Comprehensive assessment of body mass index effects on short-term and long-term outcomes in laparoscopic gastrectomy for gastric cancer: a retrospective study.

To examine the influence of Body Mass Index (BMI) on laparoscopic gastrectomy (LG) short-term and long-term outcomes for gastric cancer. A retrospective analysis was conducted on gastric cancer patients undergoing LG at the Third Hospital of Nanchang City from January 2013 to January 2022. Based on WHO BMI standards, patients were categorized into normal weight, overweight, and obese groups. Factors such as operative time, intraoperative blood loss, postoperative complications, and overall survival were assessed. Across different BMI groups, it was found that an increase in BMI was associated with longer operative times (average times: 206.22 min for normal weight, 231.32 min for overweight, and 246.78 min for obese), with no significant differences noted in intraoperative blood loss, postoperative complications, or long-term survival among the groups. The impact of BMI on long-term survival following LG for gastric cancer was found to be insignificant, with no notable differences in survival outcome between different BMI groups. Although higher BMI is associated with increased operative time in LG for gastric cancer, it does not significantly affect intraoperative blood loss, postoperative complications, recovery, or long-term survival. LG is a feasible treatment choice for obese patients with gastric cancer.

Effects of erythromycin on biofilm formation and resistance mutation of Escherichia coli on pristine and UV-aged polystyrene microplastics.

Microplastics (MPs) and antibiotics co-occur widely in the environment and pose combined risk to microbial communities. The present study investigated the effects of erythromycin on biofilm formation and resistance mutation of a model bacterium, E. coli, on the surface of pristine and UV-aged polystyrene (PS) MPs sized 1-2 mm. The properties of UV-aged PS were significantly altered compared to pristine PS, with notable increases in specific surface area, carbonyl index, hydrophilicity, and hydroxyl radical content. Importantly, the adsorption capacity of UV-aged PS towards erythromycin was approximately 8-fold higher than that of pristine PS. Biofilms colonizing on UV-aged PS had a greater cell count (5.6 × 108 CFU mg-1) and a higher frequency of resistance mutation (1.0 × 10-7) than those on pristine PS (1.4 × 108 CFU mg-1 and 1.4 × 10-8, respectively). Moreover, erythromycin at 0.1 and 1.0 mg L-1 significantly (p < 0.05) promoted the formation and resistance mutation of biofilm on both pristine and UV-aged PS. DNA sequencing results confirmed that the biofilm resistance was attributed to point mutations in rpoB segment of the bacterial genome. qPCR results demonstrated that both UV aging and erythromycin repressed the expression levels of a global regulator rpoS in biofilm bacteria, as well as two DNA mismatch repair genes mutS and uvrD, which was likely to contribute to increased resistance mutation frequency.

A degradome-related signature for predicting the prognosis and immunotherapy benefit in stomach adenocarcinoma based on machine learning procedure.

Stomach adenocarcinoma (STAD) is one of the subtype of gastric cancer with high invasiveness, extreme heterogeneity, high morbidity, and high mortality. The degradome is the most abundant class of cellular enzymes that play an essential role in regulating cellular activity and carcinogenesis. An integrative machine learning procedure including 10 methods was performed to develop a prognostic degradome-based prognostic signature (DPS) in TCGA, GSE15459, GSE26253, and GSE62254 datasets. Investigations of the DPS concerning immune infiltration, immunotherapy benefits, and drug priority were orchestrated. The DPS developed by Enet [alpha = 0.3] method was regarded as the optimal prognostic model. The DPS had a stable and powerful performance in predicting the clinical outcome of STAD and served as an independent risk factor in training and testing cohorts. The C-index of DPS was higher than that of age, sex, and clinical stage. STAD patients with low DPS scores had a higher abundance of B cells, CD8+ T cells, higher cytolytic scores, and T cell co-stimulation scores. Moreover, low DPS score indicated a lower tumor immune dysfunction and exclusion score, lower T cell dysfunction and exclusion score, higher PD1&CTLA4 immunophenoscore, and higher tumor mutation burden score in STAD, demonstrating a better immunotherapy response. STAD patients with a high DPS score had a lower IC50 value of common chemotherapy and targeted therapy regimens (Cisplatin, Docetaxel, Gefitinib, etc). Our study developed an optimal DPS for STAD. The DPS could predict the prognosis, risk stratification and guide treatment for STAD patients.

A prognostic nomogram for recurrence survival in post-surgical patients with varicose veins of the lower extremities.

Varicose veins of the lower extremities (VVLEs) are prevalent globally. This study aims to identify prognostic factors and develop a prediction model for recurrence survival (RS) in VVLEs patients after surgery. A retrospective analysis of VVLEs patients from the Third Hospital of Nanchang was conducted between April 2017 and March 2022. A LASSO (Least Absolute Shrinkage and Selection Operator) regression model pinpointed significant recurrence predictors, culminating in a prognostic nomogram. The model's performance was evaluated by C-index, receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). The LASSO regression identified seven predictors for the nomogram predicting 1-, 2-, and 5-year RS. These predictors were age, body mass index (BMI), hypertension, diabetes, the Clinical Etiological Anatomical Pathophysiological (CEAP) grade, iliac vein compression syndrome (IVCS), and postoperative compression stocking duration (PCSD). The nomogram's C-index was 0.716, with AUCs (Area Under the Curve scores) of 0.705, 0.725, and 0.758 for 1-, 2-, and 5-year RS, respectively. Calibration and decision curve analyses validated the model's predictive accuracy and clinical utility. Kaplan-Meier analysis distinguished between low and high-risk groups with significant prognostic differences (P < 0.05). This study has successfully developed and validated a nomogram for predicting RS in patients with VVLEs after surgery, enhancing personalized care and informing clinical decision-making.