To explore the association between physical activity level (PAL) and Circadian syndrome (CircS) in Chinese middle-aged and elderly population.

Based on the 2013 China Health and Retirement Longitudinal Study (CHARLS) data, middle-aged and elderly people ≥45 years old with complete key data were selected. The association between PAL and CircS was analysed by multiple logistic regression. In addition, subgroup analyses, interaction tests, smoothed curve fitting, and threshold effect analyses were performed.

A total of 5 851 middle-aged and older adults were included as study subjects, with a prevalence of CircS of 24.18% and PAL of 4 548 (1 732.5, 10 584)(MET-min/w). Fully adjusted multivariate logistic regression showed a significant negative association between PAL and CircS prevalence (OR=0.73, 95% CI: 0.62-0.87; P<0.001). The consistency of this association was confirmed by subset analyses and interaction tests for multiple subgroups. Smoothed curve fitting and threshold effect analyses revealed a nonlinear relationship with a threshold of 3 810 MET-min/w.

There is a negative association between the PAL and the risk of developing CircS. Moderate physical activity may allow early intervention in individuals at risk for CircS.

This study aimed to identify the dual trajectories of social isolation and depression among middle-aged and older patients with hypertension, discuss the relationship between the dual trajectories, and investigate common influential factors. Method Using data from 2013 to 2020 of the China Health and Retirement Longitudinal Study (CHARLS), a longitudinal cohort was formed for the study. A group-based trajectory model was used to identify trajectories of social isolation and depression in 3 223 middle-aged and older patients with hypertension and the relationship between the dual trajectories. Multi-class logistic regression was used to analyze common influential factors of the dual trajectories.

Three trajectories of social isolation were identified: low-stable without social isolation, medium-stable without social isolation, and high-increasing with social isolation. Three depression trajectories were observed: low-stable without depression, medium-increasing with depression, and high-stable with depression. Dual-trajectory analysis showed in middle-aged and older patients with hypertension who were in the medium-stable without social isolation and high-increasing with social isolation trajectory groups, the probability of depression trajectories in the medium-increasing with depression and high-stable with depression groups was 61.84% to 87.46%. In middle-aged and older patients with hypertension who belonged to the medium-increasing with depression and high-stable with depression trajectory groups, the probability of social isolation in the medium-stable without social isolation and high-increasing with social isolation trajectory groups was 70.03% to 91.63%. The level of education(social isolation trajectories in middle school RRR=0.756, 95% CI：0.599-0.954, RRR=0.496, 95% CI: 0.326-0.755; social isolation trajectories in high school or above RRR=0.516, 95% CI: 0.375-0.709, RRR=0.262, 95% CI: 0.137-0.501; depression trajectories in middle school RRR=0.773, 95% CI: 0.622-0.959, RRR=0.728, 95% CI: 0.574-0.994, depression trajectories in high school or above RRR=0.421, 95% CI: 0.309-0.571, RRR=0.439, 95% CI: 0.253-0.763) and sleeping 7-9 hours a night (social isolation trajectories RRR=0.824, 95% CI: 0.681-0.997, RRR=0.596, 95% CI: 0.440-0.806; depression trajectories RRR=0.597, 95% CI: 0.501-0.711, RRR=0.486, 95% CI: 0.362-0.653) were common influential factors of the dual trajectories of social isolation and depression.

There is a high degree of consistency and significant correlation between the social isolation trajectory and the depression trajectory. Interventions targeting the dual trajectories and co-factors of social isolation and depression should be considered to improve their effectiveness.

To explore the effects of individual smoking cessation cognition and spousal support on married smokers’ smoking cessation behavior, and to analyse the role of gender differences on smoking cessation behavior.

A convenience sampling method was used to recruit married smokers from Jiangsu and Shandong to conduct an online questionnaire survey to collect information on demographic characteristics, smoking and cessation, individual smoking cessation cognition and spousal support. Binary logistic regression was used to analyse the relationships between smoking cessation cognition, spousal support, smoking cessation attempts, and the willingness to quit smoking with family support.

715 married smokers completed the questionnaire. After controlling for potential confounders, the results showed that perceived risk of smoking-related diseases (aOR=1.29, 95% CI: 1.05–1.59) and positive outcome expectations for quitting (aOR=1.27, 95% CI: 1.06–1.51) were positively associated with smoking cessation attempts among married male smokers, whereas no statistical associationwas found between smoking cessation cognition and smoking cessation attempts among women. Regardless of gender, perceived risk of smoking-related diseases, self-efficacy, smoking cessation plan, and spousal emotional support were positively associated with the willingness to quit smoking; negative outcome expectations for quitting (aOR=0.78, 95% CI: 0.65–0.93) were negatively associated with the willingness to quit smoking among male smokers, while no statistically significant associationwas found among female smokers.

Perceived risk of smoking-related diseases and positive outcome expectations for quitting are protective factors for smoking cessation attempts among married male smokers, while female smokers’ smoking cessation cognition failed to translate into actual quitting behavior. Additionally, negative outcome expectations for quitting are risk factors for willingness to quit smoking among married male smokers. Therefore, individualized smoking cessation intervention strategies should be developed taking into account gender differences.

To understand the current status of digital health literacy among rural elderly individuals in Shandong Province and analyze the main influencing factors.

A multi-stage stratified cluster random sampling method was employed to select 720 rural individuals aged 60 years and older from the eastern, central, and western regions of Shandong Province for a questionnaire survey. Multiple linear regression analysis was used to explore the factors influencing digital health literacy among the elderly.

The average digital health literacy score of the 720 rural elderly participants was 58.31±16.34. Multiple linear regression revealed that factors associated with higher digital health literacy included normal BMI (β=8.28, P<0.001), low body weight (β=18.61, P<0.001), self-reported good health status (β=6.90, P<0.001), general health status (β=10.20, P<0.001), being married (β=3.49, P=0.001), monthly income between 3 000-4 999 yuan (β=6.75, P<0.001), income ≥5 000 yuan (β=11.48, P<0.001), and having health insurance coverage (urban employee health insurance/rural resident health insurance) (β=5.58, P=0.001).

The level of digital health literacy among rural elderly individuals in Shandong Province needs improvement. Targeted measures should be implemented from five aspects: personal traits, behavioral characteristics, interpersonal relationships, living and working conditions, and policy environment, in order to enhance digital health literacy in this population.

To explore the mechanism of Mycobacterium tuberculosis (Mtb) resistance to fluoroquinolones (FQs) drugs at the genetic level, the whole genome sequencing of fluoroquinolone-resistant Mtb induced in vitro and clinical isolates was conducted.

Mtb standard strain H37Rv was induced into standard levofloxacin (LFX) resistant strain and high-level drug-resistant strain in LJ medium by concentration gradient induction method in vitro. The induced strains and drug-free control strains of each generation were collected and preserved. FQs-resistant strains in clinical isolates were screened, and the sensitivity of the induced strains and clinical isolates to 14 anti-tuberculosis drugs was detected by liquid microplate method, and then the whole genome was sequenced and analyzed.

The analysis of LFX-resistant Mtb model found that the resistance of Mtb to FQs drugs may be related to gene mutations, gyrB (Ala504Thr, Asp461Asn), gyrA (Ala90Val), PE_PGRS31 (Ala395fs), panB (Asp184_Ala187del), aroD (Asp61Asn), devS (Gly348Arg) and rv3446c (Ala178Thr). GWAS analysis of clinical isolates detected 17 new mutation sites that may be related to FQs drug resistance, namely gyrA(p.Glu21Gln, p.Gly668Asp, p.Ser95Thr, p.Glu213Asp, p.His280Arg, p.Ala384Val), gyrB(er132Ala, p.Met291Ile), PE_PGRS31(p.Ser365Phe, p.Pro254Leu, p.Thr252Ile, p.Val352Ile), rv3446c(p.Arg284Pro, p.Leu389Phe, p.Ala164Val) anddevS(p.Val307Ala, p.Ile283Thr).

The LFX-resistant Mtb model constructed in this study provides an ideal biological model for exploring the mechanism of Mtb drug resistance to FQs. Whole genome sequencing has analyzed the mechanism of Mycobacterium tuberculosis resistance to fluoroquinolones from the gene level, and the obtained new mutation sites related to fluoroquinolone resistance still need to be further studied and verified.

To study the effect and mechanism of nicotinamide mononucleotide (NMN) in alleviating silica-induced lung injury, and to provide a new option for the adjuvant treatment of silicosis.

The male C57BL/6 mice were randomly divided into control group, SiO₂ group, and NMN intervention group according to body weight, with 10 mice in each group. Mice were given SiO₂ (50 mg/ml, 80 μl) by tracheal instillation to construct a mouse model of silicosis, and NMN (1 000 mg/kg) was given by gavage for 7 days and 28 days. Histopathological staining was used to assess lung lesions, and transcriptomic sequencing was used to analyze gene expression and screen for key genes.

NMN intervention alleviated SiO₂-induced lung injury. Gene clustering results showed that NMN intervention improved SiO₂-induced gene expression disorders to a certain extent, and the improvement effect of 28 days was better than 7 days of NMN intervention. After 7 and 28 days of SiO₂ exposure, 1 163 genes were up-regulated in the SiO₂ group compared with the control group, and were down-regulated in the NMN group compared with the SiO₂ group, of which 445 were differential genes. Similarly, 1 657 genes were down-regulated in the SiO₂ group compared with the control group, and were up-regulated in the NMN group compared with the SiO₂ group, of which 571 were differential genes. The main GO term of the above differential genes was RNA polymerase and transcriptional regulation, and main KEGG pathways were IL-17 signaling pathway (P<0.001), cytokine-cytokine receptor interaction (P<0.001), Th17 cell differentiation (P<0.001), TNF signaling pathway (P<0.001). According to the number of pathways involved in the regulation of differential genes, the TOP8 hub genes were Mapk11, Mapk12, Il1b, H2-Ob, Csf2, Shc2, Mmp9, Ccl25.

NMN alleviates lung injury in silicosis mice by regulating immunity.

To assess Hantaan virus infection risk across districts in Sichuan Province, providing a scientific basis for prevention and intervention measures for Hemorrhagic Fever with Renal Syndrome (HFRS) and data for evaluating their effectiveness.

This study utilized open-source databases and mathematical modeling. HFRS case report data were collected to analyze epidemic status and spatial distribution using traditional epidemiological methods, while a Bayesian spatiotemporal model examined temporal effects, spatial effects, spatiotemporal interactions, and the impact of meteorological, socioeconomic, and healthcare factors on regional risk levels.

From 2015 to 2021, HFRS incidence in Sichuan showed temporal variation and seasonality, with Yanyuan County reporting the highest cases. Spatial analysis indicated that most districts had risk values consistent with the provincial average, with high-risk areas in the southern, northeastern and central regions. Relative risk declined overall from 2015 to 2020, with a 41.7% decrease in 2020 compared to 2015, although a slight increase occurred in 2021 (0.22 per 100 000). Yanyuan County had the highest relative risk (2.66 [1.64, 4.57]), while other regions aligned with the provincial average. Urbanization rate and humidity affected HFRS incidence negatively, and precipitation affected HFRS incidence positively.

HFRS incidence in Sichuan Province is generally low, with higher rates in specific districts, highlighting spatial risk variability. Meteorological, socioeconomic, and healthcare factors influence infection risk. Monitoring relevant indicators and implementing timely interventions are essential to prevent increased human infection risk.

To compare the prediction effect of SARIMA and its combined models on the incidence of hand foot and mouth disease (HFMD), and to explore the influence of COVID-19 on the SARIMA model.

The incidence trend of HFMD in Shenzhen was analyzed through the time series decomposition method. A SARIMA model was established based on the monthly incidence of HFMD from 2011 to 2023. The optimal model was selected by comparing the performance of MAE, MSE, RMSE, and MAPE, and was used to construct a combined model with the SVR model and the XGBoost model. The incidence from January to July 2024 was predicted using the optimal model.

The incidence trend of HFMD in Shenzhen from 2011 to 2023 was seasonal, and the peak was from May to June and September to October each year. The SARIMA model that did not include incidence data during the COVID-19 pandemic outperformed the included model. Based on MAE, MSE and RMSE indicators, the combined model performed better than the single SARIMA model when the prediction time exceeded 4 months. The SARMI-SVR model wassuperior to the SARMI-XGBoost model in overall performance, especially in the performance of MAPE.

Including the incidence data during the COVID-19 epidemic will degrade the performance of the SARIMA model. The prediction effect of SARMI-SVR model is better than SARIMA model and SARMI-XGboost model, which can be used to predict the incidence of HFMD and provide a reference for disease surveillance and early warning.

To analyze the compensation for adverse events following immunization from vaccination under Anhui Province’s National Immunization Program (NIP) from 2012 to 2024.

Data from cases compensated for adverse events following immunization from vaccination in Anhui Province from 2012 to 2024 were collected and analyzed using descriptive NIP demiological methods.

From 2012 to 2024, there were a total of 80 AEFI compensation cases in Anhui Province for NIP vaccines, with the lowest compensation amount being 13 200 yuan and the highest compensation amount being 1.54 million yuan. The total compensation amounted to 35.49 million yuan, with an average compensation of 443 600 yuan per case (ranging from 13 200 yuan to 1.54 million yuan). The number of cases and compensation amount for those under 1 year old were the highest, with 64 cases (80.00%) and 25.29 million yuan (71.26%) respectively. In the vaccine distribution, BCG vaccine had the highest number of AEFI compensation cases and compensation amount, with 33 cases (41.25%) and 1.05 million yuan (29.64%), respectively. In terms of clinical diagnoses, neurological diseases had the highest number of cases and total compensation amount, with 33 cases (41.25%) and 2.03 million yuan (57.26%). In the damage severity classification, Grade IV had the most compensation cases, with 20 cases (25.00%), while Grade II-B had the highest total compensation amount, totaling 7.49 million yuan(21.09%). The average payment time after the investigation and diagnosis conclusion was 252.28 days.

The overall implementation of compensation for adverse events following immunization from vaccination under Anhui Province’s NIP is good, but there is a need for further improvement in compensation procedures and mechanisms.

To evaluate the efficacy of three treatment modalities, preoperative, postoperative, and combined preoperative and postoperative systemic therapy, in elderly patients with rectal cancer (RC), and to analyze the prognostic factors for elderly RC patients.

Data from 4612 RC patients aged 60 and above were used, sourced from the SEER database between 2011 and 2015. The Overlap Weighting (OW) method based on XGBoost was employed to balance covariate differences between treatment groups and assess the impact of different treatment regimens on the survival prognosis of RC patients. Survival curves were plotted using the Kaplan-Meier method, and Log-rank tests were conducted. Cox regression analysis was utilized to evaluate independent risk factors affecting the survival of RC patients.

After OW weighting, the three treatment groups achieved balance across all covariates. The survival rates among different treatment groups were statistically significant (P<0.001). The 1-year, 3-year, and 5-year survival rates were 94.6%, 82.2%, and 71.6% for the preoperative systemic therapy group, 95.0%, 79.0%, and 67.8% for the postoperative systemic therapy group, and 97.3%, 85.5%, and 73.4% for the combined preoperative and postoperative systemic therapy group, respectively. Multivariate Cox regression analysis revealed that, compared to the preoperative systemic therapy group, the specific death hazard ratio for the postoperative systemic therapy group was 1.216(95% CI: 1.072-1.381). Patients with liver metastasis had a specific death hazard ratio of 1.719(95% CI: 1.253-2.358) compared to those without liver metastasis.

The sequence of systematic treatment has a significant impact on the survival prognosis of elderly RC patients. After controlling for factors such as age and gender, preoperative systemic treatment had a better survival prognosis among the three treatment methods; Liver metastasis may be an independent factor affecting the prognosis of RC patients.