From Endoscopic Inspection to Gene-Expression: A Thorough Assessment of the Duodenal Mucosa After Resurfacing-A Prospective Study.

Aims: Duodenal Mucosal Resurfacing (DMR) is an endoscopic ablation technique aimed at improving glycemia in patients with type 2 diabetes mellitus (T2DM). Although the exact underlying mechanism is still unclear, it is postulated that the DMR-induced improvements are the result of changes in the duodenal mucosa. For this reason, we assessed macroscopic and microscopic changes in the duodenal mucosa induced by DMR + GLP-1RA.

Deep learning-based multiclass segmentation in aneurysmal subarachnoid hemorrhage.

Introduction: Radiological scores used to assess the extent of subarachnoid hemorrhage are limited by intrarater and interrater variability and do not utilize all available information from the imaging. Image segmentation enables precise identification and delineation of objects or regions of interest and offers the potential for automatization of score assessments using precise volumetric information. Our study aims to develop a deep learning model that enables automated multiclass segmentation of structures and pathologies relevant for aneurysmal subarachnoid hemorrhage outcome prediction.

Analyzing emergency department presentations linked to secondary earthquake effects.

Objective: The earthquakes that struck Türkiye on February 6, 2023, significantly impacted the province of Hatay. A portion of the patients presenting to emergency departments (ED) following the earthquake were exposed to secondary effects without experiencing direct physical trauma. This study aims to evaluate the demographic, clinical, and psychosocial characteristics of patients presenting to the ED during the early post-earthquake period due to secondary effects, as well as to examine the challenges encountered during this process.