Machine learning-based identification of pyroptosis-related genes as biomarkers and targets in primary Sjögren's syndrome
This study provides novel insights into the molecular mechanisms of pSD and highlights potential diagnostic biomarkers and therapeutic targets related to pyroptosis. The integration of bioinformatics and machine learning offers a robust framework for understanding the complex interplay between pyroptosis and pSD pathogenesis.
Authors
- Sheng Gao (ORCID: https://orcid.org/0000-0002-8622-5694)
- Xinyue Liang (ORCID: https://orcid.org/0000-0003-2177-2782)
- Chunyan Hua (ORCID: https://orcid.org/0000-0001-7957-6106)
- Yanggang Hong (ORCID: https://orcid.org/0009-0004-4507-0093)
- Ting Zhang (ORCID: https://orcid.org/0000-0002-0317-9662)
- Xiaoyang Jiang (ORCID: https://orcid.org/0009-0008-8368-5637)
Institutions
- Wenzhou Medical University (CN)
- First Affiliated Hospital of Wenzhou Medical University (CN)
Publication Details
- Journal
- Clinical and Experimental Rheumatology
- Published
- 2025-12-18
- DOI
- https://doi.org/10.55563/clinexprheumatol/zpd69e
- Primary Topic
- Salivary Gland Disorders and Functions
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Science and Technology Plan Project of Wenzhou, China
- Natural Science Foundation of Zhejiang Province