Identification of Endometriosis Pathophysiologic-Related Genes Based on Meta-Analysis and Bayesian Approach.

Endometriosis is a complex disease with diverse etiologies, including hormonal, immunological, and environmental factors; however, its exact pathogenesis remains unknown. While surgical approaches are the diagnostic and therapeutic gold standard, identifying endometriosis-associated genes is a crucial first step. Five endometriosis-related gene expression studies were selected from the available datasets.

Atomic-level Ru-Ir mixing in rutile-type (RuIr)O for efficient and durable oxygen evolution catalysis.

The success of proton exchange membrane water electrolysis (PEMWE) depends on active and robust electrocatalysts to facilitate oxygen evolution reaction (OER). Heteroatom-doped-RuO has emerged as a promising electrocatalysts because heteroatoms suppress lattice oxygen participation in the OER, thereby preventing the destabilization of surface Ru and catalyst degradation. However, identifying suitable heteroatoms and achieving their atomic-scale coupling with Ru atoms are nontrivial tasks.

Systemic Sodium Iodate Injection as a Model for Expanding Geographic Atrophy.

Purpose: Geographic atrophy (GA), an advanced form of dry age-related macular degeneration (AMD), has limited treatment options. This study introduces a novel mouse model featuring an expanding GA patch that can be used to test mechanisms and therapeutics.

Methods: C57Bl/6J male mice (n = 96) aged 9-10 weeks received an intraperitoneal (IP) injection of 20 mg/kg sodium iodate (NaIO3).

Preliminary experience and learning curve of endoscopic nipple-areolar-complex sparing total mastectomy: A single-center retrospective study.

Background: In this study, the preliminary experience of endoscopic nipple-areolar-complex (NAC) sparing total mastectomy were analyzed and reported.

Methods: The medical records of the patients who underwent Endoscopic NAC sparing total mastectomy from November 2019 to June 2022 in a single institute were collected and analyzed. The medical records of their clinicopathologic characteristics, perioperative parameters, postoperative complications, oncologic results were collected retrospectively.

StackDILI: Enhancing Drug-Induced Liver Injury Prediction through Stacking Strategy with Effective Molecular Representations.

Drug-induced liver injury (DILI) is a major challenge in drug development, often leading to clinical trial failures and market withdrawals due to liver toxicity. This study presents StackDILI, a computational framework designed to accelerate toxicity assessment by predicting DILI risk. StackDILI integrates multiple molecular descriptors to extract structural and physicochemical features, including the constitution, pharmacophore, MACCS, and E-state descriptors.