To explore the association between the systemic immune-inflammation index (SII) and adult obesity, and to provide insights for the prevention and early diagnosis of obesity.

This study was based on the survey data of the National Health and Nutrition Examination Survey (NHANES). A binary logistic regression model was used to evaluate the relationship between the systemic immune-inflammation index and obesity (general obesity, central obesity) by calculating the odds ratio (OR) and its 95% confidence interval (CI). In addition, stratified analysis was performed by age (< 60 years old and ≥ 60 years old) and gender.

After adjusting all covariates, when general obesity was taken as the outcome variable, compared with the subjects in the lowest quartile (Q1) of SII, the risk of general obesity in the subjects in the third quartile (Q3) increased by 0.374 times (OR=1.374, 95%CI: 1.111-1.699); the risk of general obesity in the subjects in the fourth quartile (Q4) increased by 0.843 times (OR=1.843, 95%CI: 1.490-2.281). When central obesity was taken as the outcome variable, compared with the subjects in Q1, the risk of central obesity in the subjects in Q3 increased by 0.542 times (OR=1.542, 95%CI: 1.189-2.000); the risk of central obesity in the subjects in Q4 increased by 1.036 times (OR=2.036, 95%CI: 1.553-2.670). In addition, the results of stratified analysis showed that the relationship between SII and obesity was different among different ages and was only significant in the population aged <60 years old.

SII is positively correlated with the risk of adult obesity, and the higher the SII, the higher the risk of obesity. In addition, the relationship between SII and obesity may be age-specific.

To analyze the impact of smart healthcare on the health of middle-aged and elderly individuals and to provide references for exploring pathways to healthy aging.

The smart city pilot programs were treated as a quasi-natural experiment for smart healthcare. Utilizing data from the China Health and Retirement Longitudinal Study, this research employed the difference-in-differences approach and an improved mediation effect model to examine the impact of smart healthcare on the health of middle-aged and elderly individuals and the mechanisms involved.

Smart healthcare significantly improved the health levels of middle-aged and elderly individuals (P<0.05). Enhancing self-health management and promoting the utilization of medical services were important mechanisms through which smart healthcare improved health outcomes.

Smart healthcare has a positive impact on the health of middle-aged and elderly individuals, with variations observed among different subgroups. It is essential to eliminate barriers to the application of smart technologies, bridge the digital divide among the elderly population, and advance equitable access to healthcare services.

To explore the impact of follow-up management on blood pressure control in hypertensive patients in Sichuan Province, so as to improve the blood pressure control rate in the population.

Based on the data of the Seventh National Health Service Survey in Sichuan province, 3 587 hypertensive patients were included. Descriptive statistical analysis was used to analyze the follow-up management situation, demographic characteristics, lifestyle behaviors and health status of patients. Combined with the multivariate logistic regression model, the follow-up management factors affecting blood pressure control were explored.

The blood pressure control rate was 68.9%. Among the effectively controlled patients, the rate of taking medications regularly as prescribed was 84.6%, the proportion of those with a follow-up frequency of ≥4 was 71.4%, and the rate of family doctor-signed home visits was 48.1%. Among the patients not effectively controlled, the rate of taking medications regularly as prescribed was 73.4%, the proportion of those with a follow-up frequency of ≥4 was 67.6%, and the rate of family doctor-signed home visits was 45.2%. Multivariate Logistic regression analysis showed that not taking medications regularly as prescribed (OR=1.742, 95%CI:1.453-2.089), a follow-up frequency of <4 (OR=1.287, 95%CI: 1.057-1.567) and other follow-up methods (OR=1.286, 95%CI:1.092-1.516) had significant negative impacts on the blood pressure control effect of patients.

Follow-up management of hypertension is beneficial to blood pressure control. The follow-up frequency should be optimized, drug compliance should be improved, and the interaction between the signed doctor and the patient should be enhanced.

To construct a structural equation model to explore the pathways of factors influencing fertility behavior among nulliparous couples of reproductive ages, providing direction for medical interventions aimed at fertility pathways.

A cross-sectional study was conducted using convenience sampling, selecting 400 nulliparous couples of reproductive ages from the permanent residents of Chengde city, Hebei Province. Data were collected through general demographic questionnaires, the Childbirth Fear Scale, the Social Support Rating Scale, the Fertility Motivation Questionnaire, and the Fertility Intention-Behavior Questionnaire. Path analysis and mediation effect testing were performed using structural equation modeling.

The constructed structural equation model demonstrated good overall fit. Childbirth fear negatively predicted fertility motivation, intention, and behavior (β values of -0.245, -0.120, and -0.123, respectively), while social support positively predicted fertility motivation, intention, and behavior (β values of 0.247, 0.145, and 0.149, respectively). Fertility motivation positively predicted fertility intention (β value of 0.816), and fertility intention positively predicted fertility behavior (β value of 0.760).

Childbirth fear and social support among nulliparous couples of reproductive ages can indirectly influence fertility behavior through fertility motivation and intention. Medical institutions should strengthen collaboration with community efforts to develop targeted intervention measures that alleviate childbirth concerns among the reproductive population and promote positive fertility behaviors.

To analyze the transmission characteristics of the CRF105_0108 subtype in Luzhou, aiming to provide a scientific basis for effective control of its spread in the region.

Genetic sequences obtained from drug-resistant testing of antiretroviral therapy failures among AIDS/HIV patients in Luzhou from 2017 to 2023 were collected for subtype and genotype resistance analysis. The molecular transmission network of CRF105_0108 was constructed using genetic distance methods, and factors influencing network inclusion were analyzed.

A total of 61 CRF105_0108 gene sequences were obtained. A molecular transmission network was constructed at a 1.5% genetic distance, achieving an inclusion rate of 80.33%(49/61), forming 3 molecular clusters and 247 edges. A high-resolution molecular transmission network was constructed at a 0.6% genetic distance, with an inclusion rate of 40.98% (25/61), forming 9 molecular clusters and 22 edges. Univariate analysis indicated a statistically significant difference in network inclusion based on different residential locations (χ²=12.739, P=0.025), while differences in gender and other factors were not statistically significant. The genotype resistance rate for the CRF105_0108 subtype was 54.10% (33/61), with 8 samples exhibiting dual resistance to NRTI and NNRTI.

The transmission of the CRF105_0108 subtype in Luzhou may have formed a large transmission cluster. It is recommended to conduct genetic subtype monitoring and pre-treatment resistance testing for newly reported AIDS/HIV patients, to dynamically monitor the constructed transmission network, and to implement timely intervention measures for high-risk transmitters, thereby enhancing the specificity of antiretroviral therapy and improving the precision of prevention and control efforts.

To analyze the external exposure levels of nitrate in rural drinking water in Guangdong Province and provide technical support for the safety management of rural water supply.

Monitoring was conducted on the finished water and terminal water from rural drinking water supply units in Guangdong Province from 2018 to 2022. The compliance of nitrate levels in water quality was evaluated according to the Standards for Drinking Water Quality (GB 5749-2022). The Kolmogorov-Smirnov test was used to determine the normality of the data. For non-normally distributed data, the median was used for description. The chisquare test or Fisher’s exact test was employed to analyze differences in rates between groups. The Mann-Whitney U test was used to compare nitrate exposure levels between two groups, and the Kruskal-Wallis H test was applied for comparisons among multiple groups.

A total of 62 998 water samples were monitored, with an overall compliance rate of 99.52%. The nitrate exposure levels ranged from 0.001 to 63.80 mg/L. Significant differences in nitrate exposure levels were observed across different years (H=445.586, P<0.01), regions (H=2 050.151, P<0.01), water source types (Z=-5.268, P<0.01), sample types (Z=-11.888, P<0.05), water supply capacities (Z=-33.794, P<0.01), water treatment methods (H=27.750, P<0.01), and the presence or absence of advanced treatment (Z=-2.121, P<0.05).

The overall compliance rate of nitrate levels in rural drinking water in Guangdong Province is relatively high. However, special attention should be paid to nitrate pollution in certain areas of western and eastern Guangdong, groundwater sources, decentralized and small-scale centralized water supplies, as well as the high exposure risks for infants and young children.

To explore the relationship between uric acid and the risk of hepatic steatosis and non-alcoholic fatty liver disease (NAFLD), providing new insights for the prevention of NAFLD.

Utilizing data from the 2017-2018 NHANES population and summary data from genome-wide association studies (GWAS), the association between uric acid and the risk of hepatic steatosis and NAFLD was analyzed using restricted cubic spline models, generalized linear models, and binary logistic regression models. The inverse variance weighted method was employed as the primary approach for Mendelian randomization (MR) analysis to assess the causal relationship between uric acid and NAFLD. Additional verification of results was conducted using MR Egger regression, weighted median methods, simple models, and weighted models, followed by sensitivity testing.

After adjusting for all covariates, a linear relationship was observed between uric acid and the risks of hepatic steatosis and NAFLD (P_non-linear > 0.05). Populations with higher uric acid levels exhibited increased risks of hepatic steatosis (β=3.559,95%CI: 1.722-5.395, P < 0.001) and NAFLD (OR=1.151, 95%CI: 1.048-1.265, P=0.003). The MR analysis using the inverse variance weighted method indicated a causal relationship between uric acid and NAFLD (OR=1.68, 95%CI: 1.01-2.81, P=0.049),with the other four analytical methods providing similar directional causal inferences. Sensitivity tests suggested no significant heterogeneity or horizontal pleiotropy among instrumental variables (P > 0.05), and the results were not influenced by individual genetic variations.

Uric acid is positively linearly correlated with the risk of hepatic steatosis and NAFLD, indicating that controlling uric acid levels may play a crucial role in the prevention and management of NAFLD.

To explore whether N⁶-methyl adenosine (m⁶A) is involved in arsenic-induced tau protein phosphorylation.

Neuroblastoma (SH-SY5Y) cells were treated with 0, 1, 5, 10 μmol/L sodium arsenate for 24 hours. Then, the intracellular m⁶A level was detected, the mRNA expression levels of m⁶A-related enzymes in the cells were detected by qPCR,and the total tau protein expression level, phosphorylated tau protein level and m⁶A-related enzyme expression levels in the cells were detected by Western Blot. After inhibiting the intracellular m⁶A level with 3-deoxyadenosines, the changes in the intracellular m⁶A level and tau protein phosphorylation level were verified. SPSS was used for analysis of variance of the experimental results, with α=0.05.

After SH-SY5Y cells were treated with various concentrations of arsenic for 24 hours, there was no significant difference in the total tau protein level in the cells (F=3.047, P > 0.05). After the cells were treated with 5 μmol/L arsenic for 24 hours, the intracellular m⁶A level increased by 31.4% (F=4.511, P < 0.05), and the phosphorylated tau protein (at site T231) level increased by 42.6% (95%CI: 0.165-0.689, P < 0.01). The level of phosphorylated tau protein (at sites S202 + T205) increased with the increase in arsenic concentration, and the highest increase was 55.2%(95%CI: 0.050-0.409, P < 0.05) after treatment with 10 μmol/L arsenic for 24 hours. As the arsenic treatment concentration increased, the METTL3 mRNA expression in the cells increased, with the highest increase of 73.2% (95%CI: 0.201-1.423, P < 0.05) at a concentration of 10 μmol/L. The mRNA expression levels of METTL14, WTAP and FTO decreased, and they decreased to 65.4% (95%CI:-1.055 to-0.337, P < 0.01), 64.8% (95%CI:-0.389 to -0.111, P < 0.05) and 85.4% (95%CI: -0.030 to -0.010, P < 0.01) of the control group respectively after treatment with 10 μmol/L arsenic. The ALKBH5 mRNA expression first increased and then decreased, with an increase of 27.5% (95%CI: 0.033-0.147, P < 0.05) after treatment with 1 μmol/L arsenic for 24 hours; while it decreased by 30.7% (95%CI:-1.62 to -0.038, P < 0.01) after treatment with 10 μmol/L arsenic. Arsenic treatment led to an increase in METTL3 protein expression, with the highest increase of 107.1% (95%CI: 0.331-1.009, P < 0.01) after treatment with 5 μmol/L arsenic for 24 hours, while the protein expression levels of METTL14, WTAP and ALKBH5 decreased to 20.4% (95%CI: -0.788 to -0.509, P < 0.001), 23.5% (95%CI:-1.371 to -0.685, P <0.001) and 49.2% (95%CI:-0.423 to -0.183, P < 0.001) of the control group respectively after treatment of SH-SY5Y cells with 10 μmol/L arsenic for 24 hours. The FTO protein expression level showed a decreasing trend with the increase in arsenic concentration, with the lowest decrease of 45.3% (95%CI:-0.709 to -0.413, P < 0.001) after treatment with 10 μmol/L arsenic for 24 hours. After DAA inhibited the intracellular m⁶A level, the phosphorylated tau protein levels were significantly decreased (P < 0.05).

Arsenic can increase the m⁶A level in SH-SY5Y cells by increasing the expression level of the m⁶A methylase METTL3 and decreasing the expression levels of the m⁶A demethylases FTO and ALKBH5, thereby inducing the phosphorylation of tau protein in the cells.

To explore the influence and lag effects of different groups of relative humidity, temperature, atmospheric pollutants and their interactions on respiratory disease mortality in a basin city in southwest China under a subtropical humid climate.

Daily meteorological, air pollutant and respiratory-related mortality data of residents in a city in southwest China from 2018 to 2022 were collected, and time-series analysis was carried out using the distributed lag-wise nonlinear model (DLNM) with quasi-Poisson distribution and the generalized additive model (GAM).

A total of 11 779 people died of respiratory diseases in this city. At lag15, when the SO₂ concentration increased by 10 μg/m³, the impact on the respiratory disease mortality of the population was the greatest, with RR=1.055 (95%CI: 0.993-1.120). In the single-factor grouped lag model, in the extremely high-temperature group (≥P₉₅), when the temperature increased by 1 °C, the impact on respiratory disease mortality was the greatest at lag0, which was 1.710(95%CI: 1.209-2.418). In the multi-factor model, when SO₂ and NO₂ were taken as synergistic factors, the impact of relative humidity on respiratory mortality was the greatest at lag18, which was 1.026 (95%CI: 1.000-1.053), and the RR of temperature on mortality was the greatest at lag0, which was 1.024 (95%CI: 1.010-1.038). Interaction analysis showed that there were interactions among relative humidity, temperature and various pollutants, and the mortality risk generated by the interaction between 60%-80% humidity level and SO₂ and NO₂ was the greatest.

Each factor has an independent influence and lag effect on respiratory disease mortality.The interactions between different humidity levels and pollutants have different impacts on respiratory disease mortality and may have synergistic or antagonistic effects. Among them, the mortality risk generated by the interaction between medium humidity level and pollutants is the greatest, while the impact generated by the interaction between high humidity and pollutants is instead reduced.

To construct a mitochondrial-related risk assessment model to explore the impact of mitochondria on the survival of patients with non-small cell lung cancer (NSCLC), predict immune status, and evaluate its potential value.

Mitochondrial and NSCLC-related data were downloaded from the MitoCarta3.0 database and The Cancer Genome Atlas (TCGA) database, respectively. Differentially expressed mitochondrial-related genes were screened, and a risk scoring model was constructed using Cox regression analysis. Based on the median risk score, NSCLC patients in the TCGA database were divided into high-risk and low-risk groups. The validity of the prognostic model was verified using Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, clinical case feature analysis, and immune status assessment.

A total of 320 mitochondrial-related genes were obtained from NSCLC samples. Four key model genes (TIMM10, CYP24A1, BCL2L10, ACSM5) were selected through COX analysis, leading to the construction of a nomogram prediction model for NSCLC. Immune cell infiltration assessment revealed a negative correlation between risk scores and the enrichment of T cells, B cells, and macrophages; conversely, the enrichment of resting mast cells, cancer-associated fibroblasts, and myeloid progenitor cells was positively correlated with risk scores. Patients in the high-risk group had shorter overall survival and exhibited higher levels of immune suppressive cell infiltration. Validation of the IMvigor210 immunotherapy model showed significant differences in survival probabilities between high-risk and low-risk groups in bladder cancer.

This study established a mitochondrial gene risk scoring model for predicting the prognosis of NSCLC. TIMM10,CYP24A1, BCL2L10, and ACSM5 are promising potential targets for further research on NSCLC.