MedComm – Future Medicine

This review provides an overview of large-scale AI models, including language models (e.g., ChatGPT), vision-language models, and language-conditioned multiagent models, and discusses their potential applications in medicine, as well as their limitations and future trends. We also propose how large-scale AI models can be integrated into various scenarios of clinical applications.

The advent of next-generation sequencing (NGS) has revolutionized genome analysis, allowing for high-throughput sequencing and in-depth genomic insights. Contemporary NGS techniques, including fusion gene detection, whole genome sequencing, and spatial transcriptomics, play crucial roles in disease diagnosis, therapeutic development, evolutionary research, and agricultural advancements. NGS technologies continue to drive genomic research forward, deepening our understanding of disease mechanisms and paving the way for innovative treatments.

Cordyceps sinensis demonstrates efficacy in reducing mitochondrial reactive oxygen species (mitROS) production and mitigating oxidative stress and inflammation by targeting mitochondrial complexes I and II. These mechanisms contribute to its therapeutic effect in pulmonary fibrosis.

Long coronavirus disease (COVID) affects various body systems resulting in heterogeneous symptomatology, which could be due to increased immunity through vaccination or multiple exposures to the virus. Current data indicate that the incidence of long COVID from the severe acute respiratory syndrome coronavirus 2 wild-type variant to Omicron may be decreasing.

This review provides an overview of traditional and modern methods for protein structure prediction and their characteristics and introduces the groundbreaking network features of the AlphaFold family model. We summarize the applications of different bioinformatics databases and various models based on deep learning architectures (convolutional neural network, recurrent neural network, Transformer, etc.) in this field, which may provide directions for future development of predictive models such as prediction of the structure of large protein complexes and integration of protein language models.