Extreme cold exposure is an emerging climate-related stressor, but its impact on glaucoma-related outcomes and intraocular pressure (IOP) remains unclear. We conducted an integrated epidemiological and experimental study combining a time-stratified case-crossover analysis of 4090 glaucoma patients in Shanghai with multivariable linear regression and mechanistic experiments. Extreme cold exposure was associated with increased glaucoma outpatient visits, and lower ambient temperature was associated with higher IOP across multiple lag days after adjustment for demographic, meteorological, and air pollution factors. In vivo, chronic cold exposure (4 °C, 22 h/day, 4 weeks) was associated with sustained IOP elevation and anterior segment changes, accompanied by increased extracellular matrix (ECM) deposition, enhanced trabecular meshwork contractility, and elevated serum glucocorticoid and norepinephrine levels. In vitro, dexamethasone increased α-smooth muscle actin (αSMA) and collagen type I alpha 1 chain (COL1A1), while norepinephrine increased myosin regulatory light chain 2 (MLC2) phosphorylation. Transcriptomic analysis identified 5168 differentially expressed genes enriched in ECM organization, TGF-β signaling, calcium signaling, and cGMP-PKG pathways. In conclusion, extreme cold exposure was associated with glaucoma-related outcomes and IOP elevation, and integrated evidence suggests that cold-related neuroendocrine activation may contribute to extracellular matrix remodeling and trabecular meshwork dysfunction, potentially affecting aqueous humor outflow and IOP regulation.

BackgroundOccupational environments contain a wide variety of harmful factors, with noise often coexisting with other physical, chemical factors, leading to combined exposure that may increase the risk of hearing impairment among workers. This study aims to investigate the association of occupational noise and coal dust combined exposure on noise-induced hearing loss in workers, providing evidence for the prevention and control of occupational noise-induced hearing loss in occupational populations.MethodsWe conducted a cross-sectional study of 1,187 occupationally exposed workers. These workers who underwent occupational health examinations at a certain occupational health examination institution in Baiyin City in 2023 were selected as study subjects and divided into a noise only group (276 participants) and a combined noise-coal dust exposure group (911 participants). Pure-tone air-conduction audiometry was used to assess hearing loss, and the χ2 test and multivariate logistic regression analysis were applied to identify risk factors for high-frequency hearing loss (HFHL).ResultsThe prevalence rates of HFHL were 35.5 and 46.8% in the noise group and the combined noise-coal dust exposure group, respectively, with a statistically significant difference (p < 0.001); the prevalence of speech-frequency hearing loss was relatively low. Hearing abnormalities were primarily concentrated in the high-frequency range, with a marked decline around 4,000 Hz. Multivariate logistic regression analysis indicated that age, gender, and exposure to occupational hazards were independent risk factors for HFHL. After multivariable adjustment, combined exposure to occupational noise and coal dust was associated with higher odds of HFHL compared with noise exposure alone (OR = 1.620, 95% CI: 1.198–2.190, p = 0.002).ConclusionOccupational noise-induced hearing loss is predominantly HFHL, and Workers classified as jointly exposed to occupational noise and coal dust had higher adjusted odds of HFHL than workers classified as exposed to occupational noise alone. Comprehensive protection and occupational health surveillance for workers exposed to combined hazards should be strengthened.

Introduction: Methyl-N'-nitro-N-nitrosoguanidine (MNNG) is an environmental carcinogen that induces Gastric Cancer (GC). N7-methylguanosine (m7G) is a prevalent RNA modification closely linked to cancer onset and progression. However, the role of m7G in regulating gene expression during MNNG-induced gastric carcinogenesis remains unclear. This study aims to investigate the role of m7G modification in MNNG-induced GC and to identify potential downstream regulatory genes. Methods: Cell proliferation and migration were evaluated using CCK-8 and scratch assays in Malignant transformed cells (MC) and GC cells with different METTL1 expression levels. The m7G MeRIP-seq and whole-transcriptome sequencing were integrated to screen potential genes regulated by m7G modification in MC-30 cells. GO and KEGG analyses were performed for gene function. Candidate gene expression was screened and validated in MC and GC cells by RT-qPCR. Finally, we validated SLC2A3 by analyzing gene expression using the TCGA STAD cohort and 24 pairs of clinical GC samples. Results: METTL1 knockdown significantly inhibited proliferation and migration by about 25% (p < 0.001). Sequencing analysis identified SLC2A3 as a key METTL1 downstream target, with significantly altered m7G modification levels (fold change > 2, p < 0.05) and enrichment in cancer-related pathways. Clinically, SLC2A3 expression was significantly up-regulated in GC tissues versus normal controls (FC = 2.52, p < 0.001) and was significantly associated with tumor stage and prognosis in GC patients (p < 0.05). Conclusion: Our study revealed that m7G methyltransferase METTL1 plays an oncogenic role in MNNG-induced gastric carcinogenesis. SLC2A3 is a key downstream target of METTL1, which is associated with clinical progression in GC patients. These findings may provide evidence for developing prognostic biomarkers for GC.

This study explored relationship between concentrations of perchlorate, nitrate, and thiocyanate and serum liver function markers using data from 3366 adults in the 2013-2018 National Health and Nutrition Examination Survey (NHANES) of the United States. Generalized linear model (GLM), restricted cubic spline (RCS) regression model, and quartile g-computation (Qgcomp) regression model were used to assess the relationship. The median concentrations of perchlorate, nitrate, and thiocyanate in urine were 2.33, 42,900, and 1060 ng/mL. The median concentrations for serum liver function indicators were albumin (ALB, 4.2 g/dL), alkaline phosphatase (ALP, 67 IU/L), aspartate aminotransferase (AST, 22 U/L), alanine aminotransferase (ALT, 20 U/L), globulin (GLB,2.9 g/dL), gamma-glutamyl transferase (GGT, 20 IU/L), lactate dehydrogenase (LDH, 132 IU/L), total bilirubin (TBIL, 0.5 mg/dL), total protein (TP, 7.1 g/dL). Adjusted GLM results showed perchlorate was positively correlated with AST and ALT, but negatively with ALP, GLB, GGT, LDH, and TP. Nitrate correlated positively with ALB, AST and ALT, and negatively with GLB and GGT. Thiocyanate was positively correlated with ALP, and negatively with AST, ALT, GLB, LDH, TBIL, and TP. RCS analysis, adjusted for confounders, revealed non-linear relationships for perchlorate with LDH, TBIL, and TP (P-overall < 0.0001, P-nonlinear < 0.05), for thiocyanate with ALB, ALP, ALT, and TBIL (P-overall < 0.0001, P-nonlinear < 0.05). Qgcomp results suggested that exposure to these chemicals was negatively correlated with GLB, TBIL and TP. The study found complex correlations between chlorate, nitrate and thiocyanate concentrations and serum liver function indices.

Oral fungal homeostasis is closely related to the state of human health, and its composition is influenced by various factors. At present, the effects of long-term soil heavy metal exposure on the oral fungi of local populations have not been adequately studied. In this study, we used inductively coupled plasma–mass spectrometry (ICP-MS) to detect heavy metals in agricultural soils from two areas in Gansu Province, northwestern China. ITS amplicon sequencing was used to analyze the community composition of oral buccal mucosa fungi from local village residents. Simultaneously, the functional annotation of fungi was performed using FUNGuild, and co-occurrence networks were constructed to analyze the interactions of different functional fungi. The results showed that the species diversity of the oral fungi of local populations in the soil heavy metal exposure group was lower than that of the control population. The relative abundance of Apiotrichum and Cutaneotrichosporon was higher in the exposure group than in the control group. In addition, Cutaneotrichosporon is an Animal Pathogen, which may lead to an increased probability of disease in the exposure group. Meanwhile, there were significant differences in the co-occurrence network structure between the two groups. The control group had a larger and more stable network than the exposure group. Eight keystone taxa were observed in the network of the control group, while none were observed in that of the exposure group. In conclusion, heavy metal exposure may increase the risk of diseases associated with Apiotrichum and Cutaneotrichosporon infection in the local populations. It can also lead to the loss of keystone taxa and the reduced stability of the oral fungal network. The above results illustrated that heavy metal exposure impairs oral fungal interactions in the population. This study extends our understanding of the biodiversity of oral fungi in the population and provides new insights for further studies on the factors influencing oral fungal homeostasis.

To explore the exposure-lag-response relationships and the interaction effects of meteorological and air pollutants on cerebrovascular disease admissions (CDA), this study used a distributed lag nonlinear model of time series. Univariate analysis showed a "U" shaped between relative humidity (RH) and CDA, daily mean temperature (DMT) and CDA showed fluctuating variations. Except O3, the relative risk (RR) between air pollutants and CDA showed a monotonically increasing trend. The RR values were maximum at the highest air pollutant concentration, which were RR(NO2) =2.86(95 %CI:1.79-2.58), RR(PM2.5) = 1.82 (95 %CI:1.13-2.94), RR(PM10) = 2.94(95 %CI:1.33-6.52), RR(SO2) = 2.16(95 %CI:1.24-3.75), RR(CO) = 1.91(95 %CI: 1.19-3.06). The interaction results showed statistically significant relative excess risk of interactions (RERI) except DMT with CO and O3, and RH with PM2.5 and NO2. The RERI of DMT with PM2.5, PM10, and NO2 on CDA were all greater than 0, with RERI of 0.99 (95 % CI:0.08-1.90), 0.25 (95 %CI:0.03-0.47), and 1.51 (95 %CI:0.49-2.55), respectively, whereas the RERI of DMT with SO2 on CDA were less than 0. The RERI of RH with PM10 and O3 on CDA were greater than 0 and were 1.08 (95 %CI:0.03-1.97), 2.32 (95 %CI:0.19-5.51), respectively. All factors except O3 had cumulative risks on the CDA and there was an interaction between meteorological factors and air pollutants on CDA.

The purpose of this study was to examine the relationship between extreme temperature and the risk of hospitalization for cardiovascular diseases (CVDs). A distributed lag nonlinear model (DLNM) in combination with a quasi-Poisson regression model was employed to assess the relationship between extreme temperature and risk of hospitalization for CVDs. This approach can be utilized to deal with lag and nonlinear effects. By comprehensively leveraging data information, it can explain the influencing factors from multiple aspects. Due to the complexity of the model, parameter estimation and model fitting typically require significant computational resources and extended processing time. Additionally, we identified the sensitive populations through subgroup analyses based on age and sex. Extremely low temperature (≤-10℃) (Relative Risk (RR) = 1.156, with a 95

Although studies have demonstrated the influence of meteorological factors on morbidity and mortality in type 2 diabetes mellitus (T2DM), research focusing specifically on their impact on hospitalization for T2DM with complications remains Limited.This study aimed to investigate the impact of meteorological factors on hospitalization for type 2 diabetes mellitus (T2DM) with complications. The distributed lag nonlinear modelling (DLNM) was used to investigate this effect of temperature and relative humidity (RH) on hospitalization for T2DM with complications. A total of 50,108 T2DM hospitalizations with complications were performed from 2014 to 2019 in Lanzhou, China. Compared to the reference temperature of 12.7 °C, low temperature (-4.1 °C) had harmful effects, with the maximum impact at lag0-1 (cumulative RR = 1.0265, 95

Research on the associations between PM2.5 and total respiratory diseases (RD) in Lanzhou is limited. We investigated the short-term impact of PM2.5 on total RD hospitalizations in Lanzhou (2015–2019) using various exposure metrics. We collected data on hospitalizations, daily air pollutant concentrations, and meteorological factors during the study period. Daily excessive concentration hours (DECH) were calculated according to the World Health Organization's air quality guidelines. A distributional lag nonlinear model (DLNM) based on a generalized additive model (GAM) was used to comparatively analyze the association between three PM2.5 exposure metrics (DECH (DECH PM2.5), daily mean concentration (Mean PM2.5), and hourly peak concentration (Peak PM2.5)) and RD hospitalizations. Subgroup analyses and sensitivity analyses were also performed. We found similar effects on RD hospitalizations using DECH PM2.5 and Mean PM2.5, but relatively weak associations observed using Peak PM2.5. The cumulative lag effect increased daily. Subgroup analyses showed that females and children aged 0–17 years were more susceptible to PM2.5 pollution and that the association was enhanced during the cold season. Our research strengthened the evidence that exposure to ambient PM2.5 increases the risk of RD. This study revalidated the reliability of the new metrics and confirmed that DECH PM2.5 effect estimates for exposure-disease were more accurate than the Mean PM2.5.

Chronic low-level exposure to nickel (Ni), copper (Cu), and arsenic (As) may contribute to myocardial injury via oxidative stress. This study investigated the effects of these metals in male Sprague–Dawley rats exposed to aerosols of Ni (0.106 mg/m3), Cu (0.048 mg/m3), and As (0.025 mg/m3) at environmental and 10-fold concentrations for 3 mo. Blood metal levels were analyzed using inductively coupled plasma–mass spectrometry (ICP–MS), and oxidative stress and myocardial injury biomarkers were measured with enzyme-linked immunosorbent assay (ELISA). Blood As levels showed a dose-dependent increase in both exposure groups. Myocardial ultrastructural damage, including mitochondrial swelling, disorganized myofibrils, and increased autolysosomes, was observed. Biomarkers of oxidative stress, including catalase (CAT), superoxide dismutase (SOD), and glutathione (GSH), were significantly elevated in both exposure groups, while malondialdehyde (MDA) levels were notably higher in the 10-fold group. Myocardial injury markers (TNNI3, LDHA, and α-HBDH) were elevated in both exposure groups. Significant correlations were found between Cu and As levels and oxidative stress and myocardial injury biomarkers. These findings demonstrate that prolonged low-level exposure to Ni, Cu, and As induces oxidative stress and myocardial injury in rats. The results highlight the potential cardiovascular risks associated with environmental exposure to mixed heavy metals and emphasize the importance of stricter regulatory measures to limit such pollutants.

There is scant research on the association between humidex exposure and urinary system diseases. Hospitalization records from Lanzhou city were collected for the period 2015 to 2019, alongside daily meteorological and air pollution data for the study duration. Daily humidex was calculated using temperature and relative humidity indices. The study employed a combined approach of generalized additive models and distributed lag non-linear models (DLNMs) to estimate the exposure-lag-response relationship between humidex and hospital admissions for urinary system diseases, as well as for subgroups of diseases (urolithiasis and tubule-interstitial diseases). A total of 55,365 patients with urinary system diseases were included. The single lag effect of overall urinary system diseases was most significant on lag13 with the relative risk (RR) = 1.066 (95% confidence interval [CI]: 1.011, 1.124), while the cumulative lag effect over lag0-14 was most significant with RR = 1.387 (95% CI: 1.240, 1.550). The goal of this study was to establish an early warning system and allocate medical resources effectively to reduce hospital admissions for urinary system diseases.

Research on the impact of changes in air pollutant concentrations during peak traffic hours on hospital admissions for respiratory diseases (RD) is limited. This study utilized a distributed lag nonlinear model (DLNM) to investigate this effect. Between 2014 and 2019, a total of 109,419 RD patients were hospitalized across seven hospitals in Lanzhou, China. Except for ozone (O3), fine particulate matter (PM2.5), inhalable particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2) and carbon monoxide (CO), which increased by 10 µg/m3 (1 mg/m3 for CO), the relative risk (RR) values of hospitalization for RD were 1.0211 [95% confidence interval (CI) 1.0090, 1.0333] (lag0-7), 1.0026 ( 95% CI 1.0010, 1.0043) (lag0), 1.0615 (95% CI 1.0355, 1.0882) (lag0-7), 1.0650 (95% CI 1.0478, 1.0824) (lag0-7) and 1.1229 (95% CI 1.0686, 1.1800) ( lag0-7), respectively. The stratified analyses revealed that air pollutants, except for O3, affected both males and females. PM2.5, PM10, NO2, and CO had a greater impact on individuals aged < 15 years, while SO2 had a more pronounced effect on those aged ≥ 65 years. The impact of air pollutants on RD hospitalizations was more significant during the cold season. It was recommended that people reduce short-term outdoor exposure during peak traffic hours.

Angina is a crucial risk signal for cardiovascular disease. However, few studies have evaluated the effects of ambient air pollution exposure on angina. We aimed to explore the short-term effects of air pollution on hospitalization for angina and its lag effects. We collected data on air pollutant concentrations and angina hospitalizations from 2013 to 2020. Distributed lag nonlinear model (DLNM) was used to evaluate the short-term effects of air pollutants on angina hospitalization under different lag structures. Stratified analysis by sex, age and season was obtained. A total of 39,110 cases of angina hospitalization were included in the study. The results showed a significant positive correlation between PM2.5, SO2, NO2, and CO and angina hospitalization. Their maximum harmful effects were observed at lag0-7 (RR = 1.042; 95

Nitrogen dioxide (NO2) represents a deleterious effect on acute myocardial infarction (AMI), but few relevant studies have been conducted in China. We aim to evaluate the acute effects of NO2 exposure on hospitalization for AMI in Lanzhou, China. In this study, we applied a distributional lag nonlinear model (DLNM) to assess the association between NO2 exposure and AMI hospitalization. We explored the sensitivity of various groups through stratified analysis by gender, age, and season. The daily average concentration of NO2 is 47.50 +/- 17.38 mu g/m3. We observed a significant exposure-response relationship between NO2 concentration and AMI hospitalization. The single pollutant model analysis shows that NO2 is positively correlated with AMI hospitalization at lag1, lag01, lag02, and lag03. The greatest lag effect estimate occurs at lag01, where a 10 mu g/m3 increase in NO2 concentrations is significantly associated with a relative risk (RR) of hospitalization due to AMI of 1.027 [95% confidence interval (CI): 1.013, 1.042]. The results of the stratified analysis by gender, age, and season indicate that males, those aged >= 65 years, and the cold season are more sensitive to the deleterious effects caused by NO2 exposure. Short-term exposure to NO2 can enhance the risk of AMI hospitalization in urban Lanzhou.Implications: Exposure to particulate matter can lead to an increased incidence of AMI. Our study once again shows that NO2 exposure increases the risk of AMI hospital admission. AMI is a common and expensive fatal condition. Reducing NO2 exposure will benefit cardiovascular health and save on healthcare costs.

With the backdrop of global climate change, the impact of climate change on respiratory diseases like asthma is receiving increasing attention. However, the effects of temperature and diurnal temperature range (DTR) on asthma are complex, and understanding these effects across different seasons, age groups, and sex is of utmost importance. This study utilized asthma hospitalization data from Lanzhou, China, and implemented a distributed lag nonlinear model (DLNM) to investigate the relationship between temperature and DTR and asthma hospitalizations. It considered differences in the effects across various seasons and population subgroups. The study revealed that low temperatures immediately increase the risk of asthma hospitalization (RR = 1.2010, 95

The aim of this study was to determine the relationship between short-term exposure to ambient air pollution and the number of daily hospital admissions for genitourinary disorders in Lanzhou. Hospital admission data and air pollutants, including PM2.5, PM10, SO2, NO2, O38h and CO, were obtained from the period 2013 to 2020. A generalized additive model (GAM) combined with distribution lag nonlinear model (DLNM) based on quasi-Poisson distribution was used by the controlling for trends, weather, weekdays and holidays. Short-term exposure to PM2.5, NO2 and CO increased the risk of genitourinary disorder admissions with RR of 1.0096 (95

Air pollution is a major environmental risk factor. Hypertension is one of the most important modifiable risk factors for cardiovascular diseases. However, few studies have evaluated the impact of exposure to ambient air pollution on hypertension hospitalizations. This study aims to explore the correlation between exposure to air pollution and hospital admissions for hypertension, to evaluate the short-term effects of air pollution on hypertension hospitalizations and its lag effects. We collected air pollution concentration and hypertension hospitalization data from 2013 to 2020. Distributed lag non-linear models were employed to assess the impact of air pollution on hypertension hospitalizations in Lanzhou City. We also performed subgroup analyses and sensitivity analyses. A total of 47,884 cases of hypertension hospitalizations were included. Short-term exposure to NO2 and CO increased the risk of hypertension hospitalization. For each 10 µg/m3 increase in NO2 and each 1 mg/m3 increase in CO, the relative risk (RR) for hypertension hospitalization were highest at lag0-3 (RR: 1.0427; 95

The study focuses on the effect of temperature and relative humidity on hospitalization for acute lower respiratory tract infections (LRTI) in children, respectively. In this study, the Distributed Lag Nonlinear Model (DLNM) based on quasi-Poisson distribution was used to investigate the effect of temperature and relative humidity on LRTI hospitalization in children, and subgroup analyses were conducted to identify sensitive populations by gender and age. A total of 43,951 children were hospitalized for LRTI from 1 January 2014 to 31 December 2019 in Lanzhou. The mean temperature during the study period was 11.34 °C and the mean relative humidity was 51.03

This study investigates the correlation between short-term exposure to nitrogen dioxide (NO2) and hospitalization for chronic kidney disease (CKD) in Lanzhou, China. A distributed lag nonlinear model (DLNM) was employed to examine the relationship between changes in NO2 concentration and CKD hospitalizations. Subgroup analyses were conducted to assess the sensitivity of different populations to NO2 exposure. A total of 35,857 CKD hospitalizations occurred from 1 January 2014 to 31 December 2019. The average daily concentration of NO2 was 47.33 ± 17.27 µg/m3. A significant exposure response relationship was observed between changes in NO2 concentration and the relative risk (RR) of CKD hospitalization. At lag0 (the same day) and lag0-1 (cumulative same day and the previous 1 day) to lag0-4 (cumulative same day and the previous 4 days), NO2 exhibited a harmful effect on CKD hospitalizations, with the maximum effect occurring at lag0-1. For every 10 µg/m3 increase in NO2 concentration, the RR of CKD hospitalization was 1.034 [95% confidence interval (CI): 1.017, 1.050]. Subgroup analyses revealed that the adverse effects of NO2 were more pronounced in females and individuals aged ≥65 years. The harmful effects were also more significant during the cold season. In conclusion, short-term NO2 exposure is associated with an increased relative risk of CKD hospitalization. Continuous efforts to improve air quality are essential to protect public health.

Extensive evidence has shown that air pollution increases the risk of cardiovascular disease (CVD) admissions. We aimed to explore the short-term effect of air pollution on CVD admissions in Lanzhou residents and their lag effects. Meteorological data, air pollution data, and a total of 309,561 daily hospitalizations for CVD among urban residents in Lanzhou were collected from 2013 to 2020. Distributed lag non-linear model was used to analyze the relationship between air pollutants and CVD admissions, stratified by gender, age, and season. PM2.5, NO2, and CO have the strongest harmful effects at lag03, while SO2 at lag3. The relative risks of CVD admissions were 1.0013(95% CI: 1.0003, 1.0023), 1.0032(95% CI: 1.0008, 1.0056), and 1.0040(95% CI: 1.0024, 1.0057) when PM2.5, SO2, and NO2 concentrations were increased by 10 mu g/m(3), respectively. Each 1 mg/m(3) increase in CO concentration was associated with a relative risk of cardiovascular hospitalization of risk was 1.0909(95% CI: 1.0367, 1.1479). We observed a relative risk of 0.9981(95% CI: 0.9972, 0.9991) for each 10 mu g/m(3) increase in O-3 for CVD admissions at lag06. We found a significant lag effects of air pollutants on CVD admissions. NO2 and CO pose a greater risk of hospitalization for women, while PM2.5 and SO2 have a greater impact on men. PM2.5, NO2, and CO have a greater impact on CVD admissions in individuals aged <65 years, whereas SO2 affects those aged >= 65 years. Our research indicates a possible short-term impact of air pollution on CVD. Local public health and environmental policies should take these preliminary findings into account.