Transcriptomics

Dataset Information

0

Few-shot Learning-driven discovery of Lutein suppresses Th1-mediated inflammation via glucose metabolism


ABSTRACT: Artificial intelligence (AI)-driven drug discovery is often hindered by the “few-shot” data bottleneck and the limited representational power of traditional two-dimensional models, challenging the accurate identification of functional molecules. In this study, we addressed these challenges by establishing a high-precision screening platform, which leverages transfer learning to recognize the key 3D molecular features of T cell inhibitors. Using this approach, we identified Lutein as a novel, specific immunomodulatory agent from a natural product library. Integrated multi-omics analyses revealed that Lutein activates peroxisome proliferator-activated receptor gamma (PPARγ), suppressing glucose uptake and glycolysis, thereby selectively inhibiting Th1 cell differentiation. In a dextran sulfate sodium (DSS)-induced mouse model of ulcerative colitis, Lutein treatment significantly restored Th1-mediated immune balance and alleviated pathological tissue damage. Our findings not only highlight the great potential of “few-shot” AI strategies that leverage transfer learning and 3D molecular features for the discovery of bioactive natural compounds, but also identify Lutein as a promising therapeutic candidate for ulcerative colitis.

ORGANISM(S): Homo sapiens

PROVIDER: GSE304676 | GEO | 2026/08/03

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

| PRJNA1302318 | ENA
2024-01-29 | GSE245843 | GEO
2026-06-25 | GSE301891 | GEO
2026-04-01 | GSE317028 | GEO
2025-09-01 | GSE306268 | GEO
2020-01-31 | GSE144574 | GEO
2019-03-01 | E-MTAB-6672 | biostudies-arrayexpress
2024-09-23 | PXD055368 | JPOST Repository
2023-12-31 | GSE185102 | GEO
2025-03-31 | GSE281696 | GEO