2150 results about "Tissue sample" patented technology

Localized detection of RNA in a tissue sample that includes cells is accomplished on an array. The array include a number of features on a substrate. Each feature includes a different capture probe immobilized such that the capture probe has a free 3′ end. Each feature occupies a distinct position on the array and has an area of less than about 1 mm2. Each capture probe is a nucleic acid molecule, which includes a positional domain including a nucleotide sequence unique to a particular feature, and a capture domain including a nucleotide sequence complementary to the RNA to be detected. The capture domain can be at a position 3′ of the positional domain.

Localized detection of RNA in a tissue sample that includes cells is accomplished on an array. The array include a number of features on a substrate. Each feature includes a different capture probe immobilized such that the capture probe has a free 3′ end. Each feature occupies a distinct position on the array and has an area of less than about 1 mm2. Each capture probe is a nucleic acid molecule, which includes a positional domain including a nucleotide sequence unique to a particular feature, and a capture domain including a nucleotide sequence complementary to the RNA to be detected. The capture domain can be at a position 3′ of the positional domain.

This document generally describes methods and systems for generating digital reconstructions of tissue from humans or other species. The method can, for example, include receiving, at a computing system, image data of a tissue sample, where one or more sections of the tissue sample are stained with hematoxylin and eosin (H&E), registering the image data to generate registered image data, identifying tissue subtypes based on application of a machine learning model to the registered image data, annotating the identified tissue subtypes to generate annotated image data, and determining a digital volume of the tissue sample in three dimensional (3D) space based on the annotated image data. The disclosed technology can provide for single-cell analysis and other analysis of tissue samples, such as early detection of cancer in human tissue samples.

A method for diagnosing diseases in human patients can include providing a set of global X-ray diffraction (XRD) data to a global data center (GDC) and processing the set of global XRD data and categorizing it into data clusters, where each data cluster corresponds to a diagnostic indicator for assessment of a physiological or pathological condition. The method can further include communicating local XRD data and local patient data from a local autonomous cell (LAC) to the GDC, where the local XRD data includes information about a tissue sample measured using a tissue diffractometer of the LAC, and wherein the tissue sample includes skin. The method can further include processing the local XRD data, comparing it with the data clusters to determine a local diagnostic indicator for the local patient, and communicating the local diagnostic indicator to the LAC.

The invention discloses a graph convolution spatial domain identification method of a fusion gene interaction network, and relates to the technical field of biological information, and the method comprises the steps: preprocessing spatial transcriptome data; constructing a spatial diagram according to the spatial position information of the spot and the gene expression matrix; constructing a conditional gene interaction network based on at least a part of key genes in the spatial transcriptome data, constructing a conditional gene interaction network matrix, combining the conditional gene interaction network matrix and the gene expression matrix to obtain an expression degree-interaction matrix, and constructing a feature map; performing graph neural network convolution on the space graph and the feature graph, and introducing an attention mechanism to obtain final embedding; and clustering and finally embedding, and identifying a spatial domain with a similar gene expression mode. According to the method, the spatial domain is identified through the fusion gene interaction network, the problem that the spatial domain is discontinuous is effectively solved, the robustness and accuracy of the spatial domain identification method are improved, and high performance is shown in complex and highly heterogeneous tissue samples.

One or more methods for treating a tissue site comprises collecting a tissue sample that has keratinoytes and placing the tissue sample in a cartridge that has a well plate, positioning the cartridge within a base unit that has a tissue disaggregator, activating the base unit to rotate the well plate to align wells in the well plate with the tissue sample and the tissue disaggregator, operate the tissue disaggregator to separate the tissue sample to form a regenerative epidermal suspension, and provide the regenerative epidermal suspension to a tissue site to enhance healing of the tissue site.

The disclosure provides a method for immunotherapy of a subject afflicted with cancer, comprises administering to the subject a composition comprising a therapeutically effective amount of an antibody that inhibits signaling from the PD-1 / PD-L1 signaling pathway. This disclosure also provides a method for immunotherapy of a subject afflicted with cancer comprising selecting a subject that is a suitable candidate for immunotherapy based on an assessment that the proportion of cells in a test tissue sample from the subject that express PD-L1 on the cell surface exceeds a predetermined threshold level, and administering a therapeutically effective amount of an anti-PD-1 antibody to the selected subject. The invention additionally provides rabbit mAbs that bind specifically to a cell surface-expressed PD-L1 antigen in a FFPE tissue sample, and an automated IHC method for assessing cell surface expression in FFPE tissues using the provided anti-PD-L1 Abs.

The invention provides an esophageal cancer marker screening method based on enzyme transfer method methylation sequencing, which comprises the following steps: S1, collecting esophageal early cancer and para-carcinoma tissue samples, and carrying out enzyme transfer method whole genome methylation sequencing; s2, integrating methylation data of esophageal cancer and para-carcinoma tissues in databases of TCGA, GEO, MethMarker DB and the like; s3, screening differential methylation sites, preferably sites which are hypermethylated in esophageal cancer but hypomethylated in samples such as leukocytes, so as to reduce plasma background interference; s4, obtaining a candidate marker combination based on an integrated methylation feature screening model of LASSO regression and a random forest algorithm; s5, constructing a classifier model based on the candidate marker combination, carrying out training and reasoning test on the model, and evaluating the prediction performance of the model; and S6, obtaining the esophageal cancer marker combination. According to the method, enzyme transfer sequencing and machine learning are combined, the marker prediction accuracy is remarkably improved, and a new reference is provided for clinical research of esophageal cancer.

A system for optical interrogation of tissue samples, the system including: a microtome configured to section one or more tissue sections from a tissue block, the one or more tissue sections including one or more tissue samples; a transfer medium configured to gather the one or more tissue sections and to transfer the one or more tissue sections to one or more slides; and an optical interrogation system including an illumination system configured to illuminate the one or more tissue sections and an imaging system configured to perform an imaging analysis on the one or more tissue sections illuminated with the illumination system.

The invention provides a bioelectrical impedance lung cancer detection method based on artificial intelligence, which comprises the following steps: acquiring multi-dimensional electric signal data of a tissue sample, preprocessing the data, and acquiring preliminary feature representation of the sample through a static spatial feature extraction method; based on the time sequence characteristics of the signals, constructing a dynamic feature extraction model, extracting dynamic features from time sequence association, and mining the difference and regularity between samples; static space features and dynamic time sequence features are fused, multi-dimensional attributes of signals are comprehensively analyzed, high-dimensional key feature representation is generated, the distinguishing capacity and reliability of the features are improved, and attention to the key features is enhanced; according to the method, the characteristics of a sample are fused, the fused characteristics are analyzed and classified, the normal state and the abnormal state of the sample are judged in combination with model output, finally, accurate detection and diagnosis results are achieved, the performance of the method on various bioelectrical impedance data sets is superior to that of a traditional method, and the sensitivity and specificity of lung cancer detection are effectively improved.

The invention provides automatic dyeing equipment for biological tissue sample slices, which comprises a feeding mechanism, a feeding and discharging buffering mechanism, an automatic dyeing mechanism, a reagent adding mechanism, an after-dyeing drying mechanism, a reagent storage mechanism and a main console, the main console is in control connection with the feeding mechanism, the feeding and discharging buffering mechanism, the automatic dyeing mechanism, the reagent adding mechanism, the after-dyeing drying mechanism and the reagent storage mechanism, the feeding mechanism is provided with a plurality of microscope glass slide vertical placing supports, the automatic dyeing mechanism is provided with a dyeing groove, and the dyeing groove can be filled with a dyeing reagent and is matched with the microscope glass slides; the reagent adding mechanism can automatically add and supplement a dyeing reagent to the dyeing tank, the reagent storage mechanism can add and supplement the dyeing reagent to the reagent adding mechanism, and the post-dyeing drying mechanism is matched with the feeding and discharging temporary storage mechanism and the automatic dyeing mechanism. The microscope glass slide has the beneficial effect that the risk of cross contamination between microscope glass slides filled with biological tissue sample slices can be avoided.

The invention discloses an early-stage prostate tumor recognition method based on a hyperspectral image, and belongs to the technical field of image recognition, and the method comprises the steps: collecting early-stage prostate tumor samples with different lesion degrees; performing hyperspectral scanning on the prostate tumor early tissue sample to generate corresponding hyperspectral image data and performing preprocessing; extracting features of the preprocessed hyperspectral image data; organizing feature data and label data, wherein the label data classifies and marks a sample based on a known pathological diagnosis result; constructing an early prostate tumor recognition model based on the feature data and the label data, and performing optimization training; and performing early prostate tumor recognition on a new sample to be detected by using the trained recognition model. The method has the beneficial effects that the actual canceration condition can be easily mastered, and compared with an existing tissue slice inspection mode, the method is easier to operate, the detection result can be obtained more quickly, the result accuracy is higher, and the objectivity is higher.

The disclosure provides a method for immunotherapy of a subject afflicted with cancer, comprises administering to the subject a composition comprising a therapeutically effective amount of an antibody that inhibits signaling from the PD-1 / PD-L1 signaling pathway. This disclosure also provides a method for immunotherapy of a subject afflicted with cancer comprising selecting a subject that is a suitable candidate for immunotherapy based on an assessment that the proportion of cells in a test tissue sample from the subject that express PD-L1 on the cell surface exceeds a predetermined threshold level, and administering a therapeutically effective amount of an anti-PD-1 antibody to the selected subject. The invention additionally provides rabbit mAbs that bind specifically to a cell surface-expressed PD-L1 antigen in a FFPE tissue sample, and an automated IHC method for assessing cell surface expression in FFPE tissues using the provided anti-PD-L1 Abs.

The present invention relates to: a method for evaluating the efficacy of an anti-cancer drug, a method for screening an anti-cancer drug, a system for evaluating the efficacy of an anti-cancer drug, or a system for screening an anti-cancer drug, using a mixture of peripheral blood mononuclear cells (PBMC) and a cancer organoid. Specifically, the present invention relates to: a method for evaluating the efficacy of an anti-cancer drug, a method for screening an anti-cancer drug, a system for evaluating the efficacy of an anti-cancer drug, or a system for screening an anti-cancer drug, using a mixture of cytotoxic T cells differentiated from PBMC and cancer organoids. According to the method for evaluating the efficacy of an anti-cancer drug, the screening method, the efficacy evaluation system, or the screening system of the present invention, a tumor microenvironment, i.e. The form in which cancer cells are present in a living body, can be very closely reproduced. Furthermore, since PBMCs derived from normal individuals are used and differentiated into cancer patient-specific cytotoxic T cells, the burden of collecting biological samples such as blood and tissue samples from cancer patients can be reduced, and the efficacy of an anti-cancer drug can be evaluated with high accuracy.

The present disclosure relates to systems and methods for facing a tissue block. In some embodiments, a method is provided for facing a tissue block that includes imaging a tissue block to generate imaging data of the tissue block, the tissue block comprising a tissue sample embedded in an embedding material, estimating, based on the imaging data, a depth profile of the tissue block, wherein the depth profile comprises a thickness of the embedding material to be removed to expose the tissue sample to a pre-determined criteria, and removing the thickness of the embedding material to expose the tissue to the pre-determined criteria.

The invention provides a construction method of a predictive cell senescence model, a method for predicting the senescence state of a tissue sample based on the senescence model, a method for screening potential therapeutic drugs, equipment, a medium and a program product, and relates to the field of intelligent medical treatment. The model construction method comprises the following steps: acquiring a training set sample expression profile data set; identifying a key senescence gene set from the data set by using a feature selection algorithm; inputting the key senescence gene set into a machine learning model to fit a prediction model, and determining an optimal hyper-parameter to obtain a cell senescence model containing the weight of a single gene in the key senescence gene set; the cell senescence model is a senescence score obtained by calculating the sum of the product of the expression quantity of a single gene and the regression coefficient thereof. The cell senescence model, namely PreCSenM, is constructed by integrating a plurality of senescence characteristic gene sets and a gene scoring algorithm, the accuracy in CS evaluation is superior to that of 10 existing methods, and the application of CS from biological research to clinical scenes is also realized.

A cartridge for dissociating tissue, comprising: a processing chamber comprising a stator, a side wall, a top orifice, and a first processing chamber port positioned in the side wall; and a grinder assembly comprising a plunger comprising a rotor, a grinder assembly slidably positioned in the processing chamber through the top orifice; wherein: the stator comprises a plurality of teeth arranged in a spaced-apart array of rings; and the rotor comprises one or more central teeth and a plurality of teeth arranged in a spaced-apart array of rings, wherein one ring of teeth is positioned at or substantially at a circumference of the rotor; wherein the rings in the stator and the rings in the rotor are positioned such that when the rotor contacts the stator, rings of teeth in the stator mesh with the one or more central teeth and rings of teeth in the rotor

The invention belongs to the technical field of kidney histopathology and immunological evaluation, and particularly relates to a kidney pathology detection kit, a detection method and application, the detection kit comprises 37 rare metal element labeled monoclonal antibodies combined with antigens of in-situ tissue cells, and the detection method comprises the following steps: (1) collecting a sample to be detected, preparing a pre-dyed paraffin section; (2) mixing 37 monoclonal antibodies labeled by rare metal elements, and carrying out antibody staining on various antigen targets on the surfaces of cells in the in-situ tissue; (3) carrying out nucleus DNA staining on the stained tissue sample; and (4) detecting the stained tissue sample through an imaging mass spectrum flow system, and collecting original information data through laser spot firing. The method is an analysis method for fine grouping identification and relative quantification of structural cells, immune cells and pathological injury cells in the clinical nephropathy sample in-situ tissue. And auxiliary diagnosis information is provided for diagnosis, grading, treatment and prognosis detection of various clinical nephropathy.

The invention discloses a gastric cancer multi-omics marker detection method, system and device, and the method comprises the following steps: S1, collecting a public database open-source space transcriptome, a single cell sequencing sample and bulk-RNAseq data for pre-processing, and collecting a primary tissue sample of a gastric cancer patient in the center for data processing; s2, integrating different modal data samples to obtain a patient label of an input end, and constructing a marker detection model and training the marker detection model; and S3, extracting a target feature value from the input external pathological section by using the trained model, and generating a diagnosis prediction result. Through multi-modal data chimerism, algorithm optimization and AI system development, subpopulation cell marker proportion prediction and prognosis diagnosis and marker evaluation with population prognosis information are realized, and an integrated diagnosis scheme for breaking through molecule-space-prognosis information is constructed.

Apparatuses and methods for recovering solid tissue and dislodged cells (“D-cells”) from a biopsy are disclosed herein. In an embodiment, a biopsy container apparatus for recovering solid tissue and D-cells from a biopsy includes a receiving container and a sieve container. The receiving container has a receiving chamber with an upper opening and a watertight bottom surface. The sieve container is configured to be located at least partially within the receiving chamber and removed from the receiving chamber through the upper opening. The sieve container has a bottom sieve surface including a plurality of apertures configured to pass the D-cells from the biopsy but not the solid tissue from the biopsy into the receiving chamber after the solid tissue and the D-cells from the biopsy are placed into the sieve container.

The disclosure provides a method for immunotherapy of a subject afflicted with cancer, comprises administering to the subject a composition comprising a therapeutically effective amount of an antibody that inhibits signaling from the PD-1 / PD-L1 signaling pathway. This disclosure also provides a method for immunotherapy of a subject afflicted with cancer comprising selecting a subject that is a suitable candidate for immunotherapy based on an assessment that the proportion of cells in a test tissue sample from the subject that express PD-L1 on the cell surface exceeds a predetermined threshold level, and administering a therapeutically effective amount of an anti-PD-1 antibody to the selected subject. The invention additionally provides rabbit mAbs that bind specifically to a cell surface-expressed PD-L1 antigen in a FFPE tissue sample, and an automated IHC method for assessing cell surface expression in FFPE tissues using the provided anti-PD-L1 Abs.

Disclosed herein, inter alia, are devices and methods for efficient transfer and analyses of cellular material, tissue samples, such as tissue sections, using carrier substrates and devices.

For a biopsy guided by contrast-enhanced x-ray imaging, a breast imaging system may image a patient's breast subsequent to injection of contrast agent to locate a site for biopsy and / or position a biopsy device relative to the site. Once a tissue specimen is removed from the site for diagnostic evaluation, a confirmation that the specimen was removed from an intended area of interest for biopsy is performed using the systems and methods described herein. For example, the breast imaging system and / or a separate specimen imaging system may capture high and low energy images of the specimen, subtract the low energy image from the high energy image to generate a subtracted image of the specimen, and determine, based on the subtracted image, that the contrast agent is present within the specimen to confirm the site from which the specimen was removed is the intended site for biopsy.

A method for inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology includes receiving at least one histology image of a tissue sample at a histology feature extractor. The histology feature extractor partitions the at least one histology image into image tiles and partitions each of the image tiles into image sub-tiles. The histology feature extractor extracts histology features from the histology image, the extracted histology features include low-level image features extracted from the image sub-tiles and high-level image features extracted from the image tiles. A super-resolution gene expression predictor predicts gene expression for the image sub-tiles using the extracted histology features and a predictor model trained with spot-level gene expression observations. A tissue architecture annotator clusters the image sub-tiles based on the predicted gene expression of the image sub-tiles and annotates each of the image sub-tiles using the predicted gene expressions and a marker gene reference panel.

Described herein are prediction models based on the transcriptomic, exomic, and / or radiological analyses on tissue samples to predict the likelihood of the original cancer (such as Hepatocellular carcinoma (HCC)) recurrence into the liver transplant. An example computer implemented method for predicting the likelihood of liver cancer recurrence 5 into a liver transplant includes receiving gene expression data related to a liver tissue sample for a subject having a liver cancer, inputting the gene expression data into a trained machine learning model, and predicting, using the trained machine learning model, a risk of recurrence of the liver cancer in the subject after liver transplantation.

The disclosure provides a method for immunotherapy of a subject afflicted with cancer, comprises administering to the subject a composition comprising a therapeutically effective amount of an antibody that inhibits signaling from the PD-1 / PD-L1 signaling pathway. This disclosure also provides a method for immunotherapy of a subject afflicted with cancer comprising selecting a subject that is a suitable candidate for immunotherapy based on an assessment that the proportion of cells in a test tissue sample from the subject that express PD-L1 on the cell surface exceeds a predetermined threshold level, and administering a therapeutically effective amount of an anti-PD-1 antibody to the selected subject. The invention additionally provides rabbit mAbs that bind specifically to a cell surface-expressed PD-L1 antigen in a FFPE tissue sample, and an automated IHC method for assessing cell surface expression in FFPE tissues using the provided anti-PD-L1 Abs.

The present disclosure relates in some aspects to methods for analyzing target nucleic acids and their spatial locations in a biological sample. In some aspects, the presence / absence, amount, and / or identity of variant sequences (e.g., single nucleotide variations such as SNPs or point mutations) in a plurality of target nucleic acids in a cell or tissue sample are analyzed in situ in the sample. Also provided are compositions and kits for use in accordance with the methods.

Systems and methods for producing an ultrafast functional photoacoustic microscopy system are disclosed herein. Such systems are configured to enable the imaging of microvasculature and functional dynamics of tissue samples with a broad field of view and high spatial resolution. According to several disclosed embodiments, a combination of a Raman path and a polygon scanner in water immersion and air immersion environments enables rapid imaging of target materials.

The invention belongs to the technical field of medical instruments, and particularly relates to a negative pressure biopsy needle which comprises an inner needle rod and an outer needle rod, the outer needle rod is coaxially arranged on the outer side of the inner needle rod in a sleeving mode, the inner needle rod is configured to be of a non-through type hollow structure, the two ends of the outer side of the inner needle rod are provided with an adsorption hole and a communicating hole respectively, and the adsorption hole is communicated with the communicating hole. The adsorption holes are communicated with the communicating holes; the outer needle rod is configured to move in the direction away from the handle assembly along the axis of the inner needle rod in a rotating mode in the process that the biopsy device is converted from the to-be-fired state to the fired state. When the launching assembly is converted from a to-be-fired state to a release state, the outer needle rod cuts and samples focus tissue in a rotating mode under the cooperation of the outer needle base and the spiral guide groove, and meanwhile, negative pressure is formed in the first negative pressure channel and the second negative pressure channel at the same time through the negative pressure assembly, and a tissue sample is adsorbed.

The invention discloses a temperature-controllable preparation method for tissue temperature dissociation into single cells and application, the temperature-controllable preparation method for tissue temperature dissociation into single cells comprises the following steps: S1, providing a tissue sample, and pre-treating the tissue sample to obtain a sample block; s2, mixing the sample blocks with a compound digestive enzyme, and filtering to obtain a single-cell suspension after digestion treatment is completed; wherein the compound digestive enzyme is prepared from collagenase, hyaluronidase and papain; and selectively, S3, carrying out red removing treatment. The invention not only provides an improved preparation method of the single-cell suspension, but also has higher efficiency on the premise of ensuring the yield and activity of single cells, and provides a new strategy and tool for cancer research and treatment by particularly enriching CSCs.