To explore the relationship between gaseous air pollutants and inflammatory indices in patients with schizophrenia (SCZ).

A total of 866 hospitalized SCZ patients were included from October 2020 to December 2023.The daily average exposure values of gaseous air pollutants (SO₂, NO₂, O₃, CO) for the seven days prior to hospitalization were estimated using Kriging interpolation. Based on the biochemical test results on the day of admission, four inflammatory indices were calculated for the SCZ patients: Platelet to Lymphocyte Ratio (PLR), Neutrophil to Lymphocyte Ratio (NLR), Systemic Immune Inflammation Index (SII), and Systemic Inflammation Response Index (SIRI). Spearman correlation and multiple linear regression models were employed to analyze the association between individual gaseous air pollutants and inflammatory indices;Bayesian Kernel Machine Regression (BKMR) was used to assess the joint effects of mixed gaseous air pollutants on inflammatory indices.

The daily average exposure values of SO₂, NO₂, and CO in the seven days prior to hospitalization showed a positive correlation with PLR（r_SO-PLR=0.08;r_NO-PLR= 0.069; r_CO-PLR=0.078）、NLR（r_SO-NLR=0.075; r_NO-NLR= 0.077; r_CO-NLR=0.069） and SII（r_SO-SII=0.081; r_NO-SII=0.072; r_CO-SII=0.075）, with statistical significance (all P<0.05). The multiple linear regression results indicated a positive correlation between the daily average NO₂ exposure and NLR levels, with β=0.006(95%CI: 0.001-0.011). The BKMR analysis revealed that when the daily averages of the four gaseous air pollutants exceeded their 50^th percentile (P₅₀) in the seven days prior to hospitalization, the mixture of SO₂, NO₂, CO, and O₃ had a positive joint effect on the NLR and SII of SCZ patients.

Short-term exposure to a mixture of gaseous air pollutants may influence the inflammatory response in SCZ patients.

To explore the alterations in gut microbiota following the oral administration of pomegranate peel extract (PPE) in vanadium-exposed mice, providing new insights into the mechanisms of vanadium toxicity and its prevention and treatment.

Male C57BL/6J mice were used as subjects and randomly divided into a control group, a model group, and three PPE dosage groups, with 10 mice in each group. Mice were administered sodium metavanadate solution via intraperitoneal injection (3 mg/kg, once every 2 days) for modeling, and PPE was injected intraperitoneally at doses of 100, 200, and 400 mg/kg every 2 days. The control group received physiological saline. At the end of 12 weeks, fecal samples were collected to extract gut bacterial genomic DNA for amplification and sequencing of the 16S rDNA. Statistical analysis was conducted using one-way ANOVA and the SNK (Student-Newman-Keuls) test.

Long-term vanadium exposure resulted in a decrease in gut bacterial abundance, with a reduction in OTU numbers (P < 0.05).The α-diversity indices, including Shannon, Simpson, ACE, and Chao1, significantly decreased (P < 0.05). The β-diversity analysis, represented by PCoA and NMDS plots, showed significant differentiation. The relative abundances of Actinobacteria, Verrucomicrobia, and Akkermansiaceae significantly increased (P < 0.05), while the relative abundance of Ruminococcaceae significantly decreased (P < 0.05).However, low and medium doses of PPE were able to partially restore the reduction in gut microbiota abundance and diversity caused by vanadium exposure (P < 0.05), bringing the abundance of affected characteristic bacterial groups back to normal levels (P < 0.05).

Vanadium exposure leads to a decrease in the abundance and diversity of gut microbiota in mice, while low and medium doses of PPE intervention can effectively improve the gut microbiota disorder induced by vanadium exposure.

To explore whether the newly proposed cardiovascular health indicator LE8 provides greater predictive value for adverse cardiovascular events (ACE) than LS7 in the Chinese population.

Based on the China Health and Nutrition Survey (CHNS), 5 772 participants who had not experienced ACE prior to the 2009 survey were included. The cardiovascular health indicators LE8 and LS7 were calculated, and the Kaplan-Meier method and Cox proportional hazards model were used to estimate the 5-year risk of ACE occurrence. The differences in predictive value for ACE occurrence between the two indicators were compared using C statistics.

For LE8, the participants in the highest percentile had a 5-year ACE risk of 2.3%,whereas those in the lowest percentile had a risk approximately six times higher. The results of the Cox proportional hazards model indicated that the C statistic for LS7 was 0.728 (95%CI: 0.706-0.75), while that for LE8 was 0.726 (95%CI: 0.703-0.748), with no statistically significant difference (P=0.51).

In the Chinese population, both LE8 and LS7 are associated with new ACE. However, LE8 incurs higher collection costs and has not demonstrated superior predictive value; therefore, LS7, which is easier to implement in clinical practice, is recommended as the risk prediction indicator for new cardiovascular events.

To analyze the relationship between different combinations of chronic diseases and health-related quality of life (HRQoL) among rural patients with chronic diseases in Shandong Province, and to provide references for improving the HRQoL of patients with chronic diseases.

A multi-stage random sampling method was used to select 531 patients with chronic diseases in Shandong Province for face-to-face questionnaires. The EuroQol five-dimensional five-level questionnaire (EQ-5D-5L) was used to evaluate the patients’ HRQoL. The Tobit regression model was used to analyze the influencing factors of patients’HRQoL.

Among rural patients with chronic diseases, the combinations of chronic diseases with relatively high prevalence rates were arthritis + other diseases (excluding digestive system diseases), pure metabolic diseases, and stroke + metabolic diseases or stroke + metabolic diseases + heart disease, accounting for 27.68%, 19.59%, and 12.81% respectively. The results of the Tobit model showed that the influencing factors of the health utility value of rural patients with chronic diseases were age ≥ 75 years, the course of multiple chronic diseases exceeding 10 years, and disease combinations: patients with any one of digestive system diseases, arthritis, or stroke as part of multiple chronic diseases had significantly lower HRQoL than those with other combinations of chronic diseases.

There are significant differences in the HRQoL of rural patients with chronic diseases with different combinations of chronic diseases. Attention should be paid to health promotion among rural residents, and early screening and prevention should be carried out for high-risk patients with digestive system diseases, arthritis, and stroke to improve the HRQoL of rural residents.

To understand the current situation of adult tobacco prevalence in each sub-district and township of Dingzhou city, Hebei Province, provide data support for formulating grass-roots tobacco control policies, and provide a reference for estimating tobacco prevalence indicators at the county-district level.

A multi-stage stratified cluster sampling method and Probability Proportional to Size (PPS) sampling method were used to conduct a questionnaire survey among permanent residents aged 15 and above in Dingzhou city. The survey data were cleaned, weighted, and analyzed using SAS 9.4. The current smoking rate, quitting rate, and second-hand smoke exposure rate in Dingzhou city were reported. The Small Area Estimation (SAE) method was used to estimate the above-mentioned indicators for each sub-district and township.

A total of 7 660 valid questionnaires were collected in this survey, with an overall response rate of 68.70%. In 2023, the current smoking rate among people aged 15 and above in Dingzhou city was 22.27%, the quitting rate was 9.60%, and the second-hand smoke exposure rate among non-smokers was 36.84%. The estimation results of the SAE model showed that there were differences in tobacco prevalence monitoring indicators among different sub-districts and townships. Townships such as Xingyi Town, Liqinggu Town, and Dongliuchun Township in the southern part of Dingzhou city had relatively high current smoking rates (25%-35%). Some townships in the northwest and southeast regions had relatively low quitting rates (less than 10%), while the sub-districts and townships with relatively high second-hand smoke exposure rates were more scattered, with the rates in Dongting Town and Xizhong Town exceeding 50%.

The SAE model can be used to estimate tobacco prevalence monitoring indicators at the county-district and even sub-district and township levels. Currently, the tobacco prevalence situation in some sub-districts and townships of Dingzhou city is relatively severe. Targeted grass-roots tobacco control work should be carried out, the construction of smoke-free environments should be strengthened, and grass-roots smoking cessation services should be promoted.

To analyze the epidemiological characteristics of Hepatitis A (HA) and Hepatitis E (HE) in Huai’an City,Jiangsu Province from 2004 to 2023, providing a scientific basis for infectious disease prevention and control in the region.

Case report data for HA and HE from 2004 to 2023 in Huai’an city were extracted from the Chinese Disease Prevention and Control Information System for descriptive analysis.

From 2004 to 2023, a total of 1 956 cases of HA were reported in Huai’an city, accounting for 4.14% of viral hepatitis cases, with an average annual incidence rate of 1.97 per 100 000 population.Join point regression analysis indicated a significant overall declining trend in HA incidence from 2004 to 2023, with an Average Annual Percentage Change (AAPC) of -12.816% (P=0.016), with inflection points identified in 2006, 2015, and 2018. The peak months for HA cases were March to June and August; the male-to-female incidence ratio was 2.04, with the highest number of cases reported in the age group of 50 to <55 years. Farmers constituted the largest occupational group, accounting for 72.65% (1 421 cases). During the same period, a total of 3 097 cases of HE was reported, accounting for 6.55% of viral hepatitis cases, with an average annual incidence rate of 3.12 per 100 000 population. Join point regression analysis showed a significant overall increasing trend in HE incidence from 2004 to 2023, with an AAPC of 9.266% (P=0.001) and inflection points in 2011 and 2020.The peak months for HE cases were January to May; the male-to-female incidence ratio was 2.93, with the highest number of cases reported in the age group of 55 to <60 years. Farmers also represented the highest occupational group, accounting for 74.91%(2 320 cases).

From 2004 to 2023, HA showed a declining trend while HE exhibited an increasing trend in Huai’an city. Future efforts should focus on implementing vaccination strategies and prioritizing farmers as a key population for comprehensive prevention and control measures to effectively manage the spread of HA and HE.

To assess the association between the trajectories of depression symptoms and the risk of stroke in the elderly.

Data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018 were utilized.Group-based trajectory modeling was employed to identify the trajectories of depression symptoms, and logistic regression models were used to evaluate the relationship between these trajectories and stroke.

Four trajectories of depression symptoms were identified:low stable (n=2 392, 60.7%), moderate decreasing (n=762, 20.2%), moderate increasing (n=416, 12.3%), and high stable (n=250, 6.8%).During the period from 2015 to 2018, a total of 305 respondents experienced a stroke. Compared to participants with the low stable depression symptom trajectory, those following the moderate decreasing (OR=1.48, 95%CI: 1.09-2.02), moderate increasing (OR=2.22,95%CI: 1.58-3.11), and high stable depression symptom trajectories (OR=1.78, 95%CI: 1.12-2.83) had a higher risk of stroke.

Over time, elderly individuals following moderate decreasing, moderate increasing, and high stable trajectories of depression symptoms exhibited an increased risk of stroke. Long-term depression symptoms may serve as a strong predictor for stroke.

To explore the potential causal relationship between Sjögren’s syndrome (SS) and thyroid diseases using a two-sample bidirectional Mendelian randomization (MR) approach.

Data were sourced from genome-wide association studies (GWAS), obtaining samples and single nucleotide polymorphisms (SNPs) related to SS and thyroid diseases, which included hyperthyroidism, hypothyroidism, goiter, Hashimoto thyroiditis (HT), Graves’ Disease (GD), and thyroid carcinoma (THCA). The inverse variance weighting (IVW) method was employed as the primary analysis approach, supplemented by the weighted median method (WME) and MR-Egger regression model for MR analysis, along with sensitivity analyses to ensure the robustness of results. The Bonferroni method was used to correct for multiple testing, with a correction threshold set at P=0.008(0.05/6), considering P-values between 0.008 and 0.05 as potentially relevant.

Genetically predicted SS was found to have a positive causal relationship with the risk of hypothyroidism (IVW: OR=1.372, 95%CI: 1.124-1.674) and HT (IVW: OR=1.254, 95%CI: 1.142-1.377). SS was not associated with an increased or decreased risk of hyperthyroidism (IVW: OR=1.435,95%CI: 1.012-2.036), goiter (IVW: OR=0.933, 95%CI: 0.838-1.040), GD (MR-Egger: OR=4.094, 95%CI: 2.818-5.947), or THCA (IVW: OR=1.057, 95%CI: 0.866-1.29). Hyperthyroidism (IVW: OR=1.950, 95% CI: 0.776-1.163), hypothyroidism (IVW: OR=1.149, 95%CI: 0.93-1.42), goiter (IVW: OR=0.992, 95%CI: 0.85-1.157), HT (IVW: OR=1.532, 95%CI: 1.055-2.225), GD (IVW: OR=1.041, 95%CI: 0.728-1.488), and THCA (IVW: OR=0.987, 95%CI: 0.874-1.114) were not found to increase or decrease the risk of SS.

Genetically predicted SS is a risk factor for hypothyroidism and HT. There is no association between SS and the risk of hyperthyroidism, goiter, GD, or THCA.

To elucidate antibacterial effects and mechanism of Rosa sertata×Rose rugosa methanol extraction (RME) against extended-spectrum β-lactamases producing Klebsiella pneumoniae (ESBL-KP).

Minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of RME against various ESBL-KP strains were determined by micro broth dilution method. Impact of RME on the growth, cell membrane and extended-spectrum β-lactamases (ESBLs) activity of ESBL-KP was evaluated by growth and time-kill curves, scanning electron microscopy and nitrocefin hydrolysis test, seperately. Components of the extracts were analyzed using Ultra-High Performance Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry (UHPLC-Q-TOF MS).

The MIC of RME was 1 mg/ml for standard strains and 8-32 mg/ml for ESBL-producing strains. Concentrations of RME at 1/4 MIC, 1/2 MIC, and MIC could inhibit bacterial growth, with higher concentrations showing stronger effects. For D141 strain, treatment with RME at 4MIC concentration for 4 hours resulted in cell membrane collapse, bacterial agglutination, and a 77.49% inhibition rate of ESBLs activity; no bacterial growth was observed after 24 hours of this treatment. Totally, 1 550 compounds were identified in RME, with quinic acid, tricoumaroyl spermidine, thioetheramide-PC, and kaempferol-3-O-rutinoside being the predominant components.

RME can inhibit and kill ESBL-KP through disrupting its cell membrane and inhibiting the enzymatic activity of ESBLs, which provided a scientific basis for further research on Rosa sertata × Rosa rugosa.

To explore the trends in cognitive function and depression symptoms over time among middle-aged and older adults in China, and to identify populations with differing trajectories of cognitive function and depression symptoms, thereby providing a scientific basis for formulating targeted prevention and control measures.

A total of 11 863 individuals aged 45 and above from the China Health and Retirement Longitudinal Study (CHARLS) were included. The Group-based Dual Trajectory Model (GBDTM) was employed to identify the developmental trajectories of cognitive function and depression symptoms, and multinomial logistic regression analysis was utilized to examine the influencing factors of different trajectories.

The GBDTM identified four trajectory groups: “Poor cognitive function but mild depression symptoms” (Group 1, 32.9%),“Poor cognitive function and severe depression symptoms” (Group 2, 10.8%), “Good cognitive function and mild depression symptoms” (Group 3, 40.5%), and “Moderate cognitive function and moderate depression symptoms” (Group 4, 15.7%). Factors associated with a higher likelihood of being classified in the“Poor cognitive function and severe depression symptoms” group included being female (OR=4.70, 95%CI: 3.82-5.78), unmarried (OR=2.09, 95%CI: 1.67-2.60), residing in rural areas (OR=4.26,95%CI: 3.59-5.07), smoking (OR=1.26, 95%CI: 1.02-1.56), having activities of daily living (ADL) disabilities (OR=1.92, 95%CI:1.39-2.65), and having instrumental activities of daily living (IADL) disabilities (OR=7.43, 95%CI: 5.90-9.35).

There is a partially “joint development” trajectory relationship between cognitive function and depression symptoms in middle-aged and older adults. Early intervention targeting the influencing factors of different trajectory groups is crucial.