Background/Aims: Biliary tract cancer (BTC) frequently harbors KRAS mutations, which are associated with resistance to traditional treatment and a poor prognosis. Synthetic lethality (SL) strategy may provide other targets of KRAS. Therefore, we aim to identify and validate potential therapeutic targets of KRAS for the treatment of BTC via SL. Methods: The dependency (DepMap) projects were used to predict the synthetic lethal gene of KRAS. FDA-approved anticancer drug library was applied to screen potential drugs effective against KRAS-mutant BTC. Furthermore, the synthetic lethal effects or corresponding mechanisms of potential genes and drugs on BTC were investigated using KRAS-mutant and KRAS-wild type BTC cell lines, patient-derived xenografts (PDX), and KRAS oncogene-driven tumor models, as well as other KRAS-mutant cancer cell lines. Results: Initially, we discovered that the loss of GATA2 reduced the viability of KRAS-mutant but not KRAS-wild-type BTC. Subsequently, the drug library screened out disulfiram, which primarily exerts a synthetic lethal effect by inhibiting interleukin-1β (IL-1β) in KRAS-mutant BTC. Mechanistically, GATA2 specifically enhanced the transcription of IL-1β to promote NF-κB signaling in KRAS-mutant BTC. IL-1β inhibition phenocopied GATA2 deficiency, leading to reduced KRAS-mutant BTC viability. These synthetically lethal effects were confirmed using PDX, a KRAS oncogene-driven tumor model, as well as in other KRAS-mutant cancer cell lines. Conclusions In summary, these results indicate that inhibiting GATA2/IL1β could be a therapeutic strategy in KRAS-mutant BTC and potentially other cancers.

Objective:To study the alternation of plasma ghrelin in patients with acute pancreatitis (AP) and to evaluate the efficacy of gastric slow wave analysis in predicting the severity of AP.Methods:Clinical data and blood samples of 129 patients with AP and 16 individuals for normal physical examination in the Department of Gastroenterology, Jiangnan University Affiliated Central Hospital (Wuxi No.2 People's Hospital) from September 2018 to August 2024 were prospectively collected. Individuals with normal physical examinations were included in the normal control group, including 9 males and 7 females, aged (50.9±14.2) years. The finally enrolled 125 patients with AP included 82 males and 43 females, aged (49.5±15.6) years, which were grouped according to disease severity. Mild AP (MAP) was included in the MAP group ( n=84), while moderate to severe and severe acute AP were included in the non-MAP group ( n=41). The surface gastrogram of all AP patients was detected on the 2nd and 4th day after admission. The slow waves of gastric electricity were recorded, and gastric growth hormone-releasing hormone, C-reactive protein (CRP), etc. were detected simultaneously. Univariate and multivariate logistic regression analyses were conducted to analyze the influencing factors of AP severity (MAP or non-MAP). Receiver operating characteristic (ROC) curve was used to evaluate the indicators in predicting the severity of AP. Results:The levels of gastric growth hormone-releasing hormone in both the non-MAP group and MAP group on the 2nd and 4th day after admission were lower than those in normal control group (all P<0.05). The percentages of normal gastric electrical slow waves in the first and fourth leads, the mean percentages of normal gastric electrical slow waves in the four leads, and the main frequency on the 2nd day of admission in the non-MAP group were lower than those in the normal control group, and the main power and C-reactive protein were higher than those in the MAP group, the differences were statistically significant (all P<0.05). Multivariate logistic regression analysis showed the percentage of normal gastric electrical slow wave in the first lead on the 2nd day of admission ( OR=0.914, 95% CI: 0.869-0.961, P=0.001) and CRP ( OR=1.008, 95% CI: 1.002-1.013, P=0.012) were the influencing factors of the severity of AP. The area under the ROC curve of the percentage of normal gastric electrical slow wave in the first lead on the 2nd day of admission in predicting the severity of AP was 0.705, with a sensitivity of 97.6% and a specificity of 35.7%. Conclusion:The plasma gastric growth hormone-releasing hormone in patients with AP decreases in the early stage. The low percentage of normal slow waves in the first lead of gastric electrocardiogram on the 2nd day of admission is a risk factor for the severity of AP and can be used for the early prediction of the severity.

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve

Objective:To summarize the initial experience of 5G-ultra-long-distance robotic hepatectomy.Methods:This is a retrospective case series study. The clinical information from 5 cases of 5G ultra-long-distance robot-assisted hepatectomy performed was collected from June 2023 to October 2024, in collaboration between Sir Run Run Shaw Hospital, Zhejiang University School of Medicine in Hangzhou and Alaer Hospital, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine in Alaer, located 4 600 km apart. The patients comprised 1 male and 4 females, aged from 36 to 59 years, with an average age of 48 years. Their body mass index ranged from 20.4 to 30.9 kg/m2, with an average of 24.62 kg/m2. Preoperatively, 5 patients were diagnosed with liver disease requiring hepatectomy. The operations used 5G ultra-remote four-arm endoscopic robot surgery system. The remote control room was located in Sir Run Run Shaw Hospital (Hangzhou, Zhejiang), and the robot operating room was located in Alaer Hospital (Alaer, Xinjiang). The wired network relied on 60 Mb/s high-speed public Internet special line (China Telecom). In order to ensure the security of data transmission, the system implemented a double-layer encryption strategy for the wired network, and carried out strict debugging and verification for both the wired and wireless networks. Perioperative data and information on network performance were collected for 5 patients.Results:The surgical duration of the 5 cases of 5G ultra-long-distance robot-assisted hepatectomy ranged from 49 to 342 minutes, with an average of 184 minutes. Intraoperative blood loss varied from 5 to 800 ml, averaging 183 ml. Network performance was evaluated during the surgery, revealing an average network latency of 108.2 ms, with no significant lag or delay observed during any of the procedures. All patients recovered smoothly, with a postoperative hospital stay ranging from 5 to 10 days, averaging 7.2 days. Postoperative complications included 1 case of hypoproteinemia and 1 case of pleural effusion. Pathological examination confirmed that all cases suffered benign liver diseases (three patients with hepatic hemangioma, one with regenerative nodule in cirrhosis, and one with hepatolithiasis and choledocholithiasis).Conclusion:The preliminary exploration of clinical practice indicated that 5G-ultra-long-distance robot-assisted surgery is feasible for hepatectomy, with no severe complications affecting patients′ recovery.

Objective:To investigate the impact of body composition and inflammatory nutritional indicators on postoperative complications in patients with obstructive colorectal cancer,and to develop and validate a nomogram model.Methods:This is a retrospective case series study. The clinical data of 293 patients with obstructive colorectal cancer who were treated at the Department of Gastrointestinal Surgery,the Affiliated Hospital of Qingdao University,between January 2016 and January 2024,were retrospectively collected. The cohort included 182 males and 111 females,aged (65.0±12.1) years (range: 18 to 80 years). The dataset was randomly divided into a training group ( n=196) and a validation group ( n=97) with a 7∶3 ratio. Independent sample t test and multivariate logistic regression analysis were employed to identify independent risk factors associated with postoperative complications in patients with obstructive colorectal cancer. A preoperative nomogram model was subsequently developed for predicting postoperative complications,which was further validated using a validation cohort. Results:The training group comprised 119 males and 77 females,with 68 cases experiencing postoperative complications and 128 cases without complications. The validation group included 63 males and 34 females,with 30 cases experiencing postoperative complications and 67 cases without complications.Univariate analysis and multivariate analysis revealed that low skeletal muscle index ( OR=0.867,95% CI: 0.795 to 0.947),high visceral fat index ( OR=1.058,95% CI: 1.028 to 1.089),high systemic immune inflammation index ( OR=1.002, 95% CI: 1.000 to 1.003), low prognostic nutritional index ( OR=0.847,95% CI: 0.782 to 0.917),and preoperative anemia ( OR=2.714,95% CI: 1.161 to 6.344) were independent risk factors for postoperative complications (all P<0.05). A nomogram prediction model based on these five indicators was established. The area under the receiver operating characteristic (ROC) curve for the prediction model was 0.878 (95% CI: 0.829 to 0.928) in the training group and 0.849 (95% CI:0.767 to 0.930) in the validation group. Conclusions:The preoperative nomogram model,which incorporates inflammatory and nutritional indicators,demonstrates a good accuracy in predicting postoperative complications for patients with obstructive colorectal cancer. This model can effectively assist in guiding treatment decisions.

Objective:To summarize the initial experience of 5G-ultra-long-distance robotic hepatectomy.Methods:This is a retrospective case series study. The clinical information from 5 cases of 5G ultra-long-distance robot-assisted hepatectomy performed was collected from June 2023 to October 2024, in collaboration between Sir Run Run Shaw Hospital, Zhejiang University School of Medicine in Hangzhou and Alaer Hospital, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine in Alaer, located 4 600 km apart. The patients comprised 1 male and 4 females, aged from 36 to 59 years, with an average age of 48 years. Their body mass index ranged from 20.4 to 30.9 kg/m2, with an average of 24.62 kg/m2. Preoperatively, 5 patients were diagnosed with liver disease requiring hepatectomy. The operations used 5G ultra-remote four-arm endoscopic robot surgery system. The remote control room was located in Sir Run Run Shaw Hospital (Hangzhou, Zhejiang), and the robot operating room was located in Alaer Hospital (Alaer, Xinjiang). The wired network relied on 60 Mb/s high-speed public Internet special line (China Telecom). In order to ensure the security of data transmission, the system implemented a double-layer encryption strategy for the wired network, and carried out strict debugging and verification for both the wired and wireless networks. Perioperative data and information on network performance were collected for 5 patients.Results:The surgical duration of the 5 cases of 5G ultra-long-distance robot-assisted hepatectomy ranged from 49 to 342 minutes, with an average of 184 minutes. Intraoperative blood loss varied from 5 to 800 ml, averaging 183 ml. Network performance was evaluated during the surgery, revealing an average network latency of 108.2 ms, with no significant lag or delay observed during any of the procedures. All patients recovered smoothly, with a postoperative hospital stay ranging from 5 to 10 days, averaging 7.2 days. Postoperative complications included 1 case of hypoproteinemia and 1 case of pleural effusion. Pathological examination confirmed that all cases suffered benign liver diseases (three patients with hepatic hemangioma, one with regenerative nodule in cirrhosis, and one with hepatolithiasis and choledocholithiasis).Conclusion:The preliminary exploration of clinical practice indicated that 5G-ultra-long-distance robot-assisted surgery is feasible for hepatectomy, with no severe complications affecting patients′ recovery.

Objective:To investigate the impact of body composition and inflammatory nutritional indicators on postoperative complications in patients with obstructive colorectal cancer,and to develop and validate a nomogram model.Methods:This is a retrospective case series study. The clinical data of 293 patients with obstructive colorectal cancer who were treated at the Department of Gastrointestinal Surgery,the Affiliated Hospital of Qingdao University,between January 2016 and January 2024,were retrospectively collected. The cohort included 182 males and 111 females,aged (65.0±12.1) years (range: 18 to 80 years). The dataset was randomly divided into a training group ( n=196) and a validation group ( n=97) with a 7∶3 ratio. Independent sample t test and multivariate logistic regression analysis were employed to identify independent risk factors associated with postoperative complications in patients with obstructive colorectal cancer. A preoperative nomogram model was subsequently developed for predicting postoperative complications,which was further validated using a validation cohort. Results:The training group comprised 119 males and 77 females,with 68 cases experiencing postoperative complications and 128 cases without complications. The validation group included 63 males and 34 females,with 30 cases experiencing postoperative complications and 67 cases without complications.Univariate analysis and multivariate analysis revealed that low skeletal muscle index ( OR=0.867,95% CI: 0.795 to 0.947),high visceral fat index ( OR=1.058,95% CI: 1.028 to 1.089),high systemic immune inflammation index ( OR=1.002, 95% CI: 1.000 to 1.003), low prognostic nutritional index ( OR=0.847,95% CI: 0.782 to 0.917),and preoperative anemia ( OR=2.714,95% CI: 1.161 to 6.344) were independent risk factors for postoperative complications (all P<0.05). A nomogram prediction model based on these five indicators was established. The area under the receiver operating characteristic (ROC) curve for the prediction model was 0.878 (95% CI: 0.829 to 0.928) in the training group and 0.849 (95% CI:0.767 to 0.930) in the validation group. Conclusions:The preoperative nomogram model,which incorporates inflammatory and nutritional indicators,demonstrates a good accuracy in predicting postoperative complications for patients with obstructive colorectal cancer. This model can effectively assist in guiding treatment decisions.

The profound integration of novel qualitative productive forces throughout the entire process of diagnosing and treating gastrointestinal cancer has catalyzed innovative advance-ments in surgical techniques and postoperative rehabilitation. In the field of minimally invasive resection, technological innovations, from laparoscopic surgery to robot-assisted surgical systems that transcend traditional visual and operational limitations, and further to the integration of artificial intelligence and 5G technologies that overcome spatiotemporal barriers for real-time decision-making and telemedicine, have significantly enhanced the precision and safety of gastrointestinal tumor surgery. Concurrently, the development of innovative medical devices plays a pivotal role in improving perioperative and postoperative rehabilitation efficiency. Functional device design focuses on addressing the holistic needs of patients throughout their clinical journey, systematically resolving efficiency and safety bottlenecks inherent in conventional diagnostic and therapeutic approaches. Technological progress has further enabled non-invasive, convenient remote health management for patients. Novel qualitative productive forces not only redefine surgical paradigms but also deliver efficient, safe, and patient-centered diagnostic and therapeutic experiences through comprehensive innovation across all treatment phases. This evolution marks a critical breakthrough in modern medicine's transition toward intelligence and systematization, heralding a new era of intelligent healthcare delivery.

The profound integration of novel qualitative productive forces throughout the entire process of diagnosing and treating gastrointestinal cancer has catalyzed innovative advance-ments in surgical techniques and postoperative rehabilitation. In the field of minimally invasive resection, technological innovations, from laparoscopic surgery to robot-assisted surgical systems that transcend traditional visual and operational limitations, and further to the integration of artificial intelligence and 5G technologies that overcome spatiotemporal barriers for real-time decision-making and telemedicine, have significantly enhanced the precision and safety of gastrointestinal tumor surgery. Concurrently, the development of innovative medical devices plays a pivotal role in improving perioperative and postoperative rehabilitation efficiency. Functional device design focuses on addressing the holistic needs of patients throughout their clinical journey, systematically resolving efficiency and safety bottlenecks inherent in conventional diagnostic and therapeutic approaches. Technological progress has further enabled non-invasive, convenient remote health management for patients. Novel qualitative productive forces not only redefine surgical paradigms but also deliver efficient, safe, and patient-centered diagnostic and therapeutic experiences through comprehensive innovation across all treatment phases. This evolution marks a critical breakthrough in modern medicine's transition toward intelligence and systematization, heralding a new era of intelligent healthcare delivery.

Objective:To study the alternation of plasma ghrelin in patients with acute pancreatitis (AP) and to evaluate the efficacy of gastric slow wave analysis in predicting the severity of AP.Methods:Clinical data and blood samples of 129 patients with AP and 16 individuals for normal physical examination in the Department of Gastroenterology, Jiangnan University Affiliated Central Hospital (Wuxi No.2 People's Hospital) from September 2018 to August 2024 were prospectively collected. Individuals with normal physical examinations were included in the normal control group, including 9 males and 7 females, aged (50.9±14.2) years. The finally enrolled 125 patients with AP included 82 males and 43 females, aged (49.5±15.6) years, which were grouped according to disease severity. Mild AP (MAP) was included in the MAP group ( n=84), while moderate to severe and severe acute AP were included in the non-MAP group ( n=41). The surface gastrogram of all AP patients was detected on the 2nd and 4th day after admission. The slow waves of gastric electricity were recorded, and gastric growth hormone-releasing hormone, C-reactive protein (CRP), etc. were detected simultaneously. Univariate and multivariate logistic regression analyses were conducted to analyze the influencing factors of AP severity (MAP or non-MAP). Receiver operating characteristic (ROC) curve was used to evaluate the indicators in predicting the severity of AP. Results:The levels of gastric growth hormone-releasing hormone in both the non-MAP group and MAP group on the 2nd and 4th day after admission were lower than those in normal control group (all P<0.05). The percentages of normal gastric electrical slow waves in the first and fourth leads, the mean percentages of normal gastric electrical slow waves in the four leads, and the main frequency on the 2nd day of admission in the non-MAP group were lower than those in the normal control group, and the main power and C-reactive protein were higher than those in the MAP group, the differences were statistically significant (all P<0.05). Multivariate logistic regression analysis showed the percentage of normal gastric electrical slow wave in the first lead on the 2nd day of admission ( OR=0.914, 95% CI: 0.869-0.961, P=0.001) and CRP ( OR=1.008, 95% CI: 1.002-1.013, P=0.012) were the influencing factors of the severity of AP. The area under the ROC curve of the percentage of normal gastric electrical slow wave in the first lead on the 2nd day of admission in predicting the severity of AP was 0.705, with a sensitivity of 97.6% and a specificity of 35.7%. Conclusion:The plasma gastric growth hormone-releasing hormone in patients with AP decreases in the early stage. The low percentage of normal slow waves in the first lead of gastric electrocardiogram on the 2nd day of admission is a risk factor for the severity of AP and can be used for the early prediction of the severity.