Latest Articles

Identified endoplasmic reticulum stress-related molecular cluster and immune characterization in endometriosis.

Endometriosis is a common disease among women of childbearing age, and endoplasmic reticulum stress (ERS), a response involved in regulating protein homeostasis, has been linked to its pathogenesis. To identify …

Identification of metabolic reprogramming-associated biomarkers in endometriosis through integrated bioinformatics analysis.

Endometriosis (EMs), a common gynecological disorder, involves complex molecular mechanisms. Metabolic reprogramming (MR) has been recognized as a hallmark of EMs, contributing to lesion survival and immune microenvironment remodeling. This …

Integrated bioinformatics analysis and machine learning identifies FZD4, SRPX2, and COL8A1 as angiogenesis hub genes in endometriosis.

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 …

Integrative transcriptomic analysis identifies shared EndMT-related gene signatures in endometriosis and recurrent miscarriage.

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 …

Analysis of diagnostic apoptosis-related biomarkers and immune cell infiltration characteristics in endometriosis by integrating bioinformatics and machine learning.

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 …

Comment on "Deciphering the Molecular Crosstalk of Endoplasmic Reticulum Stress and Immune Infiltration in Endometriosis".

Identification of biomarkers for endometriosis based on summary-data-based Mendelian randomization and machine learning.

Endometriosis (EM) significantly impacts the quality of life, and its diagnosis currently relies on surgery, which carries risks and may miss early lesions. Noninvasive biomarkers are urgently needed for early …

Unraveling shared diagnostic genes and cellular microenvironmental changes in endometriosis and recurrent implantation failure through multi-omics analysis.

Endometriosis and Recurrent Implantation Failure (RIF) are both pivotal clinical issues within the realm of reproductive medicine, sharing significant overlap in their pathophysiological mechanisms. However, research exploring the commonalities between …

The expression of autophagy-related gene CXCL12 in endometriosis associated ovarian cancer and pan-cancer analysis.

Endometriosis-associated ovarian cancer (EAOC), an aggressive form of malignant ovarian neoplasm with origins in endometriosis (EM), has risen to prominence recently. Despite extensive investigation, the precise pathophysiology remains elusive.This article …

Potential biomarkers and immune infiltration linking endometriosis with recurrent pregnancy loss based on bioinformatics and machine learning.

Endometriosis (EMs) is a chronic inflammatory disease characterized by the presence of endometrial tissue in the non-uterine cavity, resulting in dysmenorrhea, pelvic pain, and infertility. Epidemiologic data have suggested the …