Endometriosis is a prevalent condition where tissue similar to the uterine lining grows outside the uterus, causing pain and infertility. Diagnosing endometriosis typically requires invasive procedures like laparoscopy. MicroRNAs (miRNAs) …
Endometriosis, a common and complex gynecologic disorder, continues to pose a challenge to clinicians in diagnosis process due to its complexity. The aim of this review was to examine cancer …
Endometriosis (E) is multifactorial disease affecting around 10% of women worldwide. The association between E and infertility is clinically well recognized. For E patients to achieve a successful pregnancy, assisted …
Endometriosis affects approximately 10% of women of reproductive age; this prevalence may be underestimated, mostly in developing countries, including Mexican and Hispanic populations, due to socioeconomic barriers and limited access …
Endometriosis is a mysterious disease that affects 5 %-10 % of the women of reproductive age. Circular RNAs (circRNAs), a type of noncoding RNA, are involved in its progression, yet …
The role of microRNAs (miRNAs) in human reproduction represents an area of research, as these regulatory molecules appear to play essential roles in reproductive function. However, the current understanding of …
Background: Endometriosis is a chronic gynecological condition marked by ectopic endometrial-like tissue, leading to inflammation, pain, and infertility. Diagnosis is often delayed by up to 10 years. Identifying non-invasive biomarkers …
Ovarian cancer (OC) remains the most lethal gynecologic malignancy due to late diagnosis and limited effective biomarkers. Hepatoma-derived growth factor (HDGF) has emerged as an oncogene implicated in tumor progression, …
(PDF) Expression analysis of plasma extracellular vesicle associated candidate MiRNAs in endometriosis using integrative bioinformatics and experiential data researchgate.net
Expression analysis of plasma extracellular vesicle associated candidate MiRNAs in endometriosis using integrative bioinformatics and experiential data Nature