IntroductionRobotic-assisted gastrectomy has transformed the surgical management of gastric cancer, particularly in procedures requiring precise and extensive dissection such as D2 lymphadenectomy[1]. The robotic platform enhances three-dimensional visualization, offers tremor filtration, and allows for articulated instrument control, potentially improving outcomes in complex oncological surgery[2]. Yet, these advantages may be undermined if port configurations do not align with the robotic system’s unique spatial and functional requirements, distinct from those of traditional laparoscopy. Historically, many robotic surgeons initially adopted laparoscopic port placements with minimal adjustment[3][4]. This direct translation often led to suboptimal ergonomics for the surgeon, increased risk of instrument collision (both external and internal), and limited assistant functionality, particularly in confined spaces or during multi-quadrant surgery[5][6]. The need for a robotics-specific port placement strategy is critical to harness the full potential of robotic surgery, especially in anatomically complex areas such as the suprapancreatic region during D2 gastrectomy. D2 lymphadenectomy necessitates extensive node dissection along major perigastric vessels, including the left gastric, common hepatic, splenic, and celiac arteries[7]. These areas require unobstructed access, stable retraction, and clear visualization—tasks frequently complicated by poorly designed or non-optimized trocar setups. This review examines the evolution of port strategies in robotic gastrectomy, discusses current challenges and technical solutions reported in the literature, and synthesizes principles for an optimized configuration that prioritizes surgical fluency, safety, and team coordination.

Background: Kinase inhibitors (KIs) are mainstays of targeted cancer therapy, but their clinical utility is frequently limited by cardiotoxicity. A systematic resource to explore the underlying causal mechanisms is urgently needed. Methods: We present the KICDB ( Kinase Inhibitor Cardiotoxicity Data base), a comprehensive and interactive web server. KICDB is built upon a framework integrating large-scale transcriptomics meta-analysis with causal inference. Results: This database centralizes the findings from a comprehensive meta-analysis of 26 kinase inhibitors (KIs) across 7 studies (n=5291) identified 8,907 significant gene expression changes in human cardiomyocytes. To establish causality, we performed a two-pronged Mendelian randomization (MR) analysis testing hundreds of downstream genes and a panel of 43 key kinase proteins against 46 cardiovascular outcomes. This large-scale analysis revealed 26 significant causal associations, implicating novel molecular mediators in KI-induced cardiotoxicity. Conclusions: KICDB serves as a valuable and accessible platform for the cardio-oncology community. By integrating transcriptomic signatures with causal inference data, the database empowers researchers to formulate mechanistic hypotheses, accelerate biomarker validation, and guide the design of future cardioprotective strategies.