Low rectal cancer accounts for a high proportion of colorectal cancer cases in China, and the choice of treatment strategies critically impacts patient prognosis and quality of life. With the advancement of precision treatment, clinical decision-making requires integrating multi-dimensional factors to move beyond the traditional "one-size-fits-all" approach. The authors focus on the anatomical complexity, high recurrence risk, and functional preservation demands of low rectal cancer, incorporating the latest research advances to explore precision treatment pathways in terms of preoperative high-resolution magnetic resonance imaging assessment, breakthroughs in immunotherapy and precision surgical techniques. Future efforts should further optimize individua-lized strategies through multimodal assessment and multidisciplinary collaboration, refining inte-grated approaches based on evidence-based medicine to enhance clinical efficacy and patient survival outcomes.

With the rapid development of minimally invasive techniques in surgery, arti-ficial intelligence (AI), particularly deep learning, is playing an increasingly important role in mini-mally invasive surgery. By automated analysis of surgical videos, AI can efficiently perform key tasks such as instrument recognition, surgical phase identification, action analysis, anatomical structure recognition, intraoperative diagnosis, adverse event monitoring and smart desmoking. These appli-cations provide essential support for real-time monitoring, surgical navigation and skill assessment during surgery. The authors summarize the current research progress of AI in minimally invasive surgery, including its applications in the fields of hepatobiliary and pancreatic surgery, as well as gastrointestinal surgery. It also explores the potential of AI in enhancing surgical safety, efficiency and skill assessment. By synthesizing the latest research achievements of AI technology in the field of surgery, as well as analyzing its technical challenges and risks, it aims to provide guidance for future innovations and clinical applications, promoting the advancement and implementation of AI in minimally invasive surgery.

Colorectal cancer is one of the most common malignant tumors in the digestive system, posing a serious threat to human health. In recent years, with the rapid development of medical technology, the treatment model for colorectal cancer has undergone profound changes, gradually shifting from traditional single-surgery treatment to multidisciplinary team (MDT) treat-ment. The concept of precision medicine has been deeply integrated into the entire process of colo-rectal cancer treatment, aiming not only to achieve radical tumor removal but also to focus on impro-ving postoperative quality of life of patients. In surgical treatment, accurate grasping of operative opportunity and precise preservation of anus have become key factors in enhancing the effectiveness of colorectal cancer treatment. Current research and trends are dedicated to addressing these issues. Tailored treatments based on individual patient conditions and highly personalized treatment plans aim to achieve optimal outcomes while minimizing adverse reactions. This philosophy is reflected in multiple aspects of colorectal cancer treatment, including precise judgment of surgical timing, accurate selection of sphincter-preserving surgery, and meticulous application of surgical techniques. After reviewing relevant literature both domestically and internationally, combined with practical experi-ence, the authors focus on the selection of surgical timing under neoadjuvant therapy, precise sphincter-preserving strategies, and the critical role of surgical techniques in sphincter preservation.

Objective:To investigate the clinical characteristics and prognosis of acute pancreatitis (AP) with different etiologies.Methods:The retrospective cohort study was conducted. The clinical data of 702 patients with AP who were admitted to Xuanwu Hospital of Capital Medical University from January 2018 to December 2022 were collected. There were 451 males and 251 females,aged (52±17)years. Observation indicators: (1) clinical characteristics of AP patients with different etiologies; (2) complications and prognosis of AP patients with different etiologies; (3) complications and prognosis of moderately severe and severe AP patients with different etiologies. Comparison of measurement data with normal distribution among multiple groups was conducted using the one-way analysis of variance. Comparison of measurement data with skewed distribution among multiple groups was conducted using the Kruskal-Wallis H test. Comparison of count data among multiple groups was conducted using the chi-square test. Results:(1) Clinical characteris-tics of AP patients with different etiologies. Of the 702 AP patients, 434 cases were biliary AP, 199 cases were hypertriglyceridemic-induced AP,29 cases were alcoholic AP, and 40 cases were idiopathic AP. There were significant differences in gender,age,body mass index,combined cardiovascular disease,combined diabetes,combined nephrosis,disease severity and modified computed tomography severity index among AP patients with different etiologies ( χ2=24.61, F=48.65, 12.24, χ2=13.67, 12.90, 14.12, 15.56, H=17.62, P<0.05). (2) Complications and prognosis of AP patients with different etiologies. There was no significant difference in infectious pancreatic necrosis,duration of intensive care unit stay,total duration of hospital stay, and death of patients during hospitalization among AP patients with different etiologies ( P>0.05). (3) Complications and prognosis of moderately severe and severe AP patients with different etiologies. Of the 395 patients with moderately severe and severe AP, 217 cases were biliary AP, 128 cases were hypertriglyceridemic-induced AP, 19 cases were alcoholic AP, and 31 cases were idiopathic AP. There were significant differences in renal injury, multiple organ dysfunction syndrome and walled-off necrosis among moderately severe and severe AP patients with different etiologies ( χ2=12.62, 8.25, 14.33, P<0.05), and there was no significant difference in infectious pancreatic necrosis, lung injury, circulation system injury, duration of intensive care unit stay, total duration of hospital stay, or death of patients during hospitalization among moderately severe and severe AP patients with different etiologies ( P>0.05). Conclusions:The clinical charac-teristics vary among AP patients with different etiologies. The risk of complications varies among moderately severe and severe AP patients with different etiologies.

Objective:To investigate the application value of robotic-assisted surgery for pancreatic cancer after neoadjuvant chemotherapy (NAT).Methods:The retrospective and descrip-tive study was conducted. The clinicopathological data of 10 pancreatic cancer patients who underwent robotic-assisted surgery after NAT at The First Affiliated Hospital of Sun Yat-sen University from November 2021 to January 2025 were collected. There were 7 male and 3 female, aged (62±7)years. Observation indicators: (1) NAT conditions; (2) intraoperative conditions; (3) postoperative condi-tions; (4) follow-up. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M(range). Count data were described as absolute numbers. The Kaplan-Meier method was used to calculate survival time. Results:(1) NAT conditions. Of the 10 patients, 4 cases had tumor surrounding the portal vein or superior mesenteric vein more than 180° (no invasion of superior mesenteric artery), 3 cases had concomitant hepatic oligometastasis, and 3 cases had tumor invasion of adjacent organ (2 cases with tumor invasion of left kidney, 1 case with tumor invasion of duodenum). Nine of the 10 patients received chemotherapy of gemcitabine+albumin-paclitaxel, and the other 1 patient received chemo-therapy of fluorouracil + irinotecan + oxaliplatin. After treatment, 3 patients were evaluated as partial remission and 7 patients were evaluated as stable disease. (2) Intraoperative conditions. Of the 10 patients, 5 cases received robotic-assisted pancreatoduodenectomy and 5 cases received robotic-assisted radical antegrade modular pancreatosplenectomy, with no case converted to open surgery. There were 3 cases receiving combined vascular resection and reconstruction, including 2 cases with portal vein resection plus side wall repairing and 1 case with superior mesenteric vein resection plus end to end anastomosis. There were 2 cases receiving combined other organ resection intra-operatively, including 1 case with local hepatectomy and 1 case with left nephrectomy. The operation time of 10 patients was 465(range, 195?565)minutes, volume of intraoperative blood loss was 70(range, 20?350)mL. One case with preoperative anemia required red blood cell transfusion during the operation, while the other cases did not receive any transfusion during the operation. All 10 patients achieved R 0 resection and the number of lymph node dissected was 12±8. Three patients who underwent combined vascular resection and reconstruction had negative margin of the portal vein or superior mesenteric vein. (3) Postoperative conditions. Duration of postoperative hospital stay of 10 patients was (15±8)days, and 1 case developed major complications in grade Ⅲa of Clavein-Dindo classfication. Of the 10 patients, 1 case developed grade B pancreatic fistula, 1 case experienced delayed gastric emptying, and no case had postoperative biliary fistula, chyle leakage, abdominal or anastomotic bleeding, no case underwent reoperation, no case died within postoperative 30 days. (4) Follow-up. All 10 patients were followed up after surgery for 10.0(range, 2.7?40.4)months. All 10 patients underwent postoperative adjuvant chemotherapy, and the time from surgery to the start of adjuvant chemotherapy was (40±12)days. The median overall survival time of 10 patients was 30.4 months, and the median recurrence-free survival time was 10.9 months. Conclusion:Robotic-assisted surgery can be used for pancreatic cancer after neoadjuvant chemotherapy.

Objective:To investigate the predictive efficacy of Delta radiomics for the patholo-gical complete remission (pCR) of pancreatic cancer after total neoadjuvant therapy (TNT).Methods:The retrospective cohort study was conducted. The clinicopathological data of 263 patients with pancreatic cancer who were admitted to Henan Provincial People′s Hospital (Zhengzhou University People's Hspital) from January 2019 to September 2024 were collected. There were 166 males and 97 females, aged (56±12)years. All patients underwent TNT. The 263 patients were randomly divided into a training set of 184 cases and a test set of 79 cases using a 7∶3 random seed count. The training set was used to construct the prediction model, and the test set was used to validate the performance of the prediction model. Observation indicators: (1) postoperative and follow-up condi-tions; (2) imaging feature selection and model construction; (3) evaluation of predictive efficacy of different radiomic models. Comparison of measurement data with normal distribution between groups was conducted using the t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. The Kaplan-Meier method was used to calculate the survival rate and draw survival curve. The Log-rank test was used for survival analysis. The perfor-mance of the prediction model for pCR after TNT was evaluated using the receiver operator charac-teristic (ROC) curve, precision-recall (P-R) curve and Bootstrap method, along with the calculation of area under the curve (AUC), precision rate, recall rate, F1-score. Results:(1) Postoperative and follow-up conditions. All 263 patients underwent surgery after TNT, with pathological examination revealing 124 cases of pCR (86 cases in the training set, 38 cases in the test set) and 139 cases of non-pCR (98 cases in the training set, 41 cases in the test set), respectively. All 263 patients were followed up for 6(range, 3-12) months after surgery, of which 15 cases (4 cases of pCR and 11 cases of non-pCR) were lost to follow-up or died due to non-tumor reasons within 6 months after surgery. The postoperative 6-month recurrence-free survival rate of 124 pCR patients and 139 non-pCR patients were 80% and 50%, respectively, showing a significant difference between the two groups of patients ( χ2=22.84, P<0.05). (2) Imaging feature selection and model construction. Construction of the traditional radiology model: based on the response evaluation criteria in solid tumors 1.1, the Logistic regression model was constructed using the relative shrinkage (D%) as a predictive variable. The AUC of traditional radiology model was 0.72 [95% confidence interval ( CI) as 0.63?0.81] in the training set and 0.75 (95% CI as 0.66?0.84) in the test set, respectively. Construction of the Delta radiomics model: 10 non-zero coefficient features were selected. The Delta radiomics models were constructed by using the regularized Logistic regression, random forest, gradient boosting machine, and support vector machine algorithms through using selected features as input variables. (3) Evaluation of predictive efficacy of different radiomic models. The AUC of Delta radiomics model constructed by regularized Logistic regression algorithm in the test set for predicting pCR in pancreatic cancer after TNT was 0.90, higher than that of the random forest algorithm, gradient boosting machine algorithm, support vector machine algorithm (AUC as 0.81, 0.81, 0.83), and higher than that of the traditional radiology model (AUC as 0.72). Results of Bootstrap method revealed significant differences in the predictive efficacy of Delta radiomics model constructed by regularized Logistic regression algorithm compared to the Delta radiomics model constructed by random forest algorithm, gradient boosting machine algorithm, support vector machine algorithm and the tradi-tional radiology model (95% CI as 0.03?0.16, 0.03?0.16, 0.03?0.13, 0.08?0.29, P<0.05). The regularized Logistic regression algorithm within the Delta radiomics model demonstrated the best overall performance among the above models evaluated. Conclusion:Compared to the traditional radiology model, the Delta radiomics model offers superior efficacy in predicting pCR of pancreatic cancer after TNT, in which the regularized Logistic regression algorithm demonstrates the best overall performance metrics.

In 2025, coinciding with the 110th anniversary of the establishment of Chinese Medical Association, the authors systematically review the evolution of liver cancer research and liver surgery in China from its infancy to systematic development, and summarize the unremitting efforts and outstanding contributions made by the Chinese Medical Association in the field of liver cancer research in China, focusing on four technical dimensions: the update of surgical resection technology, breakthroughs in liver transplantation technology, the establishment of liver cancer transformation treatment paradigm, and the construction of Chinese characteristic liver cancer staging. With the elaborating on the development trajectory of the discipline in detail, and analysis of key historical nodes and major milestone events, the authors aim to provide historical insights for the prevention and treatment of liver cancer in China, and provide reference for future development directions.

As the Chinese Medical Association (CMA) marks its 110th anniversary, the authors reflect with profound admiration on the groundbreaking contributions made by its founders Wu Lien-teh, Yan Fuqing, etc. since its establishment in 1915. Their visionary work laid the founda-tion for China's medical advancement. The year 2025 also commemorates the 24th anniversary of the Chinese Journal of Digestive Surgery. This milestone prompts the authors to revisit the enduring academic legacy of the "Zhiqiang Spirit" that continues to inspire future generations, as well as the journal's extraordinary role in establishing itself as a premier publication and fostering a high-quality academic exchange platform to advance digestive surgery in China and even all over the world. At these twin commemorative moments, the authors synthesize pivotal developments in digestive surgery for the new era: the establishment of precise medicine frameworks. The transfor-mative wave of minimally invasive surgery. The diagnosis and treatment models change in digestive surgery. As CMA marks its 110th anniversary, through this work, we pay tribute to the physicians dedicated to propel digestive surgery forward in the new times.

On the occasion of celebrating the 110th anniversary of the Chinese Medical Association, the authors take the Chinese Journal of Digestive Surgery, a leading Chinese journal under the excellent action plan for Chinese scientific and technological journals, as the research subject to systematically analyze practices in academic exchange and scientific innovation develop-ment models advocated by the Chinese Medical Association. Through establishing a pyramid-shaped academic ecosystem, implementing strategic guidance with standard outputs, and building collabo-rative empowerment mechanisms, the journal has achieved breakthrough improvements in academic influence and communication efficacy. The study reveals that Chinese scientific journals can effec-tively overcome traditional development constraints by deeply integrating with national strategies, reconstructing academic value chains, and innovating knowledge service models, thereby providing China-specific solutions for constructing world-class scientific journals.

In recent years, with continuous advancements in molecular biology and gene testing technologies, the diagnosis and treatment of colorectal cancer have been rapidly transitioning toward precision medicine. The application of molecular classification, target detection, and liquid biopsy technologies has driven ongoing updates to clinical guidelines. Multidisciplinary team colla-boration, innovations in precision surgical techniques, and the widespread adoption of neoadjuvant combination therapies have collectively promoted more individualized and scientific management of colorectal cancer. Looking ahead,the authors believe that as multi-omics biomarkers, organoid models, and artificial intelligence are increasingly integrated into clinical practice, precision diagnosis and treatment of colorectal cancer will deepen further, offering patients more efficient and personalized therapeutic options.