Splenic flexure mobilization: does body topography matter?

Background: Splenic flexure mobilization can be technically challenging, and its oncological benefits remain uncertain. This study aims to explore the relationship between patient and clinical characteristics and splenic flexure mobilization time as well as the implications of prolonged splenic flexure mobilization duration.

Methods: This retrospective cohort study includes 105 patients who underwent laparoscopic distal colorectal cancer surgery between 2013 and 2018.

Unveiling the significance of Gremlin-1 as a novel biomarker for enhanced severity prediction in COVID-19 patients.

Gremlin-1 is associated with lung disease and plays a role in the initiation and progression of pulmonary fibrosis. This suggests that Gremlin-1 may be associated with lung involvement in COVID-19 and poor clinical outcomes and warrants further investigation. This prospective, cross-sectional, single-blind study was the first to investigate Gremlin-1 levels in COVID-19 patients and whether Gremlin-1 levels could be used to predict and guide clinical follow-up in outpatients and inpatients.

Controlling the Intrinsic Charge Carrier Properties of Two-Dimensional Monochalcogenides (GeSe).

Strong anisotropy exhibited by materials, particularly in their low-dimensional forms, is a highly intriguing characteristic. In this study, we investigate the effects of geometrical potential and thermodynamics on the electronic properties of monolayer monochalcogenide charge carriers. First, the geometrical potential is introduced in a monolayer structure.

Development trends and knowledge framework of artificial intelligence (AI) applications in oncology by years: a bibliometric analysis from 1992 to 2022.

Purpose: Oncology is the primary field in medicine with a high rate of artificial intelligence (AI) use. Thus, this study aimed to investigate the trends of AI in oncology, evaluating the bibliographic characteristics of articles. We evaluated the related research on the knowledge framework of Artificial Intelligence (AI) applications in Oncology through bibliometrics analysis and explored the research hotspots and current status from 1992 to 2022.