Metabonomics

This study comprehensively examines metabolic and lipidomic dynamics in gastric cancer patients initiating PD-1/PD-L1 inhibitor therapy, employing a longitudinal design with pre- and post-treatment patients. The primary objectives include identifying irAE-associated metabolic and lipid biomarkers, developing predictive risk models, and evaluating the prognostic value of these molecular profiles. The findings are expected to contribute significantly to personalized treatment strategies and improved clinical decision-making in immunooncology.

Gut microbiota dysfunction is associated with Alzheimer's disease (AD). However, the potential modulatory mechanism remains unclear. Previous studies have shown that gut-derived metabolites short-chain fatty acids (SCFAs) may be the key mediators between gut microbiota and brain, participating in the modulatory pathway "gut microbiota-SCFAs-brain networks". In this project, high-throughput targeted metabolomics technique will be used to explore the differences of SCFAs in the spectrum of AD, including cognitively normal individuals, subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD dementia. Then, the gut microbiome and multi-modal MRI techniques will be combined to elucidate potential interaction mechanisms of "gut microbiota-SCFAs-brain networks". Finally, based on multi-omics features extracted from gut microbiome, metabolomics, and neuroimaging after five years, the diagnostic model of SCD due to preclinical AD will be established using machine learning methods.