2352 results about "Hepatocyte" patented technology

The invention provides a multi-modal large language model for generating a hepatocellular carcinoma key pathological diagnosis report, a framework main body is a visual coding module, and a multi-modal feature alignment module, a multi-head low-rank attention mechanism, an enhanced medical MoE mechanism and a structured output decoding layer are also introduced. The visual coding module is constructed on the basis of a Swin Transform architecture, visual pre-training is completed on hepatocellular carcinoma MRI data, and after a task specific classification head is stripped, a trunk feature extraction network is reserved to serve as an image modal representation encoder. The multi-modal feature alignment module guides the model to learn a cross-modal semantic mapping relation between a hepatocellular carcinoma MRI image and a key pathological diagnosis report language, image modal input is a visual feature sequence, and text modal output is a structured description text; and the structured output decoding layer generates six types of liver cancer focus attributes. According to the method, the pre-operative multi-parameter and multi-stage enhanced MRI image is utilized, and the open-source large model is finely adjusted to generate a matched liver cancer postoperative pathology report.

The invention discloses a preparation method and application of fresh dendrobium officinale refined polysaccharide, and the preparation method of the fresh dendrobium officinale refined polysaccharide comprises the following steps: adding a proper amount of water into fresh dendrobium officinale, juicing, concentrating filtrate, adding ethanol for alcohol precipitation, dissolving precipitate with water, deproteinizing, and drying to obtain crude polysaccharide; the crude polysaccharide is subjected to graded alcohol precipitation and ion exchange column purification to obtain semi-refined polysaccharide, the semi-refined polysaccharide is purified by a gel column to obtain the fresh dendrobium officinale refined polysaccharide, and the polysaccharide is acidic glucomannan which is high in purity, uniform and moderate in molecular weight and contains beta-configuration pyranoside. In-vivo and in-vitro activity tests show that the compound polysaccharide has exact curative effects of preventing drunkenness, dispelling the effects of alcohol and preventing stomach injury and hepatocyte injury, is prepared by compounding the compound polysaccharide with traditional Chinese medicines of radix puerariae, hovenia dulcis thunb and tomato seed oil, and has the effect of obviously enhancing the immunity of liver functions.

The invention discloses an image segmentation method for evaluating a hepatocellular carcinoma neutron therapy dose, and relates to the technical field of neutron therapy. A 3D U-Net GAN network model is trained through a medical image data set; a generator model and a discriminator model in a 3D U-Net GAN network model are alternately trained by using a real image and a false image randomly generated by the generator model, so that the trained generator model can generate a segmentation result which is more accurate and rich in details for a medical image; the trained discriminator model can more accurately evaluate the authenticity of the output of the generator model, and the trained network can accurately reflect the anatomical structure of the patient, the distribution condition of 10B in the body and the radionuclide dynamics condition when segmenting the medical image, so that the information in the medical image can be accurately and fully displayed, and the medical image segmentation efficiency can be improved. The application is convenient.

The invention discloses a hepatocellular carcinoma pathological micro-necrosis recognition system and method based on federal continuous learning. The method comprises the following steps: firstly, obtaining time sequence image data of a multi-center full-size hepatocellular carcinoma tumor pathological section; performing foreground segmentation on the image data, removing a non-tumor background region, and generating a classification task-oriented standardized image block group; then, after each round of training is completed, the local model weight of each center is uploaded to a server, the server calculates the global weight according to the data scale of each center by adopting a weighted average strategy based on the data sample size, and the global weight is distributed to all participating centers for model iteration; a timing sequence sensitive regularization constraint is designed, and the weight updating strength of local training of each center is dynamically adjusted; and finally, comprehensively calculating the cross entropy loss and the proportion label fitting loss of the image block classification task, and the regular term loss in the model iteration process.

The invention belongs to the technical field of biological medicines, and provides application of DRAM1 as a diagnosis and treatment target for resisting non-alcoholic fatty liver disease related hepatocellular carcinoma in preparation of a kit, a carrier and a medicine aiming at the problem of lack of effective treatment targets of NAFLD-related HCC. As a target spot for resisting the non-alcoholic fatty liver disease related hepatocellular carcinoma, the expression level of the DRAM1 in liver tissues of non-alcoholic fatty liver disease related hepatocellular carcinoma patients and mice is increased. According to the application disclosed by the invention, research is developed aiming at the effect of the DRAM1 in the generation and development of NAFLD-related HCC, the analysis of TCGA liver cancer queue data and a GSE164760 data set is taken as an entry point, the influence of the DRAM1 on the diagnosis and prognosis of the liver cancer is comprehensively analyzed, and verification is carried out through a mouse in-vivo experiment, so that a new thought and a new target spot are provided for clinical diagnosis and treatment of the liver cancer.

Described are RNAi agents, compositions that include RNAi agents, and methods for dual inhibition of an Apolipoprotein C-III (APOC3) and Proprotein Convertase Subtilisin Kexin 9 (PCSK9) gene. The APOC3-PCSK9 RNAi agents disclosed herein inhibit the expression of an APOC3 and a PCSK9 gene. Pharmaceutical compositions that include one or more APOC3-PCSK9 RNAi agents, optionally with one or more additional therapeutics, are also described. Delivery of the described TSLP RNAi agents to hepatic cells, in vivo, provides for inhibition of APOC3 and / or PCSK9 gene expression, which can provide a therapeutic benefit to subjects, including human subjects, for the treatment of various diseases including hypertriglyceridemia and hypercholesterolemia.

The invention provides an application of an active peptide in preparation of a medicine for preventing and treating ALD (Atomic Lymphosis Disease). The amino acid sequence of the active peptide is shown as SEQ ID NO: 1, the active peptide can effectively relieve damage of ethyl alcohol to liver cells, increase of glutamic-pyruvic transaminase activity, lactic dehydrogenase activity and malondialdehyde content and decrease of glutathione content caused by ethyl alcohol can be remarkably inhibited, then the preventing and treating effect on ALD is achieved, and the active peptide is suitable for preparing drugs for preventing and treating ALD and has a good application prospect. Meanwhile, an active peptide resource library with ALD prevention and treatment effects is also enriched.

The invention relates to the technical field of treatment of chronic diseases of old people, and discloses a metabolic characteristic-based medicine dosage optimization method for chronic diseases of old people. The method comprises the following steps: acquiring drug metabolism parameters (including a plasma concentration peak value, a half-life period curve and the like) and organ function data (including a hepatocyte metabolism rate, a glomerular filtration rate and the like) of a plurality of monitoring nodes, arranging the drug metabolism parameters and the organ function data into a time sequence input vector, and extracting a dynamic feature vector by using a time convolution network and an adaptive filter network; performing feature crossing, pharmacokinetic constraint correction and feature enhancement processing, performing fusion to generate a joint feature vector, inputting the joint feature vector into a dose decision model to obtain an adjustment coefficient, and generating a drug dose interval with a safety threshold in combination with a historical drug use record. According to the method, multi-dimensional data integration and dynamic modeling are realized, the accuracy and safety of chronic disease medication of old people are improved, and the method is suitable for individualized treatment.

The present disclosure relates to RNAi agents, e.g., double stranded RNAi agents such as siRNAs, able to Inhibin Subunit Beta E (INHBE) gene expression. Also disclosed are pharmaceutical compositions that include INHBE RNAi agents and methods of use thereof. The INHBE RNAi agents disclosed herein may be conjugated to targeting ligands to facilitate the delivery to cells, including to hepatocytes. Delivery of the INHBE RNAi agents in vivo provides for inhibition of INHBE gene expression. The RNAi agents can be used in methods of treatment of diseases, disorders, or symptoms mediated in part by INHBE gene expression, such as obesity, diabetes, liver inflammation, dyslipidemia, or metabolic disease.

The invention relates to the field of biological medicine, in particular to application of hispidulin in preparation of a lipid de novo synthesis inhibitor or a metabolism-related fatty liver disease treatment or prevention product. The hispidulin disclosed by the invention has a chemical structure as shown in a formula (I). The hispidulin in the invention reverses liver cell lipid droplet excessive infiltration induced by high-dose fructose in a dose-dependent manner; furthermore, the hispidulin dose-dependent ameliorating obesity signs in HFD-induced MAFLD model mice, including liver weight, body weight, blood lipid level, liver fat content, and insulin resistance, without significantly reducing food intake.

The invention relates to the technical field of artificial intelligence precision medical treatment, in particular to a multi-mode hepatocellular carcinoma recurrence risk prediction method and system and application, and the prediction method comprises the steps of multi-mode data acquisition, data standardization preprocessing, model training and recurrence risk prediction. The method comprises the following steps: firstly, collecting multi-modal data of a patient, wherein the multi-modal data comprises preoperative data, postoperative data and a recurrence risk label; secondly, carrying out standardized preprocessing on the collected multi-modal data; and updating parameters of the pre-operation model and the post-operation model by using an adaptive moment estimation algorithm to obtain a trained multi-modal hepatocellular carcinoma recurrence risk prediction model which comprises the pre-operation model and the post-operation model and can be used for performing recurrence risk prediction before and after an operation respectively. According to the method, the deep learning technology is used, the multi-modal data before and after the operation can be respectively utilized, the recurrence risk of the HCC patient can be accurately predicted before and after the operation, and a targeted treatment scheme is formulated for the HCC patient.

The method and system for evaluating the curative effect of hepatocellular carcinoma based on immune microenvironment characteristics are high in accuracy and reliability of evaluating the curative effect of hepatocellular carcinoma. The method comprises the following steps: (1) preparing a sample; (2) carrying out multiple immunohistochemical staining; (3) image acquisition and analysis; (4) analyzing spatial distribution characteristics; (5) multiplying the input image voxel signal numerical value by the weight vector of the convolution kernel, transmitting the multilayer convolution kernel, and finally obtaining a calculation result output by each network; and (6) establishing a prediction model: based on the spatial distribution characteristics and clinical characteristics of immune cells, constructing the prediction model by using the positive rate of CD8 + PD-L1 + and CD103 + CD8 + cells in the total area and the number of CD103 + cells within 30 microns around tumor cells so as to predict the immunotherapy curative effect of the HCC patient.

The invention provides camel milk active peptide and application thereof in preparation of drugs and edible products for treating and / or preventing diabetes mellitus. Two polypeptide compounds are obtained from papain enzymolysis products of fresh camel milk. Bioactivity evaluation shows that the polypeptide compound has remarkable protein tyrosine phospholipase 1B (PTP1B) inhibitory activity, can enhance insulin receptor sensitivity and promote hepatocyte glucose uptake, has patent medicine potential in the aspect of treating type II diabetes, and can be used for preparing medicines for treating type II diabetes. And a new material basis is provided for developing innovative medicines for treating type II diabetes and developing innovative PTP1B inhibitor hypoglycemic medicines.

The invention provides a hypoglycemic peptide which is prepared by taking bovine whey protein as a raw material and is stable in gastrointestinal digestion and absorption. In an in-vitro cell experiment, the peptide fragment can improve the uptake of insulin-resistant HepG2 hepatocytes and synthesize glycogen by using glucose, can promote intestinal endocrine cells NCI-H716 to secrete GLP-1, has a certain synergistic effect, and can further play the effects of promoting GLP-1 secretion and activating a GLP-1 receptor through combined use. An insulin resistance mouse model is constructed by utilizing high-fat diet, and the peptide fragment is adopted for intervention, so that the hypoglycemic peptide is further proved to have obvious effects on losing weight, reducing lipid accumulation and assisting in reducing blood fat, and meanwhile, the hypoglycemic peptide can be used for improving insulin resistance related symptoms. The milk peptide provided by the invention has gastrointestinal digestion stability and hypoglycemic activity, can be used as a functional milk base material for developing food, medicines or health care products with the effect of regulating blood sugar, and is wide in application prospect.

The present invention the invention concerns bifunctional compounds of Formula (I) A-T-L1-AG, Formula (II) A-L1-Con(L2-AG)n or Formula (III) Ak´-Th-L3 ii-AGj' wherein A is a protein that binds to the hinge region of galactose deficient IgA1 antibodies or a protein that binds to autoantibodies of galactose deficient IgA antibodies and AG is an asiaglycoprotein receptor binding moiety (ASGPR binding moiety). L1, Con and L2 are part of a linker between A and AG. The A has the ability to bind to antibodies that are a cause of IgA nephropathy and the asiaglycoprotein receptor binding moiety binds to hepatic cells thereby initiating endocytosis and removal of the antibodies that are a cause of IgA nephropathy from the blood stream.

The present invention discloses the application of a molecular marker methylation level detection reagent for primary hepatocellular carcinoma in the preparation of a detection reagent product, and belongs to the field of gene detection technology. By screening the methylation level of the CpG site in the detected region and its reverse complementary sequence, it is identified whether the target sample is from a primary hepatocellular carcinoma patient. The methylation level of the CpG site in the above region has good sensitivity and specificity for the screening or auxiliary diagnosis of primary hepatocellular carcinoma, and can be used to distinguish samples from patients with primary hepatocellular carcinoma, samples from patients with benign liver diseases (cirrhosis, hepatitis, etc.) and samples from healthy people. The detection reagent and application of the methylation level of the molecular marker can improve the detection rate of early primary hepatocellular carcinoma.

The present disclosure related to compounds that can be useful as inhibitors of PD-1, PD-L1 or the PD-1 / PD-L1 interaction. Also disclosed herein are pharmaceutical compositions of that can include a compound of Formula (I), or a pharmaceutically acceptable salt thereof, and uses of or methods of using a compound of Formula (I), or a pharmaceutically acceptable salt thereof, for the treatment of PD-L1 related diseases including but not limited to liver diseases, cancer, hepatocellular carcinoma, viral diseases, or hepatitis B.

The invention relates to the field of food and health care products, and discloses a composition for dispelling effects of alcohol and protecting liver, which comprises 20-100 parts of ampelopsis grossedentata leaf extract; 50 to 200 parts of a radix puerariae extract; 10-50 parts of a semen hoveniae extract; 10-50 parts of a turmeric extract; 10 to 100 parts of a yeast extract; 5-50 parts of a licorice extract; and 5 to 20 parts of pyrroloquinoline quinone disodium salt. The ampelopsis grossedentata leaf extract, the kudzuvine root extract and the hovenia dulcis thunb extract are utilized, alcohol decomposition is promoted, the blood ethanol concentration is reduced, and drunkenness symptoms are relieved. Puerarin improves activity of liver metabolic enzymes, accelerates discharge of ethanol and acetaldehyde, and reduces liver damage. The anti-oxidation effects of dihydromyricetin and PQQ can eliminate alcohol metabolism free radicals and protect liver cells. The components such as puerarin, hovenia dulcis thunb, curcumin and glycyrrhizic acid jointly promote liver cell regeneration, inflammation and oxidative damage are reduced, the levels of ALT and AST in serum are reduced, and liver health is maintained.

The invention belongs to but is not limited to the technical field of biomedicine, and discloses application of golden amide alcohol ester to preparation of a medicine for treating cholestasis. The in-vitro cell level verifies that the golden amide alcohol ester has relatively strong activity of activating FXR and CAR. The golden amide alcohol ester can relieve the cholestasis symptom of a cholestasis model mouse. The golden amide alcohol ester can obviously reduce the content of total bile acid and bilirubin in cells, relieve cholestasis and relieve hepatocyte damage. The golden amide alcohol ester can regulate and control the protein level of transporters and metabolic enzymes related to bile acid and bilirubin through double excitation of FXR and CAR, relieve cholestasis and achieve the purposes of benefiting gallbladder and removing jaundice.

The present invention relates to a use of benzethonium chloride in preparing a drug for improving or treating non-alcoholic fatty liver disease, and relates to the technical field of new uses of products. The present invention discovers for the first time a new use of benzethonium chloride for improving or treating non-alcoholic fatty liver disease. Benzethonium chloride can reduce hepatocyte lipid deposition and regulate hepatocyte lipid metabolism disorder by intervening in a cell lipid deposition model; it can improve liver lipid accumulation in mice caused by lipid metabolism disorder by administering through the digestive tract, and can improve liver coefficient, liver function, hepatic lobular inflammation, and liver fibrosis. The benzethonium chloride of the present invention can be used for the preparation of drugs for improving or treating non-alcoholic fatty liver disease. The benzethonium chloride of the present invention can inhibit the expression of human apolipoprotein C3, thereby reducing the generation of lipids, and is applied to drugs for treating non-alcoholic fatty liver disease, opening up a new use of benzethonium chloride and providing a new drug option for treating non-alcoholic fatty liver disease.

The invention relates to the technical field of stem cell injections, in particular to a human umbilical cord mesenchymal stem cell injection and a preparation method thereof. The cell cryoprotectant comprises the following components: a cell cryoprotectant and P6-generation human umbilical cord mesenchymal stem cells. By selecting P6-generation human umbilical cord mesenchymal stem cells, the capacity of secreting hepatocyte growth factors (HGF) can be improved; the cell cryoprotectant contains 6-9wt% of dimethyl sulfoxide and a certain amount of human serum albumin, can better protect cells and maintain the motility rate and biological functions of the cells, and is more beneficial to preparation of cryopreserved human umbilical cord mesenchymal stem cell injection. The P6-generation human umbilical cord mesenchymal stem cells are obtained by culturing a culture medium containing fetal calf serum, and the ability of the injection to repair liver injury can be improved.

The invention discloses a hepatocellular carcinoma postoperative early recurrence prediction method based on multi-modal fusion. The method comprises the following steps: firstly, integrating clinical data of a training set, a preoperative enhanced CT image and a postoperative full-view digital pathological image, and carrying out standardized correction; then, traditional image omics features and deep learning features are extracted from the CT image, cell nucleus morphological features and tumor microenvironment spatial configuration features are extracted from the pathological image, and key feature signatures are screened out through a maximum correlation minimum redundancy algorithm (mRMR) and LASSO regression in combination with clinical features. And then carrying out progressive model construction by adopting an XGBoost algorithm, sequentially establishing a clinical single-mode model, an image single-mode model, a pathological single-mode model and a multi-mode fusion model, and explaining and visualizing the models by utilizing an SHAP value and a Grad-CAM technology. Finally, the performance of the model is evaluated in a multi-dimensional mode through internal cross validation, foresight and external independent validation, risk layering is carried out based on the prediction probability, and individualized postoperative management is guided.

The invention provides an application of a CXCR6 + PDCD1 + TOX + T cell in predicting the curative effect of hepatocellular carcinoma immunotherapy. In particular, the present invention provides a new depleted T cell subset, called TEX3 cells (CXCR6 + PDCD1 + TOX + T cells). In HBV + HCC, the TEX3 cells become an effective tumor killer. In addition, the TEX3 cell shows that the TEX3 cell obviously interacts with macrophages rich in CXCL9 and PD-L1 in HBV + HCC, a stronger immunosuppression tumor environment is shown, and the TEX3 cell obviously exists in a patient, so that the TEX3 cell shows an obviously better treatment effect.

The invention discloses a diagnosis model for hepatocellular carcinoma microvascular invasion and a construction method and application thereof, and belongs to the technical field of medical examination. Metabolite in the blood of a hepatocellular carcinoma patient is taken as a cut-in, preoperative clinical tumor indexes are combined, it is found that PIVKA-II, GGT, L-Serine, Sarcosine and tumor sizes have important significance on formation of hepatocellular carcinoma MVI, a diagnosis model based on multiple omics and multiple dimensions is established based on the diagnosis indexes, the diagnosis model is used for diagnosis of the preoperative MVI of the hepatocellular carcinoma patient, and the diagnosis model is used for diagnosis of the preoperative MVI of the hepatocellular carcinoma patient. The defects of existing diagnosis means in the aspect of preoperative diagnosis are overcome, and a more timely and accurate basis is provided for clinical decision making.

The invention relates to the technical field of bioinformatics analysis, in particular to an enhanced CT image-based hepatocellular carcinoma postoperative early recurrence multi-modal prediction model and a construction method thereof, and the construction method comprises the following steps: S1, data acquisition: collecting clinical data and liver enhanced CT images of a hepatocellular carcinoma surgical patient, and evaluating the recurrence condition of the HCC patient; s2, image preprocessing: sketching a region of interest in the image, and extracting deep learning features; s3, establishing a model: establishing a plurality of image omics models, constructing a plurality of deep learning models, and constructing a multi-modal model; s4, evaluating and verifying the model: evaluating the prediction accuracy of the multi-modal model by adopting an ROC curve and an AUC value, and evaluating the prognosis prediction capability of the patient by using a Kaplan-Meier curve; according to the method, the characteristic expression ability and the recurrence risk discrimination performance are improved, a scientific basis can be provided for follow-up visit and treatment of the hepatocellular carcinoma postoperative patient, and the lifetime of the patient is prolonged.

The invention relates to a gadolinium-doped carbon dot complex based on liver cancer cell membrane coating and a preparation method of the gadolinium-doped carbon dot complex. The gadolinium-doped carbon dot complex is prepared on the basis of gadolinium-doped carbon dots Gd-CDs which are prepared from indocyanine green, citric acid, polyethylene glycol and gadolinic acid through a one-step microwave thermal method and have fluorescence-magnetic resonance bimodal imaging capacity. The Gd-CDs complex Gd-CDs coated HCM is placed in a cell membrane suspension extracted from human hepatoma carcinoma cells HepG2, and the Gd-CDs complex Gd-CDs coated HCM which is uniform in particle size and has the capacity of photothermal and immunotherapy of hepatocellular carcinoma is obtained through extrusion construction of a liposome extruder. The Gd-CDs (at) HCM complex constructed by the invention not only has good bimodal imaging ability, but also has a specific inhibition effect on liver tumor cells, can be applied to preparation of drugs for inhibiting the growth of the liver tumor cells, and realizes a good treatment effect on liver cancer at a nanometer level.

The invention discloses a human-derived iPSC (induced pluripotent stem cell)-induced liver organ and a preparation method thereof. The method comprises the following steps: digesting human induced pluripotent stem cells obtained by culture into single cells; single cells are prepared into cell clusters through self-balling, or cell matrigel microspheres are prepared by using a T-type microfluidic technology and then are distributed one by one, so that one cell cluster is formed in each pore of the low-adsorption 96-pore plate; carrying out step-by-step induction culture on the obtained cell cluster, and culturing in a culture medium I for 5 hours; replacing with a culture medium II and culturing for 2 days; a culture medium III is used for culturing for 2 days; replacing with a culture medium IV and culturing for 5 days; replacing with a culture medium V, and culturing for 6 days; and replacing with a culture medium VI, and culturing for 10 days to obtain the mature human liver organ. According to the invention, liver organs with human normal liver cell characteristics and protein expression can be formed within 25 days, and the method can realize homogenization and high efficiency of iPSC induction.

The invention discloses a construction method of a risk prediction model for early diagnosis of liver cancer. The construction method of the risk prediction model comprises the following steps: 1, preparing clinical data; 2, processing, analyzing and learning clinical data, and constructing a project database of a hepatocellular carcinoma clinical diagnosis path based on big data; 3, determining main diagnosis key points in the disease timing sequence diagnosis scheme and related indexes influencing the operation, and formulating a diagnosis and treatment path extraction rule; 4, constructing a quality-efficiency evaluation index system for the diagnosis and treatment path set, and calculating the early diagnosis probability and postoperative recurrence probability of the liver cancer; and 5, establishing a Markov model for early screening and diagnosis of liver cancer and risk prediction of postoperative recurrence. According to the method, the ANN principle is utilized, an HCC early diagnosis risk prediction model and an HCC clinical diagnosis and treatment path evaluation system are established, HCC high-risk groups are subjected to early recognition, and the HCC early diagnosis rate is increased; meanwhile, an optimal clinical diagnosis and treatment decision is provided for HCC treatment.

The present invention provides a multi-modal model construction method and system for predicting the efficacy of sorafenib in hepatocellular carcinoma. The method comprises: step 1, collecting clinical information of a target patient, and generating a whole slide image; step 2, preprocessing clinical data, and retaining clinical features as input for a multi-modal deep learning model; step 3, preprocessing the whole slide image; step 4, constructing an image model, acquiring patch-level scores of the pathological image on the basis of the preprocessed image and by using different aggregation algorithms, and predicting the score of the whole pathological image to obtain best model features; step 5, constructing a multi-modal model, performing modal fusion on the best model features and the clinical features, and outputting an image-level or patient-level prediction result; and step 6, testing and evaluating the model. The present invention achieves bimodal input of a pathological image and clinical information, fully utilizes the complementarity of the two types of modal data, and thus improves prediction accuracy.