Quercetin enhances decidualization through AKT-ERK-p53 signaling and supports a role for senescence in endometriosis.

Background: Patients with endometriosis suffer with chronic pelvic pain and infertility, and from the lack of pharmacologic therapies that consistently halt disease progression. Differences in the endometrium of patients with endometriosis vs. unaffected controls are well-documented.

Endoscopic Normalization and Transition of J-Pouch Phenotypes Over Time in Patients With Inflammatory Bowel Disease.

Background: Patients with inflammatory bowel disease (IBD) who undergo proctocolectomy with ileal pouch-anal anastomosis may develop pouchitis. We previously proposed a novel endoscopic classification of pouchitis describing 7 phenotypes with differing outcomes. This study assessed phenotype transitions over time.

Understanding Patients' Negative Experiences with Telehealth: A Content Analysis of Survey Data.

Understanding differences in how demographic groups experience telehealth may be relevant in addressing potential disparities in telehealth usage. We seek to identify and examine themes most pertinent to patients' negative telehealth experiences by age and race in order to inform interventions to improve patients' future telehealth experiences. We performed a content analysis of Press Ganey patient experience surveys from adult patients at 17 primary care sites of a large, public healthcare system with visits from April 30, 2020 to August 27, 2021.

Performance of Artificial Intelligence Chatbots on Glaucoma Questions Adapted From Patient Brochures.

Introduction With the potential for artificial intelligence (AI) chatbots to serve as the primary source of glaucoma information to patients, it is essential to characterize the information that chatbots provide such that providers can tailor discussions, anticipate patient concerns, and identify misleading information. Therefore, the purpose of this study was to evaluate glaucoma information from AI chatbots, including ChatGPT-4, Bard, and Bing, by analyzing response accuracy, comprehensiveness, readability, word count, and character count in comparison to each other and glaucoma-related American Academy of Ophthalmology (AAO) patient materials. Methods Section headers from AAO glaucoma-related patient education brochures were adapted into question form and asked five times to each AI chatbot (ChatGPT-4, Bard, and Bing).