105 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.

The invention provides a bladder cancer prognosis prediction method and system, and relates to the technical field of intelligent detection, and the method specifically comprises the steps: obtaining and preprocessing a bladder cancer hematoxylin-eosin (HE) staining pathological image to obtain an effective color block, and marking to obtain a tumor and necrosis training set; respectively training the two initial models based on the tumor training set and the necrosis training set to correspondingly obtain a tumor model and a necrosis model; acquiring a to-be-predicted bladder cancer pathological image, and performing tumor and necrosis region identification based on the tumor model and the necrosis model to correspondingly obtain a tumor region and a necrosis region; based on the space coordinate information of the tumor area and the necrotic area, carrying out numerical calculation to obtain a space distribution index of the necrotic area relative to the tumor area; and carrying out survival analysis based on the spatial distribution index to obtain survival prognosis information of the bladder cancer patient. The deep learning technology is applied to the prognosis direction of the bladder cancer, a clinician is assisted in evaluating survival prognosis of a patient, and a reference basis is provided for diagnosis and treatment decisions.

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.

The invention discloses a high-resolution breast cancer HER2 scoring method based on deep learning. The high-resolution breast cancer HER2 scoring method comprises the following steps: constructing a full-slide image data set containing hematoxylin-eosin and HER2 staining; accurately marking by a pathological expert, and distinguishing normal, in-situ and invasive tumor areas; cutting, classifying and marking blocks with different sizes and magnification times; carrying out gray level conversion, binarization and morphological operation on the image blocks to extract a tissue region; designing a deep learning model combining a visual converter and Fourier transform, and optimizing feature extraction and frequency domain analysis; an optimal backbone network structure is selected through comparison; the model is trained, parameters are optimized, and the recognition and evaluation accuracy is improved; and finally integrating to an automatic scoring software system to realize automatic identification, HER2 protein expression evaluation and automatic scoring. The system is high in automation degree, the HER2 scoring process is simplified, the auxiliary diagnosis precision is improved, the workload of doctors is reduced, and pathologists are helped to concentrate on complex diagnosis tasks, so that the patient management effect is improved.

A machine learning (ML) workflow for virtual staining and computational pathology based on a label-free tissue sample is provided to avoid a laborious and time-consuming procedure of pathologist-based interpretation of formalin-fixed and paraffin-embedded histology. A virtual-staining ML model translates a label-free autofluorescence (AF) whole slide image (WSI) of the tissue sample into a virtual hematoxylin and eosin (H&E) -stained WSI, which is further transformed into a WSI virtually stained with a special stain by a stain-transformation ML model. Each of the ML models can be realized as a U-Frame model. A multiple instance learning (MIL) network with attention-based pooling can be applied to the virtual H&E-stained WSI or AF WSI to provide fast and accurate tumor diagnosis. Furthermore, the attention-based MIL network can be configured as a clustering-constrained-attention multiple instance learning (CLAM) model for providing multiclass tumor subtyping, or even multiclass disease typing, in diagnosis of the tissue sample.

A machine learning system makes medical predictions based, at least in part, on pathomic features indicating collagen fiber organization extracted from pathology images that include lesions. The pathomic features are extracted from pathology images. The pathology images may be routine clinical images gathered in the course of diagnosis and treatment, such as hematoxylin and eosin (H&E)-stained whole slide images (WSIs) of tissue. The medical predictions may concern, e.g., the diagnosis, prognosis, genotype, or phenotype of a lesion, and may include disease-free survival (DFS) and overall survival (OS) of patients known or suspected of having malignant lesions. Methods for training a machine model to make, and for making, such predictions are also disclosed.

The invention belongs to the technical field of biology, and particularly relates to a reagent and a kit for detecting eosinophilic granulocyte chronic sinusitis with nasal polyp. The detection reagent comprises the following components: a substance which is used for detecting the Galectin-10 protein (Charcot-Leyden Crystal, CLCs) in a crystalline state, and a detection reagent which is used for detecting the Galectin-10 protein (Charcot-Leyden Crystal, CLCs) in the crystalline state. The reagent for detecting CLCs comprises a mixture of eosin, glacial acetic acid and water. The mass volume ratio of eosin to glacial acetic acid is 1: (1-50) g / mL, and the volume ratio of glacial acetic acid to water is 1: (2-100). According to the invention, the reagent capable of efficiently detecting the CLCs is found for the first time, and the CLCs is a biomarker of the eosinophilic chronic sinusitis with nasal polyp, so that the detection reagent for the eosinophilic chronic sinusitis with nasal polyp is provided. By detecting CLCs, eosinophilic granulocyte chronic sinusitis with nasal polyp can be predicted, and the method is simple, convenient and fast and has good prediction performance.

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.

A technique for expansion microscopy (ExM) utilizing anchorable derivatives of hematoxylin and eosin (H&E) stained tissue specimens within tissue samples, in order to achieve high resolution detection of biomolecules with precise morphological features of cells and nuclei, which in turn, allows for effective for accurate early stage disease diagnosis including various cancers. Staining with H&E employs anchorable derivatives that can be cross-linked into the ExM hydrogel matrix.

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.

To provide a system and method of training a model capable of identifying the hormone receptor status of a subject by means of whole slide images (WSIs) of hematoxylin and eosin (H&E) stain of his / her biopsies, and to provide a method of identifying the hormone receptor status of a subject using the above mentioned method and model.SOLUTION: A method disclosed herein comprises a step S101 of acquiring multiple WSIs having known hormone receptor information, a step S102 of dividing each of the WSIs into a plurality of patches, a step S104 of selecting and combining patches expressing abnormal H&E stain to produce a combined image; and a step S105 of training a plurality of combined images independently with the aid of the known hormone receptor information of the WSIs so as to construct a model.SELECTED DRAWING: Figure 1

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 relates to the technical field of biology, and particularly provides a hematoxylin staining solution and a preparation and staining method thereof.The hematoxylin staining solution is prepared from hematoxylin, absolute ethyl alcohol, aluminum potassium sulfate, sodium iodate, glacial acetic acid and water, the proportion of all the raw materials is adjusted in a targeted mode, the dosage of all the raw materials is strictly controlled, and it is accidentally found that the hematoxylin staining solution can be used for staining hematoxylin. After a tissue slice is stained by the hematoxylin staining solution provided by the invention, cell nucleus coloring is good, a tissue structure is clear, the tissue slice subjected to eosin restaining is bright in color, strong in contrast, easy to observe, ideal in staining effect, high in staining stability, not easy to fade and beneficial to long-term preservation of the slice, the preparation method is simple, and an unexpected effect is achieved.

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.

The invention discloses a method for in-situ labeling of lysosomal protein in living cells and a reagent used in the method. The invention discloses a method for in-situ labeling of lysosomal protein in a living cell. The method comprises the following steps: treating a cell to be detected by using Eosin-N2 to obtain the cell treated by the Eosin-N2; treating the cells treated by the Eosin-N2 by using a thiomethylene quinone precursor probe, so as to obtain the cells treated by the Eosin-N2 and the probe; and irradiating the Eosin-N2 and the cells treated by the probe with green light to realize in-situ labeling of the lysosomal protein in the cells. According to the method, the lysosomal proteins in different types of cells can be efficiently labeled in situ, the specificity is high, the labeled lysosomal proteins can be further used for enriching the lysosomal proteins, and the method has a very good application prospect.

The invention discloses a formula of an eosin staining solution, and every 1000 ml of the eosin staining solution comprises the following components: 5-8 g of eosin which is any one of water-soluble eosin Y or alcohol-soluble eosin Y; 2.5 to 3.5 g of potassium dichromate; 5-25 g of picric acid; 5 to 60 ml of absolute ethyl alcohol; the balance is water, and the water is any one of deionized water or distilled water. According to the eosin staining solution formula disclosed by the invention, the absolute ethyl alcohol not only can promote good dissolution of all the components and effectively ensure a good uniform mixing effect among all the components, but also can be used as a dehydrating agent and can play a role in dehydrating and fixing cells, so that a cell environment in tissues is similar to the tissues, cell coloring in the tissues is facilitated, and the quality of the cells in the tissues is improved. The dyeing liquid has a certain level dyeing effect, is clear in coloring, avoids overdyeing, uneven dyeing and other conditions, utilizes the synergistic effect of potassium dichromate and picric acid, promotes the dissolution of each component, ensures the stability of the dyeing liquid, is simpler to prepare, is not easy to fade, and has a longer period of validity.