Identification of diagnostic markers related to inflammatory response and cellular senescence in endometriosis using machine learning and in vitro experiment.

Yang, Pusheng; Miao, Yaxin; Wang, Tao; Sun, Jing

Yang, Pusheng; Miao, Yaxin; Wang, Tao; Sun, Jing.

Affiliation

Yang P; Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Tongji University, Shanghai, 200092, China.
Miao Y; Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Tongji University, Shanghai, 200092, China.
Wang T; Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Tongji University, Shanghai, 200092, China.
Sun J; Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Tongji University, Shanghai, 200092, China. sunjing61867@tongji.edu.cn.

Inflamm Res ; 73(7): 1107-1122, 2024 Jul.

Article in En | MEDLINE | ID: mdl-38704432

Subject(s)
Key words

Cellular senescence; Diagnostic markers; Endometriosis; Immune infiltration; Inflammatory response

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Cellular Senescence / Endometriosis / Machine Learning / Inflammation Limits: Female / Humans Language: En Journal: Inflamm Res Journal subject: ALERGIA E IMUNOLOGIA / PATOLOGIA Year: 2024 Document type: Article Affiliation country: China Country of publication: Suiza

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