40 results about "Cellular development" patented technology

The invention discloses a treatment response prediction method and system, a storage medium and a terminal, and the method comprises the steps: carrying out the heterogeneity analysis and cell division of first single cell sequencing data of a patient through employing a clustering algorithm, and obtaining a plurality of corresponding cell subgroups; performing feature extraction and biomarker recognition on all the cell subgroups to obtain corresponding cell subgroup features; wherein the cell subset characteristics comprise a cell development trajectory and a plurality of cell markers; and inputting the clinical information and the cell subset characteristics of the patient into the treatment response prediction model, so that the model performs multi-factor analysis and outputs a treatment response prediction result of the patient for each treatment scheme. By adopting the embodiment of the invention, the tiny key difference between the cells is captured, the cells are divided based on the difference between the cells, and then feature extraction and biomarker recognition are performed on each cell subset, so that the specific gene expression modes of different cell subpopulations corresponding to diseases can be recognized, and the treatment response prediction accuracy is further improved.

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.

The invention discloses an scRNA-seq missing data prediction method based on depth map contrast learning. The scRNA-seq missing data prediction method comprises the following steps: 1, acquiring an scRNA-seq data matrix; 2, the scRNA-seq matrix is preprocessed; and 3, constructing a cell map by using the preprocessed scRNA-seq data. And 4, inputting the cell map data into a contrast learning module, and learning and obtaining the embedded representation of the cells. And 5, determining a neighbor cell of each cell based on the cell embedding representation, calculating a related weight of the neighbor cell and the neighbor cell through a least square method, and finally filling a missing value of each cell. And 6, evaluating the accuracy of the predicted value through downstream analysis. According to the method, the missing value can be well recovered, the clustering of the cell subpopulation is promoted, and the deduction of the cell development trajectory is facilitated.

The invention discloses a rotary biological culture and observation device, and belongs to the technical field of biological culture devices, the rotary biological culture and observation device comprises a control display terminal and a control host, and further comprises an environment adjusting system, a culture dish rotating system arranged in the environment adjusting system and an imaging system; the environment adjusting system comprises a culture cabin, the culture cabin comprises a cabin chamber and a cabin door connected with the cabin chamber, and a plurality of culture dish rotating systems are circumferentially distributed in the cabin chamber. By adopting the rotary biological culture and observation device, the culture dish rotating system can optimize a cell growth environment and improve the nutrient exchange rate of biological cells by utilizing centrifugal force generated by rotation and hydrodynamic characteristics, and the environment adjusting system can provide a gas development environment and a temperature development environment for biological sample culture; the phenomena of slow development or death of biological sample cells are reduced, and the culture success rate is increased. Meanwhile, the imaging system can realize real-time imaging and observation of the development state of the biological sample on the premise of not destroying the culture environment.

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.

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.

Mammals rely on adaptive immunity to protect against infections and tumors, with the thymus playing a crucial role by producing T cells that target infected or cancerous cells. The thymus, however, undergoes functional decline with age, significantly impairing the immune system in the elderly. To investigate reversing this decline, compositions and methods for activation and differentiation of T cell progenitors in extrathymic tissues are disclosed that stimulate production of differentiated T cells. For example, LNP-mediated delivery of mRNAs encoding DLL-1, IL-7, and FLT3L to the liver is shown to create a temporary site for T cell maturation that enhances T cell-mediated immunity in aged mice without causing autoimmunity. This approach facilitates ectopic T cell development from hematopoietic precursors and activates dendritic cells, providing evidence that engineering adaptive immunity in vivo can effectively mitigate immune aging.

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.

The methods have application to the tissue culture of plant cells, ovules and microspores. Automated imaging, automated cell tracking and predictive modeling are used to develop methods that predict the likelihood that a plant cell will develop into a desired phenotype and / or which cellular reprogramming factors will assist in this development. The methods taught herein can also be used to evaluate the toxicity effects of compounds on plant cells, predict genotypic responses to tissue culture and cellular reprogramming factors, determine cell ploidy status, and predict other types of cell phenotype development.

In one aspect, methods of promoting bone growth are described herein. In some embodiments, a method of promoting bone growth described herein comprises promoting cell differentiation or phenotype progression in a population of bone cells by providing a citrate-presenting composition to the population of bone cells. In some embodiments, the citrate-presenting composition is provided to the bone cells at a first stage of cell development selected to obtain a first cell differentiation or phenotype progression. Additionally, in some cases, a second citrate-presenting composition is further provided to the bone cells at a second stage of cell development selected to obtain a second cell differentiation or phenotype progression.

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 discloses an scRNA-seq missing data prediction method based on a bidirectional auto-encoder. The scRNA-seq missing data prediction method comprises the following steps: 1, acquiring an scRNA-seq data matrix; 2, carrying out normalization on the scRNA-seq matrix; and 3, respectively learning similarity characteristics between cells and between genes by using a row auto-encoder and a column auto-encoder, and respectively reconstructing data by using the learned characteristics. And 4, introducing a cross point loss function to restrain a cross point of reconstruction data of the two auto-encoders, and realizing information sharing between cells and between genes by sharing weights. And 5, predicting scRNA-seq data by using features learned by the row auto-encoder and the column auto-encoder, and taking a mean value of the scRNA-seq data as a final predicted value. Meanwhile, non-zero values in the original scRNA-seq data are identified and are regarded as real expression values, and only zero values are filled. According to the method, the missing value can be well recovered, the clustering of the cell subpopulation is promoted, the identification of the marker gene is perfected, and the inference of the cell development trajectory is facilitated.