Abnormal expression levels of microRNAs are associated with numerous diseases in the female reproductive tract. A small subset of human endogenous retroviruses (HERVs) genes have retained open reading frames (ORFs) …
This study explores the relationship between inflammatory biomarkers and the risk of endometriosis, aiming to develop a predictive model using National Health and Nutrition Examination Survey (1999-2006) data. The dataset …
Endometriosis is a gynecological disorder predominantly affecting women of reproductive age and is considered a potential risk factor for the development of endometrial cancer. However, the molecular mechanisms underlying the …
This study evaluated the diagnostic potential of Fourier-transform infrared (FTIR) spectroscopy combined with machine learning for the detection of ovarian, bowel, and peritoneal endometriosis. The Boruta algorithm was applied to …
Endometriosis (EM), a prevalent gynecological disorder in reproductive-age women, lacks reliable noninvasive diagnostic tools. EM may be detected by neutrophil extracellular traps (NETs), which are essential to inflammation and immunological …
To identify the predictors for periureteral adhesions preoperatively.
Endometriosis is a long-term health problem that affects a significant number of women globally. Among the various forms of endometriosis, ovarian endometriosis (OEM) is the most prevalent. This research aimed …
This study aims to identify angiogenesis-associated genes (AAGs) in endometriosis (EM) by integrating bioinformatics analysis with machine learning, and to investigate their underlying mechanisms. Differentially expressed genes (DEGs) were screened …
Endometriosis (EMs) and recurrent miscarriage (RM) represent major reproductive health challenges. This study investigates the involvement of endothelial-mesenchymal transition (EndMT) in these conditions through integrative bioinformatics analysis, focusing on the …
Endometriosis (EMs) is a chronic disease affecting millions of women worldwide, yet its pathogenesis remains unclear, and current diagnostic methods are limited. This study based on the EMs dataset from …