Machine learning models for non-invasive endometriosis triage using a laparoscopically and histologically verified cohort.
To develop and internally validate machine-learning models for non-invasive triage of women at risk for endometriosis using structured clinical variables in a laparoscopically and histologically verified cohort.
Anti-NRP1 peptide-engineered ROS/pH dual-responsive nanoparticles for Alpelisib delivery regulate Sema3A-NRP1/PI3K-AKT signaling to balance oxidative stress and inhibit angiogenesis in endometriosis.
Endometriosis progression is driven by oxidative stress and excessive angiogenesis within an inflammatory microenvironment. To overcome these challenges, we designed ROS/pH dual-responsive Alpelisib-loaded nanoparticles (Alp@TAT-AT7-NPs) functionalized with an anti-NRP1 peptide …
Out of pocket expenditure incurred by couples seeking infertility services at tertiary level facilities in India.
Background and objectives Diagnosis and treatment of infertility, mostly sought at tertiary facilities, contribute to substantial out-of-pocket expenditure (OOPE). This study estimated OOPE among couples seeking care for endometriosis, male …
Deep Dyspareunia One Year After Nerve-Sparing Endometriosis Surgery: An Observational Study Highlighting Undesirable Outcomes.
Background/Objectives: This study evaluates the 1-year follow-up outcomes after minimally invasive nerve-sparing surgery for the complete excision of deep endometriosis (DE), with a specific focus on deep dyspareunia. Cases with …