50 results about "Cellular distribution" patented technology

The invention provides a blood smear device and method for a clinical laboratory. The method comprises the following steps: collecting a staining image of a blood smear; segmenting a gathering region and a sparse region of the blood cells in the blood smear from the dyed image, and determining edge features of each blood cell in the dyed image; performing overlapping analysis on the overlapped blood cells in the aggregation area based on the edge features of the blood cells in the aggregation area to obtain an overlapping influence area of the blood cells in the aggregation area; based on the edge features of the blood cells in the sparse region, reconstructing gaps among the blood cells in the sparse region to obtain a gap reconstruction region of the blood cells in the sparse region; determining the density distribution characteristics of the blood cells in the dyeing image according to the overlapping influence area and the gap reconstruction area; and detecting the uniformity of the blood smear according to the density distribution characteristics. By adopting the scheme of the invention, the blood cell distribution condition can be accurately identified under complex interference factors.

The invention provides a cell distributed storage coding rule method, and aims to solve the problem that in the prior art, homologous cells are difficult to identify and trace quickly due to lack of uniform coding rules when being stored in different storage containers and places. According to the method, cell source information, storage position information, time information, feature information and the like are integrated into a multi-dimensional code by establishing a uniform coding system, so that cross-container and cross-site cell rapid identification and tracing are realized. And the coding system comprises a verification mechanism, so that the coding accuracy and integrity can be ensured. The invention also provides a corresponding decoding and verification method and a specific embodiment.

The invention relates to a myocardial tissue construct with a bionic structure and a function as well as a preparation method and application of the myocardial tissue construct. The myocardial tissue construct with both the bionic structure and the function comprises the following components: a hydrogel matrix suitable for 3D printing rheological properties, a cross-linking agent dispersed in the hydrogel matrix, inorganic biological material particles with myocardial protection and vascularization biological activity promotion, myocardial cells and vascularization related cells, the myocardial cells and the vascularization-related cells are regularly arranged in a three-dimensional space by simulating a cell distribution mode in a natural myocardial tissue; preferably, the regularly arranged structure comprises at least one of spatial arrangement of myocardial cell-angiogenesis related cells in a left-right / up-down side-by-side mode and spatial arrangement of myocardial cell-angiogenesis related cells in a core-shell / shell-core coaxial mode.

The invention relates to the fields of epigenetic regulation and tumor treatment, and aims to evaluate that the cell distribution of the mutant is consistent with that of H3 by constructing Bas-2B (H3K9R) and Bas-2B (H3K18R) stably transfected cell strains and analyzing the cell positioning condition of the H3K9R / H3K18R mutant through an immunofluorescence technique. According to the present invention, a Western blotting technology is adopted to detect the H3K9 / H3K18 lactic acid modification level of Bas-2B (H3K9R) and Bas-2B (H3K18R) cells compared to control cells so as to verify the influence of the H3K9R / H3K18R mutant on the H3K9 / H3K18 lactic acid modification; after Bas-2B (H3K9R), Bas-2B (H3K18R) cells and control cells of the Bas-2B (H3K9R) and the Bas-2B (H3K18R) cells are subjected to nickel compound exposure treatment, the influence of the H3K9R / H3K18R mutant on the nickel compound induced lung cancer is evaluated through a soft agar cloning formation experiment. An AGS cell line stably transfecting H2BK16R is constructed, and the cell localization condition of the H2BK16R mutant is analyzed through an immunofluorescence technology. According to the present invention, a Westernbloting technology is adopted to detect the lactic acid modification level of AGS (H2BK16R) cells so as to verify the influence of the H2BK16R mutant on the H2BK16 lactic acid modification; the influence of the H2BK16R on the malignant proliferation ability of the gastric cancer is researched through a soft agar clone formation experiment.

The invention provides an organoid drug sensitivity automatic detection method and system for multi-sample parallel processing, and the method comprises the steps: obtaining the optical path length data of each hole site of a cell culture perforated plate, and determining the initial focal plane position of each hole site; matching the deformed feature point coordinates with the initial three-dimensional structure data of the similar organs, and calculating the focal plane offset caused by the deformation of the similar organs through least square fitting; adjusting the focal length of the optical imaging system according to the corrected focal plane position by adopting a fast focusing algorithm, and re-collecting an organ-like image; using a layer-by-layer stacked three-dimensional reconstruction algorithm to perform registration splicing on the recollected image sequence to obtain complete three-dimensional structure data after the organ-like body is deformed; and according to the complete three-dimensional structure data, extracting the volume, surface area and cell distribution density characteristics of the organoid, and generating a morphological characteristic report of the drug sensitivity experiment.

The invention discloses a gray clustering characteristic distribution-based cell nucleoplasm segmentation method, which comprises the following steps of: 1) constructing a self-supervised network, and solving a cell intensity distribution diagram of a cell image; 2) determining cell candidate regions in the intensity maps of the cell distribution, the staining intensities of the intensity maps of the cell distribution are different, but the deepest part in the image must belong to a cell nucleoplasm region, so that the candidate regions of the cell nucleoplasm are solved by adopting an iterative search mode; and 3) carrying out accurate segmentation on the obtained candidate cell region to obtain a segmentation result of the cell nucleoplasm, and finally, correspondingly drawing a minimum circumscribed contour of the cell nucleoplasm in the original color map. The invention belongs to the technical field of image processing and biomedicine, and solves the problems that in the prior art, when a cell image is processed, the extraction part is inaccurate, impurities are easy to mix, and the detection precision is influenced.

The invention relates to the field of medical image processing, and particularly discloses a TLS structure sketching system and method based on artificial intelligence, and the method comprises the steps: S1, image preprocessing: carrying out the standardization processing of an input HE staining section image, firstly separating cell nucleus and cytoplasm staining components through a color deconvolution algorithm, and highlighting the nucleoplasm contrast of lymphocytes; then strengthening the cell contour boundary by adopting an edge detection algorithm, and connecting the fracture edge through morphological operation to form a continuous and clear cell boundary mask; s2, morphological feature extraction: performing single cell segmentation based on the preprocessed image, and extracting geometric features and texture features of each cell; through machine learning model training, distinguishing lymphocytes and non-lymphocytes according to the characteristics, and generating a lymphocyte distribution probability graph; and S3, preliminarily identifying the aggregated area. By adopting the technical scheme of the invention, the TLSs differentiation stage can be identified, and the identification accuracy can be improved by combining morphological characteristics and spatial distribution characteristics.

The invention discloses a method and a device for detecting CAR (Chimeric Antigen Receptor) cells. The method comprises the following steps: taking a genome of a sample to be detected as a template, carrying out fluorescent quantitative PCR reaction by using a primer and a probe aiming at the sequence of a CD8 alpha transmembrane region-41 BB costimulatory molecule in a CAR gene to obtain a CT value, and calculating the copy number of the CAR gene according to the CT value and a standard curve to obtain the CAR cell distribution. Specific primers and probes are designed for CAR cells containing CD8 alpha transmembrane region-41BB costimulatory molecules, a fluorescent quantitative PCR method for detecting the copy number of CAR genes is developed, then the CAR cells are quantified, and it is proved that the method has wide applicability through multi-angle verification analysis and limitation of detection standards.

The invention discloses a pathological image data enhancement method based on guidance of a visual-language basic model, and the method comprises the steps: extracting pathological image features and corresponding text features through a pathological visual-language basic model; and performing multi-modal feature fusion by using a cross attention mechanism, and guiding a diffusion model to synthesize a high-quality pathological image matched with the label, thereby realizing data enhancement of a pathological diagnosis task. Comprising the following steps: constructing text description corresponding to a pathological image by using label information of a pathological image data set in combination with a big language visual assistant model for pathological pre-training and a cell segmentation basic model, so as to more accurately characterize a tissue type, morphological details and multi-level visual features of cell distribution of the pathological image; an image-text multi-modal feature fusion network module based on a cross attention mechanism is constructed, and a diffusion model is guided to synthesize a pathological image by taking fusion features as control conditions, so that the synthesized image is ensured to be more matched with data label information, and the scale of a pathological image data set is effectively enhanced.

The present invention discloses an intelligent load balancing method based on a zero-sample hybrid expert model, comprising the steps of: creating a task spectrum mapping relationship through zero-sample learning, generating virtual labels, refining the requirements of new tasks into resource requirement feature spectra through multi-dimensional feature cross-projection, and predicting the multi-dimensional resource requirements of new load balancing tasks; establishing a multi-perspective hybrid expert dynamic integration mechanism, configuring multi-perspective hybrid collaborative experts for tasks, applying a combination of several expert models to different demand dimensions, creating virtual image samples of new tasks, simulating resource requirements and their load effects in a virtual environment, and generating an initial resource allocation plan; in the face of dynamic load fluctuations, distributing task cells to nodes with sufficient resources; the method improves the robustness and efficiency of the system, simplifies the implementation process, and has broad application prospects and practical value.

The invention relates to the technical field of stirring paddles, in particular to a uniform mixing bioreactor stirring paddle which comprises a column body, the rotating shaft is rotationally connected into the column body; through the innovative composite design of a double-layer differential transmission mechanism and vibration stirring, three-dimensional chaotic mixing is realized, and the mixing efficiency and quality are remarkably improved; the upper-layer first rotating mechanism drives a plurality of first stirring paddles to rotate at a set speed through a gear train formed by a first gear ring, a first gear and a second gear ring; the second rotating mechanism at the lower layer drives a second stirring paddle through another independent gear system, slides in a corrugated groove with a specific angle through a T-shaped block, and generates periodic radial vibration in combination with an elastic component; the rotation-vibration composite motion breaks the flow field symmetry of traditional one-way stirring, can effectively eliminate a mixing dead zone, enables nutrient substances, dissolved oxygen and cells to be highly uniformly distributed, and is especially suitable for a high-density and high-viscosity culture system.

The invention relates to the technical field of biology, in particular to a cryopreserved stem cell diluent and application thereof.The cryopreserved stem cell diluent further comprises cysteine and polyvinylpyrrolidone besides a compound electrolyte injection, the concentration of cysteine in the cryopreserved stem cell diluent is 1-10 mM, and the concentration of polyvinylpyrrolidone in the cryopreserved stem cell diluent is 1-10 mM. The concentration of the polyvinylpyrrolidone in the cryopreserved stem cell diluent is 0.02 to 0.1 g / mL. The cryopreserved stem cell diluent can improve the cell activity and cell distribution after the cryopreserved cell preparation is recovered, and can monitor the application of cells in rat living body imaging.

Disclosed are methods and agents for predicting response to therapy, immune status and / or disease progression. More particularly, disclosed are methods, agents and kits for analyzing cellular distribution of PD-L2, including its nuclear localization, for stratifying a patient as a likely responder or non-responder to a therapy, for managing treatment of a patient with a therapy, for monitoring a disease in a patient following treatment with a therapy, for determining the status of a disease and / or for determining the immune status of a patient.

The invention relates to a red blood cell detection area selection method and device, computer equipment and a storage medium, a cell image is input into a pre-trained deep neural network to predict the cell distribution condition and generate a first thermodynamic diagram, and the more uniform the cell distribution is, the higher the thermodynamic value corresponding to the area is; carrying out filtering processing on the first heat map by adopting N preset filtering frames with different sizes to obtain N second thermodynamic diagrams; extracting a coordinate position with the maximum thermodynamic value in each second thermodynamic diagram, and generating a selected area frame with the same size as the corresponding filtering frame by taking the coordinate position with the maximum thermodynamic value on the cell image as a center; extracting cell edges in each selected area frame, and detecting circular features of the cells based on the cell edges; the cells in the selected area frames are screened based on the circular features, the number of red blood cells in each selected area frame is counted, the selected area frame with the red blood cell number closest to the target number serves as the red blood cell detection area, and the red blood cell analysis and detection efficiency is effectively improved.

This invention discloses a method for analyzing the distribution of plasmablasts and Treg cells based on tissue section images, belonging to the field of plasmablast and Treg cell distribution analysis technology. The method includes the following steps: labeling plasmablasts and Treg cells in tissue section images; statistically analyzing the distribution ratio of plasmablasts and Treg cells; calculating the mixed parameters of plasmablasts and Treg cells in the tissue section images; obtaining tissue section images with different prognostic effects as sample images and extracting mixed sample parameters; analyzing the correlation between mixed parameters and prognostic effects based on the mixed sample parameters; and determining whether the prognosis of mice is good based on the distribution of plasmablasts and Treg cells and the correlation. This invention addresses the problem that existing plasmablast and Treg cell distribution analysis techniques lack comprehensive and in-depth analysis of the distribution of plasmablasts and Treg cells, leading to biased assessments of prognostic effects.

This application relates to a method, apparatus, computer equipment, and storage medium for selecting red blood cell detection regions. The method involves inputting a cell image into a pre-trained deep neural network to predict cell distribution and generate a first heatmap. Regions with more uniform cell distribution correspond to higher heatmap values. The first heatmap is then filtered using N preset filter boxes of different sizes to obtain N second heatmaps. The coordinates of the highest heatmap value in each second heatmap are extracted, and a selection box of the same size as the corresponding filter box is generated centered on the coordinates of the highest heatmap value on the cell image. Cell edges within each selection box are extracted, and the circular features of cells are detected based on these edges. Cells within the selection boxes are then screened based on these circular features, and the number of red blood cells within each selection box is counted. The selection box with the closest red blood cell count to the target count is selected as the red blood cell detection region, effectively improving the efficiency of red blood cell analysis and detection.

The invention provides an AI-based anemia risk analysis method and system, a terminal and a storage medium, and relates to the technical field of medical image analysis, and the method comprises the steps: obtaining a plurality of to-be-analyzed single erythrocyte images; inputting each single red blood cell image into a local feature extraction network to obtain local features of each single red blood cell image so as to construct a feature matrix; the feature matrix is input into a risk analysis model, the risk analysis model comprises a global feature extraction network and a prediction network, and the global feature extraction network is used for calculating the attention weight of a single red blood cell through a self-attention mechanism according to the feature matrix, performing weighted aggregation on the local features based on the attention weight, and outputting global features; and the prediction network is used for outputting an anemia prediction probability according to the global features. According to the method, the context dependency relationship of the red blood cell population can be effectively modeled, the multi-cell distribution characteristics are integrated, and the requirement of large-scale blood form image automatic anemia analysis is met.

The invention belongs to the field of biomedical materials, and particularly relates to a hydrogel composite scaffold loaded with human spinal cord V3 precursor cells for spinal cord injury repair and a preparation method of the hydrogel composite scaffold. The hydrogel composite scaffold comprises hydrogel and human spinal cord V3 neural precursor cells, hydrogel is used as a carrier, the human spinal cord V3 neural precursor cells are loaded on the hydrogel, and the hydrogel is formed by oxidized hyaluronic acid and carboxymethyl chitosan through a Schiff base cross-linking reaction. The specific preparation method comprises the following steps: mixing the human spinal cord V3 neural precursor cells with hydrogel to obtain the hydrogel composite scaffold loaded with the human spinal cord V3 neural precursor cells. Therefore, the technical problems of low cell survival rate, non-uniform cell distribution and difficulty in controlling the cell differentiation direction in spinal cord injury repair in the prior art are solved.

The invention discloses a bionic scaffold for treating osteoporotic bone defect, and relates to a bionic material, the scaffold is composed of three parts, namely melatonin-loaded PLGA sustained release microspheres, a silk fibroin / nano-hydroxyapatite (SF / n-HA) composite scaffold and methacrylic anhydride gelatin (GelMA) hydrogel wrapping bone marrow mesenchymal stem cells. The preparation method comprises the following steps: firstly, preparing PLGA sustained-release microspheres by an emulsion solvent evaporation method, and encapsulating melatonin in a PLGA matrix; secondly, mixing SF and n-HA according to a specific proportion, and freeze-drying to form a porous scaffold; then, the microspheres are compounded in pores of the stent through vacuum adsorption; and finally, performing negative pressure perfusion on the stem cell-containing GelMA hydrogel, and performing ultraviolet light crosslinking and curing on the surface of the composite scaffold. According to the scheme, the synergistic effect of drug sustained release, bone conduction and stem cell osteogenesis activity is achieved through layered structure design, and the problems that in the prior art, drug release is unstable, cell distribution is uneven, and stent degradation and bone regeneration are not matched are solved.

System and method for exercising cells and / or tissue in a sealed bioreactor. System includes a cartridge having a stretching means and a means to retain cells on a scaffold mounted within the cartridge during seeding. System includes a bioreactor including a sealed enclosure, the sealed enclosure housing the scaffold and the cartridge, the bioreactor enabling uniform seeding of the scaffold with the cells, the seeding occurring within the sealed enclosure to protect from environmental contamination. The bioreactor system provides a means to supply fresh media to the cells and / or tissue, and a means to remove waste products.

Describes systems and methods for providing quantitative measurements of the distribution of a contrast agent in a tissue sample by identifying the cellular distribution of the contrast agent using a combination of high-resolution optical sectioning imaging modalities. In some cases, the systems and methods can be used in an intraoperative setting to guide biopsies or surgeries.

The present application discloses a method, apparatus, device and medium for constructing a database based on Nephila clavata spiders, relating to the field of databases, including: assembling the chromosomal genome of Nephila clavata spiders that meets the first preset high-quality condition; annotating the chromosomal genome to obtain an initial annotation file, and deleting the annotations of gene sequences that do not meet the screening criteria in the initial annotation file to obtain a target annotation file; determining the expression value and co-expression relationship of each gene sequence based on the ordinary transcriptome; performing functional annotation on the classified cell clusters obtained by classifying the single-cell transcriptome after sequencing to obtain an annotated transcriptome; determining the cell distribution within the spatial structure based on the spatial transcriptome after sequencing; constructing a database based on the target annotation file, expression value and co-expression relationship, annotated transcriptome and cell distribution within the spatial structure. A comprehensive spider database is constructed to facilitate the rapid acquisition of comprehensive information on the genome and other omics of spiders.

The present invention relates to the technical field of powder metallurgy of superalloys, and particularly relates to a preparation method of a high-strength superalloy with a cellular distribution of γ' phase, comprising: preparing superalloy powder; loading the prepared superalloy powder into a first sheath, evacuating and sealing the first sheath; performing a preheating treatment on the first sheath; dispersing the superalloy powder in the first sheath; opening the first sheath, and transferring the superalloy powder from the first sheath into a second sheath through a charging tank under vacuum conditions; performing hot isostatic pressing treatment on the second sheath after powder loading to obtain a first workpiece; cooling the first workpiece to obtain a second workpiece; removing the second sheath outside the second workpiece to obtain a blank, and performing a heat treatment on the blank to obtain a target alloy; the present invention utilizes powder metallurgy technology and adjusts the preparation process to form a γ' phase with a special distribution inside the alloy, thereby improving the tensile strength and creep strength of the alloy.

Systems, methods, and devices disclosed herein include three-dimensional bioprinting technologies which produce cell scaffolds with a high degree of complexity and precision. A bioprinting ink mixture can be formed with coated gold nanoparticles in an alginate-gelatin solution. Upon bioprinting a 3D scaffold microstructure from the bioink mixture, an imaging procedure is performed on the 3D scaffold microstructure using the coated gold nanoparticles as a contrasting agent. A microstructure characterization is determined from the imaging procedure, and a virtual 3D reconstruction of the microstructure characterization can be generated for presentation on a graphical user interface (GUI) of a computing device. These techniques can be used to determine whether the resultant internal core of the microstructure properly mimics the architecture of the native tissue extracellular matrix (ECM) present in-vivo by determining the degree of pore interconnectivity which can improve cell distribution, attachment, and growth in the 3D scaffold microstructure.

A cell image instance segmentation method based on Bayesian inference and Boosting. For the instance segmentation of cell images, since it contains very complex image features (low foreground-background contrast, large image noise, high cell distribution density, cell adhesion, multi-layer cell overlap, etc.), it is very difficult to accurately segment each cell individual from the pathological image. Some of the methods in the past research can only segment out some cells, or require a large amount of data sets and computing power. Therefore, we urgently need a method that can completely segment each cell without consuming a lot of computing power, and the segmentation effect can achieve the expected method. The present invention introduces a multi-level set energy function and a minimum description length to perform contour reasoning, and then adds multi-layer cascade Boosting for classification and regression, so that each target in the image can be identified and accurately segmented.

The invention discloses a tissue sealing reagent, a multi-index RNA-protein co-dyeing method and application, and belongs to the technical field of molecular biology. The tissue sealing reagent comprises the following components: ethylene carbonate, dextran sulfate, sodium chloride, citric acid, trisodium citrate dihydrate and herring sperm DNA (deoxyribonucleic acid). The invention further discloses a multi-index RNA-protein co-dyeing method, multi-index co-dyeing of RNA-protein on the same tissue slice can be achieved, multiple RNA in-situ hybridization strategies are compatible, and an effective solution is provided for the non-specific dyeing problem occurring in the existing hybridization strategies. By optimizing sample treatment, a co-staining method and a signal enhancement strategy, high-resolution spatial localization of gene expression on the tissue slice is achieved, the method is particularly suitable for research of cell distribution and gene expression modes of complex tissues, and important technical support can be provided for research of disease mechanisms, development of targeted therapy and precision medicine.

This invention relates to the field of image analysis technology, specifically to a method for assessing the distribution of cardiac mesothelial cells based on immunofluorescence images. The method includes: acquiring multiple immunofluorescence images of cardiac mesothelial cells at different antibody concentrations within the assessment group; determining initial cardiac mesothelial cell regions based on the staining status of the isotype control group and the differences in staining depth among multiple staining regions in the immunofluorescence images; analyzing non-specific staining based on changes in the staining area and irregular cell boundaries of the initial cardiac mesothelial cell regions, and adjusting the antibody concentration accordingly; determining multiple target cardiac mesothelial cell regions, and obtaining the location information of the cardiac mesothelial cells based on the degree of overlap and similarity between these regions; and analyzing the spacing distribution of cardiac mesothelial cells and their distribution in the immunofluorescence images based on the location information to obtain the uniformity of the cardiac mesothelial cell distribution.

The invention discloses a cell image analysis method and system based on a geometric mean and a graph structure, and the method comprises the steps: inputting a multi-channel fluorescence image into a cell recognition algorithm model, and obtaining a cell distribution graph; calculating a cell deviation degree parameter in the cell distribution diagram according to a geometric mean algorithm; based on a graph neural network, extracting cell graph features corresponding to the cell distribution graph and the cell deviation degree parameter; and according to the time sequence corresponding to the cell map features at the plurality of historical time points, predicting cell pathology classification and change trend at a future time point based on an LSTM neural network. Therefore, the method can achieve the accurate prediction of the cell pathology classification and the evolution trend of the cell pathology classification at the future time point, improves the automation level and the prospective judgment capability of cell pathology analysis, and provides efficient and reliable technical support for disease monitoring and auxiliary diagnosis.

The embodiment of the invention provides a method and system for analyzing spatial transcriptome data, and belongs to the technical field of data analysis. The system comprises a data uploading and quality control module which is used for uploading spatial transcriptome data, bright field pictures and sample clinical information and performing quality control on the uploaded data; the spatial multi-omics feature identification and integration module is used for identifying spatial multi-omics features, integrating multi-omics data, carrying out batch processing on the data and unifying a data format; the spatial multi-omics data analysis module is used for performing data analysis of gene expression, genome variation, RNA modification, variable polyadenylation and pathogen and cell distribution dynamics according to different omics data types; the user management module is used for providing multi-level authority management; and the analysis report module is used for automatically generating analysis report data. According to the method, the depth and breadth of spatial transcriptome data analysis can be improved, and spatial multi-omics features can be analyzed more comprehensively and accurately.

The invention relates to the technical field of image analysis, in particular to a cardiac mesothelial cell distribution assessment method based on immunofluorescence images, which comprises the following steps: acquiring a plurality of immunofluorescence images corresponding to cardiac mesothelial cells under different antibody concentrations in a group to be assessed; determining an initial heart mesothelial cell region according to the dyeing condition of the same type control group and the dyeing depth difference of a plurality of dyeing regions in the immunofluorescence image; analyzing the non-specific staining condition according to the staining area change and the cell boundary irregularity condition of the initial heart mesothelial cell region, and adjusting the antibody concentration; determining a plurality of target cardiac mesothelial cell regions, and obtaining the position information of cardiac mesothelial cells according to the overlapping similarity among the plurality of target cardiac mesothelial cell regions; and according to the position information of the heart mesothelial cells, analyzing the spacing distribution of the heart mesothelial cells and the distribution of the heart mesothelial cells in the immunofluorescence image to obtain the distribution uniformity of the heart mesothelial cells.