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Objective: This study aimed to explore the predictive value of baseline CT body composition and its early changes on recurrence-free survival (RFS) following radical gastrectomy, while also assessing potential sex-related differences.

Methods: We conducted a retrospective analysis of gastric cancer (GC) patients with confirmed pathology from October 2019 to May 2023. All patients underwent preoperative and postoperative CT scans to assess visceral fat area (VFA), subcutaneous fat area (SFA), skeletal muscle area (SMA), and skeletal muscle density (SMD), along with calculating their respective rates of change.

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Exploring Dysphagia in Congenital Diaphragmatic Hernia: A Retrospective Analysis.

Pediatr Rep

January 2025

Department of Pediatric Surgery, Division of Pediatric Surgery, Baylor College of Medicine, Houston, TX 77030, USA.

Congenital diaphragmatic hernia (CDH) is a complex congenital disorder often accompanied by long-term feeding difficulties. There is a paucity of published data regarding the impact of swallowing difficulties on long-term patient outcomes. Our study attempts to evaluate this phenomenon.

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Gastric cancer is the fifth most common cancer and the fourth leading cause of cancer-related deaths worldwide, accounting for nearly 800,000 fatalities annually. ITGAX (Integrin alpha X) is closely associated with immune cells, such as macrophages and dendritic cells. Its involvement in gastric cancer was identified through an analysis of The Gene Expression Omnibus (GEO) database, which highlighted as one of four key gastric cancer-related genes.

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Objective: Gastric cancer (GC) is a common malignant tumor of the digestive tract. Accumulating studies suggest that inflammation is linked with the pathogenesis of GC. The study delves into novel hematological inflammatory markers, such as systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and prognostic nutritional index (PNI), to explore their potential applications in early diagnosis of GC.

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Background: Endoscopic diagnosis of early gastric cancer (EGC) is a challenge. It is not clear whether deep convolutional neural network (DCNN) model could improve the endoscopists' diagnostic performance.

Methods: We established a DCNN-assisted system and found that accuracy of diagnosis is higher than endoscopists.

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