1672 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 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 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 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 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 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 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 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 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 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 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.

The invention provides a detection method of an end face integrated reflection type SPR optical fiber biosensor manufactured based on a 2PP technology. An experiment system mainly comprises a single-mode optical fiber, an optical fiber coupler, an SPR probe, a tungsten lamp light source, a sample pool, a spectrum analyzer and a computer. The method is characterized in that a volcanic three-dimensional microstructure is directly constructed on the end face of a single-mode fiber through a 2PP technology, a metal film with the thickness of about 50nm is deposited on the inner wall of the volcanic three-dimensional microstructure, and a stable and efficient SPR excitation structure is formed; the structural parameters are subjected to FDTD simulation optimization design, and have the characteristics of high quality factor and high sensitivity. The sensor can be used for AFP detection, the sensitivity reaches 0.684 nm / (ng / mL) within the linear range of 0-10 ng / mL, the normal and risk early warning concentration interval of human serum AFP is covered, and the sensor has good biological suitability and early hepatocellular carcinoma screening capacity; in addition, the probe structure is small in size, detection can be completed only by a few microliters of liquid to be detected, and the probe is suitable for a microfluidic platform with an extremely low sample size or a clinical sampling scene. Compared with the prior art, the device has the advantages of high structural integration, high sensitivity, low sample consumption, convenience in manufacturing, stability, reliability and the like.

The invention relates to a hepatocellular carcinoma gene knockout target library based on multiple omics and a screening method of the hepatocellular carcinoma gene knockout target library, and the gene knockout target library for precise treatment of hepatocellular carcinoma is finally obtained through data collection and integration, data screening and target verification in sequence. According to the invention, through multi-omics data integration and bioinformatics analysis, key driving genes of hepatocellular carcinoma are systematically screened, and the important effects of the genes in occurrence, development, metastasis, drug resistance and immune escape of hepatocellular carcinoma are disclosed; the genes not only deepen the understanding of the hepatocellular carcinoma molecular mechanism, but also provide important theoretical basis and potential intervention targets for the development of targeted therapy and personalized therapy strategies.

The invention belongs to the technical field of biomedicine, and particularly relates to application of ceramide as a marker in prediction of hepatocellular carcinoma microvascular invasion risk. The invention finds that the preoperative plasma ceramide CER (d18: 1 / 16: 0) level can be used for predicting the MVI of HBV-HCC patients and evaluating the postoperative prognosis of the patients for the first time. The invention provides a preoperative non-invasive detection method based on plasma ceramide CER (d18: 1 / 16: 0), and trauma of traditional histopathology detection is avoided. According to the method, the occurrence risk of the MVI can be effectively reduced by simply detecting a blood sample of a patient. According to the method, the MVI risk of a patient is evaluated through a multi-factor prediction model, and a basis is provided for personalized treatment. The method is not only suitable for preoperative MVI risk assessment, but also can assist in making postoperative follow-up visit and treatment plans, and helps to reduce the postoperative recurrence rate and improve the survival rate of patients.

The invention discloses application of an Aurora-A kinase inhibitor combined with dorafenib in preparation of a medicine for treating hepatocellular carcinoma, and relates to the technical field of medicines. The Aurora-A kinase inhibitor is Alisertib, and the Aurora-A kinase inhibitor is Alisertib. The dorafenib pharmaceutical composition has the beneficial effects that the dorafenib and the Aurora-A inhibitor Alisertib are jointly applied to form the pharmaceutical composition, so that a remarkable synergistic anti-tumor effect is achieved; to a certain extent, the problem of drug resistance during single-drug treatment is effectively solved; moreover, the pharmaceutical composition can achieve a remarkable anti-tumor effect at a relatively low dosage, and the dosage demand when a single drug is used is reduced, so that the potential toxic and side effects are reduced, and the pharmaceutical composition has a good clinical application prospect.

The invention discloses a preoperative risk stratification system based on hepatic resection after transformation treatment in the technical field of biomedicine, and the system comprises a sample module which is used for selecting a proper hepatocellular carcinoma patient as a sample, distributing the patient sample to a training queue and an internal verification queue, and building an external verification queue; the treatment module is used for providing a treatment strategy for the patient based on whether liver resection is performed or not after conversion treatment; the tracking module is used for carrying out regular follow-up visit on the patient subjected to the liver resection or not subjected to the liver resection after the conversion treatment; and the data analysis module is used for determining prediction factors related to recurrence-free survival in the training queue by adopting a minimum absolute contraction and selection operator regression analysis method, further analyzing and screening out independent prognosis factors through multivariable Cox regression, and constructing a column graph based on the factors to predict the postoperative recurrence rate. Through verification of the internal and external verification queues, the method can effectively guide and select a patient who is most likely to benefit from the liver resection operation after transformation treatment.

The invention relates to the technical field of biological medicines, in particular to application of an EIF3A inhibitor in preparation of a medicine for treating hepatic fibrosis. The EIF3A inhibitor relieves the hepatic fibrosis process by inhibiting EIF3A expression of hepatic tissue, relieving endoplasmic reticulum stress, inhibiting an NF-kappa B inflammation pathway and reducing pathological damage of hepatic cells, and the EIF3A inhibitor can be selected from a medicine for knocking down or knocking out EIF3A, a medicine for inhibiting EIF3A protein synthesis or a medicine for promoting EIF3A protein degradation. New mechanism research is provided for occurrence and development of hepatic fibrosis, hepatic cell damage and inflammation can be relieved through targeting EIF3A, hepatic fibrosis related pathological phenotypes are relieved, the protection and treatment effects are achieved, safety is higher, and therefore the application has good practical application value.

The invention belongs to the technical field of biological medicine, and particularly relates to application of magnoflorine in preparation of a product for preventing / treating liver injury. The invention discusses the protective effect and mechanism of magnoflorine on MTX hepatotoxicity for the first time, and magnoflorine regulates ROS accumulation and mPTP permeability through targeting GSK3beta to inhibit pyroptosis of hepatocytes so as to reduce MTX hepatotoxicity. A new target and a new choice are provided for the prevention and treatment of MTX hepatotoxicity, and a research foundation is laid for the research of a new magnoflorine component liver-protecting drug.

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 a RNA interference triggers for inhibiting the expression of an AAT gene through the mechanism of RNA interference. The invention also relates to a pharmaceutical composition comprising the AAT RNAi trigger together with an excipient capable of improving delivery of the RNAi trigger to a liver cell in vivo. Delivery of the AAT RNAi trigger to liver cells in vivo provides for inhibition of AAT gene expression and treatment of alpha 1-antitrypsin deficiency and associated diseases.

The application discloses a kind of hepatic organoids containing mesenchyme induction method, belong to organoid culture technical field.The method includes the following steps: (1) human embryonic stem cell WIBR3 pretreatment;(2) utilize human embryonic stem cell WIBR3 and induce liver organoids and mesenchymal cells;(3) mesenchymal cells and liver organoid cells are co-cultured, i.e. obtain the hepatic organoids containing mesenchyme.There is beneficial effect: the application changes the culture mode and method of the hepatic organoids containing mesenchyme.The hepatic organoids containing mesenchyme induction method proposed in the application is simple, and mesenchymal cells and other liver cells have the same genetic background source, suitable for the safety evaluation of drug and other chemical substances, liver fibrosis, non-alcoholic hepatitis modeling and pharmacodynamic evaluation.

The invention discloses a preparation method of cordyceps sobolifera polysaccharide and application of the cordyceps sobolifera polysaccharide in relieving acute chemical liver injury. Monosaccharide of the cordyceps sobolifera polysaccharide (abbreviated as CCPW) is composed of glucose, mannose and galactose according to the molar ratio of 8.918: 1: 0.356, and the relative molecular mass is 2.62 * 10 < 4 > Da. Efficacy experiments show that the cordyceps sobolifera homogeneous polysaccharide CCPW can significantly inhibit increase of ALT and AST in a CCl4-induced acute chemical liver injury model mouse, effectively improve the degree of liver cell disruption and swelling, relieve liver inflammatory response, relieve CCl4-induced mouse liver tissue injury, protect mouse intestinal barriers, recover intestinal microbial balance and have obvious liver protection activity. The cordyceps sobolifera polysaccharide CCPW is clear in composition and remarkable in effect, and has wide development and application prospects in the aspect of relieving acute chemical liver injury.

The disclosure provides compositions and methods for identifying subjects having hepatocyte stress associated with a risk for developing hepatocellular carcinoma (HCC), and therapeutic methods for reducing a subject's risk of HCC, for example, by inhibiting RELB, SOX4, or HMGCS2.

Methods of treating, suppressing, or reducing the severity of a liver cancer in a subject are described herein. The disclosed methods involve administering a therapeutically effective amount of a composition including safranal or its pharmaceutically acceptable pro-drug, and a pharmaceutically acceptable carrier to the subject. The disclosed methods may be used to treat, suppress, or reduce the severity of various liver cancers, including hepatocellular carcinoma (HCC), fibrolamellar HCC, cholangiocarcinoma, angiosarcoma, a metastatic liver cancer, and combinations thereof.