Associations of metals and metal mixtures with glucose homeostasis: A combined bibliometric and epidemiological study.

This study employs a combination of bibliometric and epidemiological methodologies to investigate the relationship between metal exposure and glucose homeostasis. The bibliometric analysis quantitatively assessed this field, focusing on study design, predominant metals, analytical techniques, and citation trends. Furthermore, we analyzed cross-sectional data from Beijing, examining the associations between 14 blood metals and 6 glucose homeostasis markers using generalized linear models (GLM). Key metals were identified using LASSO-PIPs criteria, and Bayesian kernel machine regression (BKMR) was applied to assess metal mixtures, introducing an "Overall Positive/Negative Effect" concept for deeper analysis. Our findings reveal an increasing research interest, particularly in selenium, zinc, cadmium, lead, and manganese. Urine (27.6%), serum (19.0%), and whole blood (19.0%) were the primary sample types, with cross-sectional studies (49.5%) as the dominant design. Epidemiologically, significant associations were found between 9 metals-cobalt, copper, lithium, manganese, nickel, lead, selenium, vanadium, zinc-and glucose homeostasis. Notably, positive-metal mixtures exhibited a significant overall positive effect on insulin levels, and notable interactions involving nickel were identified. These finding not only map the knowledge landscape of research in this domain but also introduces a novel perspective on the analysis strategies for metal mixtures.

Constructing and Evaluating a Mitophagy-Related Gene Prognostic Model: Implications for Immune Landscape and Tumor Biology in Lung Adenocarcinoma.

Mitophagy, a conserved cellular mechanism, is crucial for cellular homeostasis through the selective clearance of impaired mitochondria. Its emerging role in cancer development has sparked interest, particularly in lung adenocarcinoma (LUAD). Our study aimed to construct a risk model based on mitophagy-related genes (MRGs) to predict survival outcomes, immune response, and chemotherapy sensitivity in LUAD patients. We mined the GeneCards database to identify MRGs and applied LASSO/Cox regression to formulate a prognostic model. Validation was performed using two independent Gene Expression Omnibus (GEO) cohorts. Patients were divided into high- and low-risk categories according to the median risk score. The high-risk group demonstrated significantly reduced survival. Multivariate Cox analysis confirmed the risk score as an independent predictor of prognosis, and a corresponding nomogram was developed to facilitate clinical assessments. Intriguingly, the risk score correlated with immune infiltration levels, oncogenic expression profiles, and sensitivity to anticancer agents. Enrichment analyses linked the risk score with key oncological pathways and biological processes. Within the model, MTERF3 emerged as a critical regulator of lung cancer progression. Functional studies indicated that the MTERF3 knockdown suppressed the lung cancer cell proliferation and migration, enhanced mitophagy, and increased the mitochondrial superoxide production. Our novel prognostic model, grounded in MRGs, promises to refine therapeutic strategies and prognostication in lung cancer management.

Recent Advances in Metal-Hydride-Based Disease Treatment.

In comparison to traditional antioxidant treatment methods, the use of hydrogen to eliminate reactive oxygen species from the body has the advantages of high biological safety, strong selectivity, and high clearance rate. As an energy storage material, metal hydrides have been extensively studied and used in transporting hydrogen as clean energy, which can achieve a high hydrogen load and controlled hydrogen release. Considering the antioxidant properties of hydrogen and the delivery ability of metal hydrides, metal-hydride-based disease treatment strategies have attracted widespread attention. Up to now, metal hydrides have been reported for the treatment of tumors and a range of inflammation-related diseases. However, limited by the insufficient investment, the use of metal hydrides in disease treatment still has many shortcomings, such as low targeting efficiency, limited therapeutic activity, and complex material preparation process. Particularly, metal hydrides have been found to have a series of optical, acoustic, and catalytic properties when scaled up to the nanoscale, and these properties are also widely used to promote disease treatment effects. From this new perspective, we comprehensively summarize the very recent research progress on metal-hydride-based disease treatment in this review. Ultimately, the challenges and prospects of such a burgeoning cancer theranostics modality are outlooked to provide inspiration for the further development and clinical translation of metal hydrides.

Architecture of Vanadium-Based MXene Dysregulating Tumor Redox Homeostasis for Amplified Nanozyme Catalytic/Photothermal Therapy.

Taking the significance of the special microenvironment for tumor cell survival into account, disrupting tumor redox homeostasis is highly prospective for improving therapeutic efficacy. Herein, a multifunctional 2D vanadium-based MXene nanoplatform, V4 C3 /atovaquone@bovine albumin (V4 C3 /ATO@BSA, abbreviated as VAB) has been elaborately constructed for ATO-enhanced nanozyme catalytic/photothermal therapy. The redox homeostasis within the tumor cells is eventually disrupted, showing a remarkable anti-tumor effect. The VAB nanoplatform with mixed vanadium valence states can induce a cascade of catalyzed reactions in the tumor microenvironment, generating plenty of reactive oxygen species (ROS) with effective glutathione consumption to amplify oxidative stress. Meanwhile, the stable and strong photothermal effect of VAB under near-infrared irradiation not only causes the necrosis of tumor cells, but also improves its peroxidase-like activity. In addition, the release of ATO can effectively alleviate endogenous oxygen consumption to limit triphosadenine formation and inhibit mitochondrial respiration. As a result, the expression of heat shock proteins is effectively suppressed to overcome thermoresistance and the production of ROS can be further promoted due to mitochondrial injury. Moreover, VAB also presents high photoacoustic and photothermal imaging performances. In brief, the multifunctional nanoplatform can provide ATO-enhanced nanozyme catalytic/photothermal therapy with broadening the biomedical applications of vanadium-based MXene.

Long-term effects of particulate matter on incident cardiovascular diseases in middle-aged and elder adults: The CHARLS cohort study.

BACKGROUND: Although there is evidence of long-term effects of particulate matter (PM) on cardiovascular diseases (CVD), researches about long-term effects of PM1 on CVD are limited. We aimed to examine the long-term effects and magnitude of PM, especially PM1, on incident CVD in China. METHODS: We included 6016 participants aged ≥ 45 years without CVD at baseline in 2011 from the China Health and Retirement Longitudinal Study. Personal PM (PM1, PM2.5, and PM10) concentrations were estimated using geocoded residential address. Generalized linear mixed models and SHapley Additive exPlanation were utilized to calculate the impacts and contributions of PM on CVD. Sensitivity analyses were used to check the robustness. RESULTS: After a follow up of 4-year, 481 (7.99 %) participants developed CVD. Per 10 µg/m3 uptick in 1-year average concentrations of PM1, PM2.5 and PM10 was associated with a 1.20 [95 % confidence interval (CI): 1.05-1.37], 1.13 (95 % CI: 1.11-1.15), and 1.10 (95 % CI: 1.06-1.13) fold risk of incident CVD, respectively. The 2-year average concentrations of PM1, PM2.5 and PM10 were associated with incident CVD, corresponding to a 1.03 (95 % CI: 0.96-1.10), 1.11 (95 % CI: 1.02-1.21), and 1.09 (95 % CI: 1.03-1.15) fold risk, respectively. The SHapley Additive exPlanation values of PM1, PM2.5, and PM10 were 0.170, 0.153, and 0.053, respectively, corresponding to the first, second, and fifth among all air pollutants. Effects of PM1, PM2.5 and PM10 on CVD remained statistically significant in two-pollutant models. The elderly, males, smokers and alcohol drinkers tended to have slightly higher effects, while the differences were not statistically significant (all P-values > 0.05) between subgroups. CONCLUSION: Long-term exposure to PM1, PM2.5, and PM10 was associated with an increased incidence of CVD. The smaller the particle size, the more important it was for incident CVD indicating that emphasis should be placed on small size of PM.

Long-term effect of intermediate particulate matter (PM1-2.5) on incident asthma among middle-aged and elderly adults: A national population-based longitudinal study.

BACKGROUND: There is insufficient evidence about the long-term effects of intermediate particulate matter (PM1-2.5) on asthma development in adults aged 45 years and above. This study aimed to investigate the relationship between long-term exposure to PM1-2.5 and the incidence of asthma in adults aged 45 years and above. METHODS: A cohort study based on the China Health and Retirement Longitudinal Study (CHARLS) database was conducted to investigate the long-term effects of PM1-2.5 on self-reported asthma incidence in adults aged 45 years and above in China from 2011 to 2018. The PM concentrations were estimated using a high-resolution (1 km2) satellite-based spatiotemporal model. A covariate-adjusted generalized linear mixed model was used to analyze the relationship between long-term exposure to PM1-2.5 and the incidence of asthma. Effect modifications and sensitivity analysis were conducted. RESULTS: After a 7-year follow-up, 103 (1.61 %) of the 6400 participants developed asthma. Each 10 µg/m3 increment in the 1-, 2-, 3-, and 4-year moving average concentrations of PM1-2.5 corresponded to a 1.82 [95 % confidence interval (CI):1.11-2.98], 1.95 (95 % CI: 1.24-3.07), 1.95 (95 % CI: 1.26-3.03) and 1.88 (95 % CI: 1.26-2.81) fold risk for incident asthma, respectively. A significant multiplicative interaction was observed between socioeconomic level and long-term exposure to PM1-2.5. Stratified analysis showed that smokers and those with lower socioeconomic levels were at higher risk of incident asthma related to PM1-2.5. Restricted cubic splines showed an increasing trend in asthma incidence with increasing PM1-2.5. Sensitivity analyses showed that our model was robust. CONCLUSION: Long-term exposure to PM1-2.5 was positively associated with incident asthma in middle-aged and elderly individuals. Participants with a history of smoking and lower socioeconomic levels had a higher risk. More studies are warranted warrant to establish an accurate reference value of PM1-2.5 to mitigate the growing asthma burden.

Long-term effect of submicronic particulate matter (PM1) and intermodal particulate matter (PM1-2.5) on incident dyslipidemia in China: A nationwide 5-year cohort study.

BACKGROUND: There is insufficient evidence of associations between incident dyslipidemia with PM1 (submicronic particulate matter) and PM1-2.5 (intermodal particulate matter) in the middle-aged and elderly. We aimed to determine the long-term effects of PM1 and PM1-2.5 on incident dyslipidemia respectively. METHODS: We studied 6976 individuals aged ≥45 from the China Health and Retirement Longitudinal Study from 2013 to 2018. The concentrations of particular matter (PM) for every individual's address were evaluated using a satellite-based spatiotemporal model. Dyslipidemia was evaluated by self-reported. The generalized linear mixed model was applied to quantify the correlations between PM and incident dyslipidemia. RESULTS: After a 5-year follow-up, 333 (4.77%) participants developed dyslipidemia. Per 10 µg/m³ uptick in four-year average concentrations of PMs (PM1 and PM1-2.5) corresponded to 1.11 [95% confidence interval (CI): 1.01-1.23)] and 1.23 (95% CI: 1.06-1.43) fold risks of incident dyslipidemia. Nonlinear exposure-response curves were observed between PM and incident dyslipidemia. The effect size of PM1 on incident dyslipidemia was slightly higher in males [1.14 (95% CI: 0.98-1.32) vs. 1.04 (95% CI: 0.89-1.21)], the elderly [1.23 (95% CI: 1.04-1.45) vs. 1.03 (95% CI: 0.91-1.17)], people with less than primary school education [1.12 (95% CI: 0.94-1.33) vs. 1.08 (95% CI: 0.94-1.23)], and solid cooking fuel users [1.17 (95% CI: 1.00-1.36) vs. 1.06 (95% CI: 0.93-1.21)], however, the difference was not statistically significant (Z = -0.82, P = 0.413; Z = -1.66, P = 0.097; Z = 0.32, P = 0.752; Z = -0.89, P = 0.372). CONCLUSIONS: Long-term exposure to PM1 and PM1-2.5 were linked with an increased morbidity of dyslipidemia in the middle-aged and elderly population. Males, the elderly, and solid cooking fuel users had higher risk. Further studies would be warranted to establish an accurate reference value of PM to mitigate growing dyslipidemia.

Research on prediction of daily admissions of respiratory diseases with comorbid diabetes in Beijing based on long short-term memory recurrent neural network.

To compare the performance of generalized additive model (GAM) and long short-term memory recurrent neural network (LSTM-RNN) on the prediction of daily admissions of respiratory diseases with comorbid diabetes. Daily data on air pollutants, meteorological factors and hospital admissions for respiratory diseases from Jan 1st, 2014 to Dec 31st, 2019 in Beijing were collected. LSTM-RNN was used to predict the daily admissions of respiratory diseases with comorbid diabetes, and the results were compared with those of GAM. The evaluation indexes were calculated by five-fold cross validation. Compared with the GAM, the prediction errors of LSTM-RNN were significantly lower [root mean squared error (RMSE): 21.21±3.30 vs. 46.13±7.60, <0.01; mean absolute error (MAE): 14.64±1.99 vs. 36.08±6.20, <0.01], and the value was significantly higher (0.79±0.06 vs. 0.57±0.12, <0.01). In gender stratification, RMSE, MAE and values of LSTM-RNN were better than those of GAM in predicting female admission (all <0.05), but there were no significant difference in predicting male admission between two models (all >0.05). In seasonal stratification, RMSE and MAE of LSTM-RNN were lower than those of GAM in predicting warm season admission (all <0.05), but there was no significant difference in value (>0.05). There were no significant difference in RMSE, MAE and between the two models in predicting cold season admission (all >0.05). In the stratification of functional areas, the RMSE, MAE and values of LSTM-RNN were better than those of GAM in predicting core area admission (all <0.05). has lower prediction errors and better fitting than the GAM, which can provide scientific basis for precise allocation of medical resources in polluted weather in advance.

Influence of PM1 exposure on total and cause-specific respiratory diseases: a systematic review and meta-analysis.

An increasing number of studies examined the potential effects of PM1 (submicronic particulate matter with an aerodynamic diameter ≤ 1 µm) on the risk of respiratory diseases; however, the results have been inconclusive. This study aimed to determine the overall association between PM1 with total and cause-specific respiratory diseases. A systematic review and meta-analysis was conducted with 68 related articles retrieved, and six articles met the full inclusion criteria for the final analysis. For a 10 µg/m3 increase in PM1, the pooled odds ratio (OR) was 1.05 (95% CI 0.98-1.12) for total respiratory diseases, 1.25 (95% CI 1.00-1.56) for asthma, and 1.07 (95% CI 1.04-1.10) for pneumonia with the I2 value of 87%, 70%, and 0%, respectively. Subgroup analyses showed that long-term exposure to PM1 was associated with increased risk of asthma (OR 1.47, 95% CI 1.33-1.63) with an I2 value of 0%, while short-term exposure to PM1 was not associated with asthma (OR 1.07, 95% CI 0.89-1.27) with the I2 value of 0%. Egger's test showed that publication bias existed (P = 0.041); however, the funnel plot was symmetrical with the inclusion of the moderator. In conclusion, elevated levels of PM1 may increase morbidity in total and cause-specific respiratory diseases in the population.

The association between ozone and ischemic stroke morbidity among patients with type 2 diabetes in Beijing, China.

BACKGROUND: The association between ozone and ischemic stroke has been widely reported; however, the association among patients with type 2 diabetes (T2D) has remained largely unknown. METHODS: The time series data of daily morbidity and concentrations of ozone from 2014 to 2018 were collected in Beijing, China. A time-stratified case-crossover study combined with a distributed lag nonlinear model was used to estimate the ozone effect on stroke morbidity among T2D patients. Based on principal diagnosis, ischemic stroke cases were identified according to the International Classification of Diseases (I63), and a history of T2D was coded as E12. RESULTS: A total of 149,757 hospital admissions for ischemic stroke among T2D patients were recorded in Beijing. Approximately U-shaped exposure-response curves were observed for ozone and ischemic stroke morbidity among T2D patients. With a reference at 54.91 µg/m3, extreme-low (5th: 9.59 µg/m3) ozone was significantly associated with a decreased risk for ischemic stroke [RR = 0.88, 95% confidence interval (CI): 0.80-0.98]. Subgroup analysis showed that extremely low-ozone (5th) level only had a significant protective effect in males and elderly population, with a RR value of 0.86 (95% CI: 0.76-0.97) and 0.85 (95% CI: 0.75-0.96), respectively. Extreme-high ozone (99th: 157.06 µg/m3) was significantly associated with an increased risk for ischemic stroke (RR = 1.33, 95% CI: 1.12-1.57). The effect size was 1.34 (95% CI: 1.10-1.63) for males and 1.32 (95% CI: 1.07-1.63) for females, and the difference was not significant (Z = -0.29, P = 0.77). The effect size in younger adults was significantly higher than that in participants aged ≥65 years [1.52 (95% CI: 1.21-1.91) vs. 1.22 (95% CI: 1.01-1.47), Z = -1.62, P < 0.05]. CONCLUSIONS: U-shaped associations were observed between ozone and ischemic stroke morbidity in T2D patients. Men and elderly population are vulnerable to low-ozone level, and the younger adults are more susceptible to extremely high-ozone level than the elderly.

Acute effect of particulate matter pollution on hospital admissions for cause-specific respiratory diseases among patients with and without type 2 diabetes in Beijing, China, from 2014 to 2020.

BACKGROUND: Scientific studies have identified various adverse effects of particulate matter (PM) on respiratory disease (RD) and type 2 diabetes (T2D). However, whether short-term exposure to PM triggers the onset of RD with T2D, compared with RD without T2D, has not been elucidated. METHODS: A two-stage time-series study was conducted to evaluate the acute adverse effects of PM on admission for RD and for RD with and without T2D in Beijing, China, from 2014 to 2020. District-specific effects of PM2.5 and PM10 were estimated using the over-dispersed Poisson generalized addictive model after adjusting for weather conditions, day of the week, and long-term and seasonal trends. Meta-analyses were applied to pool the overall effects on overall and cause-specific RD, while the exposure-response (E-R) curves were evaluated using a cubic regression spline. RESULTS: A total of 1550,154 admission records for RD were retrieved during the study period. Meta-analysis suggested that per interquartile range upticks in the concentration of PM2.5 corresponded to 1.91% (95% CI: 1.33-2.49%), 2.16% (95% CI: 1.08-3.25%), and 1.92% (95% CI: 1.46-2.39%) increments in admission for RD, RD with T2D, and RD without T2D, respectively, at lag 0-8 days, lag 8 days, and lag 8 days. The effect size of PM2.5 was statistically significantly higher in the T2D group than in the group without T2D (z = 3.98, P < 0.01). The effect sizes of PM10 were 3.86% (95% CI: 2.48-5.27%), 3.73% (95% CI: 1.72-5.79%), and 3.92% (95% CI: 2.65-5.21%), respectively, at lag 0-13 days, lag 13 days, and lag 13 days, respectively, and no statistically significant difference was observed between T2D groups (z = 0.24, P = 0.81). Significant difference was not observed between T2D groups for the associations of PM and different RD and could be found between three groups for effects of PM10 on RD without T2D. The E-R curves varied by sex, age and T2D condition subgroups for the associations between PM and daily RD admissions. CONCLUSIONS: Short-term PM exposure was associated with increased RD admission with and without T2D, and the effect size of PM2.5 was higher in patients with T2D than those without T2D.