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<p>The discovery of selective immunosuppressants for T cell-mediated diseases like Ulcerative Colitis (UC) is a significant challenge. While traditional screening is inefficient, Artificial intelligence (AI)-driven approaches are often hindered by the scarcity of high-quality labeled data, challenging the accurate identification of functional molecules. In this study, we leveraged a transfer learning strategy to compensate for the lack of high-quality data, establishing a screening platform to identify potential T cell inhibitors. Using this approach, we identified Lutein as a novel, specific immunomodulatory candidate 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 highlight the feasibility of using a few-shot learning strategy based on transfer learning to screen for specific immunosuppressants and indicate that Lutein is a promising therapeutic candidate for ulcerative colitis.</p><p></p>

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

  • 期刊论文

  • 发表日期：

    2026年5月18日

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  • Li-jun Yang,
  • Zong-hui Wei,
  • Pei-jian Cao,
  • Zhi-bin Li,
  • Xiang Li,
  • Jun-wei Zhao,
  • Yi-wen Du,
  • Ke-han Wang,
  • Qiao-hong Zheng,
  • Qiao-jun He,
  • Bo Yang,
  • Jia-jia Wang,
  • Qin-jie Weng

摘要

The discovery of selective immunosuppressants for T cell-mediated diseases like Ulcerative Colitis (UC) is a significant challenge. While traditional screening is inefficient, Artificial intelligence (AI)-driven approaches are often hindered by the scarcity of high-quality labeled data, challenging the accurate identification of functional molecules. In this study, we leveraged a transfer learning strategy to compensate for the lack of high-quality data, establishing a screening platform to identify potential T cell inhibitors. Using this approach, we identified Lutein as a novel, specific immunomodulatory candidate 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 highlight the feasibility of using a few-shot learning strategy based on transfer learning to screen for specific immunosuppressants and indicate that Lutein is a promising therapeutic candidate for ulcerative colitis.