Objective To understand the association and mediating role of PM_2.5 exposure and metabolic phenotypes in the risk of cardiovascular disease （CVD） among middle-aged and elderly populations. Methods A total of 12 395 participants aged ≥45 years and free of baseline CVD were enrolled based on the 2011-2015 longitudinal data from the China Health and Retirement Longitudinal Study（CHARLS）. Annual average PM_2.5 exposure concentrations were stratified into four quartile groups （Q₁-Q₄）. Participants were categorized into four metabolic phenotypes according to waist circumference and metabolic indicators：metabolically healthy non-obese （MHN），metabolically healthy obese （MHO），metabolically unhealthy non-obese （MUN），and metabolically unhealthy obese （MUO）. Cox proportional hazard models were applied to assess the independent and combined effects. Relative excess risk due to interaction（RERI） and attributable proportion（AP） were calculated to evaluate additive interaction，and the Bootstrap approach was used to test the mediating effect. Results During the follow-up period，1 084 incident CVD cases were identified，with a crude incidence rate of 8.75%. After adjustment for confounding factors，the highest PM_2.5 exposure quartile（Q₄） was associated with a 39% higher CVD risk relative to Q₁ （HR=1.39，95%CI：1.18-1.64）. Compared with the MHN group，elevated CVD risks were observed sequentially in the MHO，MUN and MUO groups，with HRs of 1.43，1.58 and 1.85，respectively（P for trend <0.001）. Joint analysis revealed that PM_2.5 exposure exerted no obvious impact on CVD risk in the MHN group，whereas significantly increased CVD risks were observed across all PM_2.5 exposure levels in the MUN and MUO groups. No significant interactive effect was detected between metabolic phenotype and PM_2.5 （P_interaction=0.333）. Mediation analysis confirmed that metabolic phenotype exerted a partial mediating effect，with a mediating proportion of 23.20%（95%CI：12.50%-61.40%）. Conclusions Long-term PM_2.5 exposure confers more pronounced cardiovascular hazards on individuals with metabolically unhealthy phenotypes，particularly those with MUO. Metabolic phenotype acts as a partial mediator in the association between PM_2.5 exposure and CVD. Optimizing metabolic status may help alleviate cardiovascular damage induced by air pollution.

Objective To understand the association between acute ambient fine particulate matter（PM_2.5） exposure and mortality of respiratory diseases and its subtypes in the elderly population，and to know the modification effects of gender and age factors on PM_2.5-related effects，as well as to clarify the interaction with other pollutants. Methods The data of daily respiratory diseases mortality，air pollutants and meteorological factors were collected in Ji'nan from 2013 to 2023. generalized additive model （GAM） combined with distributed lag nonlinear models （DLNM） were used to analyze the lag effects of PM_2.5 exposure on mortalities form respiratory diseases，influenza and pneumonia，and chronic lower respiratory diseases in elderly individuals aged ≥60 years. Subgroup analyses were conducted to explore the effect differences by gender （male，female） and age （non-high-aged elderly <80 years，high-aged elderly≥80 years）. Relative excess risk due to interaction（RERI），attributable proportion of interaction（API），and synergy index（SI） were used to assess the interactions of PM_2.5 with NO₂，SO₂，CO and O₃. Results Among the 41 636 respiratory disease deaths，influenza and pneumonia（37.89%） and chronic lower respiratory diseases（50.36%） were the predominant mortality subtypes. From 2013 to 2023，the mean daily concentration of PM_2.5 reached（63.97±47.42） μg/m³. The single-day lag analysis revealed peak excess risk（ER） for respiratory diseases deaths at lag0（ER=0.96%，95%CI：0.56%-1.37%） per 10 μg/m³ PM_2.5 increase. The cumulative effects peaked at lag07 （ER=2.62%，95%CI：1.51%-3.74%）. The subtype specific analyses showed the maximal single-day effects at lag0 were identified for influenza and pneumonia（ER=1.01%，95%CI：0.36%-1.67%），chronic lower respiratory diseases （ER=0.74%，95%CI：0.23%-1.26%），and chronic obstructive pulmonary diseases（ER=0.59%，95%CI：0.02%-1.17%），while the cumulative risk peaked at lag07 for influenza and pneumonia （ER=4.18%， 95%CI：2.38%-6.02%），lag04 for chronic lower respiratory diseases（ER=1.53%，95%CI：0.49%-2.59%），and lag06 for chronic obstructive pulmonary diseases （ER=1.93%，95%CI：0.51%-3.38%）. No significant difference in effect values was found between gender subgroup and age subgroup （P>0.05）. The interaction analyses revealed an antagonistic effect between PM_2.5 and O₃ on the mortality of respiratory diseases. The PM_2.5 effect remained robust in the multi-pollutant models（P>0.05）. Conclusions Acute PM_2.5 exposure may increase the mortality risk from respiratory diseases and its subtypes in the elderly. Additionally，PM_2.5 and O₃ have an antagonistic effect on respiratory diseases mortality in the elderly.

Objective To systematically review the publication characteristics，collaboration network，research hotspots，and evolution of research on healthcare professionals' satisfaction in China from 2011 to 2025. Methods The literature was retrieved from CNKI，Wanfang Data，and VIP，and analyzed by using CiteSpace 6.4.R2 through author collaboration，keyword co-occurrence，clustering，timeline，and burst detection analyses. Results A total of 688 articles were included. Annual publications increased and then declined，peaking at 80 in 2016. The author collaboration network contained 1 489 nodes and 2 233 links，with a density of 0.002 0. The keyword co-occurrence network contained 450 nodes and 606 links，with a density of 0.006 0. Ten keyword clusters were identified（Q=0.636 8，S=0.901 4）. Research topics expanded from job satisfaction，nurses，and turnover intention to hospital management，healthcare system reform，mental health，young professionals，primary healthcare professionals，and mediating effects. Conclusions The research topics have become increasingly diversified，whereas author collaboration remains dispersed. Future studies should strengthen cross-institutional and cross-regional collaboration，focus on young and primary healthcare professionals，conduct longitudinal and multicenter studies，and further examine the mechanisms underlying satisfaction.

Objective To understand the correlation between gut microbiota characteristics and immune function in children with recurrent respiratory tract infections （RRTI） based on metagenomics. Methods A total of 100 children with RRTI（RRTI group），100 children with occasional respiratory tract infections（infection group），and 100 healthy children（control group） admitted to Nanyang Central Hospital from January 2023 to January 2026 were enrolled. The overall structure，species composition differences，gene function annotation and differences of gut microbiota，as well as immune function were compared among the three groups. The correlation between differential gut microbiota species and immune indicators was analyzed. Results The Chao1，Shannon，and Simpson indices in the RRTI group were lower than those in the infection group，which were in turn lower than those in the control group （P<0.05）. The gut microbiota species richness was the highest in the control group，followed by the infection group，and the lowest in the RRTI group. The relative abundances of short-chain fatty acid synthesis pathways and intestinal barrier-related functional pathways in the gut microbiota of the RRTI group were lower than those in the infection group，which were further lower than those in the control group（P<0.05）. In contrast，the relative abundances of lipopolysaccharide synthesis pathways and bacterial adhesion and invasion pathways in the RRTI group were higher than those in the infection group，which were further higher than those in the control group （P<0.05）. The levels of CD3⁺，CD4⁺，CD4⁺/CD8⁺，and IgA in the RRTI group were lower than those in the infection group，which were in turn lower than those in the control group（P<0.05）. The characteristic species of the control group（Firmicutes，Clostridiales，Ruminococcaceae，Faecalibacterium） were positively correlated with the levels of CD3⁺，CD4⁺，CD4⁺/CD8⁺，and IgA. The characteristic species of the infection group （Bacteroidetes，Bacteroidaceae，Bacteroides） were positively correlated with the levels of CD3⁺，CD4⁺，CD4⁺/CD8⁺，and IgA（P<0.05）. However，the characteristic species of the RRTI group （Bacilli，Lactobacillales，Enterococcaceae，Enterococcus） were negatively correlated with the levels of CD3⁺，CD4⁺，CD4⁺/CD8⁺，and IgA （P<0.05）. Conclusions The gut microbiota characteristics and immune function of children with RRTI are in a state of imbalance，and the imbalance of gut microbiota characteristics is associated with immune dysfunction in these children. This study provides a reference for understanding the pathogenesis of RRTI in children.

Objective To examine the multidimensional value of medical-preventive integration for medical institutions and doctors from the perspective of social environment，and to understand how social environmental factors influence the realization of such value，so as to provide the evidence-based insights for optimizing the policy environment. Methods A multiple case study was conducted. The cases of medical-preventive integration practice across China were retrieved from official websites of governments at all levels and authoritative media between 2023 and 2025，using keywords including ‘medical-preventive integration'，‘prevention-treatment integration'，and ‘medical-preventive collaboration'. Drawing on the Political Economic Social Technological （PEST） analytical framework，an analysis framework was constructed along four dimensions -economic，institutional，sociocultural，and technological environments- and thematic analysis was performed on typical cases. Results A total of 22 typical cases were included，covering 13 provinces such as Sichuan and Shandong. The cases involving the economic environment numbered 14 （63.64%），the institutional environment numbered 8 （36.36%），the sociocultural environment numbered 4 （18.18%），and the technological environment numbered 5 （22.73%）. In terms of the economic environment，medical-preventive integration generated significant economic value for medical institutions through performance reform and medical insurance payment innovations such as the ‘global budget with surplus retention'（e.g.，C1 with a 230% year-on-year growth in medical revenue and C15 with a 110 million yuan surplus in the medical insurance fund）. In terms of the institutional environment，the disease control supervisor system，the compound talent training policy，and the mechanism linking professional title evaluation with public health practice broadened the career development path for doctors（e.g.，C9，C13，C17）. In terms of the sociocultural environment，medical-preventive integration enhanced doctors' sense of professional achievement through improved doctor-patient relationships and service effectiveness（e.g.，C2，C10，C19）. In terms of the technological environment，the construction of information platforms effectively reduced the workload of medical personnel（e.g.，C2 work efficiency increased by 40% and C22 with treatment initiation rates rising from 12.6% to 65.0%）. However，an imbalance remained across the four dimensions，with relatively sufficient economic incentives and institutional supply but relatively weak sociocultural identity and technological support. Conclusions Medical-preventive integration exerts remarkable multidimensional value effects on medical institutions and doctors，yet the realization of such value is profoundly affected by the synergy level across social environment dimensions. It is recommended to further optimize medical insurance payment and performance incentive mechanisms，improve career development channels for compound talents，strengthen social publicity and information-based support，and construct a four-dimension coordinated social environment to fully unleash the value potential of medical-preventive integration.

Objective To understand the relationship between atmosphere fine particulate matter（PM_2.5） and inhalable particulate matter（PM₁₀） exposure and daily emergency hospital visits of residents' respiratory diseases in Nanchang. Methods The daily data on emergency hospital visits for respiratory diseases，average daily concentrations of ambient air pollutants （PM_2.5，PM₁₀），and meteorological data （average daily temperature and relative humidity） in the city from 2020 to 2024 were collected. A generalized additive model （GAM） was employed to quantitatively assess the association between concentration changes of PM_2.5 and PM₁₀ and emergency hospital visits for respiratory diseases. Results The effect of PM₁₀ was strongest at lag07，with a 4.21%（95%CI：0.27%-8.29%） increase in emergency hospital visits per 10 μg/m³ increase in concentration. No significant association was found between PM_2.5 and the general population. Subgroup analysis showed that both PM_2.5 and PM₁₀ affected only males，with the strongest effects observed at lag07，yielding ER（95%CI） values of 8.46%（0.45%-17.57%） and 4.85%（0.89%-9.83%），respectively. For the population aged ≤60 years，the effects of PM_2.5 and PM₁₀ peaked at lag6 and lag5，respectively，with ER（95%CI） values of 3.42%（0.75%-6.17%） and 1.62%（0.29%-2.96%）. For the population aged >60 years，the effects peaked at lag02 and lag06，with ER（95%CI） values of 5.17%（0.05%-10.54%） and 4.61%（0.51%-8.88%），respectively. During the cold season（October to March），the effects of PM_2.5 and PM₁₀ on the general population were strongest at lag7 and lag07，respectively，with ER（95%CI） values of 3.42%（0.48%-6.44%） and 7.62%（1.51%-14.10%）. No significant effects were observed during the warm season. Conclusions Males and individuals aged over 60 are more susceptible to exposure to both particulate matters. Compared to PM₁₀，ambient air PM_2.5 increase is more likely to elevate the risk of emergency room visits for respiratory diseases among males and those aged over 60. The cold season represents a sensitive period.

Objective To clarify the pathophoresis characteristics of respiratory pathogens in Guiyang City for the year 2025 and determine the low-temperature prevention and control threshold，thereby providing a basis for precision prevention and control of respiratory infectious diseases in high-altitude regions of Southwest China. Methods Nucleic acid detection data for respiratory pathogens from 2 910 clinical cases collected at two national sentinel hospitals in Guiyang City during 2025 were obtained，and the data were matched with monthly average temperature records from the same period. Descriptive epidemiological methods and Pearson correlation analysis were employed for statistical analysis. Results In 2025，the overall positive detection rate of respiratory pathogens in Guiyang City was 45.16%. The peak incidence occurred during late winter and early spring（February：56.72%；April：54.38%） and during the winter season（December：58.68%），while September during the summer and autumn months recorded the lowest annual level （28.44%）. The overall positive detection rate showed a strong negative correlation with monthly average temperatures（r=-0.82，P<0.01）. The highest positive detection rate was observed among minors aged 0-18 years（58.23%），showing the strongest negative correlation with temperature（r=-0.86，P<0.001）. Influenza viruses were the only pathogen exhibiting a strong negative correlation with temperature（r=-0.87，P<0.001）. When the monthly average temperature was <10 ℃，the overall positive detection rate reached its highest value at 54.21%，with an attributable risk percentage of 37.65%. Conclusions The positive detection rate of respiratory pathogens in Guiyang City in 2025 exhibited significant seasonal fluctuations，and low temperatures served as a key environmental factor driving the prevalence of respiratory pathogens，particularly affecting the influenza viruses and the group of minors.

Objective To understand the epidemiological characteristics，vaccination status and etiological test results of influenza among elderly individuals aged ≥60 years in Linping District，Hangzhou City from 2023 to 2025，and to provide the scientific data for influenza prevention and control in this population. Methods The data on influenza cases，vaccination and etiological testing among the elderly in Linping District，Hangzhou，were collected from the China Disease Prevention and Control Information System and the Zhejiang Provincial Intelligent Vaccination Service Information System. Descriptive epidemiological methods were used to analyze the distribution characteristics of influenza incidence，vaccination coverage and etiological profiles. Results A total of 5 565 influenza cases were reported among the elderly in Linping District，Hangzhou，from 2023 to 2025，with breakthrough cases accounting for 9.45%. The average annual reported incidence rate was 1 619.33 per 100 000，with the highest rate of 2 152.03 per 100 000 observed in 2025. The majority of cases occurred in the 60-69 age group，and the incidence rate was slightly higher in females compared with males. The influenza vaccination coverage rate was highest in 2024（33.71%），followed by 2025（11.45%）. Single-pathogen infections predominated among elderly influenza cases，accounting for 91.36% of all etiologically confirmed cases. Conclusions The incidence of influenza among the elderly in Linping District，Hangzhou City showed an increasing trend from 2023 to 2025，with considerable fluctuations in vaccination coverage rates. Enhanced health education on influenza prevention and control，improved vaccination coverage among the elderly，and strengthened surveillance of influenza etiological characteristics and breakthrough cases are warranted.

Objective To analyze and forecast the outpatient volume of a stomatology hospital in 2025 by establishing a Seasonal Autoregressive Integrated Moving Average（SARIMA） model，for the rational allocation of medical resources in the hospital. Methods The outpatient volume data from 2015 to 2023 were used as the training set，and the data from 2024 were used as the test set. The grid search method was employed to systematically traverse the parameter space of the SARIMA model. The optimal parameter combination was determined based on the minimization principles of Akaike's Information Criterion（AIC），Akaike Information Criterion with Correction（AICC），and Bayesian Information Criterion（BIC）. The SARIMA model was constructed accordingly. Subsequently，using the data from 2015 to 2024 and referencing the determined model parameters，the model was fitted to forecast the monthly outpatient volume for 2025. Results The outpatient volume of the stomatology hospital showed an upward trend，with minor peaks in March and August. The optimally fitted SARIMA model was SARIMA（2，0，1）（1，1，1）₁₂，with an AIC of 1 966.77，AICC of 1 967.72，BIC of 1 982.16，and a coefficient of determination R² of 0.87. The Mean Absolute Percentage Error（MAPE） of the model was 15.21% on the training set and 8.97% on the test set（2024 data）. Conclusions The application of the SARIMA model effectively fits the outpatient volume of this stomatology hospital. The model demonstrates good predictive accuracy and can provide a theoretical basis for forecasting the hospital's outpatient volume.

Objective To understand the pollution characteristics and sources of 12 metallic elements in atmospheric PM_2.5 in two urban districts of Guiyang over the past decade，and to know the health risks. Methods The monitoring data on metal components in PM_2.5 from the Nanming and Huaxi Districts of Guiyang from 2015 to 2024 were collected. Descriptive methods were employed to analyze the distribution characteristics，while source apportionment was conducted by using enrichment factor analysis and principal component analysis. Chronic health risks via inhalation were assessed following relevant national guidelines. Results The top five metals in terms of mass concentration in PM_2.5 in both districts were aluminum，lead，manganese，arsenic，and selenium，in descending order. The annual average concentrations of various metals generally exhibited a fluctuating downward trend，with seasonal distributions showing higher concentrations in winter and spring compared to summer and autumn. The variation patterns in the two districts were largely consistent. Selenium showed the highest enrichment in both districts，followed by cadmium，with enrichment factor（EF） values greater than 430 and 180，respectively. Principal component analysis identified four main components，with a cumulative contribution rate of 60.7%. Elements with high load included selenium，thallium，lead，arsenic，mercury，beryllium，cadmium， and chromium. In both districts，manganese，arsenic，chromium，and cadmium had hazard quotient（HQ） values greater than 1. The carcinogenic risk （CR） values for arsenic and chromium in Nanming District ranged from 1.0×10^-6 to 1.0×10^-4，while in Huaxi District，arsenic's CR values fell within the same range. Conclusions Over the past decade，metallic and metalloid pollution in PM_2.5 in urban area of Guiyang likely originated primarily from coal combustion，traffic pollution，and industrial emissions. Arsenic and chromium pose certain carcinogenic risks.

Objective Based on the influenza A virus detection results during the flu season，to understand the epidemiological characteristics，and provide the reference for enhancing influenza prevention and control effectiveness. Methods This study included suspected cases who underwent influenza virus nucleic acid testing at Nanchang Central Hospital between October 2024 and December 2025. A total of 789 samples were analyzed to statistically compare the prevalence of influenza A virus and its subtypes across different seasons，while also conducting an epidemiological study. Results Among the 789 cases，the infection rate of influenza A virus was 21.67%. Compared among different subtypes，the positive rate of H3N2 was higher than that of H1N1（P<0.05）. Compared among different seasons，the positive rate of influenza A virus in autumn and winter was higher than that in spring and summer（P<0.05）. Compared among different time periods，the H1N1 subtype was the same in June 2025，while the H3N2 subtype was the same after July 2025. The positive rates of influenza A virus cases in the groups aged 0-14，≥65 and 15-64 decreased successively（P<0.05），however，there was no significant difference in the distribution of subtypes among different age groups （P>0.05）. There was no significant difference in the positive rates of influenza A virus cases and subtype distribution between males and females（P>0.05）. Conclusions The local influenza season influenza A virus infection is at a normal epidemic level，with H3N2 being the main epidemic strain. There is a significant seasonal aggregation，with a higher incidence in autumn and winter，and children are the high-risk group，followed by the elderly. It is recommended to formulate targeted strategies based on these situations to improve the effectiveness of prevention and control.

Objective To understand the relationship between systemic immune-inflammation index（SII），homocysteine（Hcy） levels and non-invasive hemodynamic parameters in elderly patients with severe heart failure （HF），and to konw their association with the risk of death. Methods A retrospective study was conducted on 104 elderly patients with severe HF admitted to the First People's Hospital of Jiande City from September 2022 to September 2025. The patients were divided into the survival group（n=62） and the death group（n=42） according to all-cause death after 6 months of onset. General data，SII，Hcy and non-invasive hemodynamic parameters were compared between the two groups. Multivariate Logistic regression analysis was used to identify the influencing factors of death. Receiver operating characteristic（ROC） curve was used to analyze the predictive efficacy of SII，Hcy and non-invasive hemodynamic parameters for death. Likelihood ratio test was used to compare the linear and natural spline models of Hcy，and the linear model was used to calculate the relationship between Hcy and the risk of death. Two-way analysis of variance was used to compare the effects of SII and Hcy on non-invasive hemodynamics. Generalized linear model was used to evaluate the effect of SII on the regression relationship between Hcy level and death risk. Results Compared with the survival group，the death group had higher age，disease duration，SII，Hcy and left ventricular end-diastolic volume（LVEDV）（P<0.05），and lower left ventricular ejection fraction（LVEF），stroke volume （SV），stroke volume index （SVI），cardiac output （CO），cardiac index （CI） and left ventricular work index （LCWI）（P<0.05）. With the increase of age，disease duration，SII，Hcy and LVEDV were risk factors for death （OR>1，P<0.05），and the increase of LVEF，SV，SVI，CO，CI and LCWI were protective factors for death（OR<1，P<0.05）. SII，Hcy，LVEF，SV，SVI，CO，CI，LCWI and LVEDV all had significant predictive efficacy for death（AUC>0.75，P<0.05）. The combined predictive efficacy of the indicators（AUC=0.916，95%CI：0.851-0.955） was significantly higher than that of a single parameter. Hcy level was positively correlated with the risk of death in different SII states （P<0.05），for each 1 μmol/L increase in Hcy，the ER values of death in elderly patients with severe HF in SII≤604.09×10⁹/L，SII（604.10-757.26）×10⁹/L and SII>757.26×10⁹/L were 1.082（95%CI：1.025-1.142），1.105（95%CI：1.043-1.171） and 1.138（95%CI：1.069-1.211），respectively. LVEF≤31.50%，SV≤48.25 mL，SVI≤27.60 mL/m²，CO≤3.45 L/min，CI≤1.90 L/（min·m²），LCWI≤28.75 kg·m/m² and LVEDV>165.50 mL had a higher risk of death（P<0.05）. With the increase of SII，LVEF，SV，SVI，CO，CI and LCWI of patients with different Hcy levels gradually decreased，while LVEDV gradually increased. The main effects of SII and Hcy on all non-invasive hemodynamic parameters were significant（P<0.05），and the interaction effects on LVEF，SVI，CI and LVEDV were significant（P<0.05）. With the increase of SII，the positive correlation between Hcy level and death gradually strengthened. Conclusions The increase of age，disease duration，SII，Hcy and LVEDV，and the decrease of LVEF，SV，SVI，CO，CI and LCWI are closely related to the risk of death in elderly patients with severe HF. The combination of these indicators can predict the risk of death. The positive correlation between Hcy and death is enhanced with the increase of SII，and the two jointly affect the cardiac function of patients through main effects and interaction effects，thereby affecting the death risk.

Objective To establish a method for the simultaneous determination of monochloroacetic acid（MCA），dichloroacetic acid（DCA），and trichloroacetic acid（TCA） in drinking water by headspace gas chromatographt. Methods The water samples（10 mL） were transferred to a 20 mL headspace bottle，added with 2.0 mL sulfuric acid-methanol（5+45） solution，immediately sealed，and shaken evenly. The bottle was placed in the headspace gas chromatography（HS-GC） system and then equilibrated at 85 ℃ for 30 minutes. The mixture was separated with the RTX-5 chromatographic column，and the MCA，DCA，and TCA were determined with the electron capture detector（ECD）. Results Under the optimal experimental conditions，the correlation coefficient of MCA，DCA，and TCA was both > 0.998 within the range of 2-100 μg/L，and the lowest limits of detection for MCA，DCA，and TCA were 1.20，0.20 and 0.20 μg/L respectively，with the spike recovery rate of 92.72% to 101.53%，and relative standard deviations of 0.94% to 4.36%. Conclusion The developed method is rapid，simple，precise，sensitive and is applicable to the accurate detection of MCA，DCA and TCA in drinking water.

Objective To optimize the digestion conditions of high-pressure tank digestion food and establish a method for accurate determination of selenium in food by hydride generation atomic fluorescence spectrometry in GB 5009.93-2017. Methods The certified quality control sample was used as the detection object，the key factors affecting the digestion effect were optimized，and the hydride atomic fluorescence spectrometry was used to determine and verify the method. The established method was applied to the blind sample assessment of inter-laboratory comparison and measurement certification review to verify the application of the method. Results Under the optimal experimental conditions，there was a good linear relationship in the linear range of 0-10.00 μg/L，and the correlation coefficient r=0.999 9. The detection of limit was 0.058 9 μg/L. The precision（RSD，n=11） was 1.4%. All determined values of CRMs were within the certified ranges. The results of inter-laboratory comparison and measurement certification review blind sample assessment were all qualified. Conclusions The pretreatment method of this method is safe，low-consumption and efficient. This method has high sensitivity，good accuracy and precision，meeting the requirements of national standards and laboratory quality control. It is suitable for the daily detection of selenium in food such as grain and vegetables，and can be popularized and applied in food safety testing laboratories at all levels.

Objective To understand the epidemiological characteristics and incidence trend of pulmonary tuberculosis（PTB） in Hedong District，Tianjin from 2015 to 2024，and provide the scientific evidence for targeted PTB prevention and control. Methods PTB cases reported in Hedong District，Tianjin during 2015-2024 were collected. Descriptive epidemiology was used to analyze the distribution characteristics，Joinpoint regression to explore the incidence trend，and R 4.5.1 software to construct an auto regressive integrated moving average model for predicting 2026 PTB incidence. Results The PTB incidence rate decreased from 27.51 per 100 000 in 2015 to 16.18 per 100 000 in 2024，with an average annual decline rate of 5.73%，and peaked in March-April and June-July. The male-to-female ratio was 2.12∶1，with a bimodal age distribution（25-29 and 60-64 years），and the highest incidence in 80-84 years group. Occupationally， the cases were mainly retired personnel，housewives and the unemployed. Spatially，Dongxin，Lushan Road and Dazhigu Subdistricts had the highest incidence rates. The overall positive rate of pathogenic detection increased during 2015-2024. The optimal ARIMA（1，1，1）（0，1，1）₁₂ model predicted that the April incidence peak would decline in 2026，while the cases would increase from August to October. Conclusions The PTB incidence in Hedong District，Tianjin decreased annually. The key high-risk groups included the elderly aged ≥60 years，retired and unemployed populations，and the high-incidence areas were densely populated subdistricts. The ARIMA（1，1，1）（0，1，1）₁₂ model is effective for PTB incidence prediction，supporting targeted prevention and control strategies.

Fine particulate matter （PM_2.5） is an important environmental risk factor for metabolic disorders. A growing body of epidemiological evidence has demonstrated that long-term exposure to PM_2.5 is closely associated with an increased risk of metabolic diseases，including type 2 diabetes mellitus（T2DM），metabolic dysfunction-associated steatotic liver disease（MASLD） and obesity. Current evidence suggests that，as an inhaled air pollutant，PM_2.5 initially induces pulmonary oxidative stress and inflammation，followed by the systemic propagation of injury signals through pathways such as circulating neurogenic inflammation and autonomic nervous system imbalance. These processes may further contribute to metabolic disturbances in the target organs by disrupting peroxisome proliferator-activated receptor（PPAR） signaling，impairing mitochondrial function and inducing endoplasmic reticulum stress，ultimately leading to insulin resistance and abnormalities in energy metabolism.Accordingly，this review focused on the mechanistic framework of “pulmonary exposure-injury signal propagation-target-organ metabolic dysfunction” and summarizes the epidemiological evidence and potential mechanisms linking PM_2.5 exposure to T2DM，MASLD and obesity，with the aim of providing a theoretical basis for the prevention and intervention of metabolic diseases associated with environmental risk factors.

Given the increasingly severe global biosafety situation，the large-scale construction of high-level biosafety laboratories（BSL-3/4） has made efficient and safe waste disposal a cornerstone of biosafety management. This paper systematically reviewed the core technologies and integrated strategies for the treatment of liquid and solid waste，as well as space decontamination，in high-level laboratories. Furthermore，it provided an in-depth exploration of the inactivation validation processes for highly pathogenic pathogens，such as the Ebola virus and Yersinia pestis. Future waste management is expected to evolve toward intelligent monitoring，environmental sustainability and synergistic emergency response，aiming to establish a full-lifecycle closed-loop management system that spans from engineering verification to environmental compliance，and for providing technical support and management references for enhancing global public health security capabilities.