Objective To analyze the effect of releasing the lower pulmonary ligament on right residual lung expansion after right upper lobe resection under different body mass index (BMI) levels. Methods The clinical data of patients who underwent thoracoscopic right upper lobe resection in the First Affiliated Hospital with Nanjing Medical University from 2021 to 2022 were retrospectively analyzed. Patients were divided into a group A (17 kg/m2＜BMI≤23 kg/m2), a group B (23 kg/m2＜BMI≤29 kg/m2) and a group C (BMI＞29 kg/m2) according to BMI. The presence of residual cavity was judged by chest X-ray at 7-10 days after operation, the degree of compensation change of the right main bronchus angle was measured, and the changes in lung volume were determined by CT three-dimensional reconstruction. Results A total of 157 patients who underwent thoracoscopic right upper lobe resection were included, including 71 males and 86 females, with an average age of (59.7±11.2) years. There were 50 patients in the group A, 75 patients in the group B, and 32 patients in the group C. In the group A, compared with those without releasing the lower pulmonary ligament, patients with releasing had a lower incidence of postoperative residual cavity (P=0.016), greater changes in bronchus angle (P<0.001), and smaller changes in lung volume (P<0.001). In the group B and C, there was no significant effect of releasing the lower pulmonary ligament on postoperative residual cavity, bronchus angle, and lung volume changes (P>0.05). Conclusion For patients with thin and long body shape and low BMI, releasing the lower pulmonary ligament is helpful to promote the expansion of the residual lung after right upper lobe resection and reduce the occurrence of postoperative residual cavity in patients.

Objective To explore the regulatory effect of amylin on the feeding behavior of mice through the ERK pathway of paraventricular nucleus of the hypothalamus(PVN).Methods A total of 54 C57BL/6J mice were randomly divided into multiple groups for experiments.First,immunofluorescence was used to detect the distribution of ERK and calcitonin receptor(CTR)neurons in the brains of 4 mice.A chemical lesion model of PVN neurons was established,and 16 mice were divided into four groups(4 mice per group):control(Ctrl)group,ibotenic acid(IBO)-lesioned group,amylin group,and amylin+IBO group.The number of ERK-positive neurons in the PVN region and food intake were then measured.Subsequently,16 mice were divided into four groups(4 mice per group),Ctrl group,amylin group,ERK antagonist U0126 group,and amylin+U0126 group.The expression level of the immediate early gene c-fos in the PVN was detected by Real-time PCR.Immunofluorescence was used to detect the distribution of p-ERK positive neurons in the brains of 4 saline-treated mice and 4 amylin-treated mice.Finally,18 mice were randomly divided into three groups(6 mice per group)through intracerebroventricular injection,Ctrl group,amylin group,and amylin+receptor antagonist AC 187 group.Then,triple immunofluorescence was used to detect the co-expression of p-ERK,neuronal nitric oxide synthase(nNOS),and CTR-immunopositive neurons in the PVN region,and food intake within 3 hours after treatment was recorded simultaneously.Results ERK-positive neurons were mainly distributed in the suprachiasmatic nucleus(SCN),arcuate nucleus(ARC),and locus coeruleus(LC),while ERK and CTR co-expressing positive neurons were specifically enriched in the PVN(P=0.0012).Lesion of PVN neurons led to a decrease in the number of ERK-positive neurons(P＜0.001)and blocked the anorectic effect of amylin(P＜0.001).Amylin activated the expression of the c-fos gene in the PVN region(P＜0.05),and this effect was inhibited by U0126(P＜0.05).After intracerebroventricular injection of amylin,the number of triple-positive neurons for p-ERK,nNOS,and CTR in the PVN increased(P＜0.05).Addition of AC 187 blocked the activation effect of amylin(P＜0.01)and reversed the anorectic effect of amylin(1 h,P=0.2218;2 h,P=0.2218;3 h,P=0.6974).Conclusion P-ERK neurons in the PVN regulate feeding behavior through an amylin receptor-dependent ERK signaling pathway.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Objective To clarify the effect of preoperative oral carbohydrate on overweight or obese patients undergoing laparoscopic hysterectomy in Trendelenburg position.Methods A total of 72 overweight or obese patients who underwent laparoscopic hysterectomy in Trendelenburg position at Yancheng Third People's Hospital from September 2022 to August 2024 were selected,and randomly divided into the control group and the observation group,with 36 cases in each group.The control group received routine restriction of fasting and fluid starting from 22:00 on the day before surgery,while the observation group was given an additional 300 mL of carbohydrate orally 2 hours before anesthesia on the basis of the control group.The preoperative ultrasound results of gastric antrum,Perlas classification,full stomach status,visual analogue scale(VAS)scores for thirst and hunger,awakening time,tracheal extubation time,intraoperative hypothermia,gastro-intestinal function recovery time,and adverse reactions were compared between the two groups.Results Before anesthesia,there was no statistically significant difference in the cross-sectional area of the gastric antrum(CSA)in the right lateral position,gastric volume(GV),or the ratio of gastric volume to body weight(GV/W)between the two groups(P>0.05).There was also no statistically significant difference in the Perlas classification of gastric antrum ultrasound or the incidence of full stomach between the two groups(P>0.05).Immediately before anesthesia,the VAS scores for thirst and hunger in the observation group were significantly lower than those in the control group(P<0.05).The awakening time,tracheal extubation time,and incidence of intraoperative hypothermia in the observation group were significantly shorter/lower than those in the control group(P<0.05).The observation group had significantly shorter time of first exhaust and defecation after surgery,as well as lower incidence of postoperative bloating,compared with the control group(P<0.05).Conclusion For overweight or obese patients undergoing laparoscopic hysterectomy in the Trendelenburg position,oral intake of 300 mL carbohydrate 2 hours before anesthesia does not increase the risk of regurgitation or aspiration,with safety and reliability.It not only can improve comfort of patients and promote post-anesthesia awakening,but also can reduce the incidences of intraoperative hypothermia and gastrointestinal adverse reactions,which is conducive to accelerating postoperative recovery.

Objective:To analyze the multi antigen distribution characteristics of Rh blood group system in Shunde area of Guangdong Province,explore the feasibility of Rh phenotype compatible blood transfusion for blood recipients in this area,and formulate the precise blood transfusion strategies.Methods:From June 2022 to December 2024,113 226 hospitalized patients scheduled for blood transfusion in Shunde Hospital of Southern Medical University and 30 832 blood donors'blood samples provided by Shunde central blood station in the same period were detected for ABO blood group and Rh phenotype by microcolumn gel method,and the Rh phenotype data of the recipients and blood donors were compared and analyzed.Results:Among 113 226 blood samples,112 963 cases(99.77％)were RhD positive,with CCDee(54.96％)and CcDEe(28.21％)phenotypes being the main phenotypes;263 cases(0.23％)were RhD negative,with ccDee(50.19％)and CcDee(36.88％)as the main phenotype.Among 30 832 blood donor samples,CCDee(54.65％)and CcDEe(27.93％)were the main phenotypes of Rh phenotype with RhD positive.The positive rates of D,C,c,E and e antigens of blood recipients and blood donors were in the same order from high to low D＞e＞C＞c＞E.The frequency of e antigen in RhD positive recipients with different ABO blood groups was statistically different from that of blood donors(P＜0.05),while there was no statistical difference in the other four antigens(P＞0.05),the distribution of ccDEe phenotypes was statistically different(P＜0.05),but there was no statistical difference in the distribution of other eight phenotypes(P＞0.05).In RhD positive recipients,the probability of finding compatible blood for phenotype CcDEe was 100％,the probability of finding compatible blood for phenotype CCDee,CCDEe and DcDee was 54％-65％,and the probability of finding compatible blood for other phenotypes was less than 10％.Providing blood with CCDee and ccDEE phenotypes according to Rh blood matching scheme can meet the needs of more than 99％of patients with 9 Rh phenotype compatible blood transfusion in this region.Conclusion:Rh phenotype detection should be carried out for hospitalized patients to be transfused,and the precise transfusion strategy of Rh phenotype isotype or compatibility should be implemented to make the transfusion treatment of patients more safe and reliable.

Objective To clarify the effect of preoperative oral carbohydrate on overweight or obese patients undergoing laparoscopic hysterectomy in Trendelenburg position.Methods A total of 72 overweight or obese patients who underwent laparoscopic hysterectomy in Trendelenburg position at Yancheng Third People's Hospital from September 2022 to August 2024 were selected,and randomly divided into the control group and the observation group,with 36 cases in each group.The control group received routine restriction of fasting and fluid starting from 22:00 on the day before surgery,while the observation group was given an additional 300 mL of carbohydrate orally 2 hours before anesthesia on the basis of the control group.The preoperative ultrasound results of gastric antrum,Perlas classification,full stomach status,visual analogue scale(VAS)scores for thirst and hunger,awakening time,tracheal extubation time,intraoperative hypothermia,gastro-intestinal function recovery time,and adverse reactions were compared between the two groups.Results Before anesthesia,there was no statistically significant difference in the cross-sectional area of the gastric antrum(CSA)in the right lateral position,gastric volume(GV),or the ratio of gastric volume to body weight(GV/W)between the two groups(P>0.05).There was also no statistically significant difference in the Perlas classification of gastric antrum ultrasound or the incidence of full stomach between the two groups(P>0.05).Immediately before anesthesia,the VAS scores for thirst and hunger in the observation group were significantly lower than those in the control group(P<0.05).The awakening time,tracheal extubation time,and incidence of intraoperative hypothermia in the observation group were significantly shorter/lower than those in the control group(P<0.05).The observation group had significantly shorter time of first exhaust and defecation after surgery,as well as lower incidence of postoperative bloating,compared with the control group(P<0.05).Conclusion For overweight or obese patients undergoing laparoscopic hysterectomy in the Trendelenburg position,oral intake of 300 mL carbohydrate 2 hours before anesthesia does not increase the risk of regurgitation or aspiration,with safety and reliability.It not only can improve comfort of patients and promote post-anesthesia awakening,but also can reduce the incidences of intraoperative hypothermia and gastrointestinal adverse reactions,which is conducive to accelerating postoperative recovery.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.