence analysis, and exploring the change of cell fate in the brain metastasis process of the lung cancer; function enrichment analysis: carrying out function annotation on different cell subgroups, and identifying key pathways and molecular markers related to brain metastasis of lung cancer; and drug sensitivity analysis before and after radiotherapy: analyzing the sensitivity difference of different cell subgroups to drugs before and after radiotherapy, and providing a basis for an individualized treatment scheme.

The present invention relates to a method for differentiating stem cells into hard tissues, and may induce differentiation into hard tissues through different cell development processes using different cell culture supports during differentiation.

The present invention provides a method, device, electronic device and storage medium for reconstructing the developmental trajectory of a single cell, which relates to the field of computer technology. The method includes: generating a gene regulatory network corresponding to the single cell based on a gene data set of the single cell; determining a differential equation corresponding to the gene regulatory network based on the gene regulatory network; determining a probability distribution corresponding to the gene regulatory network based on the differential equation; and establishing a potential energy topography map of the single cell based on the probability distribution. Through the above method, a nonlinear differential equation for reconstructing the developmental trajectory of a single cell is determined based on the gene regulatory network, and a probability distribution corresponding to the gene regulatory network is determined based on the differential equation. Based on the probability distribution, the developmental state of each cell of the single cell can be arranged in chronological order on the corresponding trajectory, thereby generating an intuitive potential energy topography map for reflecting the developmental trajectory of the single cell, thereby reconstructing the differentiation and developmental trajectory of the single cell in the tissue.

Provided herein are methods compositions and methods to generate pMHC libraries, and methods of using the pMHC libraries to determine the sequences of T cell receptors, and T cell developmental and activation status.

The application discloses application of a pumpkin CmoEXPA23 gene in regulation of pulp thickness of crops, a nucleotide sequence of the pumpkin CmoEXPA23 gene is shown in SEQ ID NO:1, and an amino acid sequence of a coded protein is shown in SEQ ID NO:2. It is found that the pumpkin CmoEXPA23 gene has a biological function of positively regulating pulp cell development in a fruit expansion process, can be used as an important gene resource for regulating pulp thickness of crops, and is expected to improve fruit traits and promote a molecular breeding process of crops.

The invention relates to a computer-implemented method for detecting oesophageal squamous cell dysplasia (OSCD) or oesophageal squamous cell cancer (OSCC) in a cell sample from a subject. This invention also relates to a computer-implemented method for generating a trained model to detect OSCD or OSCC. This invention also relates to a computer-readable storage medium or a computer program comprising instructions which when executed by a computer, are capable of causing the computer to perform the method. This invention also relates to a kit comprising the computer program or computer-readable storage medium and a non-endoscopic cell collection device. The invention also relates to an apparatus for performing the method. The invention further relates to the use of genome wide instability scores (GWIS) as a diagnostic marker for cancer, wherein GWIS is a measure of the CNV across a plurality of autosomal arms in a cell sample from a subject.

The invention discloses a 3D tissue reconstruction method and device based on spatial transcriptome data. Comprising the following steps: acquiring space transcriptome data in space-time omics research, and carrying out standardization processing on the space transcriptome data; constructing a space correlation intensity matrix according to the position information of the cells distributed in the tissue space; calculating an initial value parameter of the model, constructing a target model, and determining the weight of a spatial correlation effect constraint space factor; after determining the weight of the initial parameter and the spatial correlation effect constraint space factor, inputting a target model and carrying out iterative optimization to finally obtain an integration result; and finally, performing downstream analysis, such as spatial clustering, differential gene identification and cell development trajectory inference, on the basis of an integration result (a spatial factor), and performing high-resolution reconstruction on low-resolution spatial transcriptome data (the weight of the spatial factor is constrained by the correlation effect of the spatial factor and the space), so that high-precision tissue structure 3D visualization is realized.