Objective To investigate the protective effects and mechanisms of sulodexide on renal fibrosis induced by prolonged warm ischemia. Methods An in vivo ischemia-reperfusion injury (IRI) model was established in rats, which were randomly divided into Sham group, IRI 60 min group (IRI group), and IRI 60 min + sulodexide group (IRI+SDX group), with 20 rats in each group. Pathological examination was used to evaluate renal tissue injury and fibrosis levels in each group. Immunohistochemistry was performed to detect the expression levels of kidney injury molecule (KIM)-1, intercellular adhesion molecule (ICAM)-1, von Willebrand factor (vWF), transforming growth factor (TGF)-β, α-smooth muscle actin (SMA), and type I collagen (COL-1). Immunofluorescence staining was used to detect CD31 expression. Real-time quantitative polymerase chain reaction was employed to measure the expression of KIM-1, ICAM-1, tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6 in renal tissues. Transmission electron microscopy was used to observe the structure of the renal glycocalyx. Evans blue dye was injected to assess renal vascular permeability. Rat survival was recorded, and serum levels of syndecan (SDC)-1, heparan sulfate (HS) and serum creatinine were measured. An ex vivo perfusion model was also established, with rats randomly assigned to either the hypothermic oxygenated machine perfusion (HOPE) group or the HOPE+SDX group (five rats per group). Perfusion parameters were recorded after 2 hours of ex vivo perfusion. Results One day after reperfusion, compared with the Sham group, the IRI group exhibited more severe renal tissue injury, higher tubular injury scores, increased expression of KIM-1, ICAM-1 and vWF, decreased CD31 expression, elevated serum levels of SDC-1 and HS, increased vascular permeability, and higher expression of TNF-α, IL-1β and IL-6. Compared with the IRI group, the IRI+SDX group showed reduced renal tissue injury, lower tubular injury scores, decreased expression of KIM-1, ICAM-1 and vWF, increased CD31 expression, lower serum levels of SDC-1 and HS, decreased vascular permeability, and reduced expression of TNF-α, IL-1β and IL-6 (all P < 0.05). Ten days after reperfusion, renal tissue injury was further alleviated in the IRI+SDX group. Twenty-five days after reperfusion, the IRI+SDX group exhibited decreased expression of TGF-β, α-SMA, and COL-1, as well as reduced collagen deposition area (all P < 0.05). Compared with the HOPE group, the HOPE+SDX group showed increased renal perfusion flow and decreased intrarenal vascular resistance (both P < 0.01). Conclusions Sulodexide may alleviates renal IRI and fibrosis caused by prolonged warm ischemia by inhibiting inflammatory responses and protecting vascular endothelial glycocalyx.

Objective To investigate the registration and epidemiological characteristics of notifiable infectious diseases in a tertiary hospital in Guangzhou during 2020-2024,providing evidence for infectious disease prevention,control,and hospital infection management.Methods A retrospective analysis of surveillance data on statutory infectious diseases reported by the hospital from 2020 to 2024 was conducted using descriptive epidemiological methods.Results From 2020 to 2024,a total of 46229 cases of notifiable infectious diseases were reported at a tertiary hospital in Panyu District,Guangzhou,with an annual in-crease in reporting rates.Disease classifications showed Category B diseases accounted for 29.64％(13 703 cases),Category C diseases for 43.04％(19 895 cases),and other legally managed diseases for 27.32％(12 631 cases).Male patients signifi-cantly outnumbered female patients(63.8％ vs.36.2％).The most frequently reported infectious diseases were influenza(11 603 cases,25.10％),hand-foot-and-mouth disease(6 188 cases,13.4％),and hepatitis B(4 110 cases,8.9％).Sta-tistically significant differences(P＜0.05)were observed in disease composition ratios across years,age groups,genders,and seasons.Seasonal distribution was notable:influenza was prevalent in winter and spring(41.99％,27.16％),hand-foot-and-mouth disease peaked in summer(26.10％),and liver fluorosis was prominent in autumn(22.40％).Conclusion Notifiable infectious diseases exhibit distinct population and seasonal distribution patterns.Prioritized prevention and control measures should focus on influenza,hand-foot-mouth disease,and hepatitis B,with an integrated prevention and control system tailored to high-risk population characteristics and seasonal epidemiological patterns.

Objective:To analyze the risk factors of Mycoplasma pneumoniae（MP）lobar pneumonia with plastic bronchitis（PB）in pediatric patients，and to establish a risk nomogram prediction model.Methods:The medical informations were collected from pediatric patients diagnosed with MP lobar pneumonia who performed bronchoscopy during hospitalization in the Department of Pediatrics at the Second Affiliated Hospital of Air Force Military Medical University from April 2023 to December 2023.According to the bronchoscopic findings，the patients were divided into PB group and non-PB group.The clinical medical records and ancillary diagnostic findings were retrospectively analyzed.A multivariate Logistic regression model was used to analyze the independent risk factors for children with MP lobar pneumonia complicated with PB.A nomogram model was constructed to predict the risk of PB occurrence. Calibration curves and Hosmer-Lemeshow goodness-of-fit test were used to evaluate the predictive value of the nomogram model for MP lobar pneumonia with PB. The receiver operating characteristic (ROC) curve was used to assess the diagnostic efficacy.Results:A total of 357 pediatric patients diagnosed with MP lobar pneumonia were included，with 92 cases in PB group and 265 cases in non-PB group. No statistically significant differences in gender and age were observed between the two groups（ P>0.05）.The duration of fever and the hospitalization time in PB group were longer than those in non-PB group. The incidences of pleural effusion，consolidation area of a single lung lobe ≥2/3 and atelectasis on chest CT were higher in PB group compared to non-PB group. Additionally,the levels of neutrophil/lymphocyte ratio，C-reactive protein，procalcitonin，D-dimer（D-D），alanine aminotransferase(ALT)，aspartate aminotransferase，lactate dehydrogenase，α-hydroxybutyrate dehydrogenase，interferon-γ（IFN-γ），interleukin（IL）-6，IL-10 and IFN-γ/IL-4 ratio in PB group were higher than those in non-PB group（all P<0.05）.Logistic regression analysis showed elevated D-D, ALT and IFN-γ, pleural effusion and consolidation area of a single lung lobe ≥2/3 were independent risk factors for PB.The nomogram prediction model constructed by the model demonstrated good goodness-of-fit (χ 2=11.316， P=0.184) and provided significant clinical net benefits within a risk threshold range of 0.09–0.65. The area under the ROC curve for combined prediction was 0.771（95% CI 0.716-0.826），with a sensitivity of 0.707 and specificity of 0.706. Conclusion:In children with MP lobar pneumonia, elevated laboratory markers (D-D, ALT, IFN-γ) and imaging features (pleural effusion, consolidation area of a single lung lobe ≥2/3) are critical predictors for early diagnosis of PB.The nomogram prediction model can be used to predict MP lobar pneumonia with PB in early stage.

With the advancements in artificial intelligence (AI), computational power, and surgical robotics, the analysis of surgical performance at the granular level of individual surgical gestures has become feasible. Surgical gestures, defined as the smallest independent units of inter-action between surgical instruments and tissues, offer a quantifiable framework for surgical skill assessment. Evidence suggests that the selection and execution of surgical gestures are strongly correlated with the expertise of the surgeon and patient outcomes, underscoring their significance in both surgical training and clinical practice. Moreover, the establishment of a standardized classifi-cation system for surgical gestures and the adoption of uniform terminology have the potential to improve communication efficiency during surgical education and training. The authors synthesize existing classification systems for surgical gestures, with a focus on their applications in diverse tasks such as suturing, exposure and dissection. By examining the latest advancements in AI models applied to surgical gesture, as well as the current research landscape of surgical gesture recognition in digestive surgery, the authors explore the potential applications of such technologies in assisting surgeons during operations in the future.

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.

Objective:To investigate the impact of the number of examined lymph nodes (ELN) on survival outcomes in gastric cancer patients with postoperative pathological stage pN3b.Methods:This retrospective cohort study included 279 pN3b gastric cancer patients who underwent D2 gastrectomy at Nanfang Hospital, Southern Medical University (September 2008 to April 2023), with 35 patients receiving combination chemotherapy and anti-PD-1 therapy (immunotherapy group) and 244 receiving adjuvant chemotherapy alone (nonimmunotherapy group). Additionally, 422 patients with pN3b from the SEER database (2005 to 2020) were collected as an external validation cohort to determine the optimal cutoff value for the number of lymph nodes examined in the nonimmunotherapy group. The primary endpoints were overall survival (OS) and recurrence-free survival (RFS) in the nonimmunotherapy group of the Nanfang Hospital cohort, stratified by whether the number of examined lymph nodes was above or below the ELN optimal cutoff value. These findings were subsequently validated in the SEER cohort.Results:The optimal ELN cutoff value (34 nodes) was determined using X-tile software and by constructing an ELN-HR fitting model with inflection point identification. In the nonimmunotherapy group, patients with ELN >34 exhibited significantly prolonged survival compared to ELN ≤34 (median OS: 25.0 (95%CI:20.5-29.5) to 17.0 (95%CI:12.7-21.3) months, P=0.004; median RFS: 19.0 (95%CI:15.6-22.4) to 13.0 (95%CI:9.5-16.5) months, P=0.048). Multivariate Cox analysis also showed ELN >34 to be an independent protective factor for both OS (HR=0.576, 95%CI: 0.397-0.836) and RFS (HR=0.701, 95%CI: 0.492-0.998). In the SEER cohort, ELN >34 was associated with a 5-month OS extension (19 to 14 months, P=0.065), with multivariate analysis supporting its independent prognostic significance (HR=0.729, 95%CI: 0.580-0.915, P=0.006). Notably, in the immunotherapy group, patients with ELN >34 ( n=30) achieved a median OS of 41 months, but the median OS had not been reached in the ELN ≤34 group ( n=5) (1 death at 48 months). Conclusion:Higher ELN (>34) correlates with improved survival in nonimmunotherapy-treated pN3b gastric cancer patients. However, in pN3b gastric cancer patients treated with immunotherapy, the optimal ELN threshold requires further exploration to determine.

Objective To investigate the registration and epidemiological characteristics of notifiable infectious diseases in a tertiary hospital in Guangzhou during 2020-2024,providing evidence for infectious disease prevention,control,and hospital infection management.Methods A retrospective analysis of surveillance data on statutory infectious diseases reported by the hospital from 2020 to 2024 was conducted using descriptive epidemiological methods.Results From 2020 to 2024,a total of 46229 cases of notifiable infectious diseases were reported at a tertiary hospital in Panyu District,Guangzhou,with an annual in-crease in reporting rates.Disease classifications showed Category B diseases accounted for 29.64％(13 703 cases),Category C diseases for 43.04％(19 895 cases),and other legally managed diseases for 27.32％(12 631 cases).Male patients signifi-cantly outnumbered female patients(63.8％ vs.36.2％).The most frequently reported infectious diseases were influenza(11 603 cases,25.10％),hand-foot-and-mouth disease(6 188 cases,13.4％),and hepatitis B(4 110 cases,8.9％).Sta-tistically significant differences(P＜0.05)were observed in disease composition ratios across years,age groups,genders,and seasons.Seasonal distribution was notable:influenza was prevalent in winter and spring(41.99％,27.16％),hand-foot-and-mouth disease peaked in summer(26.10％),and liver fluorosis was prominent in autumn(22.40％).Conclusion Notifiable infectious diseases exhibit distinct population and seasonal distribution patterns.Prioritized prevention and control measures should focus on influenza,hand-foot-mouth disease,and hepatitis B,with an integrated prevention and control system tailored to high-risk population characteristics and seasonal epidemiological patterns.

Objective:To analyze the risk factors of Mycoplasma pneumoniae（MP）lobar pneumonia with plastic bronchitis（PB）in pediatric patients，and to establish a risk nomogram prediction model.Methods:The medical informations were collected from pediatric patients diagnosed with MP lobar pneumonia who performed bronchoscopy during hospitalization in the Department of Pediatrics at the Second Affiliated Hospital of Air Force Military Medical University from April 2023 to December 2023.According to the bronchoscopic findings，the patients were divided into PB group and non-PB group.The clinical medical records and ancillary diagnostic findings were retrospectively analyzed.A multivariate Logistic regression model was used to analyze the independent risk factors for children with MP lobar pneumonia complicated with PB.A nomogram model was constructed to predict the risk of PB occurrence. Calibration curves and Hosmer-Lemeshow goodness-of-fit test were used to evaluate the predictive value of the nomogram model for MP lobar pneumonia with PB. The receiver operating characteristic (ROC) curve was used to assess the diagnostic efficacy.Results:A total of 357 pediatric patients diagnosed with MP lobar pneumonia were included，with 92 cases in PB group and 265 cases in non-PB group. No statistically significant differences in gender and age were observed between the two groups（ P>0.05）.The duration of fever and the hospitalization time in PB group were longer than those in non-PB group. The incidences of pleural effusion，consolidation area of a single lung lobe ≥2/3 and atelectasis on chest CT were higher in PB group compared to non-PB group. Additionally,the levels of neutrophil/lymphocyte ratio，C-reactive protein，procalcitonin，D-dimer（D-D），alanine aminotransferase(ALT)，aspartate aminotransferase，lactate dehydrogenase，α-hydroxybutyrate dehydrogenase，interferon-γ（IFN-γ），interleukin（IL）-6，IL-10 and IFN-γ/IL-4 ratio in PB group were higher than those in non-PB group（all P<0.05）.Logistic regression analysis showed elevated D-D, ALT and IFN-γ, pleural effusion and consolidation area of a single lung lobe ≥2/3 were independent risk factors for PB.The nomogram prediction model constructed by the model demonstrated good goodness-of-fit (χ 2=11.316， P=0.184) and provided significant clinical net benefits within a risk threshold range of 0.09–0.65. The area under the ROC curve for combined prediction was 0.771（95% CI 0.716-0.826），with a sensitivity of 0.707 and specificity of 0.706. Conclusion:In children with MP lobar pneumonia, elevated laboratory markers (D-D, ALT, IFN-γ) and imaging features (pleural effusion, consolidation area of a single lung lobe ≥2/3) are critical predictors for early diagnosis of PB.The nomogram prediction model can be used to predict MP lobar pneumonia with PB in early stage.

With the advancements in artificial intelligence (AI), computational power, and surgical robotics, the analysis of surgical performance at the granular level of individual surgical gestures has become feasible. Surgical gestures, defined as the smallest independent units of inter-action between surgical instruments and tissues, offer a quantifiable framework for surgical skill assessment. Evidence suggests that the selection and execution of surgical gestures are strongly correlated with the expertise of the surgeon and patient outcomes, underscoring their significance in both surgical training and clinical practice. Moreover, the establishment of a standardized classifi-cation system for surgical gestures and the adoption of uniform terminology have the potential to improve communication efficiency during surgical education and training. The authors synthesize existing classification systems for surgical gestures, with a focus on their applications in diverse tasks such as suturing, exposure and dissection. By examining the latest advancements in AI models applied to surgical gesture, as well as the current research landscape of surgical gesture recognition in digestive surgery, the authors explore the potential applications of such technologies in assisting surgeons during operations in the future.

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.