Journal of Autoimmunity, Год журнала: 2024, Номер 149, С. 103296 - 103296
Опубликована: Сен. 5, 2024
Язык: Английский
Journal of Autoimmunity, Год журнала: 2024, Номер 149, С. 103296 - 103296
Опубликована: Сен. 5, 2024
Язык: Английский
Science Advances, Год журнала: 2022, Номер 8(17)
Опубликована: Апрель 29, 2022
Analysis of gene expression from cutaneous lupus erythematosus, psoriasis, atopic dermatitis, and systemic sclerosis using set variation analysis (GSVA) revealed that lesional samples each condition had unique features, but all four diseases displayed common enrichment in multiple inflammatory signatures. These findings were confirmed by both classification regression tree machine learning (ML) models. Nonlesional disease also differed normal other ML. Notably, the features used nonlesional more distinct than their counterparts, GSVA disease. data show skin have profiles abnormalities, especially skin, suggest a model which disease-specific abnormalities “prelesional” may permit environmental stimuli to trigger responses leading shared manifestations
Язык: Английский
Процитировано
34Journal of Autoimmunity, Год журнала: 2024, Номер 149, С. 103296 - 103296
Опубликована: Сен. 5, 2024
Язык: Английский
Процитировано
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