Atmospheric particulate matter(PM2.5)is a major contributor to the development and progression of chronic respir-atory diseases(CRD).The mechanisms involved in PM2.5-in-duced CRD are complex,in which airway epithelial barrier im-pairment is a key pathophysiological basis and initial link.PM2.5 exposure results in airway epithelial barrier disruption via various ways,including physical barrier,mucociliary barrier,immune barrier,and respiratory microbiota barrier.Currently,there are few therapeutic interventions targeting the airway epithelial barri-er in CRD.Antioxidants,vitamin D,and traditional Chinese medicine are mainly used as auxiliary regimens but clinical evi-dence is lacking.Understanding these mechanisms may provide a scientific basis for further identifying the mechanism of CRD and seeking novel treatment strategies.

Objective:To investigate the prognostic factors for esophageal cancer after radical resection and the application value of machine learning prediction model.Methods:The retrospective cohort study was conducted. The clinicopatholigical data of 406 esophageal cancer patients who were admitted to Qilu Hospital of Shandong University from January 2018 to March 2022 were collected. There were 357 males and 49 females, aged (64±8)years. All patients underwent radical resection of esophageal cancer. The 406 patients were randomly divided into a training set of 285 cases and a validation set of 121 cases at a 7∶3 ratio based on a random number table. The training set was used to construct prediction model, and the validation set was used to validate prediction model. Patients were divided into high-risk group and low-risk group based on risk scores. Observation indicators: (1) follow-up of patients and analysis of influencing factors for prognosis; (2) construction and validation of machine learning prediction models. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the rank sum test. The Kaplan-Meier method was used to calculate survival rate and plot survival curve, and the Log-rank test was used for survival analysis. The Cox proportional hazard regression model was used for univariate and multivariate analyses. Independent influencing factors were included, and data processing, machine learning model construction, and visualization were performed using R packages including random survival forest (RSF), gradient boosting machine (GBM), least absolute shrinkage and selection operator Cox regression (LASSO-Cox), Cox proportional hazards model boosting (CoxBoost), survival support vector machine (survivalsvm), extreme gradient boosting (XGBoost), supervised principal component analysis (SuperPC), and Cox partial least squares regression (plsRcox). Receiver operating characteristic (ROC) curves were drawn, and sensitivity, specificity, and area under the curve (AUC) were calculated. The Delong test was used to assess the differences in AUC among different models in the training set, and the time-dependent ROC was used to compare the predictive performance of different models. Calibration curves were used to evaluate model accuracy, and decision curve analysis (DCA) was used to evaluate overall net benefit. Results:(1) Follow-up of patients and analysis of influencing factors for prognosis. All 406 patients were followed up postoperatively for 28(range, 6-36)months, with 1- and 3-year overall survival rate of 86.5% and 40.9%, respectively. The 285 patients in the training set were followed up postoperatively for 30(range, 6-36)months, with 1- and 3-year overall survival rate of 85.1% and 35.5%, respectively. The 121 patients in the validation set were followed up postoperatively for 25(range, 6-36)months, with 1- and 3-year overall survival rate of 87.0% and 43.2%, respectively. There was no significant difference in postoperative overall survival rate between the training set and the validation set ( χ2=3.20, P>0.05). Results of multivariate analysis showed that left thoracic surgical approach, preopera-tive neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia were independent risk factors affecting postoperative survival of 285 patients in the training set ( hazard ratio=1.466, 1.037, 1.482, 1.549, 5.268, 7.727, 22.202, 2.539, 2.686, 1.425, 95% confidence interval as 1.026-2.096, 1.003-1.073, 1.008-2.179, 1.105-2.170, 1.201-23.099, 1.833-32.576, 4.734-104.128, 1.577-4.087, 1.631-4.422, 1.018-1.994, P<0.05). (2) Construction and validation of machine learning prediction models. Independent risk factors affecting postoperative survival were included to construct RSF, GBM, LASSO-Cox, CoxBoost, survivalsvm, XGBoost, SuperPC, and plsRcox machine learning prediction models. Results of Delong test showed that there were significant differences in the AUC of RSF and GBM from the other six models ( P<0.05). Results of time-dependent ROC curve showed that all 8 machine learning predic-tion models had good discriminative ability in the training cohort, among which the RSF machine learning prediction model had the best predictive performance. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postoperative 1-, 2-, and 3-year overall survival in the training cohort, with high consistency with actual results. Results of decision curve analysis showed that within a threshold range of 0-0.80, the RSF machine learning prediction model provided a better overall net benefit. Further analysis showed that in the validation set, the AUC of RSF machine learning prediction model for postoperative 1-, 2-, and 3-year survival prediction were 0.786 (95% confidence interval as 0.609-0.962), 0.774 (95% confidence interval as 0.676-0.873), and 0.750 (95% confidence interval as 0.652-0.848), respectively. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postopera-tive 1-, 2-, and 3-year overall survival in the validation set, with high consistency with actual results. In the training set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score <11.7 as the low-risk group. The median survival times of the two groups were 18.0 months and >36.0 months, respectively, showing a significant difference between them ( χ2=73.30, P<0.05). In the validation set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score<11.7 as the low-risk group. The median survival times of the two groups were 17.0 months and>36.0 months for the high-risk and low-risk groups, respectively, showing a significant difference between them ( χ2=35.20, P<0.05). Conclusions:Left thoracic surgical approach, preoperative neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia are independent risk factors affecting survival of esophageal cancer patients after radical resection. The RSF machine learning prediction model constructed based on these factors can effectively distinguish the survival prognosis of high-risk and low-risk patients.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

Objective:To investigate levels of endothelin-1(ET-1)and Apclin in patients with hypertrophic car-diomyopathy(HCM)and diagnostic value of their combination with ECG for HCM,and their association with prognosis.Methods:A total of 150 HCM patients admitted in the Second Affiliated Hospital of Xi'an Medical Uni-versity between June 2020 and June 2022 were selected as observation group.According to death during follow-up,the observation group was divided into survival group(n=64)and death group(n=86),and another 100 healthy volunteers who underwent physical examination in our hospital simultaneously were selected as control group.ET-1,Apelin and ECG indexes were compared between above-mentioned groups.Diagnostic value of ET-1,Apelin and ECG combined detection for HCM was analyzed by receiver operating characteristic(ROC)curve.Multivariate Logistic regression was used to analyze influencing factors of death within 6-month follow-up in HCM patients,and nomogram model was established.Results:Compared with participants in control group,those in the observa-tion group had significant higher ET-1[(0.64±0.15)pmol/L vs.(0.39±0.07)pmol/L],QRS wave group(∑QRS)[(23.60±3.96)mm vs.(14.02±1.78)mm],Cornell voltage index(SV3+RaVL)[(2.12±0.40)mV vs.(1.05±0.20)mV]and S-wave on V1 lead+R-wave on V5 lead(SV1+RV5)[(3.88±0.73)mV vs.(2.24±0.34)mV],and significant lower Apelin[(1.10±0.25)pg/ml vs.(1.58±0.17)pg/ml]level(P＜0.001 all).ROC curve indicated that the area under the curve(AUC)of combined detection of above five indexes diagno-sing HCM was 0.933(95％CI 0.895～0.961),significantly higher than any single detection(Z=3.681～6.428,P＜0.001 all),the H-L goodness of fit test showed P=0.056,suggesting that the model was well accepted,and DCA showed that ET-1 and Apelin combined ECG detection model had good clinical application value in HCM.Multivariate Logistic regression indicated that ET-1,∑QRS,SV3+RaV and SV1+RV5 were independent risk factors for death within 6-month in HCM patients(OR=2.617～3.600,P＜0.001 all),and Apelin was its inde-pendent protective factor(OR=0.271,P＜0.001).The nomogram model of HCM patients dying within 6 months was 4.627+0.452 × ET-1+0.536 × Apelin+0.575 × ∑QRS+0.541 × SV3+RaVL+0.352 × SV1+RV5.Conclusion:Serum ET-1 and Apelin levels significantly change in HCM patients,and the combination of ECG detection and both indexes have good performance diagnosing HCM and are independent influential factors for the death of HCM patients within 6 months.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objectives:To analyze factors associated with physical fitness and health in children and adolescents from the perspective of cohort and urban-rural differences in order to provide evidence for optimizing health intervention policies.Methods:Using data from the China Family Panel Studies(CFPS)from 2012 to 2020,this study examined trends in the health of children and adolescents in terms of height and weight.A hierarchical mixed-effects model was used to examine the impact of socioeconomic factors such as household income,health insurance and regional public health expenditure on physical fitness and health.Interaction models were also used to assess heterogeneous effects across birth cohorts and urban-rural contexts.Results:The physical fitness and health of children and adolescents in China have improved significantly,but urban-rural disparities persist.Household income,parental education and health insurance have protective effects on health,but the strength of these effects varies by cohort and between urban and rural areas.Height and weight outcomes for rural children were more closely associated with economic development and health insurance coverage.Conclusions:The factors associated with physical fitness and health in children and adolescents are dynamic.It is necessary to establish a tiered and targeted health promotion system,strengthening health insurance coverage and interventions in rural areas,while prioritizing family-based healthy lifestyle counselling in urban areas.

Objective To study the damage effect of high-voltage electric shock on skin based on metabolomics,analyze its metabolic differences,and explore its injury mechanism.Methods A total of 16 SPF C57BL/6J male mice were divided into the electric shock group(head skin received electric shock treatment)and control group(head skin received electric shock acoustic-optical stimulation),and the skin appearance after treatment of mice in the two groups was observed.The histopathological changes caused by electric shock were analyzed by HE staining,EVG staining and Masson staining.GC-MS and LC-MS metabonomics were used to analyze the changes of skin metabolism spectrum and tissue metabolites after electric shock exposure,and the differential metabolites were analyzed.The obtained differential metabolites were combined and KEGG enrichment analysis was conducted.Results After high-voltage electric shock,the skin of mice could be damaged to the dermis,and the epidermis was partially thickened,lifted and separated.The structure of skin appendages in the dermis was destroyed,with a large number of inflammatory cells infiltrating and obvious swelling,accompanied by congestion,which led to severe skin inflammatory reaction and impaired skin barrier function.Metabonomics analysis suggested that the metabolites changed after electric shock exposure.KEGG enrichment analysis showed that electric shock significantly affected the central carbon metabolism pathway of cancer,pentose phosphate pathway,purine metabolism,glycine,serine and threonine metabolism processes,amino acid tRNA biosynthesis mechanism,glycerophospholipid metabolism pathway,pyrimidine metabolism pattern,glycolysis/gluconeogenesis,alanine metabolism process,glucagon signal pathway and so on.Conclusion High voltage electric shock can cause deep skin damage,disturb its energy metabolism and amino acid metabolism,and seriously interfere with its antioxidant and DNA repair system functions.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

To enhance the practical ability and job competency of full-time master of public health (MPH) postgraduates and explore a collaborative training mode that integrates medical education with a prevention-and-control approach, in line with standardized public health physician training, the Beijing Center for Disease Control and Prevention, in collaboration with the School of Public Health affiliated to Capital Medical University, had recruited full-time MPH postgraduates since 2015. These students were trained and assessed through a collaborative training mode based on the Beijing public health physician training mechanism. Through the introduction and analysis of the training objectives, training process, practical assessment methods, training quality, and results, this article suggests that the construction of a collaborative training mode integrating MPH postgraduate education of public health professionals and standardized public health physician training has explored a new pathway for cultivating "four-certification integration" public health professionals. This aligns with the Chinese national strategy for public health talent development and can alleviate the problems of "contradictions between work and study", including the current shortage of public health physicians at present and the difficulties in standardized training enrollment. In addition, this collaborative training mode provides valuable experience for other medical schools in training applied public health professionals who meet national public health standards and combine prevention with treatment.

This research investigated the contamination level,distribution of drug-resistant strains,and molecular epidemiologi-cal characteristics of Campylobacter,and further explored transmission pathways and prevention strategies.Cecum,chicken carcass,chicken product,and environmental samples,as well as swabs from workers'hands,were collected from a slaughterhouse in a large broiler group in the Jiaodong area between August 2023 and July 2024.Quantitative contamination assessment of Campylobacter in chicken carcasses and chicken products was performed.After microbial mass spectrometry identification,the representative strains of different links were selected for drug resistance testing and whole genome sequencing(WGS).On the basis of the sequencing results,the resistance genes,virulence genes,multilocus sequence typing(MLST),and phylogenetic characteristics of representative strains were analyzed.Homology comparisons were performed between isolates and strains from patients with diarrhea in the NCBI database.A total of 297 Campylobacter strains were isolated from 806 samples,and the overall detection rate was 36.85%.The detection rate of Campylobacter was highest in the evisceration process(47.33%),followed by the cutting process(35.64%).Overall,the Campylo-bacter detection rate first increased,then decreased,and subsequently increased.Drug sensitivity testing revealed that 90 isolates were resistant to nalidixic acid and ciprofloxacin,and 94.97%of isolates were resistant to tetracycline.WGS showed that both Campylo-bacter jejuni(C.jejuni)and Campylobacter coli(C.coli)carried many drug resistance and virulence genes.ST-14176 of C.jejuni was isolated for the first time herein.The predominant ST-8261 strain of C.jejuni and ST-860,ST-829,and ST-1586 strains of C.coli are known to cause human diarrhea.LOS expression genes associated with Guillain-Barré syndrome(GBS)were detected in both C.jejuni isolates from the slaughter chain and patients with GBS.Some strains exhibited close genetic relatedness to human-derived Campylo-bacter strains from the NCBI database.The detection rate of Campylobacter in the slaughterhouse first increased,then decreased,and subsequently increased,and the quantitative contamination level of each link was similar to the detection rate.Quantitative analysis of chicken carcasses/products revealed that the average bacterial load was highest in eviscerated carcasses(102.80 cfu/g),and the high-est amount of Campylobacter in chicken products reached 451.80 cfu/g.Abundant drug resistance genes and virulence genes were iden-tified,and the drug resistance genes were highly correlated with the drug resistance rate.Therefore,surveillance intensity and control measures for Campylobacter in slaughter processes should be strengthened.