Nucleotide Base Adducts Bind MR1 and Stimulate MR1-Restricted T Cells Abstract This article provides an overview of the latest research by Vacchini et al. on MR1-restricted T cells (MR1T cells), which discovered the presence of nucleotide base adducts as MR1T cell antigens and unveiled their metabolic pathways and physiological functions in tumor c...
Research Background γδ T cells play an important role in the immune system, particularly in protective immunity, homeostasis, and tissue repair. Unlike conventional αβ T cells, which are restricted by major histocompatibility complex (MHC), γδ T cells directly seed peripheral tissues and respond to various microbial stimuli without relying on MHC-p...
Consensus Study Report on Pediatric Epilepsy Surgery Background Introduction The incidence of epilepsy varies significantly across different age groups. According to the International League Against Epilepsy (ILAE), the highest incidence rates of epilepsy are found among those under 5 years old and over 65 years old (>60 per 100,000 people), with c...
Research on Network Construction and Application of Novel Drug Repositioning Strategies Background During the COVID-19 pandemic, researchers and pharmaceutical companies have been dedicated to developing treatments and vaccines. Drug repositioning, due to its shortcut, is considered a rapid and effective response strategy. Drug repositioning attemp...
Asthma Prediction Enhanced by Affinity Graph-Based Classifier: A Machine Learning Approach Using Routine Blood Biomarkers Background Asthma is a chronic respiratory disease that affects approximately 235 million people worldwide. According to the World Health Organization (WHO), the main characteristic of asthma is airway inflammation, leading to s...
Predicting Future Diseases: Integration of Temporal Knowledge Graphs and Medical Ontologies Electronic Health Records (EHRs) are indispensable tools in modern medical institutions. They record detailed health histories of patients, including demographics, medications, lab results, and treatment plans. This data not only improves the coordination an...
Research Report on the Integration of Medical Relation Extraction and Knowledge Graph-Based Recommendations Background Introduction In the medical field, the explosive growth of literature makes it challenging for researchers to keep up with the latest advancements in their specific areas. From the perspective of natural language processing (NLP), ...
Application of Knowledge-Enhanced Graph Topic Transformer in Interpretable Biomedical Text Summarization Research Background Due to the continuous increase in the volume of biomedical literature, the task of automatic biomedical text summarization has become increasingly important. In 2021 alone, 1,767,637 articles were published in the PubMed data...
Application of Hierarchical Attentive Relational Network in Diagnostic Prediction In recent years, Electronic Health Records (EHR) have become extremely valuable in improving medical decision-making, online disease detection, and monitoring. At the same time, deep learning methods have also achieved great success in utilizing EHR for health risk pr...
This study explores the interactions between Schwann cells and fibroblasts in neurofibromatosis type 1 (NF1) related plexiform neurofibroma (PNF). The background of the research is based on the high incidence of NF1, which affects about 1 in 3000 newborns worldwide and is associated with a series of unique clinical manifestations. PNF is a common p...