29 results about "Cellular distribution" patented technology

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 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 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.

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.

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.

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.

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 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.

The present application relates to the technical field of medical equipment monitoring, and particularly relates to a wireless temperature and humidity monitoring system and method for medical refrigerators. The system of the present application comprises a distributed wireless sensing module, an edge data processing module, a cloud monitoring platform, an intelligent early warning module and a blockchain storage module. The distributed wireless sensing terminal adopts a cellular distribution mode, integrates a high-precision temperature and humidity sensor, a laser scattering compensation component and an RFID-WiFi dual-mode communication unit, realizes global accurate collection and reliable transmission; the edge data processing module generates a three-dimensional temperature and humidity distribution model through space-time calibration and temperature field reconstruction, and predicts potential equipment failures; the intelligent early warning module performs hierarchical early warning and links the standby refrigeration unit; the blockchain storage module stores all data on the chain to ensure that the data cannot be tampered with. The present application is suitable for intelligent temperature and humidity monitoring and compliance control in medical material storage scenes such as vaccines, blood products and biological reagents.

This invention discloses a blastocyst induction culture medium derived from mouse and human embryonic stem cells (ESCs) and a method for inducing and culturing blastocysts in mice and humans. Using a chemically defined blastocyst induction culture medium, mouse / human ESCs differentiate into three different cell lineages found in natural blastocysts. Further, using the same blastocyst induction culture medium, the mixed state of mouse / human cells containing the three different cell lineages obtained in the previous step is induced to produce mouse and human blastocyst structures under suspension culture conditions. This invention utilizes a specific blastocyst induction culture medium and induction culture method to enable mouse / human ESCs to self-assemble into blastocyst structures. Experimental methods have verified that mouse and human blastocysts are similar to natural blastocysts in morphology, size, cell number, cell distribution, and gene expression characteristics, providing a new research model for in vitro tissue morphogenesis, organoid modeling, and drug screening.

The invention discloses a serous cavity effusion sample property identification method and system based on data statistics, and the method comprises the following steps: S1, preparing a serous cavity effusion sample slide, the operation comprising manual slide pushing and dyeing; s2, checking the prepared slide, wherein the checking content comprises whether cell distribution is uniform or not and whether dyeing is clear or not, and re-flaking the sample of which the flaking quality does not meet the item checking requirement; s3, observing the image of the slide under the microscope, judging the type and number of cells according to the serous cavity effusion cell morphological map, and recording the result; s4, carrying out statistical analysis on a recording result obtained in the step S3, and calculating the proportion of the total number of cancer cells in all the visual fields to the total number of nucleated cells in all the visual fields; and S5, judging the sample property according to the ratio and the number of the total number of cancer cells in the visual field. The invention provides a clear judgment rule and an implementation method of the sample property, and provides a clear judgment rule for the result in the gray region, so that the accuracy of the final result is ensured.

This invention discloses a benzo[selenazole] derivative, its preparation method, and its application in the preparation of RNA fluorescent probes. The benzo[selenazole] derivative provided by this invention has the following structural formula: [structural formula would be inserted here]. This benzo[selenazole] derivative is a typical fluorescently activated probe, exhibiting excellent selective recognition and binding ability for RNA molecules. It demonstrates excellent resistance to biological background interference and exhibits high binding selectivity and recognition specificity for RNA in both live and fixed cell systems. It possesses advantages such as high signal-to-noise ratio and excellent fluorescence photostability, making it suitable for real-time, dynamic fluorescence imaging detection of intracellular RNA. It can achieve in-situ visualization and tracing of changes in subcellular RNA distribution and content. The synthesis method of the benzo[selenazole] derivative provided by this invention has a clear process flow, mild and stable reaction conditions, requires no demanding equipment or special reagents, and uses commercially available and readily available conventional chemicals as raw materials. The operation is simple and easy to perform, with strong overall process operability, making it suitable for large-scale production applications.

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 predicting treatment outcome of a patient with 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 present invention discloses a clustering and scheduling method and device based on a cellular distribution network. The method includes: constructing a cellular distribution network topology structure, the cellular distribution network topology including microgrid nodes and commutation nodes, the commutation nodes interconnected via converters to form a polygonal structure, and the microgrid nodes connected to the lines between two adjacent commutation nodes; constructing a comprehensive index that affects clustering; establishing a first objective function for clustering based on the comprehensive index; clustering the distributed power sources in the microgrid nodes based on the first objective function based on a community discovery algorithm to obtain clustering results; monitoring each cluster, and when a cluster fails, implementing power scheduling between clusters through the commutation nodes. This method can improve the reliability of distributed power source clustering.

The application discloses a cell image analysis method and system based on geometric mean and graph structure, and the method comprises the following steps: inputting a multi-channel fluorescence image into a cell recognition algorithm model to obtain a cell distribution graph; calculating a cell deviation parameter in the cell distribution graph according to a geometric mean algorithm; extracting cell graph features corresponding to the cell distribution graph and the cell deviation parameter based on a graph neural network; and predicting a cell pathology classification and a change trend at a future time point based on an LSTM neural network according to a time sequence corresponding to the cell graph features at a plurality of historical time points. It can be seen that the application can accurately predict the cell pathology classification and the evolution trend at the future time point, improve the automation level and the forward-looking judgment ability of cell pathology analysis, and provide efficient and reliable technical support for disease monitoring and auxiliary diagnosis.

The invention is to provide a method of profiling a sample comprising a plurality of cells, the method comprising: flowing cells from the sample through a first array of pillars to obtain one or more distribution profiles of cells sorted by the first array; flowing cells from the sample through a second array of pillars that is different from the first array of pillars to obtain on one or more distribution profiles of cells sorted by the second array; and deriving a biophysical signature of the sample based on at least the one or more distribution profiles of the cells sorted by the first array and / or the one or more distribution profiles of the cells sorted by the second array. The method further comprises determining a health status of a subject based on the biophysical signature of the sample. The invention is also to provide a sample profiling system. In various embodiments, the distribution profile of cells in the output regions is indicative of one or more biophysical properties of the cells, which may include the size and deformability of the cells. The pillars in the first array and the second array may have a shape selected from the group consisting of a substantially L shape and a substantially inverse L shape, mirror reflections thereof or combinations thereof.

The invention belongs to the technical field of digital pathological image analysis, and particularly relates to a cell distribution three-dimensional reconstruction method of a planar HE staining pathological image, which comprises the following steps: acquiring a single two-dimensional HE staining pathological image under a 40-time visual field of an optical microscope, and preprocessing the single two-dimensional HE staining pathological image to obtain preprocessed data; acquiring cell characteristics of each cell nucleus in the preprocessed data; constructing a cell Z-axis distribution probability model by adopting an EM algorithm, and generating an initial Z-axis coordinate of each cell nucleus in the preprocessed data by adopting a Z-axis distribution sampling method; aiming at each cell nucleus in the preprocessed data, carrying out cell initialization according to cell characteristics and initial Z-axis coordinates; executing a PSO-EM hybrid algorithm based on the initialized cells, and generating a three-dimensional center coordinate and a radius of each cell; according to the method, the problem of cell space information loss of the two-dimensional plane pathological image is solved.

The invention relates to a cellular delivery management method and system, and relates to the field of intelligent storage and delivery, and the method comprises the steps: obtaining an order storage position and an expected storage region of a preset order; analyzing the order storage position and the expected storage area to determine an actual storage position; analyzing the order storage position and the actual storage position to determine an order moving path; obtaining an order moving speed; analyzing the order moving path and the order moving speed to generate an order moving scheme; and controlling a preset moving device to move the order from the order storage position to the actual storage position according to the order moving scheme. According to the order moving scheme, the mobile device is controlled to move the order from the order storage position to the actual storage position, so that the user can take the article more conveniently.

The embodiment of the invention discloses a nerve fiber distribution direction analysis method and device, equipment and a medium, and the method comprises the steps: obtaining a to-be-analyzed nerve tissue three-dimensional image; determining a cell distribution direction in the nervous tissue three-dimensional image according to pixel information in the nervous tissue three-dimensional image; and determining the nerve fiber distribution direction in the nerve tissue three-dimensional image based on the mapping relation between the cell distribution direction and the nerve fiber distribution direction. According to the technical scheme provided by the embodiment of the invention, the problem that the current nerve fiber distribution direction research method cannot meet the analysis precision requirement is solved, the nerve fiber distribution direction in the nerve cells is quickly and accurately analyzed from the three-dimensional image, and reference information can be more efficiently provided for brain functional structure research.

The invention discloses a cleavage-stage embryo medical image quality detection method and system, and relates to the technical field of medical image detection.The cleavage-stage embryo medical image quality detection method comprises the following steps that S1, a cleavage-stage embryo is placed in a matched agarose culture dish, and the refractive index of the agarose culture dish is consistent with that of an embryo culture solution; s2, constructing a 4D imaging model, performing continuous dynamic imaging on the cleavage stage embryo, and collecting 4D original image data of the cleavage stage embryo within a preset time range; s3, constructing a preprocessing model, carrying out refraction correction on the 4D original image data, identifying an embryo contour and cell distribution, judging an embryo body position, and forming preprocessed image data; the agarose culture dish with the refractive index consistent with that of the embryo culture solution is adopted and matched with the exclusive refraction correction sub-module for light refraction deviation compensation, refraction deviation is eliminated from the source and post-processing two dimensions, the problems of image blurring and distortion are effectively solved, and the basic quality of images is improved.

A composition comprising edible hydrogel microcarriers-comprising cells, wherein said cells are distributed throughout said hydrogel microcarriers such that said hydrogel microcarriers are devoid of a cell-free core. Also provided are methods or producing and using same.

The invention discloses a rapid onset leukemia model based on over-expression transgenic line zebrafish. The rapid onset leukemia model is constructed by injecting an expression vector for expressing human MYC gene or mouse myc gene into a zebrafish single-cell embryo. Compared with an existing mouse model and other leukemia animal models, the model provided by the invention has the advantages that the disease time is greatly shortened, leukemia phenotypes with abnormal cell expansion and cell distribution are easy to observe and analyze, and higher efficiency is achieved.