4 results about "Hepatobiliary disease" patented technology

This invention discloses a veterinary drug composition containing Bupleurum chinense extract, its preparation method, and its application, belonging to the technical field of veterinary traditional Chinese medicine preparations. The composition consists of active ingredients (only saikosaponins a and d, in a mass ratio of 0.8–1.2:1, accounting for 5%–50% of the total content) and excipients (one or more of microcrystalline cellulose, magnesium stearate, and starch). The dosage form is tablets, granules, or powder, with each unit dose containing 5–20 mg of the total mass of both. In preparation, dried Bupleurum chinense roots are pulverized and enzymatically hydrolyzed with a 1:1 complex enzyme, ultrasonically extracted with an ethanol-sodium citrate mixture, purified with AB-8 macroporous resin, and freeze-dried to obtain saikosaponin powder. This powder is then mixed with the excipients and granulated, tableted, or packaged into the corresponding dosage form. This composition shows significant efficacy against fatty liver in chickens, hepatitis in pigs, and cholestasis in ducks, exhibiting stability, high purity, and high efficiency, providing a safe new option for the treatment of liver and gallbladder diseases in livestock and poultry.

This invention discloses a plasmon resonance detection method for hepatobiliary-specific methylation sites. The method first immobilizes a sequence-specific DNA capture probe on a gold membrane surface and covalently couples it with a methylation-binding domain protein, constructing a sensor interface with dual functions of sequence capture and methylation recognition. During detection, a pre-treated plasma circulating cell-free DNA single-stranded sample is introduced into the sensor. The target DNA first hybridizes with the capture probe, and then its methylation site is specifically bound by the adjacent methylation-binding domain protein, triggering two consecutive specific surface plasmon resonance signal responses. By analyzing the increment between the two stable signal values ​​and comparing it with a preset threshold, label-free, real-time, and highly specific determination of the methylation status of the target site can be achieved. This invention eliminates the need for bisulfate treatment, effectively preserving DNA integrity, and is particularly suitable for high-sensitivity detection of hepatobiliary disease-related epigenetic markers in trace circulating cell-free DNA.

This invention discloses a deep learning-based method for predicting the disease evolution of hepatobiliary patients, belonging to the fields of medical imaging and deep learning technology. The invention first acquires multi-temporal abdominal CT images, time-series clinical laboratory indicators, and medical history follow-up data of hepatobiliary patients; it then uses a variant U-Net network with Lagrange pseudo-ordering structure constraints to accurately segment the CT images and extract radiomics features; based on the segmentation results, a three-dimensional model is constructed, and numerical simulations of hepatobiliary blood perfusion and bile fluid dynamics are performed using local entropy production theory to obtain dynamic biomechanical features; cross-dimensional feature alignment and fusion are achieved by fusing attention mechanisms and a multimodal network for complex community discovery, and then chaotic theory is introduced for phase space reconstruction to enhance dynamic features; this invention achieves an upgrade from statistical correlation to physiological causality in prediction, improving model generalization and clinical interpretability, and is suitable for prognostic assessment and intelligent early warning of disease progression in hepatobiliary diseases.