To investigate the unexplored therapeutic potential and identify the specific molecular targets of homoharringtonine (HHT) in gastric cancer (GC). HHT’s efficacy was evaluated in GC cell lines (MKN1/MKN45), normal epithelial cells (GES-1), and an HGC27 xenograft model. Mechanisms were investigated using RNA-sequencing, microscale thermophoresis (MST), molecular docking, and biochemical assays. HHT suppressed GC cell proliferation and migration, inducing G1-phase arrest and apoptosis, while demonstrating lower cytotoxicity toward normal GES-1 cells. MST and docking assays confirmed that HHT directly and stably binds to AKT (KD= 6.496 nM) and suppresses the PI3K/AKT/FOXO/GSK3β signaling pathway. Concurrently, transcriptomic profiling and experimental validation showed that HHT disrupts glutathione metabolism. It depleted intracellular GSH and downregulated GPX4, triggering ferroptosis-like oxidative damage and mitochondrial cristae loss. In vivo, HHT inhibited GC xenograft tumor growth without causing systemic toxicity, which was accompanied by decreased Ki-67 and increased Caspase-3 expression. HHT inhibits GC progression by suppressing AKT-mediated tumor growth and inducing GPX4-dependent ferroptosis. These findings highlight HHT as a promising targeted therapeutic for GC.
This review comprehensively summarizes the latest research progress on the optimal timing for colostomy reversal, a critical surgical intervention aimed at restoring normal bowel function and improving the quality of life of patients with colostomies. Colostomy is commonly performed for various gastrointestinal conditions, including colorectal cancer, diverticulitis, and inflammatory bowel diseases, but its long-term presence imposes physical and psychological burdens on patients. The timing of reversal directly affects postoperative recovery, complication rates, and overall patient outcomes, making it a key focus of clinical research. This article systematically explores the multifaceted factors influencing reversal timing, such as individual patient characteristics (age, comorbidities, nutritional status, psychological readiness), postoperative complications (anastomotic leaks, infections, bowel obstruction), and surgical considerations (colostomy type, surgical technique, enhanced recovery after surgery protocols). By analyzing current literature, the review identifies existing gaps and inconsistencies in clinical practice, highlighting the lack of standardized guidelines for reversal timing. The core goal of this work is to integrate evidence from recent studies to provide clinical practitioners with actionable insights for individualized decision-making, optimize colostomy management strategies, minimize complications such as surgical site infections and anastomotic leaks, and ultimately enhance the recovery experience and long-term quality of life of patients undergoing colostomy reversal. Additionally, the review emphasizes the importance of multidisciplinary collaboration and personalized care in addressing the complex needs of patients, laying a foundation for the development of evidence-based clinical guidelines in the future.
Glucose transporter 1 (GLUT1), the most extensively distributed member of the glucose transporter protein family, plays a pivotal role in regulating glucose metabolism and is indispensable for cellular growth, proliferation, and differentiation. Various metabolic disorders arise from the dysregulation of GLUT1 expression, which disrupts glucose homeostasis. The upregulation of GLUT1 has been identified in multiple cancer cells, facilitating tumor progression, metastasis, and resistance to treatment. Recent years have seen a surge in the discovery of GLUT1 inhibitors exhibiting improved selectivity and efficacy. Herein, we introduce the structure and biological function of GLUT1, GLUT1 related oncogenesis, and primarily focuses on recent advancements in the study of GLUT1 inhibitors over the last decade. Notably, this review is restricted to inhibitors that act through direct interaction with the GLUT1 protein, excluding agents that exert indirect effects via upstream signaling or metabolic regulation.
Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have become an important option in clinical use for type 2 diabetes due to their dual benefits of glycaemic management and metabolic improvements. Efsubaglutide alfa, a novel long-acting GLP-1RA, was developed for sustained glycaemic management. This study aimed to confirm its recommended clinical dose and evaluate its efficacy and safety in drug-naive individuals with type 2 diabetes that was inadequately managed through lifestyle interventions. This two-stage Phase IIb/III trial employed an operationally seamless adaptive design and enrolled adults who had been newly diagnosed with type 2 diabetes and whose diabetes was inadequately managed by diet and exercise. In the Phase IIb stage, participants were randomised in a 2:2:2:1 ratio to receive once-weekly subcutaneous injections of efsubaglutide alfa (1, 2 or 3 mg) or placebo for 12 weeks. Based on an interim analysis, two recommended Phase III doses (RP3Ds) were selected by an independent data monitoring committee. In the Phase III stage, participants were randomised in a 2:2:1 ratio to receive efsubaglutide alfa at one of the two RP3Ds or to receive placebo. Participants, investigators and sponsors were masked to drug/placebo allocation throughout the trial. The primary endpoint was the change in HbA1c from baseline to week 24. Secondary endpoints included changes in body weight and metabolic parameters at weeks 24 and 52. Safety was monitored throughout. In the Phase IIb stage, 140 participants were randomised to efsubaglutide alfa (1 mg, n=41; 2 mg, n=39; 3 mg, n=41) or placebo (n=19). Based on interim analysis, 1 and 3 mg were selected as the RP3Ds. In the Phase III stage, 297 participants were randomised to efsubaglutide alfa (1 mg, n=118; 3 mg, n=117) or placebo (n=62). At week 24, the HbA1c reductions from baseline were −18.91 mmol/mol (1.73
BackgroundThe critical need for precise risk stratification in severe liver cirrhosis is underscored by its substantial 30-day mortality rates, demanding reliable tools to guide clinical interventions.ObjectiveTo establish a machine learning-driven prognostic model for short-term mortality prediction in decompensated cirrhosis through comprehensive analysis of critical care data.MethodsThis retrospective cohort study analyzed 1,044 carefully curated cases from the MIMIC-IV database, randomly divided into training (n = 740) and validation (n = 304) sets. We developed a machine learning model incorporating multidimensional clinical parameters, with rigorous evaluation and internal validation. Short-term survival was analyzed via bootstrap-validated Cox proportional hazards regression. Prognostic heterogeneity across international normalized ratio (INR)-based strata was examined.ResultsThe final prediction model incorporated eight significant predictors: age (OR 1.051, 95% CI 1.033-1.070), INR (OR 1.423, 95%CI 1.231-1.644), creatinine (OR 1.171, 95%CI 1.071-1.208), platelets (OR 0.995, 95%CI 0.993-0.997), white blood cell (OR 1.116, 95%CI 1.078-1.155), total bilirubin (OR 1.027, 95%CI 1.002-1.052), peptic ulcer (OR 0.336, 95%CI 0.134-0.845), and Aspartate Aminotransferase/Alanine Aminotransferase (AST/ALT) (OR 1.508, 95%CI 1.294-1.757). The model demonstrated excellent discrimination with an AUC of 0.846 in the training cohort. Cox regression analysis confirmed these findings and identified additional associations with aspartate aminotransferase and red blood cell levels. Furthermore, the indicators within the model provide accurate predictions for the clinical outcomes of patients suffering from severe cirrhosis. Subgroup analysis revealed significant mortality variations across different INR ranges (P < 0.001).ConclusionsOur prediction model identifies high-risk cirrhotic patients and highlights critical prognostic factors, offering clinicians a valuable tool for risk stratification and timely intervention. The strong correlation between laboratory markers, complications, and outcomes underscores the importance of close monitoring in this population. However, our model is an initial step, effective within the ICU but requiring external, multi-center studies to broaden its clinical applicability, which is a clear priority for our future work.
