Hepatic fibrosis(HF)is a pathophysiological outcome of chronic liver injury and is characterized by excessive accumulation of extracellular matrix protein.A number of studies have confirmed that the signaling pathways formed by transforming growth factor-β1(TGF-β1)and its downstream Smad family play an important role in the occurrence and development of HF,and the traditional Chinese medicine(TCM)research targeting this pathway is currently a hot spot in the reversal of HF.Therefore,taking TGF-β1/Smads signaling pathway as the entry point,this paper reviewed the mechanism of action of TCM compound formula and single drug extract in intervening TGF-β1/Smad pathway and related factors upstream and downstream of the pathway to reverse HF in recent years,revealed the targeted therapeutic effect of TCM,and provided new strategies for clarifying the mechanism of TCM.

Objective To develop the functions and optimize the automatic monitoring module for arrhythmias of the adverse drug event active surveillance and assessment system-Ⅱ,in order to continuously improve the performance,enhance the monitoring efficiency,and explore the ways to optimize the module.Methods Expand and optimize the functions of the module,increase the customized configuration,and determine the optimal setting conditions;compare the optimized test data with the results of the evaluation studies on the automatic monitoring of drug-induced arrhythmias in large samples of medicated population previously,and verify the optimization extent as well as the accuracy of the module.Results In the new module optimized according to the characteristics of the monitoring population,the function of"mandatory medical order keywords"was added,and it was determined that the inclusion of 6 electrocardiogram examination-related medical order keywords with a frequency of not less than 2 occurrences was the optimal configuration condition for the optimization of the module;combining the results of the previous automatic monitoring and evaluation researches,the system functions were verified and compared under the conditions of using the whole drugs and 2 kinds of single drug.While there was no loss of true positive cases,the number of cases with system alarms decreased by 30.75％,80.13％and 90.82％,respectively,compared with that before the optimization of the module,and the positive predictive value was significantly improved.Conclusion After the function expansion and optimization,the automatic monitoring module of drug-induced arrhythmias significantly reduces the labor cost of case evaluation and keeps the accuracy of monitoring results constant;the new module can better adapt to the demands of different automatic monitoring modes and operates stably,which is more generalizable and flexible,and provides a new way of considering for the research and development of automatic monitoring modules.

Objective To observe the value of B1 corrected T1 mapping for distinguishing pathological types and differentiation degrees of lung cancers.Methods A total of 74 lesions in 65 patients with lung cancers were prospectively enrolled,including 49 poorly differentiated lesions and 25 moderately or well differentiated ones,i.e.42 adenocarcinomas,14 squamous cell carcinomas and 18 small cell lung cancers(all poorly differentiated).B1 corrected T1 mapping was performed,ROI(ROI1 and ROI2)were delineated using 2 methods,and T1 values of different pathological types and differentiation degrees lung cancers were compared.The receiver operating characteristic(ROC)curves were drawn,and the areas under the curve(AUC)were calculated.Results Significant differences of T1 values were found among different pathological types of lung cancer(all P＜0.05),as well as between small cell lung cancer and the rest 2 types of lung cancer(both P＜0.05).There were significant differences of T1 values between poorly differentiated and moderately well differentiated lung cancer(squamous cell carcinoma+adenocarcinoma)(both P＜0.05).Taken ROI1 T1 value=1 524.21 ms as the cut-off value,the AUC of T1 value for distinguishing poorly differentiated and moderately well differentiated lung cancer(squamous cell carcinoma+adenocarcinoma)was 0.698,with sensitivity of 64.50％and specificity of 76.00％.Taken ROI2 T1 value=1 630.68 ms as the cut-off value,the AUC of T1 value was 0.676,with sensitivity of 54.80％and specificity of 80.00％.Conclusion B1 corrected T1 mapping was helpful for distinguishing pathological types and differentiation degrees of lung cancers.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quantitative CT(QCT)BMD examination were retrospectively enrolled and divided into training set(n=304)and test set(n=76)at a ratio of 8∶2.The mean BMD of L1-L3 vertebrae were measured based on QCT.Spongy bones of T5-T10 vertebrae were segmented as RO1,radiomics(Rad)features were extracted,and machine learning(ML),Rad and deep learning(DL)models were constructed for classification of osteoporosis(OP)and evaluating BMD,respectively.Receiver operating characteristic curves were drawn,and area under the curves(AUC)were calculated to evaluate the efficacy of each model for classification of OP.Bland-Altman analysis and Pearson correlation analysis were performed to explore the consistency and correlation of each model with QCT for measuring BMD.Results Among ML and Rad models,MLBagging OP and RadBagging-OP had the best performances for classification of OP.In test set,AUC of MLBagging-OP,RadBagging-op and DLOP for classification of OP was 0.943,0.944 and 0.947,respectively,with no significant difference(all P＞0.05).BMD obtained with all the above models had good consistency with those measured with QCT(most of the differences were within the range of(x)±1.96s),which were highly positively correlated(r=0.910-0.974,all P＜0.001).Conclusion AI models based on non-contrast chest CT had high efficacy for classification of OP,and good consistency of BMD measurements were found between AI models and QCT.

Objective: based on summarizing the simulation and prediction of tobacco control measures across the globe and sorting out the various scenarios of tobacco control measures, the potential short-term effects of seven tobacco control measures in different scenarios were systematically analyzed. Methods: Until April 2022, PubMed, Embase, EconLit, PsychINFO, and CINAHL databases were used to retrieve literature about tobacco control measures simulation and prediction models across the globe. Inclusion and exclusion criteria were strictly followed. Meta-analysis for the potential short-term effects of seven tobacco control measures in different scenarios was performed using the R software. Results: A total of 22 papers covering 16 countries were selected. Five studies were conducted in the United States, three in Mexico, and two in Italy. There were all papers with the measures to tax increases, smoke-free air laws, and mass media campaigns, 21 papers with youth access restrictions, 20 with marketing restrictions, and 19 with cessation treatment programs and health warnings. The tax increases had diverse influences on the price elasticity of different age groups. The price elasticity in the age group 15-17 years was the highest, which was 0.044 (95%CI: 0.038-0.051). The potential short-term effects of smoke-free air laws in workplaces were higher than in restaurants and other indoor public places. The effects of youth access restrictions were greater in the age group <16 years than in the age group 16-17. The stronger the implementation of other measures, the greater the potential short-term effects. A comparison of seven tobacco control measures showed that the cessation treatment programs increase in cessation rate was the highest, 0.404 (95%CI: 0.357-0.456). The reduction in smoking rate and reduction in initiation rate of youth access restrictions strongly enforced and publicized was the highest in the age group <16 years, 0.292 (95%CI: 0.269-0.315), and 0.292 (95%CI: 0.270-0.316). Conclusions: The potential short-term effects of seven tobacco control measures in different scenarios were evaluated more accurately and objectively through Meta-analysis. In the short term, cessation treatment programs will substantially increase smoking cessation rates, and strong youth access enforcement will sharply reduce smoking and initiation rates among adolescents under 16. These results also offer strong data-related support for the simulation and prediction of tobacco control measures in China and other countries.
Adolescent ; Humans ; United States ; Tobacco Control ; Prevalence ; Computer Simulation ; Smoking Cessation ; Health Behavior ; Smoking Prevention

Objective:The decline in nutritional status in patients with severe pneumonia may contribute to an increase in in-hospital mortality. Enteral nutrition support can improve the nutritional status of patients, and is relatively easy to manage, with low cost and fewer serious complications. On the other hand, adverse reactions such as gastric retention and gastric microbiota translocation may increase the incidence of nosocomial pneumonia and increase the uncertainty of patient prognosis. There is no predictive model for in-hospital death in severe pneumonia patients receiving enteral nutrition support. The objective of this study was to investigate the risk factors of in-hospital death in patients with severe pneumonia receiving enteral nutrition support and to establish a prognostic model for such patients.Methods:This was a single-center retrospective study. Patients with severe pneumonia who were hospitalized in Peking Union Medical College Hospital and received enteral nutrition support were included from January 1, 2015 to December 31, 2020. The primary endpoints were in-hospital mortality rate and unordered discharge rate. The independent risk factors were determined using univariate and multifactorial logistic regression analysis, the nomogram scoring model was constructed, and the decision curve analysis (DCA) was performed.Results:A total of 632 severe pneumonia patients who received enteral nutrition support were included. Patients were divided into death and survival groups according to the presence or absence of in-hospital death, and 24 parameters were found with significant differences between groups. Nine parameters were independent predictors of mortality, namely the duration of ventilator use, the presence of malignant hyperplasia diseases, the maximal levels of platelet and prothrombin during hospitalization, and the nadir levels of alanine aminotransferase, serum albumin, sodium, potassium, and blood glucose. Based on these variables, a risk prediction scoring model was established (ROC = 0.782; 95% CI: 0.744 to 0.819, concordance index: 0.772). Calibration curves, DCA, and clinical impact curve were plotted to evaluate the goodness of function, accuracy, and applicability of the predictive nomogram, using the training and test sets. Conclusion:This study summarized the clinical characteristics of patients with severe pneumonia receiving enteral nutrition support and developed a scoring model to identify risk factors and establish prognostic models.

Objective: To analyze the status quo of the knowledge and related factors of cancer prevention and treatment among residents in Liaoning Province in 2021. Methods: From August to November 2021, through network sampling method, 17 474 permanent residents aged 15-69 years in Liaoning Province were surveyed. The WeChat public account was used to collect information such as demographic characteristics and core knowledge of cancer prevention and treatment. The Chi-square test was used to compare the difference of the level of the cancer prevention and treatment knowledge among different groups. The multivariate logistic regression model was used to analyze the related factors. Results: Among the 17 474 subjects, 43.1% (7 528) were male and 58.7% (10 262) were urban residents. The overall awareness rate was 72.3%, and the awareness rate of cancer cognition, prevention, early diagnosis and treatment, cancer management and rehabilitation were 71.4%, 67.6%, 72.7%, 83.4% and 63.5%, respectively. The multivariate logistic regression model showed that the residents who were man (OR: 0.850, 95%CI: 0.781-0.925), in rural areas (OR: 0.753, 95%CI: 0.694-0.817), 55-59 years old (OR: 0.851, 95%CI: 0.751-0.963), quitters (OR: 0.721, 95%CI: 0.640-0.813) and smoker (OR: 0.724, 95%CI: 0.654-0.801) had lower awareness rates, while the residents who were 35-54 years old (OR: 1.312, 95%CI: 1.202-1.432), with an educational level of junior high school/senior high school/college degree or above (OR: 1.834-5.130, 95%CI: 1.575-6.047), technical personnel (OR: 1.592, 95%CI: 1.367-1.854), civil servant/institution staff (OR: 1.282, 95%CI: 1.094-1.503), enterprise/business/service staff (OR: 1.218, 95%CI: 1.071-1.385), retired (OR: 1.324, 95%CI: 1.114-1.573) and with family history of cancer (OR: 1.369, 95%CI: 1.266-1.481) had higher awareness rates. Conclusion: The level of the awareness of core knowledge of cancer prevention and treatment among residents in Liaoning Province has met the requirements of the Healthy China Action. Region, gender, education level, age, family history of cancer and smoking are relevant factors.
Adult ; Female ; Humans ; Male ; Middle Aged ; China ; Health Knowledge, Attitudes, Practice ; Neoplasms/prevention & control* ; Surveys and Questionnaires ; Adolescent ; Young Adult ; Aged

Humans ; May-Thurner Syndrome ; Coronary Restenosis ; Constriction, Pathologic/surgery* ; Stents/adverse effects* ; Iliac Vein ; Treatment Outcome ; Retrospective Studies