Homo- or heterodimeric compounds that affect dimeric protein function through interaction between monomeric moieties and protein subunits can serve as valuable sources of potent and selective drug candidates. Here, we screened an in-house dimeric natural product collection, and panepocyclinol A (PecA) emerged as a selective and potent STAT3 inhibitor with profound anti-tumor efficacy. Through cross-linking C712/C718 residues in separate STAT3 monomers with two distinct Michael receptors, PecA inhibits STAT3 DNA binding affinity and transcription activity. Molecular dynamics simulation reveals the key conformation changes of STAT3 dimers upon the di-covalent binding with PecA that abolishes its DNA interactions. Furthermore, PecA exhibits high efficacy against anaplastic large T cell lymphoma in vitro and in vivo, especially those with constitutively activated STAT3 or STAT3^Y640F. In summary, our study describes a distinct and effective di-covalent modification for the dimeric compound PecA to disrupt STAT3 function.

Objective:To explore the mediating effect of unhealthy lifestyle and depressive symptom on the associations between life course factors and aging health.Methods:The study included 6 217 participants (aged ≥45 years) from the China Health and Retirement Longitudinal Study (CHARLS). We used principal component analysis (PCA) and hierarchical clustering analysis (HCA) to divide participants into six subgroups based on 70 life course factors. Five key life course factors were identified based on correlation analysis and their contribution to aging health. Physiological dysregulation (PD) was calculated by using eight biomarkers in the 2015 CHARLS biomarker dataset. Linear regression, logistic regression, and mediation models were used to explore the complex associations of life course subgroups, key factors, unhealthy lifestyle, depression symptom with PD.Results:Life course subgroups were significantly associated with PD after adjusting chronological age and gender ( β: 0.08-0.17, all P<0.05). Life-course subgroups and key factors, including adverse experiences in adulthood and lower education level, were significantly associated with unhealthy lifestyle ( β: 0.04-0.52, all P<0.05). Life-course subgroups and key factors, including childhood trauma, parental health in childhood, adverse experiences in adulthood, and lower education level, were significantly associated with depression symptom ( OR: 1.16-4.76, all P<0.05). Mediation analysis showed that unhealthy lifestyle had partial mediating effect on the association of life course subgroups and key factors, including adverse experiences in adulthood, and lower education levels, with PD (3.1%-3.6%). Depression symptom had partial mediating effect on the association of life course subgroups and key factors, including childhood trauma, adverse experience in adulthood, and lower education level, with PD (6.0%-16.2%). Conclusions:Unhealthy lifestyle and depression symptom has partial mediating effect on the impact of life course factors on aging health. It is important to pay attention to these two modifiable factors while targeting childhood trauma and adverse experience in adulthood.

The aim of this study was to explore the impact of chronic apical periodontitis(CAP)on atherosclerosis in apoE-/-mice fed high-fat diet(HFD).This investigation focused on the gut microbiota,metabolites,and intestinal barrier function to uncover potential links between oral health and cardiovascular disease(CVD).In this study,CAP was shown to exacerbate atherosclerosis in HFD-fed apoE-/-mice,as evidenced by the increase in plaque size and volume in the aortic walls observed via Oil Red O staining.16S rRNA sequencing revealed significant alterations in the gut microbiota,with harmful bacterial species thriving while beneficial species declining.Metabolomic profiling indicated disruptions in lipid metabolism and primary bile acid synthesis,leading to elevated levels of taurochenodeoxycholic acid(TCDCA),taurocholic acid(TCA),and tauroursodeoxycholic acid(TDCA).These metabolic shifts may contribute to atherosclerosis development.Furthermore,impaired intestinal barrier function,characterized by reduced mucin expression and disrupted tight junction proteins,was observed.The increased intestinal permeability observed was positively correlated with the severity of atherosclerotic lesions,highlighting the importance of the intestinal barrier in cardiovascular health.In conclusion,this research underscores the intricate interplay among oral health,gut microbiota composition,metabolite profiles,and CVD incidence.These findings emphasize the importance of maintaining good oral hygiene as a potential preventive measure against cardiovascular issues,as well as the need for further investigations into the intricate mechanisms linking oral health,gut microbiota,and metabolic pathways in CVD development.

Objective:To evaluate the long-term efficacy of percutaneous microwave ablation (MWA) therapy for hepatocellular carcinoma.Methods:2054 cases with Barcelona Clinic Liver Cancer (BCLC) stage 0~B at the Fifth Medical Center of the Chinese People's Liberation Army General Hospital from January 2006 to September 2020 were retrospectively collected. All patients were followed up for at least 2 years. The primary endpoint of overall survival and secondary endpoints (tumor-related survival, disease-free survival, and postoperative complications) of patients treated with ultrasound-guided percutaneous MWA were analyzed. Kaplan-Meier method was used for stratified survival rate analysis. Fine-and-Gray competing risk model was used to analyze overall survival.Results:A total of 5 503 HCC nodules [mean tumor diameter (2.6±1.6) cm] underwent 3 908 MWAs between January 2006 and September 2020, with a median follow-up time of 45.6 (24.0 -79.2) months.The technical effectiveness rate of 5 375 tumor nodules was 97.5%. The overall survival rates at 5, 10, and 15-years were 61.6%, 38.8%, and 27.0%, respectively. The tumor-specific survival rates were 67.1%, 47.2%, and 37.7%, respectively. The free tumor survival rates were 25.8%, 15.7%, and 9.9%, respectively. The incidence rate of severe complications was 2.8% (108/3 908). Further analysis showed that the technical effectiveness and survival rate over the passing three time periods from January 2006-2010, 2011-2015, and 2016-September 2020 were significantly increased, with P ?

Abstract Allergic diseases can occur in all systems of the body, covering the whole life cycle, from children to adults and to old age, can be lifelong onset and even fatal in severe cases. Children account for the largest proportion of the victims of allergic disease, Children s allergies start from scratch, ranging from mild to severe, from less to more, from single to multiple systems and systemic performance, so the prevention and treatment of allergic diseases in children is of great importance, which can not only prevent high risk allergic conditions from developing into allergic diseases, but also further block the process of allergy. At present, there is no consensus on the management system of allergic children in kindergartens and primary schools. The "Consensus on Allergy Management and Prevention in Kindergartens and Primary Schools", which includes the organizational structure, system construction and management of allergic children, provides evidence informed recommendations for the long term comprehensive management of allergic children in kindergartens and primary schools, and provides a basis for the establishment of the prevention system for allergic children.

Objective:To compare the safety and outcome between total laparoscopic and laparoscopy-assisted synchronous resection for colorectal cancer patients with liver metastases.Methods:The data of patients who underwent total laparoscopic or laparoscopy-assisted simultaneous resection of primary colorectal cancer and liver metastases in our hospital between December 2008 and December 2016 were collected and analyzed. The total laparoscopic surgery patients were matched 1∶2 to the laparoscopy-assisted surgery patients based on the propensity score. 22 patients were classified in the total laparoscopic group and 44 patients were classified in the laparoscopy-assisted group. The intraoperative conditions and postoperative outcomes of the two groups were compared.Results:There was no difference in the preoperative baseline data between the two groups ( P>0.05). The median operative time were 317.50 and 267.50 minutes in the total laparoscopic group and the laparoscopy-assisted group, respectively, and the median intraoperative blood loss were 100 and 200 ml, both with no statistically significant differences ( P>0.05). There were 1 case of intraoperative blood transfusion in the total laparoscopic group and 5 cases in the laparoscopy-assisted group, with no statistically significant difference ( P=0.650). The median postoperative hospital stay in the two groups were 11.0 and 10.0 days, the median postoperative defecation time were 4.0 and 4.0 days and postoperative complication rates were 13.6% and 20.5%, and none of these differences were statistically significant ( P>0.05). However, no Clavien-DindoⅡ level and above complications occurred in total laparoscopic group. The median disease-free survival (DFS) were 15.0 and 15.7 months in the total laparoscopic group and the laparoscopy-assisted group, the overall survival (OS) were 25.9 and 37.6 months, respectively, with no statistically significant differences ( P>0.05). Conclusion:Laparoscopy-assisted approaches are similar, so the appropriate approach should be chosen according to the clinical condition and surgeon′s experience.

Objective:To investigate the application value of machine learning algorithms and COX nomogram in the survival prediction of hepatocellular carcinoma (HCC) after resection.Methods:The retrospective and descriptive study was conducted. The clinicopathological data of 375 patients with HCC who underwent radical resection in the Cancer Hospital of Chinese Academy of Medical Sciences and Peking Union Medical College from January 2012 to January 2017 were collected. There were 304 males and 71 females, aged from 21 to 79 years, with a median age of 57 years. According to the random numbers showed in the computer, 375 patients were divided into training dataset consisting of 300 patients and validation dataset consisting of 75 patients, with a ratio of 8∶2. Machine learning algorithms including logistic regression (LR), supporting vector machine (SVM), decision tree (DT), random forest (RF), and artificial neural network (ANN) were used to construct survival prediction models for HCC after resection, so as to identify the optimal machine learning algorithm prediction model. A COX nomogram prediction model for predicting postoperative survival in patients with HCC was also constructed. Comparison of performance for predicting postoperative survival of HCC patients was conducted between the optimal machine learning algorithm prediction model and the COX nomogram prediction model. Observation indicators: (1) analysis of clinicopathological data of patients in the training dataset and validation dataset; (2) follow-up and survival of patients in the training dataset and validation dataset; (3) construction and evaluation of machine learning algorithm prediction models; (4) construction and evaluation of COX nomogram prediction model; (5) evaluation of prediction performance between RF machine learning algorithm prediction model and COX nomogram prediction model. Follow-up was performed using outpatient examination or telephone interview to detect survival of patients up to December 2019 or death. Measurement data with normal distribution were expressed as Mean± SD, and comparison between groups was analyzed by the paired t test. Measurement data with skewed distribution were expressed as M ( P25, P75) or M (range), and comparison between groups was analyzed by the Mann-Whitney U test. Count data were represented as absolute numbers. Comparison between groups was performed using the chi-square test when Tmin ≥5 and N ≥40, using the calibration chi-square test when 1≤ Tmin ≤5 and N ≥40, and using Fisher exact probability when Tmin <1 or N <40. The Kaplan-Meier method was used to calculate survival rate and draw survival curve. The COX proportional hazard model was used for univariate analysis, and variables with P<0.2 were included for the Lasso regression analysis. According to the lambda value, variables affecting prognosis were screened for COX proportional hazard model to perform multivariate analysis. Results:(1) Analysis of clinicopathological data of patients in the training dataset and validation dataset: cases without microvascular invasion or with microvascular invasion, cases without liver cirrhosis or with liver cirrhosis of the training dataset were 292, 8, 105, 195, respectively, versus 69, 6, 37, 38 of the validation dataset, showing significant differences between the two groups ( χ2=4.749, 5.239, P<0.05). (2) Follow-up and survival of patients in the training dataset and validation dataset: all the 375 patients received follow-up. The 300 patients in the training dataset were followed up for 1.1-85.5 months, with a median follow-up time of 50.3 months. Seventy-five patients in the validation dataset were followed up for 1.0-85.7 months, with a median follow-up time of 46.7 months. The postoperative 1-, 3-year overall survival rates of the 375 patients were 91.7%, 79.5%. The postoperative 1-, 3-year overall survival rates of the training dataset were 92.0%, 79.7%, versus 90.7%, 81.9% of the validation dataset, showing no significant difference in postoperative survival between the two groups ( χ2=0.113, P>0.05). (3) Construction and evaluation of machine learning algorithm prediction models. ① Selection of the optimal machine learning algorithm prediction model: according to information divergence of variables for prediction of 3 years postoperative survival of HCC, five machine learning algorithms were used to comprehensively rank the variables of clinicopathological factors of HCC, including LR, SVM, DT, RF, and ANN. The main predictive factors were screened out, as hepatitis B e antigen (HBeAg), surgical procedure, maximum tumor diameter, perioperative blood transfusion, liver capsule invasion, and liver segment Ⅳ invasion. The rank sequence 3, 6, 9, 12, 15, 18, 21, 24, 27, 29 variables of predictive factors were introduced into 5 machine learning algorithms in turn. The results showed that the area under curve (AUC) of the receiver operating charateristic curve of LR, SVM, DT, and RF machine learning algorithm prediction models tended to be stable when 9 variables are introduced. When more than 12 variables were introduced, the AUC of ANN machine learning algorithm prediction model fluctuated significantly, the stability of AUC of LR and SVM machine learning algorithm prediction models continued to improve, and the AUC of RF machine learning algorithm prediction model was nearly 0.990, suggesting RF machine learning algorithm prediction model as the optimal machine learning algorithm prediction model. ② Optimization and evaluation of RF machine learning algorithm prediction model: 29 variables of predictive factors were sequentially introduced into the RF machine learning algorithm to construct the optimal RF machine learning algorithm prediction model in the training dataset. The results showed that when 10 variables were introduced, results of grid search method showed 4 as the optimal number of nodes in DT, and 1 000 as the optimal number of DT. When the number of introduced variables were not less than 10, the AUC of RF machine learning algorithm prediction model was about 0.990. When 10 variables were introduced, the RF machine learning algorithm prediction model had an AUC of 0.992 for postoperative overall survival of 3 years, a sensitivity of 0.629, a specificity of 0.996 in the training dataset, an AUC of 0.723 for postoperative overall survival of 3 years, a sensitivity of 0.177, a specificity of 0.948 in the validation dataset. (4) Construction and evaluation of COX nomogram prediction model. ① Analysis of postoperative survival factors of HCC patients in the training dataset. Results of univariate analysis showed that HBeAg, alpha fetoprotein (AFP), preoperative blood transfusion, maximum tumor diameter, liver capsule invasion, and degree of tumor differentiation were related factors for postoperative survival of HCC patients [ hazard ratio ( HR)=1.958, 1.878, 2.170, 1.188, 2.052, 0.222, 95% confidence interval ( CI): 1.185-3.235, 1.147-3.076, 1.389-3.393, 1.092-1.291, 1.240-3.395, 0.070-0.703, P<0.05]. Clinico-pathological data with P<0.2 were included for Lasso regression analysis, and the results showed that age, HBeAg, AFP, surgical procedure, perioperative blood transfusion, maximum tumor diameter, tumor located at liver segment Ⅴ or Ⅷ, liver capsule invasion, and degree of tumor differentiation as high differentiation, moderate-high differentiation, moderate differentiation, moderate-low differentiation were related factors for postoperative survival of HCC patients. The above factors were included for further multivariate COX analysis, and the results showed that HBeAg, surgical procedure, maximum tumor diameter were independent factors affecting postoperative survival of HCC patients ( HR=1.770, 8.799, 1.142, 95% CI: 1.049- 2.987, 1.203-64.342, 1.051-1.242, P<0.05). ② Construction and evaluation of COX nomogram prediction model: the clinicopathological factors of P≤0.1 in the COX multivariate analysis were induced to Rstudio software and rms software package to construct COX nomogram prediction model in the training dataset. The COX nomogram prediction model for predicting postoperative overall survival had an consistency index of 0.723 (se=0.028), an AUC of 0.760 for postoperative overall survival of 3 years in the training dataset, an AUC of 0.795 for postoperative overall survival of 3 years in the validation dataset. The verification of the calibration plot in the training dataset showed that the COX nomogram prediction model had a good prediction performance for postoperative survival. COX nomogram score=0.627 06×HBeAg (normal=0, abnormal=1)+ 0.134 34×maximum tumor diameter (cm)+ 2.107 58×surgical procedure (laparoscopy=0, laparotomy=1)+ 0.545 58×perioperative blood transfusion (without blood transfusion=0, with blood transfusion=1)-1.421 33×high differentiation (non-high differentiation=0, high differentiation=1). The COX nomogram risk scores of all patients were calculated. Xtile software was used to find the optimal threshold of COX nomogram risk scores. Patients with risk scores ≥2.9 were assigned into high risk group, and patients with risk scores <2.9 were assigned into low risk group. Results of Kaplan-Meier overall survival curve showed a significant difference in the postoperative overall survival between low risk group and high risk group of the training dataset ( χ2=33.065, P<0.05). There was a significant difference in the postoperative overall survival between low risk group and high risk group of the validation dataset ( χ2=6.585, P<0.05). Results of further analysis by the decision-making curve showed that COX nomogram prediction model based on the combination of HBeAg, surgical procedure, perioperative blood transfusion, maximum tumor diameter, and degree of tumor differentiation was superior to any of the above individual factors in prediction performance. (5) Evaluation of prediction performance between RF machine learning algorithm prediction model and COX nomogram prediction model: prediction difference between two models was investigated by analyzing maximun tumor diameter (the important variable shared in both models), and by comparing the predictive error curve of both models. The results showed that the postoperative 3-year survival rates predicted by RF machine learning algorithm prediction model and COX nomogram prediction model were 77.17% and 74.77% respectively for tumor with maximum diameter of 2.2 cm ( χ2=0.182, P>0.05), 57.51% and 61.65% for tumor with maximum diameter of 6.3 cm ( χ2=0.394, P>0.05), 51.03% and 27.52% for tumor with maximum diameter of 14.2 cm ( χ2=12.762, P<0.05). With the increase of the maximum tumor diameter, the difference in survival rates predicted between the two models turned larger. In the validation dataset, the AUC for postoperative overall survival of 3 years of RF machine learning algorithm prediction model and COX nomogram prediction model was 0.723 and 0.795, showing a significant difference between the two models ( t=3.353, P<0.05). Resluts of Bootstrap cross-validation for prediction error showed that the integrated Brier scores of RF machine learning algorithm prediction model and COX nomogram prediction model for predicting 3-year survival were 0.139 and 0.134, respectively. The prediction error of COX nomogram prediction model was lower than that of RF machine learning algorithm prediction model. Conclusion:Compared with machine learning algorithm prediction models, the COX nomogram prediction model performs better in predicting 3 years postoperative survival of HCC, with fewer variables, which is easy for clinical use.

Objective:To investigate the definition and influencing factors of early recurrence after resection for synchronous colorectal cancer liver metastases (sCRLM).Methods:Patients with sCRLM in Department of Hepatobiliary Surgery, Cancer Hospital, Chinese Academy of Medical Sciences from December 2008 to December 2016 were included. Restricted cubic spline was used to determine the correlations between the time of recurrence and the long-term prognosis. The univariable and multivariable Cox was performed to measure the feasibility of recurrence within 6 months as the early recurrence. Then apply logistic regression, support vector machine, decision tree, random forest, artificial neural network and XGBoost, these machine learning algorithm to comprehensively rank the importance of every clinicopathological variable to early recurrence, and according to the comprehensively ranks, we introduced variables into the multivariable logistic regression model and observed the receiver operating characteristic curve (ROC) of the logistic regression model, based on the ROC area under curve, Akaike information criterion, and Bayesian information criterion, we identified the best performed variable combination and introduced them into the multivariate logistic regression analysis to confirm the independent risk factors for early recurrence. Subsequently, inverse probability weighting (IPTW) was performed on the therapy-associated independent risk factor to evaluate and validate its influence on the early recurrence of sCRLM patients after reducing the standardized mean difference of all covariates.Results:A total of 228 sCRLM patients who received resection were enrolled and followed up from 2.10 to 108.57 months. There were 142 males and 86 females, aged (55.89±0.67) years old. In 170 (74.6%) patients with recurrence, restricted cube analysis determined that the hazard ratio (HR) of disease free survival (DFS) and overall survival (OS) satisfies a linear relationship ( P<0.05), and Cox analysis indicated that 6 months as the time cutoff for defining early recurrence was feasible ( HR=3.405, 95% CI: 2.098-5.526, P<0.05). Early recurrence was occurred in 93 (40.79%) patients. The survival rate of patients in early recurrence group was significantly lower than that in the late recurrence group ( HR=3.405, 95% CI: 2.098-5.526, P<0.05, and the 5-year survival rate was 14.0% vs 52.0%). Comprehensive analysis of 6 machine learning algorithms identified that the total number of lymph node dissection >22 ( OR=0.258, 95% CI: 0.132-0.506, P<0.05) is an independent protective factor for early recurrence, while the number of liver metastases>3 ( OR=4.715, 95% CI: 2.467-9.011, P<0.05) and postoperative complications ( OR=2.334, 95% CI: 1.269-4.291, P<0.05) are independent risk factors. Finally, the IPTW analysis fully reduced the influence of covariate confounding influence via causal inference to prove lymph node dissection associated with early recurrence (IPTW OR=0.29, P<0.05), benefiting the DFS (IPTW HR=0.4887, P<0.05), but without influence on OS (IPTW HR=0.6951, P>0.05). Conclusion:Six months after sCRLM as the definition of early recurrence, it has significant feasibility. The long-term survival of patients with early recurrence is poor. The independent influencing factors of early recurrence after sCRLM are the total number of lymph node dissection, the number of liver metastases and postoperative complications disease.

Objective:To compare the safety and outcome between total laparoscopic and laparoscopy-assisted synchronous resection for colorectal cancer patients with liver metastases.Methods:The data of patients who underwent total laparoscopic or laparoscopy-assisted simultaneous resection of primary colorectal cancer and liver metastases in our hospital between December 2008 and December 2016 were collected and analyzed. The total laparoscopic surgery patients were matched 1∶2 to the laparoscopy-assisted surgery patients based on the propensity score. 22 patients were classified in the total laparoscopic group and 44 patients were classified in the laparoscopy-assisted group. The intraoperative conditions and postoperative outcomes of the two groups were compared.Results:There was no difference in the preoperative baseline data between the two groups ( P>0.05). The median operative time were 317.50 and 267.50 minutes in the total laparoscopic group and the laparoscopy-assisted group, respectively, and the median intraoperative blood loss were 100 and 200 ml, both with no statistically significant differences ( P>0.05). There were 1 case of intraoperative blood transfusion in the total laparoscopic group and 5 cases in the laparoscopy-assisted group, with no statistically significant difference ( P=0.650). The median postoperative hospital stay in the two groups were 11.0 and 10.0 days, the median postoperative defecation time were 4.0 and 4.0 days and postoperative complication rates were 13.6% and 20.5%, and none of these differences were statistically significant ( P>0.05). However, no Clavien-DindoⅡ level and above complications occurred in total laparoscopic group. The median disease-free survival (DFS) were 15.0 and 15.7 months in the total laparoscopic group and the laparoscopy-assisted group, the overall survival (OS) were 25.9 and 37.6 months, respectively, with no statistically significant differences ( P>0.05). Conclusion:Laparoscopy-assisted approaches are similar, so the appropriate approach should be chosen according to the clinical condition and surgeon′s experience.