361 results about "Tissue sections" patented technology

This disclosure relates to compositions and methods for analyzing a tissue section from a biological sample.

The system and method for processing a digital pathology image using a machine learning model that includes a self-supervised hierarchical Vision Transformer (ViT) configured to perform unsupervised clustering with multiple classification tokens. The method includes receiving a digital pathology image that depicts a tissue slice stained with histological dyes. The digital pathology image may be processed to generate a result comprising multiple predicted classifications of individual patches of the digital pathology image. The result is generated by a machine-learning model using a self-supervised hierarchical Vision Transformer (ViT) that may further comprise a multi-head self-attention module configured to predict a crosspatch relevance metric using an attention mechanism for each individual patch in the digital pathology image thereby assigning the individual patches to a cluster based on the crosspatch relevance metrics.

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.

A platform for characterizing biomolecules, biological tissue sections, viruses, or other particles of interest in a non-invasive, high-throughput, cost-effective, and label-free manner. The platform includes a merged set of imaging modalities including and capable of interferometric microscopy and wide-field or confocal microscopy (such as, for example, a wide-field super-resolution surface enhanced Raman spectroscopy, SERS), although some aspects may be employed with data sets only received from wide-field or confocal microscopy. Related devices, systems, methods, techniques, and variations to the same are also provided.

The present disclosure relates to systems and methods for tracking and printing within a histology system. In some embodiments, a system is provided that includes an information reader configured to read identifying data associated with a tissue block, a microtome configured to cut one or more tissue sections from the tissue block, one or more slides for receiving the one or more tissue sections, and a printer configured to receive the identifying data and print, after the one or more tissue sections are cut from the tissue block, one or more labels for the one or more slides, the one or more labels comprising information associating the one more tissue sections on the one or more slides with the tissue block.

An automated tape transfer apparatus including a tape feed mechanism feeding a continuous length of an adhesive tape through the automated tape transfer apparatus and a tape applicator applying the adhesive tape to a cutting face of a sample block, wherein a section of the sample block is adhered to the adhesive tape after cutting of the section from the sample block. A slide station transfers the cut section from the adhesive tape to a slide.

The invention discloses a deep learning driven spatial multi-omics data analysis and integration method, and relates to the technical field of cell sequencing, the method comprises the following steps: using each sequencing point location of different tissue slices as a node, using the adjacency relation of each sequencing point location as an edge, and constructing a spatial omics data graph structure; extracting dimension-reduced features from the space omics data graph structure, and embedding the dimension-reduced features as low-dimensional features; adjusting the coordinate information of the low-dimensional features of the different tissue slices through affine transformation so as to perform direction alignment on the sequencing point locations of the different tissue slices; according to the spatial information and the low-dimensional features, matching the sequencing point locations after the directions of the different tissue slices are aligned; and fusing the matched low-dimensional features according to the spatial information to obtain spatial multi-omics data after integration of different tissue slices. According to the method, an efficient analysis, alignment, matching and integration scheme is provided to assist in space omics data analysis and conjoint analysis, so that the accuracy and efficiency of data processing are improved.

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.

The invention relates to a method for acquiring a biomarker for assisting CRLM early diagnosis. The method comprises the following steps: acquiring sequencing data, clinical information and metabonomics characteristics of a CRC sample; evaluating and determining a plurality of differentiated machine learning models; performing classification according to the determined machine learning model, and constructing a CRLM biomarker prediction model; screening candidate biomarkers according to the prediction model; and verifying the candidate biomarker at least according to the tissue slice and the serum sample, and determining a final biomarker.

An apparatus for performing laser cutting and collection of a target micro-region of a tissue section on a blade. The apparatus comprises a carrier stage, a blade, a laser cutting system, a control module and a collector, wherein the laser cutting system comprises a laser device, a beam expander, a galvanometer scanner and an objective lens; and by means of adjusting a scanning angle θ of the galvanometer scanner and combining same with the objective lens, a scanned laser is focused to realize the cutting of a target micro-region on a tissue section and the ejection of the target micro-region. Laser microdissection is combined with mechanical sectioning, and non-contact collection of a specific micro-region of a tissue section placed on an inclined blade is achieved under the action of laser edge ejection combined with a dielectrophoretic force, such that the integrity of the morphology of a sample throughout an acquisition process is ensured, three-dimensional positional information of a target cell or cell population is accurately reserved, the cutting efficiency is improved, and non-contact cutting can also be realized to prevent the sample from being contaminated.

The invention provides an ultrasonic cutter parameter optimization method for frozen tissue slicing, and belongs to the technical field of medical instruments. The ultrasonic cutter parameter optimization method for the frozen tissue section comprises the following steps: collecting vibration frequency, amplitude, feeding speed, load power and cut tissue type in a frozen tissue cutting process of an ultrasonic cutter as an initial parameter group, and establishing a mapping relation between the initial parameter group and frozen tissue temperature change; calculating a contribution value of the initial parameter group, comparing the contribution value with a preset threshold value, determining the parameter group greater than the preset threshold value as a key parameter group, and determining the parameter group less than or equal to the preset threshold value as a non-key parameter group; by means of the ultrasonic knife, the problem that an existing ultrasonic knife cannot achieve accurate control over temperature changes in the tissue slicing process can be solved.

Methods and systems for processing a scanned tissue section include locating cells within a scanned tissue. Cells in the scanned tissue are classified using a classifier model. A tumor-cell ratio (TCR) map is generated based on classified normal cells and tumor cells. A TCR isoline is generated for a target TCR value using the TCR map, marking areas of the tissue section where a TCR is at or above the target TCR value. Dissection is performed on the tissue sample to isolate an area identified by the isoline.

Disclosed herein, inter alia, are devices and methods for transfer and analysis of tissue sections using carrier substrates.

The invention relates to the field of microneedle electrodes, in particular to a microneedle chip module, an adapter and a culture monitoring device.According to the microneedle chip module, a plurality of microneedle arrays are integrated on the surface of an electrode substrate, tissue slices are pierced through microneedle electrodes, and therefore target cells located in an inner cell layer are recorded or stimulated; according to the culture monitoring device, a probe and a back-stage equipment interface are respectively integrated inside and outside a shell through an adapter, the back-stage equipment interface and a microneedle array are connected through the probe, so that the functions of protecting and quickly connecting back-stage equipment are provided for a microneedle chip module, and a culture dish is integrated on the surface of an electrode substrate through a culture monitoring device; nutrient substances and heat are provided for the culture dish through the peristaltic pump and the heating table, so that the embodiment of the invention combines the advantages of low cost, easiness in penetrating into tissues and high biocompatibility of a rigid needle-shaped electrode.

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 method comprises the following steps: fixing with a pre-fixing solution, wrapping and forming with a solid agent, fixing with a fixing solution, embedding with an embedding agent, decomposing melanin with a melanin decomposing solution, pre-decoloring with a pre-decoloring solution, decoloring with a decoloring solution, and eluting with a rinsing solution. The invention provides a melanin removing method capable of effectively avoiding retina RPE layer cell exfoliation, protein denaturation and nucleic acid degradation. The method mainly comprises the following steps: keeping the original state of tissue cells by adopting a pre-fixing solution, keeping the complete tissue structure by adopting a solid agent, decomposing melanin particles by adopting a melanin decomposing solution composed of various extracts, separating melanin by adopting a pre-decoloring solution and a decoloring solution, eluting the melanin decomposed on the surface of the tissue by adopting a rinsing solution, and the like. On the premise that the retina tissue structure is intact and protein, nucleic acid and cell structures on the surface of the tissue section are not damaged, melanin particles in the tissue section are effectively decomposed, the biological activity of various organelles on the surface of the section is kept, and the requirements of subsequent chemical staining of various tissues are met.

The invention belongs to the technical field of biological medicine, and particularly relates to application of hUC-MSCs combined with Met in preparation of anti-diabetic drugs. The diabetes mellitus is particularly type 2 diabetes mellitus. Through construction of a T2DM rat model, paraffin tissue section detection, serum ELISA, cell experiments and the like, researches prove that T2DM can be effectively treated by HUC-MSCs combined with Met treatment, including reduction of body blood sugar and recovery of blood sugar regulation ability; liver injury caused by T2DM is relieved and repaired; the glycolipid metabolism of the liver of the T2DM rat is improved; the immune inflammation disorder caused by T2DM is relieved; and the apoptosis level of liver cells is improved. And compared with a single hUC-MSCs or Met treatment mode, the combined treatment mode has a better treatment effect. The invention provides a theoretical basis and a new treatment strategy for treatment of T2DM.

The invention belongs to the technical field of frozen slicing, and particularly relates to an animal lung tissue frozen embedding and slicing and space transcriptome sequencing method. In the first aspect, the animal lung tissue freezing and embedding method is provided and comprises the following steps that blood in animal lungs is replaced with first perfusate, and the first perfusate is selected from a first isotonic solution; liquid in the lung is replaced with second perfusate, the perfused lung is obtained, and the second perfusate comprises OCT and a second isotonic solution; and embedding the perfusion lung by adopting OCT (optical coherence tomography), and then quickly freezing. The lung is perfused with the perfusate formed by mixing OCT and the buffer solution, damage to the space structure and form can be reduced, and the tissue slice with the complete internal structure is obtained. Through experimental tests of different thicknesses of perfused lung tissue slices, the slices with the thickness of 10 microns are successfully obtained, in a space transcriptome experiment, the state that most cells belong to monolayer cells is achieved, and the data quality is improved.

The invention discloses a target micro-area laser cutting and collecting device and method for tissue slices on a blade, the target micro-area laser cutting and collecting device for the tissue slices on the blade comprises a carrier table, the blade, a laser cutting system, a control module and a collector, the laser cutting system comprises a laser, a beam expander, a galvanometer and an objective lens, and the scanning angle theta of the galvanometer is adjusted, and the scanned laser is focused in combination with the objective lens, so that the target micro-area on the tissue slice is cut and bounced up. According to the invention, laser microdissection and mechanical slicing are combined, and non-contact collection of a specific micro-area of a tissue slice placed on an inclined blade is realized under the action of laser edge ejection combined with dielectrophoretic force, so that the integration of the form of a sample in the whole acquisition process is ensured, and three-dimensional position information of a target cell or a cell population is accurately reserved; the cutting efficiency is improved, non-contact cutting can be achieved, and samples are prevented from being polluted.

The invention provides pathological tissue section dyeing equipment and method. The method comprises the following steps: dividing a to-be-dyed lymphatic tissue section into a plurality of dyeing partitions according to the structural characteristics of lymphocyte tissues in the to-be-dyed lymphatic tissue section; dyeing agents with different concentrations are applied to different dyeing partitions according to the reference light transmittance of the lymphocyte tissue to obtain color gradient vectors of the lymphocyte tissue slices, light absorption characteristics of the dyeing partitions are measured through a photometer, and dyeing characteristics are determined based on the light absorption characteristics and the color gradient vectors; obtaining a dyeing image after dyeing the lymph tissue section, extracting deep features of the dyeing partitions from the dyeing image, and determining a dyeing loss value when dyeing the dyeing partitions based on the deep features and the dyeing features; and based on the dyeing loss value, carrying out self-adaptive adjustment on the dyeing agent concentration of each dyeing zone. By adopting the scheme provided by the invention, optimal adjustment on the concentration of the coloring agent in the sample dyeing process can be realized based on the characteristic difference of the cell tissues at different parts.

The invention discloses a tissue slice high-resolution mass spectrum imaging method and system based on multi-modal data fusion, and belongs to the technical field of mass spectrum imaging and biomedical detection. The method comprises the steps of multi-modal data acquisition, data preprocessing, feature extraction, multi-modal data fusion and high-resolution imaging reconstruction. High-resolution mass spectrum data and high-stability auxiliary modal data are synchronously collected, after preprocessing and feature extraction, feature weights are dynamically distributed and fused by using a fusion model based on an attention mechanism, and then a high-resolution and high-sensitivity imaging result is output through an imaging reconstruction model of a U-Net improved architecture. On the premise that the spatial resolution is not reduced and the sample is not damaged, the mass spectrum signal intensity is effectively enhanced, the low-abundance biomarker recognition capability is improved, the imaging efficiency is high, the adaptability is high, and the method is suitable for biomedical research and clinical diagnosis scenes.

The application discloses a kind of biological tissue section rigidity measurement methods based on photonic crystal colorimetric sensor, the method is according to the set step pitch vertically to photonic crystal colorimetric sensor and is pressed down to tissue section, photonic crystal colorimetric sensor is formed by the elastomer of better biocompatibility and is covered photonic crystal, its Young's modulus can be adjusted according to the rigidity range of tissue section, in the process of pressing down, the different deformation of elastomer due to the rigidity of different regions of tissue, the wavelength of internal photonic crystal reflection changes, that is, the color difference of sensor surface is generated, then the rigidity information of tissue section is obtained according to the color difference analysis.The method realizes the rigidity of biological tissue section fast, simple, high-precision detection, and can be applied to the fields such as tissue engineering, organ chip, clinical examination and the like.

The invention relates to the technical field of pathological section image recognition, in particular to a method for accurately predicting clinical prognosis of a colorectal cancer patient, which comprises the steps of full-view digital section acquisition, full-view digital section preprocessing, Transformer-dynamic agency attention-Mama network and interpretability analysis. According to the method, firstly, a tissue slice segmentation unit and a preliminary feature extraction unit are integrated, full-view digital slice feature extraction is achieved, then a Transformer-dynamic agency attention coupling architecture is adopted, time sequence dependence modeling is achieved through a multi-layer Mama module, finally, a feature aggregation unit is used for outputting patient risk scores, and the patient risk scores are obtained. And realizing visual explanation of the model decision by adopting a thermodynamic diagram. According to the method, through fusion of long sequence data processing, a dynamic agency attention mechanism and a state space modeling technology, the technical bottlenecks of insufficient feature characterization capability, difficulty in long-range dependence modeling and the like in traditional pathological image analysis are solved.

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.

The present invention provides an information processing method, device, equipment and storage medium based on cell segmentation, which relates to the field of biological information technology. The method includes: obtaining a corrected scanned image; the scanned image is obtained based on a tissue slice attached to a biochip; performing cell segmentation on the scanned image to obtain a cell segmentation result; based on the inherent position of each barcode microsphere in the biochip, extracting the position information of the barcode microsphere corresponding to each cell in the cell segmentation result; based on the position information of the barcode microsphere corresponding to each cell in the cell segmentation result, determining the first position information of each cell and the statistical information of the corresponding barcode microsphere. The present invention can improve the efficiency and accuracy of cell analysis.

The invention discloses a method for detecting accessibility of space chromatin and application of the method. The method comprises the following steps: (1) slicing a tissue sample to be detected on a chip with spatial information; (2) fixing, permeabilizing and dyeing a tissue sample to be detected; (3) preparing fragmented genome DNA (deoxyribonucleic acid); (4) performing DNA hybridization based on a transfer mode; (5) carrying out connection and terminal repair reaction on the fragmented genome DNA by using DNA polymerase and DNA ligase; (6) denaturation and melting; and (7) sequencing. According to the method, the transcriptional activity state of chromatin can be reflected through chromatin accessibility sequencing analysis, staining imaging and chromatin accessibility information can be obtained on the same tissue slice at the same time without complex micro-fluidic equipment, experimental operation is easy, repeatability is high, and the analysis result is more remarkable.

The invention discloses a pathological image full-automatic segmentation and classification method and system based on deep learning, and the method comprises the steps: selecting a to-be-processed tissue slice image, extracting the feature information of a cell nucleus in the to-be-processed tissue slice image, and carrying out the initialization processing; the unified feature decoder is introduced to process the image, and different feature information is integrated; carrying out instance segmentation on the cell nucleus by adopting a convolutional neural network, and optimizing a feature extraction process in combination with a self-attention mechanism and a residual network; meanwhile, a classification module is used for carrying out category prediction on cell nucleuses, and tissue region guide information is fused; and carrying out comprehensive optimization on the segmentation result and the classification result through multi-task joint training until a preset stop condition is met, and obtaining a high-quality cell nucleus segmentation and classification result. The method can automatically and efficiently perform cell nucleus segmentation and classification in the digital pathological image, has high accuracy and stability, is suitable for various complicated tissue slice analysis tasks, and does not need manual intervention.

The invention relates to the technical field of medical apparatus and instruments, and discloses an intelligent full-automatic pathological slicing machine which comprises a shell, a sample clamping module, a first mechanical transmission system, a second mechanical transmission system, a waste slice buffering pool, a moving platform and an adjustable cutter module. An inclined conveying mechanism; the slice transfer mechanism and the slice selection mechanism are used for intercepting set tissue slices and applying suction force with a set numerical value to the set tissue slices; the inclined conveying mechanism and the slice transferring mechanism matched with the inclined conveying mechanism are additionally arranged on the adjustable cutter module, the inclined conveying mechanism can automatically convey slices according to the number of the generated slices, and waste slices and slices are cut and separated through the slice transferring mechanism; and then the slices are transferred from the inclined conveying mechanism to the correspondingly arranged slice conveying mechanism, the automatic slice selecting and transferring functions are achieved, tedious manual operation is not needed, and the operation difficulty of an old-fashioned mechanical system slicing machine is reduced.

Disclosed herein, inter alia, are devices and methods for transfer and analysis of tissue sections using carrier substrates.

The invention provides a method for tissue in-situ protein immunofluorescence circulating staining and data analysis, and belongs to the field of biological detection. The method comprises the following specific steps: S1, preparing a sample tissue slice; s2, carrying out fluorescent staining; s3, elution: carrying out elution by adopting an Elbixt abs994 eluent; s4, circulating dyeing: after the elution is completed, repeating the steps S2 to S3 according to the detected target protein to perform circulating dyeing; obtaining a fluorescent dyeing image after each dyeing is finished; s5, identifying a cell nucleus image; s7, performing multi-round image registration; and S8, antibody positive cell screening and connectivity segmentation based on the overlapping area: through distribution characteristics of different antibodies, based on the overlapping area with a specific cell nucleus, a surrounding relationship and a rejection relationship before different antibodies, different cell identities are divided, and in-situ detection of a plurality of proteins can be realized.