81 results about "Eosin" patented technology

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 qualifying a specimen prepared on one or more hematoxylin and eosin (H&E) slides by assessing an expected yield of nucleic acids for tumor cells and providing associated unstained slides for subsequent nucleic acid analysis is provided.

The invention provides a papillary thyroid carcinoma lymph node metastasis prediction method, system and equipment. The method comprises the following steps: acquiring a staining collagen image of a first papillary thyroid carcinoma section stained by a hematoxylin eosin staining method; obtaining a multi-photon collagen image of the second papillary thyroid carcinoma slice through a multi-photon imaging method; setting an observation area on the multi-photon collagen image according to the dyed collagen image; extracting collagen characteristics in the observation area; constructing a collagen feature scoring model according to an LASSO algorithm and the collagen features; obtaining a collagen feature score according to the collagen feature scoring model; acquiring clinical risk factors; the papillary thyroid carcinoma metastasis risk information is output according to the clinical risk factors and the collagen feature scores, the collagen features in the papillary thyroid carcinoma microenvironment can be accurately and quantitatively extracted by combining the multi-photon imaging technology and collagen feature analysis, accurate prediction of the papillary thyroid carcinoma metastasis risk is achieved, and the accuracy of the papillary thyroid carcinoma metastasis risk is improved. And the prediction accuracy can be further improved in combination with clinical risk factors.

Techniques for using combination stain types for machine learning models for digital pathology are described herein. In an example, a system accesses a first image of a sample comprising an immunohistochemistry (IHC) stain for a biomarker. The system accesses a second image of the sample comprising a hematoxylin and eosin (H&E) stain for nuclei. The system can segment tissue regions in the one or more first images and the second image, partitions the tissue regions in the one or more first images and the second image, and extracts features from the set of tiles using a feature extractor. The system can generate, by a machine-learning model, an output classification indicating a first phenotype based on the features extracted from the set of tiles. The machine-learning model can include one or more classifiers and an aggregation model that provides an aggregated output for the set of tiles.

The invention discloses a full-automatic dyeing machine water-soluble eosin dyeing method based on mechanical arm dynamic control and process optimization, which comprises the following steps: (1) mechanical arm operation logic setting: in the steps of eosin dyeing, washing and 95% ethanol differentiation, the mechanical arm is forbidden to switch idle slot positions by locking slot position distribution; (2) time parameter control: setting the eosin dyeing time to be 2-3 minutes, the washing time to be 30-45 seconds, and the 95% ethanol differentiation time to be 20-30 seconds; and (3) error calibration: performing synchronous verification by adopting a manual timer and a dyeing machine program to ensure that the error between the actual execution time of each step and a set value does not exceed + / -5 seconds.

The invention discloses application of hydrogen-rich water in preparation of a drug for treating Duchenne type muscular dystrophy, and particularly relates to the technical field of medicines.The random control experiment is adopted, homologous c57 mice serve as a normal control group, mdx mice are randomly divided into a model group and a hydrogen-rich water group, and the exercise ability is evaluated through a four-limb holding power test and a rotating bar test; detecting mouse creatine kinase by an enzyme-linked immunosorbent assay; carrying out hematoxylin-eosin, NADH-tetrazole reductase and improved Goori three-color dyeing, and carrying out cytochrome C oxidase, succinate dehydrogenase and SDH-COX combined dyeing to observe the pathological change of the skeletal muscle tissue; the invention discloses that the muscle injury condition of a Duchenne type muscular dystrophy model mouse is improved by the hydrogen-rich water through a mitochondrial protection mechanism, and the hydrogen-rich water has a relatively high application prospect and a relatively high economic value.

The present disclosure relates to a method for selection of ovarian cancer patients for treatment with PARP inhibitors This involves 1) preparing whole slide images of tissues of ovarian cancer patient to be treated 2) training and validating AI model built on Resnet-50 to recognize morphological features from tiles of hematoxylin and eosin stained whole slide images of tissues featuring the presence of homologous recombination deficiency as annotated by next generation sequencing 3) using the model to extract morphological features from the tiles of hematoxylin and eosin stained whole slide images of tissues of ovarian cancer patients, generating tile level predictions, aggregating tile level predictions to generate a probability score and selecting the patient for treatment with PARP inhibitors 4) administering PARP inhibitors treatment to the patient selected based on probability score reaching a predetermined threshold. Computer systems to implement the method are also disclosed.

The present invention belongs to the field of medicinal chemistry and specifically discloses a light-responsive ion pair composition and its anti-cancer application. The ion pair composition includes a cyclometallic gold (III) complex and a photosensitizer, wherein the photosensitizer includes eosin (EY) or rose bengal (RB), and the structural formula of the cyclometallic gold (III) complex is shown in formula (1). The composition modifies the structure of the known cyclometallic gold (III) complex skeleton by adding hydroxyl groups, morpholine rings and deuteration, thereby improving its water solubility, charge properties, stability and other aspects. It can be efficiently activated by green light or even red light and has anti-cancer applications. The present invention achieves efficient activation of the cyclometallic gold (III) complex by combining the cyclometallic gold (III) complex with eosin (EY) or rose bengal (RB), and can extend the excitation wavelength to the red light range; and based on the ion pair properties and the characteristics of the tumor microenvironment, tumor-specific treatment can be achieved more accurately on the basis of light irradiation.

The present disclosure relates to an apparatus including one or more processors configured to receive a digitized image of a region of tissue demonstrating a disease, and containing cellular structures represented in the digitized image, each of the cellular structures being associated with a cell category of a plurality of cell categories; select a cellular structure of the cellular structures based on the cell category for the cellular structure; for the cellular structure selected, compute a set of contextual features; assign, based on the set of contextual features, the cellular structure to at least one cluster of a plurality of clusters; compute cluster features, the cluster features describing characteristics of the at least one cluster of the plurality of clusters; and generate a prediction that describes a pathologic or phenotypic state of the disease based, at least in part, on the cluster features and / or the set of contextual features.

The invention discloses a gallic acid-based cationic photodynamic antibacterial agent with sterilizing, anti-infection and wound healing promoting effects and a preparation method thereof, and belongs to the technical field of antibacterial agent synthetic chemistry. The cationic photodynamic antibacterial agent EY-QEGDM-MG is prepared by taking a natural compound gallic acid as a raw material and carrying out ring opening polymerization and quaternization reaction with photosensitizer eosin EY and ethylene glycol diglycidyl ether (EGDE), and the polymer shows an excellent antibacterial effect on escherichia coli and multi-drug-resistant MRSA germs under the action of illumination, and can be used for preparing a cationic photodynamic antibacterial agent EY-QEGDM-MG. The polymer has good blood compatibility and cell compatibility, in addition, the polymer can kill bacteria around infected wounds and can rapidly promote wound healing, and therefore the polymer can provide a new method for photodynamic antibacterial agents for treating the infected wounds in hospitals.

The invention provides an application of farrerol in preparation of a medicine for preventing osteoporotic diseases caused by inflammatory bowel diseases, and belongs to the technical field of inflammatory bone disease treatment.The application comprises the steps that firstly, an ulcerative colitis (UC) mouse is constructed to simulate occurrence of the osteoporosis induced by enteritis, and the occurrence of the osteoporosis induced by enteritis is simulated through microcomputer tomography (CT), hematoxylin and eosin (Hamp; e) and tartrate-resistant acid phosphatase (TRAP) staining are used for analyzing the bone destruction degree and the number of osteoclasts, and the influence of the farrerol on osteoclast generation and bone loss is detected. The influence of the farrerol on the inflammatory bowel disease is analyzed through 16S rRNA (ribosomal Ribonucleic Acid) sequencing. In addition, PI3K-AKT and MAPK signal pathways related to osteoclast differentiation of the farrerol are detected through WB and PCR experiments to clarify the basic molecular mechanism of the farrerol for preventing osteoporosis. Results show that the farrerol can improve bone loss caused by enteritis, recover intestinal flora composition and repair intestinal barriers.

The invention also related to a device and a computer-implemented method for generating n virtual Immunohistochemical (IHC) stain images from one Hematoxylin and Eosin (H&E) stain image, using the IHC machine learning system obtained thanks to the device for training.

The invention belongs to the technical field of pathological tissue section staining, and particularly relates to a hematoxylin-eosin staining method based on short-time immersion and chaotropic standing diffusion and application of the hematoxylin-eosin staining method. According to the hematoxylin-eosin staining method based on short-time immersion and chaotropic standing diffusion, the staining process time can be remarkably shortened, the working efficiency of pathological section staining can be greatly improved, the staining solution consumption and the cross contamination risk can be effectively reduced, the experiment cost is saved, and the reliability of the staining result is guaranteed; meanwhile, the dyeing uniformity and repeatability can be remarkably improved, the result deviation caused by operation difference is reduced, the dependence on the experience of an operator is reduced, and standardized popularization and application are facilitated; besides, the dyeing method disclosed by the invention is wide in applicability, can meet the dyeing requirements of conventional paraffin sections, frozen sections and trace tissue samples, can meet the use requirements under different pathological detection scenes, and has outstanding clinical and scientific research application prospects.

The application discloses a colorectal cancer HER2 state classification method based on a double-branch cooperative optimization network and belongs to the technical field of pathological image processing. The application adopts a double-path cooperative optimization framework, combines knowledge transfer and cross-modal feature re-projection, efficiently extracts features related to the HER2 state from a conventional hematoxylin-eosin (H&E) staining section, and can directly accurately judge the HER2 state. Through the prior knowledge transfer and cross-modal feature re-projection mechanism, the application breaks through the bottlenecks such as insufficient utilization of prior knowledge and modal heterogeneity interference in the traditional method, and significantly improves the accuracy and robustness of the colorectal cancer HER2 state classification.

The invention discloses a method for collecting and dyeing sperms of Chinese prawns, and belongs to the technical field of germplasm resource protection and utilization. The method comprises the following steps: grinding Penaeus chinensis spermatophore with outer membrane removed in a glass homogenizer, adding sterilized artificial seawater, grinding until the solution becomes milky white, and filtering to obtain sperm; and mixing the sperm with eosin-nigrosine dye liquor, and standing to obtain the dyed Chinese prawn sperm. The collecting and dyeing steps are simple and easy to operate, the whole process is short in time consumption, small in sperm damage, visual in effect and high in sperm survival rate. The staining method disclosed by the invention is not only suitable for staining fresh sperms, but also can be used for staining the thawed and resuscitated sperms after cryopreservation, the staining observation after thawing is clear, and the sperms are not easy to crystallize.

This invention discloses a method for degrading dyes using dye decolorization peroxidase, belonging to the field of biotechnology. This invention expresses a DyP (RhDyPB) derived from the bacterium *Rhodococcus jostii* in *Escherichia coli*. By adjusting the pH, manganese ion, hydrogen peroxide, and Tween-80 content during the decolorization process, the decolorization efficiency of RhDyPB and *E. coli* expressing RhDyPB on the anthraquinone dye Reactive Blue 19, the oxanthracene dye Eosin Y, the indigo dye Indigo Carmine, and the triphenylmethane dye Malachite Green is effectively improved.

The present invention discloses a biopsy specimen fixing and staining solution, and its preparation and application methods. The solution comprises the following components, measured by weight: 100-200 parts of acetone, 200-400 parts of glacial acetic acid, 200-400 parts of eosin Y, 50-200 parts of eosin stain, 50-200 parts of formalin, 1-10 parts of dimethyl sulfoxide, and 50-100 parts of zinc chloride. The biopsy specimen fixing and staining solution of the present invention has good staining effect and stable coloring.

The present application relates to a kind of hematoxylin-eosin (HE) staining method and operation steps without xylene and alcohol, belong to pathological technique, apply in pathology, histology and clinical experimental diagnosis biomedical disciplines field such as embryo. The hematoxylin-eosin (HE) staining step of conventional paraffin section is at least 12 more additional steps before and after dyeing into dyeing liquid dyeing to mounting respectively needs to use including xylene and gradient concentration alcohol. Lengthy dyeing step is not only laborious and time-consuming, also pollutes air environment and harms personnel health. The present application is a kind of conventional paraffin section whole process hematoxylin-eosin (HE) dyeing step without using xylene and alcohol method and step, make its application in management HE dyeing process for improving pathological technical room work quality and efficiency, reduce reagent cost and eliminate environmental pollution is crucial.

The invention belongs to the technical field of learning model construction, and provides a colorectal adenoma recognition semantic segmentation deep learning system and a construction method, and the system comprises a data set obtaining and processing module which is used for obtaining and processing a case image of colorectal adenoma, and obtaining a target data set; the model construction module is used for constructing and obtaining Hamp on the basis of coloring agents named hematoxylin and eosin in combination with a semi-supervised learning model; e, a semantic segmentation deep learning model of adversarial average teachers; and the model learning training module is used for carrying out learning training on the semantic segmentation depth model based on the target data set. According to the method, the case image of the colorectal adenoma is acquired and processed, the semantic segmentation deep learning model is constructed, learned and trained on the basis of the coloring agent named hematoxylin and eosin and in combination with the semi-supervised learning model, the creation quality of the colorectal adenoma recognition semantic segmentation deep learning system can be ensured, and the recognition efficiency of the colorectal adenoma is improved. And a basis is provided for efficiently and accurately identifying the case image of the colorectal adenoma.

Embodiments access a digitized image of tissue demonstrating non-small cell lung cancer (NSCLC), the tissue including a plurality of cellular nuclei; segment the plurality of cellular nuclei represented in the digitized image; extract a set of nuclear radiomic features from the plurality of segmented cellular nuclei; generate at least one nuclear cell graph (CG) based on the plurality of segmented nuclei; compute a set of CG features based on the nuclear CG; provide the set of nuclear radiomic features and the set of CG features to a machine learning classifier; receive, from the machine learning classifier, a probability that the tissue will respond to immunotherapy, based, at least in part, on the set of nuclear radiomic features and the set of CG features; generate a classification of the tissue as a responder or non-responder based on the probability; and display the classification.

An apparatus and methods for determining features in an image of a Hematoxylin and Eosin (H&E) stained tissue sample. An apparatus can be configured to apply a machine learning model to the H&E stained tissue sample image to determine features in the image. Applying the machine learning model can include performing convolution operations on the H&E stained tissue sample image to generate a plurality of initial feature maps, applying octave-convolution-first-layer operations on the initial feature maps to generate initial high-frequency feature maps and low-frequency feature maps, applying octave-convolution operations on the high-frequency initial feature maps to generate refined high-frequency feature maps, applying octave-convolution operations on the low-frequency initial feature maps to generate refined low-frequency feature maps, and applying octave-convolution last layer operations on the refined high-frequency feature maps and the refined low-frequency feature maps to produce combined feature maps.

The invention belongs to the technical field of artificial intelligence and digital pathology crossing, and relates to a regulatory T cell infiltration prediction method based on a digital pathological section. According to the method, a conventional hematoxylin-eosin dyed full-section digital image is used as input, and an analysis range is limited through tissue region segmentation and tumor region positioning; extracting multi-scale morphological characteristics of the visual field units in the tumor area, and constructing a graph neural network coding local-global space context; on the premise of taking an adjacent section immunohistochemical quantification or transcriptome immune deconvolution result as a supervision signal, improving the robustness of a cross-staining batch and a cross-scanning condition by adopting regression learning in combination with adversarial regularization and transfer learning; and outputting regulatory T cell infiltration density or grade and thermodynamic diagram visualization, and further giving uncertainty and spatial heterogeneity indexes for review and decision support.

Presented herein are methods of improving the consistency of staining with a counterstain. In some embodiments, the method makes use of an automated specimen processing apparatus or other staining device. In some embodiments, the staining methods are applied manually. In some embodiments, the counterstain includes eosin.

The invention belongs to the technical field of preparation of tissue sections, and relates to a paraffin section of wheat roots and a preparation method thereof, the preparation method comprises the steps of fixing, dehydrating, transparentizing, waxing, embedding, slicing, spreading, baking, dewaxing to water, dyeing and sealing in sequence, a pre-dyeing step is carried out between the fixing step and the dehydrating step, and the pre-dyeing step is carried out between the pre-dyeing step and the dehydrating step. In the pre-dyeing step, a sarranine solution is adopted to treat the fixed wheat roots, and the treatment time is 12-20 h; treatment is carried out under the conditions of positive and negative pressure alternate circulation and temperature increase in the steps of dehydration, transparentizing and waxing; in the dyeing step, a 5% sodium sulfite solution is added for treatment, the treatment time is 0.5-1 h, and a 0.5% hydrochloric acid ethanol solution is added for treatment for 5-10 s. According to the method, the tissue structure in the obtained slice is clear and complete in combination with the optimized process, the dyeing contrast is distinct, the tissue structure of the wheat slice in a survival state is restored to a greater extent, and accurate obtaining of wheat research experiment results is facilitated.

The invention discloses a dyeing method for vagina micro-ecology detection. The dyeing method mainly comprises the following steps: 1) taking female genital tract secretions, and directly diluting the secretions with a diluent to form a suspension; (2) coating the suspension liquid on a glass slide by using a pipettor; 3) drying and fixing the suspension on the glass slide; 4) immersing the fixed suspension liquid glass slide into an eosin dye solution, and washing the glass slide with running water; (5) carrying out gram staining on the glass slide; and 6) observing by using a microscope. The invention also relates to a staining kit. According to the staining method, under the condition that the advantages of a gram staining method in the prior art are reserved, simple and rapid detection of trichomonad vaginalis can be achieved, the trophozoic form and flagellum form of trichomonad vaginalis can be clearly displayed, the accuracy of trichomonad vaginalis detection can be improved, and the method is suitable for popularization and application. The comprehensive and accurate detection on the vagina micro-ecology is facilitated.

A method of displaying biological image data in an interface application on a digital pathology analysis system includes: receiving a first user input pertaining to a first patient case; contacting a remote server for one or more stored biological image tiles corresponding to the received first user input, wherein the stored biological image tiles are derived from scans of microscope slides having one or more biological samples disposed thereon, the biological samples stained with hematoxylin and eosin or stained to identify presence of one or more biomarkers; receiving location information for the one or more stored biological image tiles corresponding to the first user input; retrieving the one or more stored biological image tiles pertaining to the first user input based on the received location information; and visualizing the retrieved one or more biological image tiles pertaining to the first user input.

A method of displaying biological image data in an interface application on a digital pathology analysis system includes: receiving a first user input pertaining to a first patient case; contacting a remote server for one or more stored biological image tiles corresponding to the received first user input, wherein the stored biological image tiles are derived from scans of microscope slides having one or more biological samples disposed thereon, the biological samples stained with hematoxylin and eosin or stained to identify presence of one or more biomarkers; receiving location information for the one or more stored biological image tiles corresponding to the first user input; retrieving the one or more stored biological image tiles pertaining to the first user input based on the received location information; and visualizing the retrieved one or more biological image tiles pertaining to the first user input.

The invention discloses a gastric cancer microsatellite instability state diagnosis model. The model comprises an instance segmentation module which is used for generating a segmentation mask for a hematoxylin eosin dyed image so as to generate an instance image block of a target pixel in a tissue related area; the feature extraction module is used for extracting initial features by utilizing a plurality of selected optimal pre-training models according to the input blocks; the dynamic weight distribution module is used for evaluating the importance of the plurality of optimal pre-training models on the primary features output by the same image and generating a fusion weight; the feature fusion module is used for fusing the primary features extracted by the plurality of optimal pre-training models into an advanced feature vector in combination with the fusion weight; the attention score calculation module is used for calculating attention scores of the high-level feature vectors of the different image blocks of the same image, and the multi-instance classifier is used for diagnosing the MSI state according to the high-level feature vectors of the image blocks which are ranked before M. Through the system, the instability state of the microsatellite can be accurately diagnosed.

The application belongs to the technical field of pathological tissue processing, and particularly relates to a pathological tissue staining automatic control method and a staining machine system. The method provided by the application detects and calculates the staining quality after each staining, adjusts the staining processing time of hematoxylin and eosin according to the staining quality, and replaces the staining solution if the staining processing time of hematoxylin and eosin exceeds the preset maximum value. The method provided by the application can effectively prolong the service life of the staining reagent, and can also ensure the uniformity and stability of pathological section staining.

A system and method of identifying a Tertiary Lymphoid Structure (TLS) by at least one processor may include receiving an Hematoxylin and Eosin (HE) image, depicting an HE-stained slide comprising a plurality of HE-stained biological cells obtained from a subject; obtaining a candidate region data element, representing a high Lymphocyte Density (LD) region in the HE image; segmenting the high LD region of the candidate region data element, to obtain a plurality of cellular segment data elements, each representing a respective depicted biological cell in the candidate region; for one or more biological cells of the cellular segment data elements, calculating at least one respective cellular structural feature value; and inferring a Machine Learning based LD classification model on the at least one cellular structural feature value of the cellular segment data elements, to classify the candidate region as a TLS region, a TLS sub-class region or a non-TLS region.