8 results about "Therapeutic evaluation" patented technology

This invention discloses a trimethyl chitosan-hyaluronic acid-FMNL2 siRNA nanomedicine and its applications. The siRNA molecule consists of a sense strand and an antisense strand, which are anti-complementary to form a double-stranded RNA structure. Each of the sense and antisense strands independently contains two pendant deoxythymidines at its 3' end. The nanomedicine uses trimethyl chitosan as its core framework, efficiently encapsulating the siRNA molecule through electrostatic interactions, and then modifying hyaluronic acid through electrostatic interactions to form core-shell structured nanoparticles. This invention forms a complete technology chain from target validation, siRNA sequence design, nanodelivery system construction, in vivo and in vitro efficacy verification to the development of combination drug strategies. It also provides quantifiable efficacy evaluation biomarkers, offering a clear basis for clinical patient screening and efficacy monitoring.

The present application relates to the medical technical field, especially to the application of FYB1 gene as a marker in preparation of gastric cancer diagnosis or prognosis judging reagent. The present application research finds that FYB1 gene is highly expressed in gastric cancer tissue and negatively correlated with the prognosis of patients, and can be used as a gastric cancer marker for gastric cancer detection and efficacy evaluation. In addition, FYB1 is positively correlated with the expression of Treg cell marker FOXP3 and co-localized in tissues, suggesting that FYB1 may promote gastric cancer tumor immune escape; the expression of FYB1 gene can significantly inhibit the proliferation, migration and invasion ability of gastric cancer cells, and inhibit tumor growth, indicating that FYB1 gene can be used as a gastric cancer treatment target and play an important role in the treatment of gastric cancer patients.

The application belongs to the technical field of medical diagnosis assistance, and provides an inflammatory bowel disease evaluation method and system. The method obtains biological sample data of a target object, pre-processes the biological sample data to standardize each index data, calculates multiple scores representing the individual state of the target object based on the pre-processed biological sample data, and constructs a comprehensive evaluation index for quantitatively evaluating the inflammatory bowel disease of the target object based on each score. The scheme provided by the application integrates multiple index data to construct a multi-dimensional comprehensive evaluation index, which can comprehensively and accurately reflect the pathophysiological nature of inflammatory bowel disease, effectively avoiding misdiagnosis or missed diagnosis caused by single-dimensional evaluation, and providing a non-invasive, convenient and standardized technical solution for the diagnosis, disease monitoring and efficacy evaluation of inflammatory bowel disease.

This invention discloses a single-domain antibody targeting DLL3, related materials, and applications. The invention provides an antibody or antigen-binding fragment thereof that binds to the human DLL3 protein, wherein the CDR1, CDR2, and CDR3 of the antibody are as shown in positions 28-35, 49-61, and 98-111, respectively, in SEQ ID NO: 1. The invention also protects a probe comprising a radionuclide and the antibody. Furthermore, the invention protects the use of the antibody or probe in the preparation of products; the uses of the products include: binding to the human DLL3 protein; detecting the human DLL3 protein; diagnosing or assisting in the diagnosis of cancer patients; and evaluating treatment efficacy in cancer patients. This invention can be used for early diagnosis and efficacy monitoring of tumors, providing a new solution for precision cancer treatment.

This invention relates to the fields of oral medicine and artificial intelligence, and particularly to a method and apparatus for evaluating the efficacy of oral and maxillofacial surgery based on deep learning. The method includes: acquiring multiple sets of image data and multiple sets of clinical indicator data from the patient to be tested; extracting features from the image data and clinical indicator data respectively, obtaining image spatial feature vectors and semantic feature vectors sequentially; fusing each image spatial feature vector and the corresponding semantic feature vector at a given time point to obtain multiple fused feature vectors at different time points; inputting each fused feature vector into a preset deep learning model to obtain multiple oral and maxillofacial postoperative efficacy scores; and determining a comprehensive score for the overall efficacy of oral and maxillofacial surgery based on these multiple scores. Thus, this invention can accurately evaluate the efficacy of oral and maxillofacial surgery following dental trauma.

This invention relates to a multi-task learning-based integrated nutritional decision-making method and system for examination, diagnosis, treatment, and evaluation, belonging to the interdisciplinary field of clinical medicine and artificial intelligence. This method aims to address the problems of isolated tasks, limited data utilization, and lack of quantitative recommendation and prognostic prediction capabilities in existing nutritional decision-making technologies. The technical solution involves constructing a serial multi-task learning neural network model, sequentially including a feature extraction module, a nutritional diagnosis module, a nutritional treatment recommendation module, and a prognostic and efficacy evaluation module. A joint loss function that dynamically balances the weights of each task and reuses prognostic labels is designed for training. This invention achieves integrated decision-making throughout the entire process of examination, diagnosis, treatment, and prognosis. It can integrate multimodal data to achieve accurate feature extraction, provide personalized quantitative nutritional recommendations, and prospectively predict efficacy to guide clinical intervention, significantly improving the efficiency and accuracy of nutritional decision-making.

The application discloses a DNA probe cell apoptosis real-time monitoring kit based on a double-receptor design, and belongs to the technical field of biological detection. The kit adopts graphene oxide and a black hole quencher to form a synergistic double receptor, combines a double anti-interference structure based on a poly-A sequence, realizes low-background and high-accuracy real-time dynamic monitoring of an apoptosis-related miRNA marker in living cells, improves fluorescence quenching efficiency through the double receptor to reduce a background signal, uses the double anti-interference to inhibit non-specific interference in a biological sample, overcomes technical bottlenecks that a traditional method cannot perform real-time monitoring of living cells and is prone to false positive signals, the kit is simple to operate, can be directly applied to blood samples of cancer patients or cultured living cells, and can realize real-time monitoring and curative effect evaluation of an apoptosis process in a treatment process through a conventional fluorescence equipment, thereby providing a new tool for avoiding over-treatment and adjusting a dosing regimen in clinic.

The application discloses an effectiveness evaluation method and system of anti-infective drugs, and relates to the technical field of data analysis, which comprises the following steps: collecting oral microbial samples of patients in the whole treatment cycle, generating time-characteristic personalized dynamic atlas of oral microbiome of the patients, capturing the composition structure and dynamic evolution law of oral microbial community; integrating multi-dimensional life habit data of the patients, extracting life behavior patterns and individual preference characteristics of the patients, coupling analysis of the time-characteristic personalized dynamic atlas of oral microbiome of the patients, establishing a patient behavior-microorganism correlation model, and obtaining the regulation path of external behavior to the microbiome; based on the regulation path of external behavior to the microbiome, introducing the physical fitness parameters of the patients as compensation factors, establishing a comprehensive evaluation function of the anti-infective drug efficacy of the patients, and realizing personalized effective evaluation of the patients for the anti-infective drugs. The application improves the accuracy, forward-looking and clinical practicability of the efficacy evaluation.