Author

Yifan Lei

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Open access Jul 2026

Targeting the FOXP3—T-bet interaction to restore Treg stability in IFN-γ—driven autoimmunity 2254306

Regulatory T cells (Tregs) maintain immune homeostasis through FOXP3-centered transcriptional complexes that tightly control lineage stability and suppressive function. However, how specific FOXP3 mutations disturb this complex and drive pathogenic Treg reprogramming in IPEX syndrome remains unclear. We identified a distinctive mechanism by which the FOXP3 V408M mutation promotes Th1-skewed inflammation and also explored a pharmacological strategy to restore Treg stability. We generated FOXP3 V408M knock-in mice and performed immunophenotyping, transcriptomic, and chromatin conformation analyses to determine how the mutation affects FOXP3—T-bet interaction and Ifng transcription. An AI-driven virtual screening strategy integrating sequence- and structure-based modeling was applied to identify compounds that stabilize FOXP3—T-bet interaction. Functional validation was performed in vitro and in multiple in vivo mouse models. FOXP3 V408M mutation disrupted the FOXP3—T-bet interaction, thereby releasing T-bet from FOXP3-mediated repression and enhancing Ifng transcription. This defect reprogrammed Tregs toward an IFN-γ—producing phenotype that promoted Th1 inflammation. Among the AI-driven screening hits, 430C10 emerged as a first-in-class FOXP3-targeting stabilizer binding an allosteric pocket within the FKH domain. 430C10 reinforced the FOXP3—T-bet interaction and suppressed T-bet—driven IFN-γ production by Tregs. Oral 430C10 treatment markedly alleviated IFN-γ+ Treg—driven inflammation in FOXP3 V408M mice and improved disease outcomes in an acute colitis model under FOXP3 WT settings. Our findings define the FOXP3—T-bet interaction as a tunable checkpoint controlling Treg stability and IFN-γ—driven autoimmunity. Pharmacological stabilization of this interaction with 430C10 provides a proof-of-concept therapeutic strategy for restoring immune homeostasis in IPEX syndrome and related autoimmune diseases. Our research is supported by National Natural Science Foundation of China (82271829, 32130041, 82441047, 82241222); The Innovation Program of Shanghai Municipal Education Commission (21140902900); Noncommunicable Chronic Diseases-National Science and Tech Therapeutic Approaches to Autoimmunity (THER)

Bin Li, Wei-Qi Zhang, Xin-Nan Liu et al. · Journal of Immunology · 0 citations

Open access Jul 2026

Multi-modal sensing and pulse sequence analysis for single-source and dual-source partial discharge diagnosis in transformers under complex operating conditions

Transformer partial discharge (PD) diagnosis may simultaneously face narrowband interference under undersampling conditions, limited fault samples, class imbalance, and multi-source signal mixing. To address these issues, this paper proposes a multi-modal pulse-sequence-based diagnostic framework using synchronized Optical, ultra-high-frequency (UHF), and high-frequency current transformer (HFCT) measurements, and experiments are conducted on a laboratory platform with five typical PD defect models of oil-immersed transformers. For front-end signal processing, a spectral dilation and linear trend replacement (SDLTR) method is proposed to suppress narrowband interference in HFCT signals while preserving the original pulse timing and amplitude characteristics. On this basis, conventional single-sensor pulse sequence analysis (PSA) is extended to an adaptive tri-modal PSA fusion scheme for single-source PD classification. By constructing the temporal union of synchronized Optical, UHF, and HFCT pulse streams and using expert-weighted decision fusion, the proposed method exploits cross-modal complementarity and enlarges the effective sample set. Under class-imbalanced conditions, the four-pulse-based PSA6 fusion scheme achieves an accuracy of 95.47% and a Macro-F1 of 95.17%. For dual-source PD mixtures, an adaptive cascaded decoupling framework (ACDF) is further proposed by combining class-level precision-weighted fusion, an adaptive confidence boundary, and two-stage dominant-source stripping based on PSA6 and PSA4. The proposed framework produces zero false decisions in single-source verification and correctly identifies both PD sources in all ten dual-source combinations. These results demonstrate that the proposed framework provides an effective and practical solution for transformer PD diagnosis under complex operating conditions.

Zehao Chen, Yong Qian, Chao Pan et al. · Measurement science and tech... · 0 citations