505 results about "Cell type" patented technology

A spatial omics multi-modal fusion method under a single cell level comprises the following steps: extracting spatial morphological characteristics of differential expression genes and cell nucleuses from spatial transcriptome data, single cell sequencing data and histological images, and realizing field adaptation among different platforms by using a conditional variation auto-encoder. And based on a probability inference model, fusing spatial transcriptome expression, unicellular omics and morphological characteristics, and jointly inferring the type and gene expression level of each cell. A spatial cell network is constructed through a graph attention mechanism, and spatial diffusion and recognition of cell types in a full slice range are realized. In combination with a multi-omics enhancement module, undetected gene and protein expression is completed based on expression similarity, and prediction consistency is improved through spatial correction. According to the method, high-resolution reconstruction of single-cell multi-omics information in a three-dimensional space is realized, the information coverage and spatial resolution of spatial omics data are improved, and an efficient and low-cost solution is provided for spatial biology and precise medical research.

The invention discloses a 3D intestinal organ differentiation method based on human pluripotent stem cells and an induction culture medium and application thereof, and relates to the technical field of stem cells. According to a culture medium formula combination, intestinal organs can be differentiated into various cell types such as epithelial cells, neuroendocrine cells and endothelial cells; the method is a key mark for successful differentiation and functional maturation of intestinal organs. According to the 3D intestinal organ differentiation method disclosed by the invention, histological structures such as intestinal crypts are differentiated from intestinal organs generated by differentiation, and the intestinal organs can creep in a maintenance stage, so that the intestinal organs are changed from structural bionics to functional simulation, and the significance of the 3D intestinal organ differentiation method is far better than that of pure morphological simulation. Through a systematic culture medium formula, a clear operation process and a multi-stage induction strategy, the 3D intestinal organ with structural integrity, cell diversity and functional activity is successfully constructed, and the system provides an efficient, reliable and extensible in-vitro model platform for intestinal biological research and related application.

The invention discloses a key marker gene-based intelligent cell type annotation method, which comprises the following steps of: constructing a static knowledge base by using known marker genes in a reference database, and endowing the marker genes with cell specific weights by using a TF-IDF method, so that the annotation accuracy and interpretability are improved. Meanwhile, under the condition that static matching is insufficient, the literature is understood through a large language model, mark information is extracted, dynamic completion of the knowledge base is achieved, the defect that updating of a traditional knowledge base is lagged is overcome, and good adaptability and expansibility are achieved. Besides, static and dynamic matching scores are fused in the annotation process, so that more robust cell type identification is realized, annotation requirements of multi-tissue, multi-species and novel cell states are adapted, high-precision and extensible cell type annotation can be realized in a scene with insufficient reference knowledge or a fuzzy sample, and the annotation efficiency is improved. And the method has good universality and practicability.

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 discloses a method for automatically constructing a pathological image data set and training cell nucleus detection and classification based on a space transcriptome technology, and belongs to the field of image processing and artificial intelligence auxiliary pathological diagnosis. According to the method, a spatial transcriptome public data set is obtained, and a data set containing image blocks, weak supervision / semi-supervision labels and cell nucleus boundary information is automatically constructed through preprocessing, deconvolution cell type annotation and cell nucleus instance segmentation, so that the dependence on manual annotation is reduced. Furthermore, a detection and classification model is designed, a multi-scale deformable attention encoder and a decoupled detection and classification decoder are adopted, a limited deformable cross attention mechanism is introduced into the classification decoder, KL divergence classification loss is combined, and instance-level cell nucleus categories are learned from region-level proportion labels. According to the method, end-to-end automation is realized, the cell nucleus detection and classification precision and efficiency are improved, and a high-quality pre-training model basis is provided for downstream pathological analysis.

The application provides a single-cell transcriptome cell annotation method and system of a fusion large language model, cell type annotation is performed through construction of special prompt words and use of a large language model, and the accuracy and universality of cell annotation are improved. The application has a significant advantage for cell annotation of non-model species, and realizes an automatic and intelligent cell annotation process.

Provided is a method for screening myocardial therapeutic targets for ischemic heart failure by using single-cell sequencing, which method comprises the following steps: S1, sample preparation; S2, construction of a single-cell expression matrix; S3, cell quality control; S4, cell type annotation; S5, cell communication analysis; and S6, co-expression network analysis. The provided method for screening myocardial therapeutic targets for ischemic heart failure by using single-cell sequencing comprises performing single-cell sequencing on hearts of healthy mice and IHF mice, screening for cell types with significant differences in cardiac transcriptional profiles of the healthy mice and IHF mice, then exploring interaction characteristics of various types of cells in malignant fibrotic IHF hearts, revealing potential regulatory modules and pathways related to malignant myocardial fibrosis in single-cell expression data of IHF hearts, and performing screening to obtain Pdgfb and Tnfsf12 genes which can be used as therapeutic targets for treating myocardial fibrosis in ischemic heart failure.

Provided herein is a DNA analysis method for detecting and quantifying immune cell types from which the DNA originated. Provided herein are also methods for determining the likelihood that a subject has a disease or condition, such as cancer.

The invention discloses a nucleic acid transfection system and method based on automatic control, and relates to the technical field of genetic engineering.The method comprises the steps that after target cells are intelligently cultured to be in a suitable state, an automatic system selects a transfection reagent and prepares a compound according to cell types; the cells and the compound are mixed through low shear force and then incubated; multi-modal monitoring equipment is used for tracking nucleic acid distribution and cell states in real time, and incubation conditions are dynamically adjusted; analyzing the monitoring data based on a machine learning algorithm and optimizing transfection parameters; after transfection, culture and multi-dimensional analysis are automatically executed. The system correspondingly comprises a cell culture module, a reagent preparation module, a mixed incubation module, a real-time monitoring module, a dynamic optimization module and a subsequent analysis module. Through closed-loop automatic control and intelligent optimization, the transfection efficiency and stability are remarkably improved, the cytotoxicity is reduced, manual intervention is reduced, and a standardized solution is provided for recombinant gene expression.

Apparatus and methods are described including preparing a blood sample for analysis by depositing the blood sample within a sample chamber (52), and placing the sample chamber, with the blood sample deposited therein, within a microscopy unit (24). One or more microscopic images of the sample chamber (52) with the blood sample deposited therein are acquired, using a microscope of the microscopy unit. Based upon the one or more images, an amount of one or more cell types within the sample chamber that had already settled within the sample chamber, prior to acquisition of the one or more microscopic images is determined. A characteristic of the sample is determined, at least partially in response thereto. Other applications are also described.

The invention provides a method and a system for predicting a cell type-specific non-coding variation function, and belongs to the technical field of bioinformatics. Comprising the steps that a DINOSNN prediction model is constructed, model training is carried out, and the model is composed of a convolution and attention mixed neural network model and a non-coding variation prediction model; obtaining all non-coding variations corresponding to each brain mental disease, inputting the non-coding variations into a DINOSNN prediction model, predicting the probability that each non-coding variation is a functional non-coding variation through a trained gradient boosting tree model, and predicting a cell type set influenced by the variation, further establishing a corresponding relationship among the brain and mental diseases, the non-coding variation and the cell type set influenced by the non-coding variation; and selecting a cell type set corresponding to the non-coding variation with the highest probability of functional non-coding variation from the non-coding variations corresponding to the brain and mental disease to be analyzed as a targeted cell set corresponding to the brain and mental disease to be analyzed.

The present disclosure provides stealth lipid nanoparticle (LNP) compositions engineered to target specific tissues or cell-types, e.g., T cells, B cells, natural killer cells, to genetically modify the cells with therapeutic nucleic acid encapsulated in the LNP. The present disclosure also provides compositions and methods of making the LNPs and treatment using the same.

Disclosed are cell penetrating peptides and compositions comprising such peptides that can be used to deliver agents to various cell types.

Several embodiments of the methods and compositions disclosed herein relate to immune cells that are engineered to express chimeric antigen receptors as well as genetically edited or otherwise engineered enhance the persistence the cells in immunotherapy. In several embodiments, the cells are edited to knock out a target gene that encodes a protein involved in antigen processing and presentation by major histocompatibility complex class I molecules. In several embodiments, a mixture of immune cell types is used, optionally in allogeneic therapy. The engineering and editing of the cells, such as NK cells and / or T cells exhibit enhanced cytotoxicity and / or persistence, as well as reduced risk of reduced graft versus host, host versus graft, and graft versus graft effects.

The invention discloses a cell interaction identification method based on cell space transcriptome data, which comprises the following steps: constructing cell pairs according to cell space proximity, and calculating an interaction signal matrix and space information of each pair of cells by combining a ligand-receptor database; then generating cell pair embedding representation by using a graph neural network, calculating the similarity between cell pairs, and calculating the similarity between cells based on a gene expression matrix; updating the similarity matrix through iteration until convergence to obtain a final similarity matrix between cells and between cell pairs; and clustering the similarity matrix, and constructing a cell type and cell pair type model, thereby realizing accurate cell interaction identification. According to the method, space and expression information can be fully utilized, inter-cell heterogeneity and context specificity interaction can be captured, the analysis precision and biological authenticity of a cell communication network are improved, and an effective tool is provided for research on tissue development, disease mechanisms, immune response and the like.

The invention discloses a cell type annotation method and annotation system. The annotation method comprises the following steps: confirming a common gene of single cell data and spatial transcriptome data, and extracting first gene expression corresponding to the single cell data and the common gene and second gene expression corresponding to the spatial transcriptome data and the common gene; performing feature extraction on the first gene expression by using a common encoder to obtain a first potential feature, and performing feature extraction on the second gene expression to obtain a second potential feature; aligning a distribution of the first potential feature and the second potential feature over a common space; and performing cell type annotation on the spatial transcriptome data based on a preset distance function in combination with the first potential feature and the second potential feature. According to the technical scheme, the accuracy of annotating the cell types can be effectively improved.

Disclosed are cell penetrating peptides and compositions comprising such peptides that can be used to deliver agents to various cell types.

The invention discloses a method for large-scale production of engineered extracellular vesicles based on freeze-drying and hydration, which comprises the following steps: carrying out freeze dehydration treatment on cells, and then inducing the cells to generate target extracellular vesicles through hydration treatment. The method provided by the invention has good cross-cell type compatibility, is adaptive to suspension cells and adherent cells through a mild membrane reconstruction process, and has good biological safety. The invention further discloses the extracellular vesicles produced by the method and application of the extracellular vesicles.

The present invention relates to lipid nanoparticle (LNP) compositions, as well as diagnostic or therapeutic polynucleotides, such as TERT mRNA, that can be delivered in a formulation together with the LNP compositions to various tissue and cell types in the whole body of a mammal, such as, for example, TNP mRNA. Comprising stem cells, progenitor cells, germ cells, differentiated cells or terminally differentiated cells, cancer cells, endothelial cells, epithelial cells, splenic cells, hepatocells, kidney cells and / or osteoblasts, for example, for use in the diagnosis, prevention and / or treatment of a condition or disease.

The invention belongs to the technical field of proton radiotherapy, and discloses a proton radiotherapy optimization method based on a proton RBE model. The method comprises the following steps: acquiring given LET, proton dose and cell type; and determining an RBE value based on a proton RBE model of cell type analysis, wherein the RBE value is used for proton radiotherapy. The method is suitable for RBE prediction under different doses and LET conditions, and is beneficial for realizing rapid and efficient biological dose evaluation in a clinical treatment plan of protons.

The present invention relates to a method for predicting a solid tumor immune cell therapy treatment response. The method comprises acquiring a tumor tissue section from a patient, and detecting the presence, number, proportion or density of one or more cell types in the tumor tissue section. A solid tumor immune cell therapy response is predicted by determining cell markers, such as α-SMA, CD3, CD4 or CD8, associated with the cell types. In addition, the present invention also relates to a kit used for predicting a solid tumor treatment response, including a reagent which detects expression levels of one or more cell types and cell markers in tumor tissue sections, and software and / or a user manual used for analyzing detection results. The method and kit provide an effective tool for clinical treatment, so as to optimize dosages and clinical regimens of immune cell therapy, thereby improving treatment response rates.

The invention relates to a method and system for detecting cells of a first cell type (1) in a biopsy sample in which a plurality of cells of different cell types (2, 3) are present. The invention further relates to a device for carrying out a magnetic field measurement on cells of a biopsy sample that are labeled with magnetic nanoparticles. The method comprises the following method steps: carrying out tissue dissociation of the biopsy sample in order to singulate the cells present in the biopsy sample; supplying magnetic nanoparticles (11) to the singulated cells in order to selectively label the cells of the first cell type (1); removing the excess magnetic nanoparticles (11); introducing the cells into a microchannel (5), the microchannel (5) having a cross section which allows only one labeled cell (1) to pass through at a time; carrying out a magnetic field measurement in the microchannel (5) by means of a quantum magnetic field sensor (6) based on the F-center principle; and sorting out the labeled cells (1) after they have passed through the microchannel (5).

Provided herein are compositions and methods for identifying the cell type origin of cells based on RNA sequencing (RNA-seq) data.The method provided herein may include: receiving a plurality of sequencing read counts; providing a set of detected cell types and a related gene set G for each cell type, such that each gene set G comprises a plurality of genes g; scoring the sequencing read counts to generate an assignment score; and assigning each cell among the plurality of cells to the cell type with the highest assignment score, thereby identifying the cell type origin of each cell.This method can be implemented, for example, using a computer system.

The generation of complex organ tissues from human embryonic and pluripotent stem cells (PSCs) remains a major challenge for translational studies. It is shown that PSCs can be directed to differentiate into intestinal tissue in vitro by modulating the combinatorial activities of several signaling pathways in a step-wise fashion, effectively recapitulating in vivo fetal intestinal development. The resulting intestinal “organoids” were three-dimensional structures consisting of a polarized, columnar epithelium surrounded by mesenchyme that included a smooth muscle-like layer. The epithelium was patterned into crypt-like SOX9-positive proliferative zones and villus-like structures with all of the major functional cell types of the intestine. The culture system is used to demonstrate that expression of NEUROG3, a pro-endocrine transcription factor mutated in enteric anendocrinosis is sufficient to promote differentiation towards the enteroendocrine cell lineage. In conclusion, PSC-derived human intestinal tissue should allow for unprecedented studies of human intestinal development, homeostasis and disease.

The application provides a double cell recognition method, comprising the following steps: step one) obtaining a data set to be subjected to double cell recognition, and then clustering and grouping the data set to be subjected to double cell recognition to obtain a plurality of cell populations; step two) determining mutually exclusive protein pairs according to the cell types of the data set to be subjected to double cell recognition, and then determining the expression negative cell population and the expression positive cell population corresponding to each protein in the mutually exclusive protein pairs by using the COSG method of cyclic iteration in the cell populations obtained in step one); step three) calculating the threshold value of the positive and negative expression of each protein in the mutually exclusive protein pairs according to the data in the expression negative cell population and the expression positive cell population; and step four) recognizing double cell data in the data set to be subjected to double cell recognition according to the threshold value. The double cell recognition method based on the COSG method of cyclic iteration is more stable and more effective in the recognition of positive and negative cell population modules.

It can be useful to regulate the growth of microbial cells. Some embodiments herein provide genetically engineered microbial cells that can produce bacteriocins to control the growth of microbial cells. In some embodiments, microbial cells are contained within a desired environment. In some embodiments, contaminating microbial cells are neutralized. In some embodiments, a first microbial cell type regulates the growth of a second microbial cell type so as to maintain a desired ratio of the two cell types.

The invention relates to a co-culture microsphere model with a core-shell structure and a preparation method of the co-culture microsphere model. The co-culture microsphere model comprises a core-shell microsphere, the core-shell microsphere is composed of an inner core and an outer shell, the inner core is an organoid loaded by matrigel, the outer shell is formed by crosslinking a photo-crosslinking hydrogel material, co-culture cells are doped in the photo-crosslinking hydrogel material, and the inner core is wrapped by the outer shell. According to the co-culture microsphere model, double-layer structure microspheres of co-culture cell wrapped organoids are formed, immune infiltration and in-vivo characteristics can be simulated, and a similar in-vivo three-dimensional tumor immune microenvironment is provided. And the types of cells loaded on the inner layer and the outer layer can be flexibly replaced to form a microsphere model for co-culture of single or multiple cells and organoids. The co-culture microsphere model is more stable in structure, the size of the diameter of the core-shell microsphere can be optimized by changing 3D printing parameters, the operability of subsequent research is high, and the co-culture microsphere model is suitable for different research application scenes.

The present invention relates to a method for plant genome modification of at least one plant cell being in the developmental stage of a plant immature inflorescence meristem (IIM) cell, wherein the modification of the specific cell type is achieved by providing a genome modification or editing system, optionally together with at least one regeneration booster, preferably wherein the effector molecules are introduced by particle bombardment. To this end, new artificial and precisely controllable booster genes and proteins are provided. Further, the modified plant cells are regenerated in a direct or an indirect way. Finally, methods, tools, constructs and strategies are provided to effectively modify at least one genomic target site in a plant cell, to obtain the modified plant cell and to regenerate a plant tissue, organ, plant or seed from the modified plant cell.

1. The name of the design product: graphical user interface for computer cell marker gene statistics. 2. The use of the design product: the design product is used in electronic equipment to count cell marker genes. 3. The design points of the design product: the interface content of the graphical user interface. 4. The picture or photo that best shows the design points: front view. 5. The product involved in the design patent application is a graphical user interface, and the rear view, left view, right view, top view and bottom view are omitted. 6. Other circumstances that need to be explained: the interface of the product is a graphical user interface for cell marker gene statistics, which is a structured design of species, system, tissue, cell type and visualization design of species structure. The first column is species, the second column is system and tissue, the third column is cell type, and the fourth column is typical marker statistics of cells. Users can filter species, system, tissue and cell type through this interface, and finally view the typical marker statistics chart of cells.

The application provides a pulmonary artery tissue-derived cell, an organoid and a construction method and application thereof. The pulmonary artery intimal stripping tissue organoid structure obtained by the preparation method is clear, has consistent cell types as the source tissue, is close to the original tissue, is convenient for researchers to operate, and thus has good practical application value.