53 results about "H&E stain" patented technology

The invention discloses a mass spectrum imaging space super-resolution reconstruction method and system based on a label propagation network, and the method comprises the steps: carrying out the preprocessing of MSI data, and obtaining the low-dimensional representation of the MSI data; representing the low dimension with the Hamp; e, registering the dyed image; for the Hamp; e, performing spatial segmentation on the dyed image to obtain a plurality of image blocks, and constructing a label propagation network for each image block; taking the MSI data as a label of a matched node in the network, propagating the MSI data along the network, and updating the label of the network node at the same time; and fusing the node labels with the statistics-based features, constructing a regression model to calculate the features of each superpixel, and realizing the spatial super-resolution reconstruction of the MSI. According to the invention, the Hamp is fused in the MSI; the method comprises the following steps: according to structural information of an E image, realizing global multi-modal registration through local affine transformation registration, and performing Hamp; and the E dyeing microscopic image is replaced by a high-resolution medical image of other modals, so that mass spectrum imaging super-resolution reconstruction driven by other modals can be realized, and the MSI spatial resolution is improved.

The invention belongs to the technical field of medical image processing, and particularly relates to an esophageal cancer treatment effect and survival combined prediction method and system based on multiple modalities, and the method comprises the steps: obtaining a preoperative CT image and Hamp of an esophageal squamous cell carcinoma patient; e, the dyed digital pathological image, transcriptome data and clinical diagnosis and treatment information are preprocessed and subjected to feature extraction, and radiomics embedding representation, pathomics embedding representation and pipeline branch embedding representation are obtained respectively; the radiomics embedded representation, the pathomics embedded representation and the pipeline branch embedded representation are aligned and input into a multi-modal fusion module based on a multi-head self-attention mechanism for feature fusion, and fusion feature representation is generated; and based on the fusion feature representation, synchronously outputting a curative effect prediction result and a survival prediction result by using a multi-task output module, and evaluating model prediction performance by using a curative effect evaluation index and a survival analysis index.

The invention provides an application of narirutin in preparation of a medicine for preventing and / or treating osteoclast of inflammatory arthritis, relates to the technical field of biomedicine, and adopts a collagen-induced mouse arthritis model to observe the treatment effect of the narirutin on the osteoclast of the inflammatory arthritis. The arthritis activity degree of the mouse is analyzed through general claw photographing, thickness measurement, near-infrared temperature measurement and a claw imprinting experiment, three-dimensional reconstruction and bone trabecula analysis are carried out on local joints and the whole body bone mass of the mouse through micro-CT scanning, and Hamp is applied; e, dyeing and Famp; through histological staining analysis such as O staining and TRAP staining, in combination with immunohistochemical staining and the like, the narirutin is proved to play a role in treating inflammatory arthritis, inhibit macrophage pro-inflammatory M1 type polarization, relieve the inflammation level, improve the bone mass of local joints and the whole body, and further improve bone destruction in inflammatory arthritis diseases. The narirutin provides a new way for medicine prevention and treatment of inflammatory arthritis.

The embodiment of the invention provides an image virtual dyeing method and device based on deep learning and a related assembly. The image virtual dyeing method comprises the following steps: utilizing a preprocessed photoacoustic microscopic image and a Hamp; e, performing iterative training on a pre-constructed virtual dyeing model by the dyeing image to obtain a trained virtual dyeing model, and performing virtual dyeing on the new photoacoustic microscopic image by using the trained virtual dyeing model to obtain Hamp; e, dyeing the image of the style (i.e., pseudo Hamp; e, dyeing the image). According to the embodiment of the invention, the image segmentation module is embedded in the generator to help the generator to distinguish cytoplasm and cell nucleus, so that the virtual staining model is constrained, and the generator can better generate a Hamp conforming result; e, dyeing the morphological characteristics of the image to ensure the generated pseudo Hamp; the E dyeing image retains more useful cell nucleus information, and the pre-constructed virtual dyeing model reduces noise in the learning process and effectively prevents the problem of overfitting due to the fact that an image segmentation module is embedded in a generator.

Tumor budding (TB) is defined as a cluster of one to four tumor cells at the tumor invasive front. Though promising as a prognostic factor for colorectal cancer, its routine clinical use is hampered by high inter-and intra-observer disagreement on routine H&E staining. Therefore, automated methods are provided that minimize the inter-and intra-observer disagreement for tumor bud detection on images of H&E-stained tissue sections.

A kind of H&E image ovarian cancer polyploid giant cell (PGCCs) detection method based on deep learning, including constructing specific data set, image annotation and data division, using OCDet model to carry out feature learning and optimization, and model training and evaluation.The method first establishes the H&E staining image data set containing PGCCs, then accurately labels the image and divides it into training, verification and test set.OCDet model takes CSPDarkNet as the core, combines ECA mechanism, focuses on the deep learning and re-encoding of pathological semantic features.Through the training data set, the model updates parameters through back propagation and gradient descent, optimizes to identify PGCCs features.The verification set is used for model tuning, and the test set is used for evaluating the performance of the model.The automatic detection technology of the application can help doctors improve the diagnosis efficiency and reduce the error, provide an important reference for clinical treatment and prognosis evaluation, and show significant clinical application value.

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 application belongs to the technical field of medicine, and discloses a method and system for detecting mucinous pancreatic cystic tumor, acquires a pancreatic cyst fluid sample; performs organoid culture on the pancreatic cyst fluid to obtain a mucinous pancreatic cystic tumor organoid; acquires cell morphology data of the mucinous pancreatic cystic tumor organoid; acquires H&E staining data and IHC detection data of the mucinous pancreatic cystic tumor organoid; acquires immunofluorescence detection data of the mucinous pancreatic cystic tumor organoid; performs scRNA-Seq sequencing on the mucinous pancreatic cystic tumor organoid to complete detection of the mucinous pancreatic cystic tumor; and the method can efficiently culture organoids and be used for verifying potential existence of malignant cells in function.

The application discloses a method for constructing a RP mouse model caused by Prpf6 gene mutation and haploinsufficiency and application thereof, and belongs to the field of molecular biology and biomedical technology. The mouse model constructed by the method provides a convenient, reliable and economical means for studying the relationship between the PRPF6 gene mutation and the retinal pigment degeneration disease and the pathogenic mechanism thereof, and provides a stable hereditary effective research model in the research of the pathogenic mechanism, treatment method and drug screening of RP. The animal model is subjected to transcriptome and a series of type detection, wherein the transcriptome result shows that the retina of the Prpf6 gene knockout mouse has a certain degree of metabolic abnormality, and the results of the electro-physiological detection, fundus examination and H&E staining show that the cell layer of the mouse retina and the shape and function of the retina are damaged, which is consistent with the disease phenotype of RP.

The invention provides a medicine for preventing or treating enteritis. Hamp is adopted; and E, dyeing, determination of IL-6 factors in serum of each group of animals and the like are used for researching the influence of the vocyclosporine on intestinal tissues, mucosal barriers and immune systems of DSS or TNBS-induced mouse colitis models. Experimental basis is provided for clinical application of the vocyclosporine in preparation of the colitis treatment medicine, and the vocyclosporine has good application prospects and huge potential value and social significance.

The invention discloses application of burdock polysaccharide in relieving motor ability decline and intestinal flora disorder caused by acute sleep deprivation, and belongs to the field of medical biology. The invention verifies the influence of the burdock polysaccharide on motor ability reduction, intestinal flora homeostasis and function reduction caused by acute sleep deprivation, and also verifies the relationship of the burdock polysaccharide on motor ability, body energy metabolism and intestinal flora of an acute sleep deprivation individual and a potential mediation mechanism of the burdock polysaccharide in an intestinal-muscle axis. According to the invention, burdock polysaccharide is used on an acute sleep deprivation model, and the application of burdock polysaccharide in treating motor ability and intestinal injury after acute sleep deprivation is verified. Through athletic ability, energy metabolism, inflammatory factors in serum, oxidative stress in liver and Hamp of ileum tissue; e staining, expression of tight junction protein and determination of indexes such as intestinal flora and the like find that the burdock polysaccharide can effectively improve the athletic ability and the intestinal flora after acute sleep deprivation.

The application discloses application of VK4 in preparation of a drug for treating leukemia, and belongs to the leukemia treatment field. The application research finds that VK4 can inhibit proliferation of leukemia cells through cycle arrest and induction of apoptosis, and VK4 can inhibit proliferation of HL60 cells and K562 cells through blocking of a JAK / STAT signal path. The results of Wright's staining, immunohistochemical staining and H&E staining of a mouse leukemia model show that VK4 also has an anti-leukemia effect in vivo, and has no obvious liver and kidney damage, and can provide a new drug selection for clinical treatment of leukemia.

The invention relates to the technical field of biological medicines, in particular to application of wild buckwheat rhizome freeze-dried powder in preparation of a medicine for preventing or treating antimony pneumoconiosis. A mouse antimony pneumoconiosis model is constructed by injecting an antimony (Sb) suspension into a trachea, and pulmonary fibrosis lesion caused by antimony exposure can be remarkably relieved by intragastric administration of the wild buckwheat rhizome freeze-dried powder prepared by the invention. Experimental results show that Hamp; e dyeing indicates that the freeze-dried powder can obviously relieve the fibrosis severity of the lung tissue; western Blot and PCR (Polymerase Chain Reaction) detection results show that the wild buckwheat rhizome can partially inhibit the expression up-regulation of Col-1 and alpha-SMA induced by antimony in protein and gene levels; in addition, the wild buckwheat rhizome can also obviously reduce the content of hydroxyproline in lung tissues. The results show that the wild buckwheat rhizome freeze-dried powder can effectively improve multiple pathological indexes and reduce the pulmonary fibrosis degree, has good potential in the aspect of preventing antimony pneumoconiosis, and has potential application value.

A rapid, label-free, non-destructive imaging method and system (100) for unprocessed biological tissue, which is based on microscopy with ultraviolet single plane illumination (MUSI). The present system (100) or method employs a selective two-axis planar illumination configuration, which decouples the illumination from the detection path, and utilize the intrinsic fluorescence of certain endogenous fluorophores from biological tissues as a natural source compared to deep UV illumination sources. In contrast to images produced by clinical standard methods (i.e. H&E staining of formalin-fixed and paraffin-embedded tissues), images generated by MUSI reveal comparable or even better diagnostic features, providing clinicians, pathologists, and surgeons with greater potential as post-operative and intra-operative diagnostic tools.

The application discloses a lung cancer gene mutation prediction method based on unsupervised clustering double-stage attention multi-instance learning, and relates to the technical field of pathological image analysis and gene detection. H&E staining pathological whole section images of non-small cell lung cancer patients and corresponding gene mutation data are collected to construct a data set; the images are preprocessed by using the OTSU method, segmented into blocks and high-dimensional feature vectors are extracted; the block features are grouped into cluster feature sets through unsupervised clustering; a double-stage attention mechanism composed of intra-cluster and inter-cluster is used to hierarchically aggregate and generate global features; finally, a classification model is used to output mutation positive / negative prediction results. The application groups the features through unsupervised clustering and structures the features, combines double-stage attention to strengthen key information, does not need complex manual annotation, adapts to various driver gene mutation prediction requirements, effectively deals with tumor heterogeneity and feature sparsity, improves prediction accuracy and generalization ability, and provides low-cost and efficient targeted therapy preliminary screening technical support for clinics.

The present application relates to the technical field of digital pathology analysis, and discloses a breast cancer chemotherapy prediction method based on pathology and spatial transcriptome anchor library, which acquires full-image, spatial transcriptome data, baseline clinical information and efficacy label in the training stage, maps transcriptome points to analysis areas corresponding to images, respectively extracts niche pathological morphology vector and molecular mechanism vector; constructs a pathological response anchor library based on morphology and molecular prototype, efficacy consistency and co-occurrence intensity; in the clinical reasoning stage, only needs to input patient's routine H&E staining full-image and clinical information, extracts regional pathological morphology vector, matches with anchor library morphology centroid, generates hit intensity, and then outputs response probability, drug resistance risk, scheme ranking, case evidence and mechanism prompt. The present application limits high-cost transcriptome detection to the library construction period, and does not need molecular detection as input in the reasoning period, so that low-cost and interpretable chemotherapy response evaluation can be realized.

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 discloses a model building method based on animal endometrial epithelium organoid and application of the model building method, and relates to the technical field of cell engineering and organoid. According to the method, healthy cow endometrial tissue serves as a raw material, a model is built through the steps of pretreatment, enzymolysis, cell cleaning and screening, seed gum culture, passage, cryopreservation resuscitation and the like, and the model is built through Hamp; e, verifying morphological integrity through dyeing, and detecting E-cadherin expression through IHC dyeing to confirm cell specificity. The animal organ model restores the in-vivo three-dimensional microenvironment and species specificity, overcomes the limitation of traditional two-dimensional culture and mouse models, can accurately simulate the pathological process of endometritis, is applied to research on the pathogenesis of endometritis of dairy cows, can also efficiently screen anti-inflammatory drugs and evaluate the drug effect, and has a wide application prospect. A reliable in-vitro tool is provided for disease prevention and treatment, and healthy development of the dairy cow breeding industry is assisted.

The invention belongs to the field of functional polymer materials, and particularly relates to a hydrogel nano material loaded with a photosensitizer and an epidermal growth factor and a preparation method of the hydrogel nano material. The preparation method comprises the following steps: preparing hydrogel nano particles NPs, loading a photosensitizer and preparing AIE-EGF-NPs nano particles. Compared with a pure antibacterial material, the product disclosed by the invention has better uniformity and dispersity, and has a better antibacterial effect compared with a traditional wound dressing. The product disclosed by the invention has good biocompatibility, and in a mouse full-thickness wound model infected by staphylococcus aureus, the hydrogel nanoparticles show an obvious function of promoting wound healing, so that wound infection is prevented. Furthermore, by means of Hamp; e, performing histological analysis on mouse organs by dyeing, and indicating that the hydrogel nanoparticles are a safe therapy for treating wound healing. Therefore, the hydrogel nanoparticles can greatly promote the healing process of the wound surface, and have potential application value in the field of biomedicine.

The application discloses a kind of H&E staining histopathological image cell nucleus segmentation and classification system, method, equipment and medium, system includes multi-task deep learning module, multi-task related attention mechanism module, cost-sensitive learning strategy module, two-step watershed algorithm post-processing module;The multi-task deep learning module is used to carry out cell nucleus semantic segmentation, instance segmentation and cell nucleus classification respectively;The multi-task related attention mechanism module is used to fuse the feature representation of cell nucleus segmentation module, cell nucleus instance segmentation module and cell nucleus classification module, to utilize global context information;The cost-sensitive learning strategy module is used to effectively solve the problem that the model performance is reduced due to the serious imbalance of the number of different cell types samples;The two-step watershed algorithm post-processing module is used to more accurately segment the cell nucleus with great difference in size and morphology.The application can realize H&E staining histopathology image cell nucleus segmentation and classification task.

The present invention provides a method for intelligently predicting the efficacy of PD-L1 inhibitors from gastric cancer H&E staining images. A cancerous region segmentation model based on semi-supervised learning is proposed to segment the cancerous regions in H&E staining images. Secondly, image patches containing cancerous regions are taken out, and the class labels of each image patch are obtained according to the efficacy labels of PD-L1 inhibitors marked by clinicians, and an image classification model based on multi-instance learning is used for prediction at the image patch level. Finally, an efficacy discrimination matrix for the entire H&E staining image is generated based on the prediction results at the image patch level, and an image classification model based on a deep convolutional neural network is used for efficacy prediction at the slice level. By applying this technical solution, the prediction results of the efficacy of PD-L1 inhibitors in gastric cancer patients can be obtained to assist doctors in making clinical decisions.

This invention discloses a spatial multi-omics sequencing method based on cross-modal generation, comprising the following steps: acquiring H&E staining images of tissue sample slices; automatically identifying and locating regions of interest (ROIs); manually cutting the tissue sample slices based on the ROIs and transferring them to a detection chip; acquiring a multi-omics expression matrix at single-cell resolution; extracting spatial feature anchor points that match the H&E staining images and the multi-omics expression matrix; performing coordinate transformation based on the coordinate mapping relationship of the spatial feature anchor points to achieve physical spatial dimension registration; and utilizing a cross-modal prediction model to perform spatial inference and full-sample information completion on discrete detection signals through spatial expression reconstruction methods. This invention effectively integrates high-precision local physical detection with global algorithm inference, ultimately outputting high-fidelity multi-omics expression information containing the entire tissue sample, completing cross-scale completion from local targeted detection to full-sample multi-omics.

The invention provides a three-level lymph structure spatial heterogeneity-based tumor prognosis evaluation method and system. The evaluation method comprises the following steps: S1, obtaining a tumor tissue Hamp; e, dyeing the section, and generating a full-section image through digital scanning; s2, identifying a T region and a P region in the full-slice image; s3, marking contour boundaries and GC regions of all TLSs on the full slice image, and counting the hair growth center area ratio GTR of each TLS, GTR = (GC area / TLS area) * 100%; s4, calculating the GTR arithmetic mean value of all the TLSs in the T region as a T score, and calculating the GTR arithmetic mean value of all the TLSs in the P region as a P score; and S5, generating a composite M score through a formula M = 0.777 * T score-0.443 * P score. According to the tumor prognosis evaluation method based on the spatial heterogeneity of the three-level lymphatic structure, only conventional Hamp is needed; the complex immunohistochemistry is replaced, the detection cost is reduced, the detection period is shortened, and the limitation that TLS is regarded as a homogeneous structure in the prior art is broken through.

The invention discloses a chicken fatty liver syndrome grading method based on oil red O staining, belongs to the technical field of poultry genetic breeding, and is used for efficiently and quantitatively grading the severity of chicken fatty liver syndrome. The method comprises the following steps: firstly, performing paraffin section Hamp on liver tissue; and E, identifying whether the high-fat hens and the low-fat hens suffer from the fatty liver syndromes or not by a staining method, and grading the severity of the diseases. Then, Hamp is used; and respectively analyzing the ranges of oil red O staining quantitative liver fatty degeneration degrees corresponding to different fatty liver syndrome grades of the high-fat hens and the low-fat hens by taking the E staining chicken fatty liver syndrome grading result as a reference, and establishing an oil red O staining chicken fatty liver syndrome grading standard. According to the method, the severity of the chicken fatty liver syndrome can be rapidly and quantitatively graded, and reference is provided for related research.

The invention provides application of tilianin in preparation of a medicine for preventing and treating femoral head necrosis, relates to the technical field of new application of medicines, and is technically characterized by providing application of tilianin in preparation of a medicine for treating steroid-induced femoral head necrosis. A rat steroid-induced femoral head necrosis model induced by LPS and large-dose glucocorticoid is adopted, and the treatment effect of tilianin on rat steroid-induced femoral head necrosis is observed. Carrying out three-dimensional analysis on the femoral head after Micro-CT scanning, and applying Hamp; the E staining is used for carrying out histopathologic analysis on femoral head tissues, and the treatment effect of tilianin on steroid-induced femoral head necrosis of rats is proved. In addition, SD rat BMSC is extracted, and the promoting effect of tilianin on osteogenic differentiation is further analyzed in vitro. Animal and cell experiments prove that tilianin can relieve the inhibition effect of glucocorticoid on femoral head bone tissues, and tilianin can effectively promote bone formation and improve osteogenesis activity of osteoblasts, so that the degree of femoral head necrosis is relieved, and a new way is provided for medicine prevention and treatment of steroid-induced femoral head necrosis.

The invention belongs to the technical field of tumor phototherapy, and particularly relates to a novel photosensitive molecule with phototherapy activity and preparation and application thereof. The novel photosensitive molecule has a structure as shown in a formula (I), is constructed by methylating a three-arm thiophene-formaldehyde skeleton in one step, is mild in synthesis condition, and is obviously superior to similar structures in yield. The novel photosensitive molecule is positioned in mitochondria and can trigger PDT and PTT at the same time under excitation of visible light, and dependence on high-power or near-infrared laser is reduced. It has been shown that the novel photosensitive molecule can effectively inhibit tumor cell proliferation and induce apoptosis after being illuminated in vitro, and can also significantly inhibit tumor growth in vivo; and E dyeing shows that the compound has no obvious toxicity to main organs and has good biological safety. The novel photosensitive molecule disclosed by the invention is simple to synthesize and high in preparation yield, has the characteristic of integration of visible light response and diagnosis and treatment, and meets the urgent clinical requirements on efficient, accurate and safe phototherapy medicines.

The invention discloses a virtual immunohistochemical staining method, device and equipment for a tissue slice and a medium, and relates to the field of computational pathology counting. E, constructing a cell map from the dyed image to generate corrected IHC semantic features of each node; generating a history Hamp by using an image generator; e, dyeing a historical virtual IHC image corresponding to the image; using the historical real IHC image and the historical virtual IHC image to optimize the parameters of the double-branch discriminator; optimizing image generator parameters by using a discrimination result of the historical virtual IHC image output by the discriminator, the corrected IHC semantic features and semantic features in the historical virtual IHC image to obtain a new image generator network, and performing optimization for multiple times to obtain a target image generator; outputting the Hamp of the tissue section to be dyed by using the generator; and E, dyeing the target virtual IHC image of the image. And performing virtual IHC with clear texture and accurate pathological features on the tissue slices.

Tumor budding (TB) is defined as a cluster of one to four tumor cells at the tumor invasive front. Though promising as a prognostic factor for colorectal cancer, its routine clinical use is hampered by high inter-and intra-observer disagreement on routine H&E staining. Therefore, automated methods are provided that minimize the inter-and intra-observer disagreement for tumor bud detection on images of H&E-stained tissue sections.

The invention relates to the technical field related to medical medicines, discloses application of glycyrrhizic acid in inhibiting ototoxicity caused by cis-platinum chemotherapy, and aims to provide novel medical application of glycyrrhizic acid, namely the glycyrrhizic acid can be used for reducing ototoxicity side effects caused by CDDP. After a C57BL6 / J mouse is administered according to a model, ABR waveform of a CDDP group mouse is disordered, a hearing threshold is obviously increased, and an I-wave incubation period is prolonged; after the GL is given to the mouse, ABR waveform differentiation of each frequency is good, the hearing threshold value is obviously reduced, and the I-wave incubation period is shortened. Hamp, Hamp; e staining results show that CDDP destroys the morphological structure of cochlear vascular lines, resulting in cytoplasm reduction, vacuole increase, cell nucleus fixation and constriction and boundary fuzziness; the GL intervention enables the whole cytoplasm of the cochlea vascular lines of the mouse to be fuller, the vacuoles to be obviously reduced, the cell nucleus to be complete and the boundary to be clearer, which indicates that the GL inhibits the cochlea vascular line injury caused by the CDDP. EB staining finds that red fluorescence in the CDDP group microvessels is weak, and a large amount of EB exudes, which prompts that the permeability of BLB is increased.

Disclosed herein is an improved system and methods implemented by the system for training a model that capable of identifying a hormone receptor status of a subject via the whole slide images (WSIs) of hematoxylin and eosin (H&E) stain of his / her biopsies. The method comprises steps of: (a) obtaining multiple WSIs having known hormone receptor information; (b) dividing each of the WSIs into a plurality of patches; (c) selecting and combining the patches that express the abnormal H&E stain into a combined image; and (d) training a plurality of combined images independently with the aid of the known hormone receptor information of the WSIs, thereby constructing the model. Also disclosed herein is a method for identifying a hormone receptor status of a subject by using the method and model implemented in the present system.