14 results about "Immunolabeling" patented technology

The invention discloses an intestinal cancer immune response graph neural network prediction method, a medium and equipment, and the method comprises the steps: collecting pathological image information, immunodetection information and basic clinical information, extracting a tissue space distribution characteristic spectrum through a deep convolutional network, and constructing a graph neural network model in combination with an immunomarker expression characteristic matrix; spatial interaction characteristics of a tumor microenvironment are modeled by adopting a graph attention mechanism, finally a treatment response probability, an optimal treatment opportunity and an adverse reaction risk are predicted through a multi-task learning framework, and a clinical decision report containing a prediction response curve, a risk early warning threshold and a treatment time window suggestion is output. According to the method, through multi-modal data fusion and spatial interaction modeling, accurate prediction of intestinal cancer immunotherapy response is realized, and a more comprehensive reference basis is provided for clinical decision making.

The invention discloses a rapid degreasing method for a biological tissue sample, which comprises the following steps: sequentially carrying out fixing, tissue dehydration, azeotropic degreasing, tissue rehydration and other treatments on the sample, and the degreasing solution is composed of alcohols and hydrocarbons according to a mass ratio of 1: 1-1: 2. According to the rapid degreasing method provided by the invention, the lipid in the tissue is efficiently extracted through mixed azeotropy of the alcohol and hydrocarbon organic reagents, so that the tissue is transparent and transparent; the problem of poor degreasing in tissues is solved by utilizing the high permeability characteristic of the micromolecular organic reagent; the dissolving capacity to phospholipid and cholesterol is improved by mixing organic reagents; through azeotropy, the degreasing efficiency is improved, the degreasing time is shortened, the internal permeability effect of the tissue is improved, and internal and external uniform permeability of the tissue is realized; by adjusting the components of the organic reagent, boiling rapid degreasing at low temperature is realized, and the retention of a fluorescence signal is improved; the tissue treated by the method is transparent and small in deformation, a fluorescent protein signal can be maintained, and the immunofluorescence staining effect can be improved.

To provide a method for providing information associated with an immune phenotype for a pathological slide image carried out by at least one computer device.SOLUTION: The method can include: a step of acquiring information associated with an immune phenotype for one or more regions of interest in a pathological slide image; a step of generating an image indicating the information associated with the immune phenotype on the basis of the information associated with the immune phenotype for the one or more regions of interest; and a step of outputting an image indicating the information associated with the immune phenotype.SELECTED DRAWING: Figure 1

The application belongs to the technical field of biological detection, and particularly relates to a composite system for MCP-1 magnetic microparticle chemiluminescence detection and application and product. The composite system comprises a coupling buffer and a labeling buffer; the coupling buffer is composed of MES, NaCl, PEG 4000, PVP K30, Tween-20, glycerol and water, and pH is 5.5-6.5; the immune labeling buffer is composed of boric acid, CAPS, NaCl, sucrose, PEG 6000, Triton X-100 and water, and pH is 9.0-10.0. The kit containing the composite system has a sensitivity of 2.31 pg / mL, good linear relationship in a concentration range, good accuracy and high repeatability. The kit can be used for researching the pathogenesis of diseases in which MCP-1 signal pathways are involved, screening MCP-1 inhibiting drugs and qualitatively and quantitatively detecting MCP-1.

The present invention relates to a method for the in vitro characterization and quantification of proliferative cells in an epidermal fragment, comprising the following steps: 1) Cultivating, on a support, the epidermal fragment, 2) Detaching the epidermal fragment from the support, 3) Carrying out immunolabeling on the epidermal fragment, 4) Acquiring images of the basal layer of the epidermal fragment over its entire surface, 5) reconstructing an image representing the entire basal layer of the epidermal fragment, 6) Selecting the immunolabeled nuclei of the proliferative cells by image processing, 7) Quantifying cell division by counting the nuclei by image analysis. The present invention also relates to a use of the method for evaluating the effect of a product or an active ingredient on epidermal cell regeneration. Figure 1

The invention belongs to the technical field of molecular biomedicine, and particularly relates to a urinary tract epithelial cell marker and application thereof in diagnosis of urinary tract epithelial cell carcinoma. The molecular marker is cytoplasm thyroid hormone binding protein CRYM, and an immunochemical staining experiment proves that the cytoplasm thyroid hormone binding protein CRYM has the potential to serve as a single immunomarker to be used for distinguishing normal urinary tract epithelial cells / reactive hyperplastic urinary tract epithelial cells and urinary tract epithelial cancer cells. Therefore, the kit plays a key identification role in histopathologic diagnosis or urine noninvasive screening of urothelial carcinoma, and provides important technical support for clinical noninvasive diagnosis.

Disclosed is an integrated or combined device for a saliva test for at least two analytes comprising a sampling member, an intermediate section and an immunolabeling section comprising a plurality of antibodies for the specific binding of the analytes and a plurality of second antibodies for detecting the analytes, which analytes are the histidine-rich protein (HRP) and the lactate dehydrogenase (LDH) protein of Plasmodium sp..

The embodiment of the invention provides a blood leukocyte precise separation method combining immune density and a centrifugation technology. The blood leukocyte precise separation method comprises the following steps: performing multicolor immunofluorescence labeling on leukocyte subgroups in a blood sample; performing flow cytometry analysis on the marked sample, and establishing an initial multicolor fluorescence compensation matrix for the current sample individual; dynamically adjusting and generating a corrected compensation matrix of the individual specificity based on the deviation degree of the initial compensation matrix in a sample group reference range; carrying out association mapping on a specific physical sorting interval which is determined after the signal recalculation and the enclosure and is rich in the target leukocyte subgroup and a density gradient centrifugal separation condition; and directly carrying out density gradient centrifugation operation on the blood sample subjected to immunolabeling by utilizing the association mapping. According to the scheme of the embodiment of the invention, the high-purity specific leukocyte subgroup can be efficiently separated from a complex blood sample on the premise of keeping high cell activity and flux.

The application relates to the technical field of biomedical imaging, and discloses a novel brain tissue transparentization and immunolabeling whole organ imaging method, which comprises the following steps: S1: collecting a whole organ sample; S2: recovering antigens in the whole organ sample tissue; S3: digesting the whole organ sample tissue; S4: blocking the whole organ sample tissue; S5: incubating the whole organ sample tissue with a primary antibody, and specifically combining the antigens in the whole organ sample tissue with the primary antibody; S6: incubating the whole organ sample tissue with a secondary antibody, combining the primary antibody with the secondary antibody in the whole organ sample tissue, and cooperating the primary antibody and the secondary antibody for immunolabeling; S7: dehydrating the whole organ sample; S8: transparently processing the whole organ sample; and S9: scanning the whole organ sample by using a microscope, and processing to obtain a three-dimensional image of the immunolabeled whole organ sample tissue. The application can improve the labeling efficiency, shorten the three-dimensional imaging cycle of the whole organ tissue, and has low cost.

The invention relates to the technical field of in-vitro diagnosis, in particular to a kit for detecting an allergen-specific IgE (Immunoglobulin E) antibody. The kit comprises an anti-interference agent used for being mixed with a to-be-detected sample, an immunolabelled allergen, a peroxidase compound capable of being combined with an immunolabel and catalyzing color development of a substrate, and the substrate capable of being catalyzed by peroxidase to develop color, the anti-interference agent is prepared from the following components in parts by weight: 3 to 6 parts of polystyrene microspheres, 12 to 18 parts of L-glucoside and 6 to 10 parts of casein. The kit provided by the invention can effectively reduce false positive and false positive results, so that the accuracy of the detection result is improved.

The application discloses an intestinal cancer immune response graph neural network prediction system, medium and equipment, through collecting pathological image information, immune detection information and basic clinical information, using a deep convolution network to extract a tissue spatial distribution feature map, combining an immune marker expression characteristic matrix to construct a graph neural network model, adopting a graph attention mechanism to model spatial interaction characteristics of a tumor microenvironment, finally predicting a treatment response probability, an optimal treatment time and an adverse reaction risk through a multi-task learning framework, and outputting a clinical decision report containing a predicted response curve, a risk early warning threshold and a treatment time window suggestion. Through multi-modal data fusion and spatial interaction modeling, the application realizes accurate prediction of the intestinal cancer immunotherapy response, and provides a more comprehensive reference basis for clinical decision-making.

Methods and systems for sorting a candidate immune checkpoint inhibition (ICI) recipient as a responder or non-responder, by inferring cell classifications generated from immunophenotyping and inputting the inferred cell classification into a machine learning model trained to predict an outcome with training data comprising at least: (a) a plurality of cell classifications, wherein the plurality of cell classifications includes, for each ICI recipient of a plurality of ICI recipients, at least two cell classifications corresponding to different respective timepoints, (b) one or more indications of the outcome for the plurality of ICI recipients at respective timepoints; outputting an outcomes candidate ICI recipient; and sorting the candidate ICI recipient as a responder or a non-responder based at least on the predicted probability of outcome. Also provided herein are methods and systems for monitoring response to ICI therapy.

This invention discloses a method for the separation and detection of exosomes in whole blood using a microfluidic chip. The method includes preparing a microfluidic chip with a specific structure for whole blood exosome separation and a PEGylated microfluidic chip with fishbone-like protrusions for capturing whole blood exosomes. Simultaneously, a viscoelastic solution is prepared and the whole blood sample is pretreated. The pretreated whole blood sample is injected into the microfluidic chip for whole blood exosome separation, and size-dependent separation of exosomes is achieved using a viscoelastic flow field. After concentration, a whole blood exosome concentrate is obtained. Exosomes are immobilized with paraformaldehyde, perforated, and biotinylated. After capture, a BODIPY polymer dot-coupled secondary antibody is prepared, combined with a primary antibody to complete exosome immunolabeling. After localization, multi-channel imaging using a total internal reflection fluorescence microscope is performed. This method achieves efficient separation and highly specific labeling detection of whole blood exosomes, improving the separation recovery rate and purity.