Timing and adequacy of peritoneal source control are the most important pillars in the management of patients with acute peritonitis. Therefore, early prognostic evaluation of acute peritonitis is paramount to assess the severity and establish a prompt and appropriate treatment. The objectives of this study were to identify clinical and laboratory predictors for in-hospital mortality in patients with acute peritonitis and to develop a warning score system, based on easily recognizable and assessable variables, globally accepted. This worldwide multicentre observational study included 153 surgical departments across 56 countries over a 4-month study period between February 1, 2018, and May 31, 2018. A total of 3137 patients were included, with 1815 (57.9%) men and 1322 (42.1%) women, with a median age of 47 years (interquartile range [IQR] 28–66). The overall in-hospital mortality rate was 8.9%, with a median length of stay of 6 days (IQR 4–10). Using multivariable logistic regression, independent variables associated with in-hospital mortality were identified: age > 80 years, malignancy, severe cardiovascular disease, severe chronic kidney disease, respiratory rate ≥ 22 breaths/min, systolic blood pressure < 100 mmHg, AVPU responsiveness scale (voice and unresponsive), blood oxygen saturation level (SpO2) < 90% in air, platelet count < 50,000 cells/mm3, and lactate > 4 mmol/l. These variables were used to create the PIPAS Severity Score, a bedside early warning score for patients with acute peritonitis. The overall mortality was 2.9% for patients who had scores of 0–1, 22.7% for those who had scores of 2–3, 46.8% for those who had scores of 4–5, and 86.7% for those who have scores of 7–8. The simple PIPAS Severity Score can be used on a global level and can help clinicians to identify patients at high risk for treatment failure and mortality.

Background: Surgical site infections (SSIs) represent a noteworthy contributor to both morbidity and mortality in the context of patients who undergo colorectal surgery. Several risk factors have been identified; however, their relative significance remains uncertain. Methods: We conducted a meta-analysis of observational studies from their inception up until 2023 that investigated risk factors for SSIs in colorectal surgery. A random-effects model was used to pool the data and calculate the odds ratio (OR) and 95% confidence interval (CI) for each risk factor. Results: Our analysis included 26 studies with a total of 61,426 patients. The pooled results showed that male sex (OR = 1.45), body mass index (BMI) ≥ 25 kg/m² (OR = 1.09), American Society of Anesthesiologists (ASA) score ≥ 3 (OR = 1.69), were all independent risk factors for SSIs in colorectal surgery. Conversely, laparoscopic surgery (OR = 0.70) was found to be a protective factor. Conclusions: The meta-analysis conducted revealed various risk factors, both modifiable and non-modifiable, associated with surgical site infections (SSIs) in colorectal surgery. These findings emphasize the significance of targeted interventions, including optimizing glycemic control, minimizing blood loss, and using laparoscopic techniques whenever feasible in order to decrease the occurrence of surgical site infections in this particular group of patients.

Therapeutic approaches focused on the inflammatory microenvironment are currently gaining more support, as biomolecules involved in the inflammatory colorectal cancer (CRC) tumor microenvironment are being explored. We analyzed tumor and paired normal tissue samples from CRC patients (n = 22) whom underwent tumor resection surgery. We assessed 39 inflammation-involved biomolecules (multiplex magnetic bead-based immunoassay), CEA and CA19-9 (ELISA assay) and the tissue expression levels of occludin and also pErk, STAT1 and STAT3 transcriptional factors (western blot). Tumor staging has been established by histopathological evaluation of HE stained tumor tissue sections. We report 32 biomarkers displaying statistically significant differences in tumor vs. control. Additionally, positive statistical biomarker correlations were found between MMP2–IL8 and BAFF–IL8 (Pearson correlation coefficients > 0.751), while APRIL–MMP2, APRIL–BAFF and APRIL–IL8 were negatively correlated (correlation coefficients < − 0.650). While APRIL, BAFF, IL8 and MMP2 did not modulate with tumor stage, they were inversely related to the immune infiltrate level and CD163 tissue expression. We conclude that the significantly decreased APRIL and increased BAFF, IL8 and MMP2 expression were tumor-specific and deserve consideration in the development of new treatments. Also, the positive correlation between Chitinase 3-like 1 and IL8 (0.57) or MMP2 (0.50) suggest a role in tumor growth and metastasis pathways.

Background: Artificial intelligence is emerging as a promising tool in surgical oncology, with growing evidence suggesting potential applications in diagnostic support, intraoperative guidance, and perioperative risk assessment. In gastric cancer surgery, emerging applications range from AI-assisted endoscopic detection to data-driven perioperative risk prediction, while some technological developments, particularly in robotic autonomy, derive from broader surgical or experimental models that may inform future gastric procedures. Methods: A narrative review was conducted following established methodological standards, including the Scale for the Assessment of Narrative Review Articles (SANRA) and the Search–Appraisal–Synthesis–Analysis (SALSA) framework. English-language studies indexed in PubMed, Scopus, Embase, and Web of Science up to October 2025 were included. Evidence was synthesized thematically across five domains: AI-assisted anatomical recognition and lymphadenectomy support, autonomous robotic systems, early cancer detection, perioperative predictive and frailty models, and ethical and regulatory considerations. Results: AI-based computer vision and deep learning algorithms have demonstrated promising capabilities for real-time anatomical recognition, surgical phase classification, and intraoperative guidance, although evidence of direct patient-level benefit remains limited. In diagnostic settings, AI-assisted endoscopy and Raman spectroscopy have been shown to improve early lesion detection and reduce dependence on operator experience. Predictive models, including MySurgeryRisk and AI-driven frailty assessments, may support individualized prehabilitation planning and perioperative risk stratification. Persistent limitations include small and heterogeneous datasets, insufficient external validation, and unresolved concerns related to data privacy, algorithmic interpretability, and medico-legal responsibility. Conclusions: Artificial intelligence is progressively emerging as a promising tool in gastric cancer surgery, integrating automation, advanced analytics, and human clinical reasoning. Its safe and ethical adoption requires robust validation, transparent governance, and continuous surgeon oversight. When developed within human-centered and ethically grounded frameworks, AI can augment, rather than replace, surgical expertise, potentially advancing precision, safety, and equity in oncologic care.

The number of colon cancer cases is increasing worldwide, and type II diabetes patients have an increased risk of developing colon cancer. Diet-borne advanced glycation end-products (AGEs) may promote neoplastic transformation; however, the mechanisms involved remain elusive. The present study helped to define the relationship between dietary AGEs and cancer progression. C2BBe1 adenocarcinoma enterocytes were exposed to 200 µg/mL glycated casein (AGEs-Csn) for up to 24 h. AGEs-Csn exposure resulted in increased cell proliferation, maladaptative changes in SOD and CAT activity and moderate levels of hydrogen peroxide (H₂O₂) intracellular accumulation. AGEs-Csn activated pro-survival and proliferation signalling, such as the phosphorylation of mTOR (Ser2448) and Akt (Ser473). GSK-3β phosphorylation also increased, potentially inducing extracellular matrix remodelling and thus enabling metastasis. Moreover, AGEs-Csn induced MMP-1, -3, -7, -9 and -10 expression and activated MMP-2 and MMP-9, which are regulators of the extracellular matrix and cytokine functions. AGEs-Csn induced inflammatory responses that included extracellular IL-1β at 6 h; time-dependent increases in IL-8; RAGE and NF-κB p65 upregulation; and IκB inhibition. Co-treatment with anti-RAGE or anti-TNF-α blocking antibodies and AGEs-Csn partially counteracted these changes; however, IL-8, MMP-1 and -10 expression and MMP-9 activation were difficult to prevent. AGEs-Csn perpetuated signalling that led to cell proliferation and matrix remodelling, strengthening the link between AGEs and colorectal cancer aggressiveness.

Background: Esophageal cancer, the seventh most common malignancy globally, requires esophagectomy for curative treatment. However, esophagectomy is associated with high postoperative morbidity and mortality, highlighting the need for minimally invasive approaches. Robotic-assisted surgery has emerged as a promising alternative to traditional open and minimally invasive esophagectomy (MIE), offering potential benefits in improving clinical and oncological outcomes. This review aims to assess the postoperative morbidity and outcomes of robotic surgery. Methods: A comprehensive review of the current literature was conducted, focusing on studies evaluating the role of robotic-assisted surgery in esophagectomy. Data were synthesized on the clinical outcomes, including postoperative complications, survival rates, and recovery time, as well as technological advancements in robotic surgery platforms. Studies comparing robotic-assisted esophagectomy with traditional approaches were analyzed to determine the potential advantages of robotic systems in improving surgical precision and patient outcomes. Results: Robotic-assisted esophagectomy (RAMIE) has shown significant improvements in clinical outcomes compared to open surgery and MIE, including reduced postoperative pain, less blood loss, and faster recovery. RAMIE offers enhanced thoracic access, with fewer complications than thoracotomy. The RACE technique has improved patient recovery and reduced morbidity. Fluorescence-guided technologies, including near-infrared fluorescence (NIRF), have proven valuable for sentinel node biopsy, lymphatic mapping, and angiography, helping identify critical structures and minimizing complications like anastomotic leakage and chylothorax. Despite these benefits, challenges such as the high cost of robotic systems and limited long-term data hinder broader adoption. Hybrid approaches, combining robotic and open techniques, remain common in clinical practice. Conclusions: Robotic-assisted esophagectomy offers promising advantages, including enhanced precision, reduced complications, and faster recovery, but challenges related to cost, accessibility, and evidence gaps must be addressed. The hybrid approach remains a valuable option in select clinical scenarios. Continued research, including large-scale randomized controlled trials, is necessary to further establish the role of robotic surgery as the standard treatment for resectable esophageal cancer.