The glucagon receptor (GCGR) is a critical target for the treatment of metabolic disorders such as Type 2 Diabetes Mellitus (T2DM) and obesity. Activation of GCGR enhances systemic insulin sensitivity through paracrine stimulation of insulin secretion, presenting a promising avenue for treatment. However, the discovery of effective GCGR agonists remains a challenging and resource-intensive process, often requiring time-consuming wet-lab experiments to synthesize and screen potential compounds. Recent advances in artificial intelligence technologies have demonstrated great potential in accelerating drug discovery by streamlining screening and efficiently predicting bioactivity. In the present work, we propose DeepGCGR, a two-layer deep learning model that leverages graph convolutional networks (GCN) integrated with a multiple attention mechanism to expedite the identification of GCGR agonists. In the first layer, the model predicts the bioactivity of various compounds against GCGR, efficiently filtering large chemical libraries to identify promising candidates. In the second layer, DeepGCGR classifies high bioactive compounds based on their functional effects on GCGR signaling, identifying those with potential agonistic or antagonistic effects. Moreover, DeepGCGR was specifically applied to identify novel GCGR-regulating compounds for the treatment of T2DM from natural products derived from traditional Chinese medicine (TCM). The proposed method will not only offer an effective strategy for discovering GCGR-targeting compounds with functional activation properties but also provide new insights into the development of T2DM therapeutics.
Deep Learning ; Drug Discovery/methods* ; Humans ; Diabetes Mellitus, Type 2/metabolism* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology*

Objectives:To investigate the early related factors for hepatic insufficiency after hemihepatectomy and to construct and validate a nomogram model.Methods:This is a retrospective cohort study.There were 207 patients with liver tumor who underwent hemihepatectomy in the Department of Hepatobiliary Surgery, Cancer Hospital, Chinese Academy of Medical Sciences from October 2016 to December 2022. Using the random number method, patients were randomly divided into a model group( n=166) and a validation group( n=41) according to an 4∶1 ratio. There were 118 males and 48 females in the modeling group,with an age ( M(IQR)) of 59.0(13.3) years (range: 22.0 to 81.0 years),42 patients in the group with postoperative liver insufficiency and 124 patients in the group without postoperative liver insufficiency. There were 32 males and 9 females in the validation group, with an age of 54.0(19.0) years (range: 25.0 to 81.0 years). The first results of the peripheral blood test of patients within 24 hours after surgery were collected,and the independent related factors for incomplete postoperative liver function were determined by multivariate Logistic regression analysis,and related factors of postoperative incomplete liver function were screened by best subset selection. A nomogram model of the related factors of postoperative hepatic insufficiency after hemihepatectomy was constructed using R software,validated by internal and external validation of the model. Results:Multivariate logistic regression analysis showed that elevated D-dimer level and decreased antithrombin Ⅲ (AT-Ⅲ) activity within 24 hours after surgery were independent related factors for the development of postoperative hepatic insufficiency in hemihepatectomized patients. The results of the best subset selection showed that ALT, D-dimer, and AT-Ⅲ activity levels within 24 hours postoperatively were the most relevant factors for postoperative hepatic insufficiency. The R software was applied to build a nomogram prediction model based on the above three indicators in the model set, and the receiver operating characteristic(ROC) curve of the model showed an area under the curve of 0.803 and the calibration curve showed a U-index of -0.012 for the model( P=0.977). The results of the clinical decision analysis and the clinical impact curve indicated that the model had good clinical utility. The internal validation results of the Bootstrap method suggested that the model had reasonable consistency. The area under the ROC curve of the validation group model was 0.806, suggesting that the model had a good generalization prediction ability. Conclusions:The levels of ALT, D-dimer, and AT-Ⅲ activity within 24 hours after hemihepatectomy are valuable indicators for predicting liver insufficiency after hemihepatectomy. The nomogram model is reliable and can be used as an indicator for close postoperative monitoring.

Hepatocellular carcinoma(HCC),commonly known as primary liver cancer,is a major cause of malignant tumors and cancer-related deaths in China,accounting for approximately 85％of all cancer cases in the country.Several guidelines have been used to diagnose and treat liver cancer.However,these guidelines provide a broad definition for classifying advanced liver cancer,with an emphasis on a singular approach,without considering treatment options for individual patients.Therefore,it is necessary to establish a comprehensive and practical expert consensus,specifically for China,to enhance the diagnosis and treatment of HCC using the Delphi method.The classification criteria were refined for Chinese patients with HCC,and the corresponding optimal treatment regimen recommendations were developed.These recommendations took into account various factors,including tumor characteristics,vascular tumor thrombus grade,distant metastasis,liver function status,portal hypertension,and the hepatitis B virus replication status of patients with primary HCC,along with treatment prognosis.The findings and rec-ommendations provide detailed,scientific,and reasonable individualized diagnosis and treatment strategies for clinicians.

OBJECTIVE:Masks are one of the most important defenses against the virus.However,the impact of wearing masks during daily activities or sports on respiratory and circulatory function remains controversial.A comprehensive quantitative evaluation of the effects of mask-wearing on human heart rate,oxygen saturation and end-expiratory carbon dioxide by Meta-analysis was conducted.The effects of wearing different types of masks at different exercise intensities and time of exercise on the human respiratory and circulatory system were explored. METHODS:By February 2023,with"mask,face mask,N95,training,sports,running,walking,cycling"as the Chinese search terms and"masks,respiratory protective devices,N95 respirators,surgical face masks,exercise,resistance training,explosive training,muscle exercises"as English search terms,the experimental studies addressing the influence of exercise with a mask on hemodynamic indexes were retrieved from CNKI,Web of Science,PubMed,Cochrane Library and WanFang databases.The outcome indicators included three continuous variables-exercise center rate,blood oxygen saturation and end-expiratory carbon dioxide.Stata16.0 software was used to analyze the outcome indicators of the included literature.The PEDro scale was used as a quality assessment tool,and the funnel plot was used to analyze the impact of publication bias. RESULTS:Totally 25 articles involving 857 healthy children and adults were included in this Meta-analysis.The overall methodological quality was high,with 22 studies scoring 6 points on the PEDro scale,2 studies scoring 7 points and 1 study scoring 8 points.The meta-analysis results showed that compared with the control group,exercise with masks had no significant effect on heart rate(SMD=0.02,95%CI:-0.11 to 0.15,P=0.81),but increased end-expiratory carbon dioxide(SMD=0.60,95%CI:0.37 to 0.83,P=0.00),decreased oxygen saturation(SMD=-0.28,95%CI:-0.47 to-0.09,P=0.03).Intensity and duration were the factors that affected the heterogeneity between studies.Wearing a mask during high-intensity exercise significantly increased heart rate(SMD=-0.20,95%CI:-0.36 to-0.04,P=0.02).The effect of high-intensity and short-time exercise on blood oxygen saturation was significantly higher than that of other exercises(SMD=-0.40,95%CI:-0.70 to-0.10;SMD=-0.25,95%CI:-0.45 to-0.04).For end-expiratory carbon dioxide,maintaining a certain intensity and increasing the exercise time or increasing the intensity further increased the index significantly,reaching a moderate effect size(SMD=0.61,95%CI:0.06 to 1.15;SMD=0.58,95%CI:0.04 to 1.13). CONCLUSION:Existing evidence suggests that exercise with masks may have the adverse effect of increasing end-expiratory carbon dioxide and decreasing blood oxygen saturation.The influence of different exercise test time and intensities on the three outcome indexes was different.Wearing a mask during high-intensity exercise can significantly increase heart rate and decrease blood oxygen saturation.Maintaining moderate intensity for a long period or further increasing the intensity of exercise will lead to increased end-expiratory carbon dioxide levels.

Cancer is a leading cause of mortality in children and results in a significant disease burden. Lipid metabolic reprogramming emerges as a pivotal cancer hallmark, bearing profound implications for understanding tumorigenesis, developing treatment strategies, and improving prognoses. However, research on lipid metabolism and lipid nutritional interventions related to childhood cancers is notably limited compared to adult cancers. This review focused on the current understanding of fatty acid, cholesterol, and phospholipid metabolism in childhood cancers and discussed the correlation between major lipid dietary patterns (such as high-fat, ketogenic, and Mediterranean diets) and the development and progression of childhood cancers. This review also highlighted existing research gaps on the mechanisms of lipid metabolism and the effects of major lipid dietary patterns, and warranted improved research depth, experimental design, and sample size. Therefore, we advocate for future epidemiological, basic science, and multidisciplinary research in the field of childhood cancers to understand more comprehensively and profoundly the role of lipid nutrition in the prevention and treatment of pediatric cancers.

Surgical resection remains the best approach for achieving long-term survival in patients with hepatocellular carcinoma(HCC);however,due to the low early diagnosis rate of HCC patients in China,only 15%-20%of the patients are eligible for surgical resection at the time of initial diagnosis.Even for the patients undergoing surgery,the 5-year recurrence rate after surgery is as high as 50%-70%,resulting in an unsatisfactory prognosis.In recent years,the advances in systemic therapies,especially targeted therapy combined with immunotherapy,have not only extended the survival of patients with advanced liver cancer,but also promoted the application of systemic therapy in the earlier stages of HCC.On the one hand,the progress in systemic therapy has made conversion therapy a possible option for HCC,allowing a substantial number of patients with unresectable HCC at initial diagnosis to get the opportunity for surgical resection after downstaging and achieve a survival rate similar to those with resectable early-stage HCC at initial diagnosis;on the other hand,effective systemic therapy is being applied as neoadjuvant and adjuvant therapies for patients with resectable HCC,aiming to increase the R0 resection rate,reduce postoperative recurrence,and improve overall survival.Meanwhile,it should be clearly noted that although the advances in systemic therapy have significantly altered conventional surgical treatment paradigms,most clinical studies on conversion therapy,neoadjuvant therapy,and adjuvant therapy are small-scale phase II trials,with limited high-grade evidence from evidence-based medicine.It is important to select a reasonable therapeutic goal and develop an individualized treatment regimen based on the characteristics of tumor,and further explorations are needed to search for new biomarkers for predicting the efficacy of conversion therapy and perioperative treatment and identify the population with true benefits.

Objectives:To investigate the early related factors for hepatic insufficiency after hemihepatectomy and to construct and validate a nomogram model.Methods:This is a retrospective cohort study.There were 207 patients with liver tumor who underwent hemihepatectomy in the Department of Hepatobiliary Surgery, Cancer Hospital, Chinese Academy of Medical Sciences from October 2016 to December 2022. Using the random number method, patients were randomly divided into a model group( n=166) and a validation group( n=41) according to an 4∶1 ratio. There were 118 males and 48 females in the modeling group,with an age ( M(IQR)) of 59.0(13.3) years (range: 22.0 to 81.0 years),42 patients in the group with postoperative liver insufficiency and 124 patients in the group without postoperative liver insufficiency. There were 32 males and 9 females in the validation group, with an age of 54.0(19.0) years (range: 25.0 to 81.0 years). The first results of the peripheral blood test of patients within 24 hours after surgery were collected,and the independent related factors for incomplete postoperative liver function were determined by multivariate Logistic regression analysis,and related factors of postoperative incomplete liver function were screened by best subset selection. A nomogram model of the related factors of postoperative hepatic insufficiency after hemihepatectomy was constructed using R software,validated by internal and external validation of the model. Results:Multivariate logistic regression analysis showed that elevated D-dimer level and decreased antithrombin Ⅲ (AT-Ⅲ) activity within 24 hours after surgery were independent related factors for the development of postoperative hepatic insufficiency in hemihepatectomized patients. The results of the best subset selection showed that ALT, D-dimer, and AT-Ⅲ activity levels within 24 hours postoperatively were the most relevant factors for postoperative hepatic insufficiency. The R software was applied to build a nomogram prediction model based on the above three indicators in the model set, and the receiver operating characteristic(ROC) curve of the model showed an area under the curve of 0.803 and the calibration curve showed a U-index of -0.012 for the model( P=0.977). The results of the clinical decision analysis and the clinical impact curve indicated that the model had good clinical utility. The internal validation results of the Bootstrap method suggested that the model had reasonable consistency. The area under the ROC curve of the validation group model was 0.806, suggesting that the model had a good generalization prediction ability. Conclusions:The levels of ALT, D-dimer, and AT-Ⅲ activity within 24 hours after hemihepatectomy are valuable indicators for predicting liver insufficiency after hemihepatectomy. The nomogram model is reliable and can be used as an indicator for close postoperative monitoring.

Humans ; Consensus ; Liver Neoplasms/therapy* ; China

Objective:To evaluate the role of virtual bronchoscopy intelligent system in improving the theory and operation level of bronchoscopy in pulmonary and critical care medicine (PCCM) teaching for standardized training specialists.Methods:A total of 50 PCCM physicians who had participated in virtual bronchoscopy training in Xijing Hospital, Air Force Medical University from 2018 to 2021 were selected as research subjects. In this study, self-controlled method was adopted to evaluate the change of assessment indicators after 1 week and 2 weeks of training. Questionnaire survey was also used to evaluate the training effect. SPSS 23.0 software was used for paired t-test and Chi-square test. Results:All the 50 PCCM physicians successfully completed the training of virtual bronchoscopy operation. The theoretical score was significantly improved after the training [(80.0±5.2) points vs. (92.4±3.8) points]. The basic operation time [(1 050.9±103.3) s vs. (386.4±47.7) s], and the number of hitting the bronchial wall [(88.3±12.7) times vs. (27.0±5.3) times] were significantly reduced. The recovery rate of alveolar lavage fluid [(27.6±7.4)% vs. (58.0±8.2)%] and the positive rate of biopsy [(19.2±13.1)% vs. (86.8±10.8)%] were significantly increased. The learning curve of the final score indicated that the score improved more rapidly in the first week of training, and the score improved more slowly in the second week of training. Questionnaires before and after the training indicated that virtual intelligent training could significantly improve the confidence and proficiency of students in bronchoscopy.Conclusion:Through the systematic training of virtual bronchoscopy intelligent system, the PCCM physicians have significantly improved their theoretical knowledge and operational proficiency. Therefore, the virtual bronchoscopy training system has practical significance for improving the overall training effect of clinical bronchoscopy for PCCM trainees, which is worthy of promotion.