{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T21:20:05Z","timestamp":1788384005190,"version":"build-2803163510"},"reference-count":61,"publisher":"BMJ","issue":"1","license":[{"start":{"date-parts":[[2024,4,18]],"date-time":"2024-04-18T00:00:00Z","timestamp":1713398400000},"content-version":"unspecified","delay-in-days":17,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["Lupus Sci Med"],"accepted":{"date-parts":[[2024,3,28]]},"published-print":{"date-parts":[[2024,4]]},"abstract":"<jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Lupus nephritis (LN) is a complication of SLE characterised by immune dysfunction and oxidative stress (OS). Limited options exist for LN. We aimed to identify LN-related OS, highlighting the need for non-invasive diagnostic and therapeutic approaches.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>LN-differentially expressed genes (DEGs) were extracted from Gene Expression Omnibus datasets (GSE32591, GSE112943 and GSE104948) and Molecular Signatures Database for OS-associated DEGs (OSEGs). Functional enrichment analysis was performed for OSEGs related to LN. Weighted gene co-expression network analysis identified hub genes related to OS-LN. These hub OSEGs were refined as biomarker candidates via least absolute shrinkage and selection operator. The predictive value was validated using receiver operating characteristic (ROC) curves and nomogram for LN prognosis. We evaluated LN immune cell infiltration using single-sample gene set enrichment analysis and CIBERSORT. Additionally, gene set enrichment analysis explored the functional enrichment of hub OSEGs in LN.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>The study identified four hub genes, namely <jats:italic>STAT1<\/jats:italic>, <jats:italic>PRODH<\/jats:italic>, <jats:italic>TXN2<\/jats:italic> and <jats:italic>SETX<\/jats:italic>, associated with OS related to LN. These genes were validated for their diagnostic potential, and their involvement in LN pathogenesis was elucidated through ROC and nomogram. Additionally, alterations in immune cell composition in LN correlated with hub OSEG expression were observed. Immunohistochemical analysis reveals that the hub gene is most correlated with activated B cells and CD8 T cells. Finally, we uncovered that the enriched pathways of OSEGs were mainly involved in the PI3K-Akt pathway and the Janus kinase-signal transducer and activator of transcription pathway.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>These findings contribute to advancing our understanding of the complex interplay between OS, immune dysregulation and molecular pathways in LN, laying a foundation for the identification of potential diagnostic biomarkers and therapeutic targets.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1136\/lupus-2023-001126","type":"journal-article","created":{"date-parts":[[2024,4,18]],"date-time":"2024-04-18T13:15:18Z","timestamp":1713446118000},"page":"e001126","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":8,"title":["Machine learning-based identification of novel hub genes associated with oxidative stress in lupus nephritis: implications for diagnosis and therapeutic targets"],"prefix":"10.1136","volume":"11","author":[{"given":"Huiqiong","family":"Zeng","sequence":"first","affiliation":[{"name":"Traditional Chinese Medicine Department of Immunology, Women & Children Health Institute Futian Shenzhen, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Department of Rheumatology and Immunology, Huizhou Central People\u2019s Hospital, Huizhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaodong","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Basic Medical Sciences, Yunnan University of Chinese Medicine, Kunming, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"He","sequence":"additional","affiliation":[{"name":"Department of Fu Xin Community Health Service Center, The Eighth Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qianwen","family":"Qiu","sequence":"additional","affiliation":[{"name":"Traditional Chinese Medicine Department of Immunology, Women & Children Health Institute Futian Shenzhen, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8142-0489","authenticated-orcid":false,"given":"Wei","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Rheumatology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China"},{"name":"National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7238-1013","authenticated-orcid":false,"given":"Ye","family":"Zhang","sequence":"additional","affiliation":[{"name":"Traditional Chinese Medicine Department of Immunology, Women & Children Health Institute Futian Shenzhen, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2024,4,18]]},"reference":[{"key":"2025091513112430000_11.1.e001126.1","doi-asserted-by":"crossref","first-page":"ITC81","DOI":"10.7326\/AITC202006020","article-title":"Systemic lupus erythematosus","volume":"172","author":"Kiriakidou","year":"2020","journal-title":"Ann Intern Med"},{"key":"2025091513112430000_11.1.e001126.2","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.freeradbiomed.2018.05.086","article-title":"Oxidative stress in autoimmune rheumatic diseases","volume":"125","author":"Smallwood","year":"2018","journal-title":"Free Radic Biol Med"},{"key":"2025091513112430000_11.1.e001126.3","doi-asserted-by":"crossref","first-page":"v39","DOI":"10.1093\/rheumatology\/keaa381","article-title":"Lupus nephritis: clinical presentations and outcomes in the 21st century","volume":"59","author":"Gasparotto","year":"2020","journal-title":"Rheumatology (Oxford)"},{"key":"2025091513112430000_11.1.e001126.4","doi-asserted-by":"publisher","DOI":"10.1093\/ndt\/gfw300"},{"key":"2025091513112430000_11.1.e001126.5","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1016\/j.jmir.2019.09.005","article-title":"Machine learning and deep learning in medical imaging: intelligent imaging","volume":"50","author":"Currie","year":"2019","journal-title":"J Med Imaging Radiat Sci"},{"key":"2025091513112430000_11.1.e001126.6","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0280251","article-title":"Predicting physician departure with machine learning on EHR use patterns: A longitudinal cohort from a large multi-specialty ambulatory practice","volume":"18","author":"Lopez","year":"2023","journal-title":"PLoS One"},{"key":"2025091513112430000_11.1.e001126.7","doi-asserted-by":"crossref","unstructured":"Lo Vercio L , Amador K , Bannister JJ , et al . 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