The Innovation

Wildfire smoke poses a growing health risk worldwide, yet the magnitude and temporal evolution of mortality after episodic exposure remain poorly resolved, limiting burden assessment. Using monthly county-level wildfire PM2.5 and mortality data from the United State, we exploit episodic exposure contrasts to deconvolve overlapping mortality responses and recover the impulse-response function. The excess mortality response peaks approximately three years after an exposure pulse and subsides by five years. We estimate 1.7 (95% uncertainty interval: 1.1-2.3) million smoke-associated deaths during 2011-2023, approximately ten times estimates using long-term ambient PM2.5 mortality relative risks. Circulatory and respiratory diseases contribute comparably and dominate this burden. Responses are markedly greater among adults [≥]65 years; during the COVID-19 pandemic, population-wide cumulative responses are significantly higher over at least the first seven months after exposure. Reducing wildfire smoke exposure can thus yield substantial health benefits over multiple years, particularly when population vulnerability is heightened.

Exposure to fine particulate matter (PM2.5) increases paediatric respiratory morbidity, but its impact on the intensity and economic burden of care in early childhood remains unclear. Here we link nationwide health records for 3,210,381 South Korean children (99,261,945 child-month observations, 2015-2019) and exploit quasi-random variation in PM2.5 induced by thermal inversions to estimate its causal effects on respiratory care and expenditure. A 1-standard-deviation increase in monthly PM2.5 (7.23 micrograms per cubic metre) raises respiratory visits broadly, peaking at age 1 (0.29 additional visits per child-month) and remaining significant through age 6. In contrast, expenditures rise disproportionately among children under 3, increasing by 46.7%, 43.0%, and 35.4% at ages 0, 1, and 2 and becoming indistinguishable from zero beyond age 4. This shift towards higher-intensity emergency care translates into a 32.2% increase in annual respiratory spending among children under 5. Air pollution thus imposes a dual burden, amplifying both the frequency and severity of illness among the youngest infants.

Ambient particulate matter (PM) is a well-established environmental risk factor for non-communicable diseases, yet its influence on mitochondrial function remains poorly defined. Mitochondrial DNA copy number (mtDNA-CN) serves as a biomarker of mitochondrial biogenesis, making it a candidate exposure biomarker. We conducted the study per PRISMA guidelines (PROSPERO-CRD420261320957) and examined the association between ambient PM exposure and mtDNA-CN. Risk of bias was assessed using Joanna Briggs Institute tools, and relative and absolute changes in mtDNA-CN were pooled using random-effects models, with subgroup analyses by pollutant type and descriptive synthesis of mechanistic evidence. Of 1,224 records identified, 24 studies met inclusion criteria for quantitative analysis, with 12 reporting percentage change and 12 reporting absolute values, covering 13,092 participants. PM exposure was significantly associated with decreased percentage mtDNA-CN (ES: -4.90; 95% CI: -7.97 to -1.82; p = 0.002), while absolute mtDNA-CN levels increased significantly (ES = 0.55; 95% CI: 0.05 to 1.04; p = 0.030). Mechanistic pathways contributing included mtDNA hypermethylation, impaired mitochondrial biogenesis and dynamics. Our findings show ambient PM exposure alters mtDNA-CN, though directionality differs by metric, pointing to the need for larger prospective studies to validate mtDNA-CN as a reliable biomarker of airborne PM and nanoparticulate exposure.

Hydroclimate whiplash, defined as the rapid transition between unusually wet and dry conditions, is expected to intensify under climate change, yet its population health impacts remain largely unknown. Here we quantified the association between hydroclimate whiplash and mortality across the contiguous United States from 2003 to 2023 using monthly county-level mortality records, standardized precipitation evapotranspiration index data, and two-stage time-series models. We identified overall and direction-specific dry-to-wet and wet-to-dry whiplash events at seasonal and sub-annual timescales and across 5-, 10-, and 20-year recurrence intervals. More severe whiplash events were associated with higher all-cause mortality risk; 5-, 10-, and 20-year sub-annual overall whiplash events increased mortality risk over five months by 3.4%, 4.5%, and 5.7%, respectively. Elevated risks were observed across cause-specific mortality outcomes, with the strongest association for infectious diseases. We estimated that 103,471 deaths were attributable to overall whiplash during the study period. These findings identify hydroclimate whiplash as an emerging climate-related public health threat and suggest that adaptation strategies focused on single hazards may underestimate the health burden of rapid, sequential hydroclimatic extremes.

Socioeconomic inequality in exposure to air pollution possess a significant public health challenge, yet little is known about how the disparities vary across the various economic status areas in Nairobi. Globally, studies have shown that exposure to air pollution is unequal across communities hence disparities in harm to human health. This study examined the association between socioeconomic characteristics and perceived air quality among residents of low- and high-socioeconomic status areas in Nairobi, Kenya. Two regions within Nairobi County were selected for this study: Mukuru kwa Njenga (representing the Low Socioeconomic Status) and Langata (representing the High Socioeconomic Status) with a sample size of 384 in HSES areas and 368 in LSES areas. A cross-sectional study was conducted among 752 respondents residing in selected LSES and HSES areas of Nairobi. Data was collected using a structured questionnaire assessing sociodemographic characteristics, income, education, employment, perceived air quality, and self-reported health outcomes associated with air pollution exposure. Descriptive statistics were used to summarize participant characteristics and perceived air quality. Chi-square tests were used to examine associations between residential area and categorical health outcomes, while ordinal logistic regression was used to assess the association between socioeconomic characteristics and perceived air-quality ratings. Perceived air quality differed significantly between residential socioeconomic groups. Respondents in LSES areas were more likely to rate air quality as poor or very poor, with 45.4% rating it as very poor, compared with only 1.6% of respondents in HSES areas. In contrast, 12.2% of HSES respondents rated air quality as good compared with 0.3% in LSES areas. The association between area of residence and perceived air-quality rating was statistically significant, {chi}2(3) = 282.672, p < 0.001. In the ordinal logistic regression model, HSES residence was associated with significantly lower odds of reporting poorer perceived air quality compared with LSES residence (OR = 0.135, 95% CI: 0.095-0.190, p < 0.001). Income was also significantly associated with perceived air quality, while respondents with no formal education had higher odds of reporting poorer perceived air quality compared with those with secondary education (OR = 3.254, 95% CI: 1.388-7.638, p = 0.007). Significant differences were also observed for several self-reported health outcomes. Respiratory problems were more prevalent among respondents in LSES areas than HSES areas (72.7% versus 50.4%; {chi}2(1) = 29.081, p < 0.001; Cramer's V = 0.224). However, allergies, eye irritation, and headaches were reported more frequently in HSES areas than in LSES areas, with significant associations observed for allergies ({chi}2(1) = 106.479, p < 0.001; Cramer's V = 0.429), eye irritation ({chi}2(1) = 136.577, p < 0.001; Cramer's V = 0.486), and headaches ({chi}2(1) = 149.180, p < 0.001; Cramer's V = 0.508). No statistically significant association was observed for cardiovascular problems, likely reflecting the very low number of reported cases. Substantial socioeconomic disparities in perceived air quality and self-reported respiratory health outcomes were observed. Residents of low-socioeconomic status areas consistently perceived poorer air quality and reported a higher burden of respiratory problems, highlighting the need for targeted interventions to reduce environmental health inequalities.

Background: Environmental noise and air pollution are both shaped by road traffic and the built environment, and exposure assessment increasingly folds them into composite indices or proxies both by traffic exposure. Whether the two share a social distribution has rarely been tested against direct measurement of several exposures in the same communities, and community noise is almost always characterized by A-weighted levels alone, which discount low-frequency energy. Methods: At 176 sites across Rhode Island, spanning the contiguous urban area of Providence, Central Falls, and Pawtucket together with four rural municipalities, we measured the acoustic environment under A- and C-weighting (LAeq, LCeq), fine particulate matter (PM2.5), night-time illuminance, and relative humidity across four session types over roughly one year (704 site-sessions). Exposures were linked to census-tract composition (American Community Survey), and mixed-effects models were fitted for each of eight area-level markers of disadvantage, adjusting for campaign and session. Relative humidity was carried through the identical model as a negative control. Results: A-weighted noise was consistently higher in more disadvantaged tracts, rising with non-White, poverty, renter, and no-vehicle shares and falling with income and older-resident share (six of eight markers significant; 1.3 to 1.8 dBA per standard deviation; 6.6 dBA between the least and most racially diverse neighborhoods). C-weighted levels followed the same gradient on every marker and exceeded their A-weighted counterparts at block-group scale for renter occupancy and vehicle absence. Night-time illuminance was also socially patterned, whereas short-term PM2.5 was roughly an order of magnitude weaker and relative humidity showed no gradient. The acoustic gradient persisted within the urban core alone. Conclusions: Measured burden was carried by the acoustic environment, including its low-frequency component, and by night-time light, not by short-term particulates. The exposure metric and the averaging time determine which disparities are visible at all.

Wildfire smoke has increasingly affected air quality across North America, raising concerns about the health effects of fine particulate matter (PM2.5) exposure, including potential impacts on brain health. However, relatively few studies have characterized personal PM2.5 exposure during these events using wearable monitoring. We examined daily personal PM2.5 concentrations during wildfire smoke episodes in southeast Michigan alongside neighborhood outdoor PM2.5 estimates. Four participants (one adolescent and three adults) wore AirBeam3 personal monitors during ongoing studies. Neighborhood outdoor PM2.5 was estimated using the average of three nearest PurpleAir outdoor air quality sensors, and wildfire smoke days were identified using state air quality advisories. Group-level descriptive statistics summarized personal and neighborhood outdoor PM2.5 and self-reported time spent outdoors. Exploratory within-participant analyses quantified associations between neighborhood outdoor and personal PM2.5 concentrations on smoke and non-smoke days. Neighborhood outdoor daily PM2.5 concentrations were higher during wildfire smoke days than non-smoke days (87.6 + 80.2 vs. 12.3 + 7.0 {micro}g/m3). Personal PM2.5 concentrations were more than five times higher during wildfire smoke days (28.2 + 20.0 vs. 5.1 + 4.7 {micro}g/m3) than non-smoke days. Within participants, every 10 {micro}g/m3 increase in neighborhood PM2.5 was associated with 2.3 {micro}g/m3 increase in personal PM2.5 concentrations. Wearable PM2.5 monitoring captured elevated personal exposures while providing individual-level exposure information beyond neighborhood outdoor air quality estimates. These findings demonstrate that wearable monitoring complements neighborhood air quality measurements by capturing individual-level exposure, providing a more comprehensive assessment of real-world wildfire smoke exposure for future studies examining the effects on brain health.

Background: Exercise training is a cornerstone intervention for cardiovascular disease, yet large cohort studies have reported attenuation of physical activity benefits at elevated air pollution concentrations, creating uncertainty around exercise prescription in polluted settings where cardiovascular disease burden is greatest. Objectives: To determine whether ambient PM2.5 concentration modifies the cardiovascular benefits of structured exercise training, using a global sample of trials spanning a >100-fold pollution gradient. Methods: We conducted a systematic review and multilevel meta-analysis of exercise training interventions reporting pre-post changes in systolic blood pressure (SBP), diastolic blood pressure (DBP), peak oxygen uptake (VO2Max), or resting heart rate (HR) in adults. Annual ambient PM2.5 concentrations (3.5-283 g/m3) were assigned to each study location from CAMS ERA5 reanalysis data. Three-level random-effects models with cluster-robust variance estimation accounted for arms nested within studies. PM2.5 meta-regression was conducted unadjusted and adjusted for world region, exercise mode, trial duration, and health condition, with subgroup analyses by exercise mode and hypertension status. Results: Across 465 studies (27,629 participants), exercise training produced clinically meaningful benefits for all outcomes (SBP - mmHg, DBP - mmHg, VO2Max +3.2 ml/kg/min, HR - bpm; all p < 0.001), with benefits consistently larger in higher-pollution settings. Hypertensive participants showed the greatest improvements, particularly from aerobic exercise (SBP standardised mean difference 0.396 in the Low vs 1.020 in the High PM2.5 stratum). Although aerobic and resistance training participants experience similar chronic ambient PM2.5 exposure, only aerobic exercise showed a stratum gradient (interaction p = 0.074). Discussion: Exercise training delivers clinically meaningful cardiovascular benefits at every pollution level tested. The larger benefits observed in higher-pollution settings reflect the greater cardiovascular risk burden of those populations, and hypertensive patients stand to gain the most, particularly from aerobic exercise.

Abstract Background: Rising global temperatures are intensifying exposure to extreme heat, yet access to air conditioning (AC) remains unequal which leaves vulnerable populations without protection against the heat. Household survey data on AC ownership is scarce in low- and middle-income countries limiting the ability to identify areas of cooling gaps. Methods: In this study, we develop a geospatial machine learning framework that integrates household data from the Demographic and Health Surveys (DHS) program with high resolution climatic, socioeconomic and demographic covariates to generate a 5km resolution prediction of AC ownership across low- and middle-income countries in Africa and Asia for the year 2023. Results: The resulting map reveals strong spatial inequalities with high predicted prevalence in wealthier and urban regions, and near zero prevalence across much of Central and West Africa and rural areas. These patterns reflect the adaptation cooling gap where those most exposed to extreme heat are least able to adapt through access to cooling. Conclusion: By producing the first continental-scale, high resolution map of AC ownership, this study lays the foundation for designing and targeting equitable cooling strategies, support heat-health planning particularly in communities most affected and informing sustainable energy policy.

Background Alcohol-associated liver disease (ALD) has emerged as a major cause of chronic liver disease and liver-related mortality in China. This study aimed to project the future burden of ALD in Chinese adults from 2020 to 2050, including prevalence of ALD, number of alcoholic steatohepatitis (ASH) cases, incident hepatocellular carcinoma (HCC) cases, liver transplantation (LT) demand, liver-related deaths, and disability-adjusted life years (DALYs). Methods We developed an agent-based state-transition microsimulation model with yearly cycles and a lifetime horizon. The model simulated 5,678,912 representative Chinese adults (mean age 36.2 years, 51.2% male). Health states included no steatosis, alcohol-associated steatotic liver, ASH, fibrosis stages F0-F4, decompensated cirrhosis, HCC, LT, and liver-related death. Model inputs were derived from the China Kadoorie Biobank, Global Burden of Disease Study 2021, China's national surveys, published meta-analyses, and transplant registry data. Projections incorporated demographic shifts, alcohol consumption trends, and calibrated transition probabilities. Uncertainty was assessed via 1,000 Monte Carlo simulations generating 95% uncertainty intervals. Results ALD prevalence was projected to increase from 4.8% (55 million individuals) in 2020 to 8.5% (94 million individuals) by 2050. ASH cases rose from approximately 18 million to 20 million. Annual incident HCC cases nearly doubled from 20,500 in 2020-2025 to 45,200 by 2046-2050. LT demand quadrupled from 2,300 to 9,800 cases. Liver-related deaths increased from 50,000 in 2020 to 85,000 in 2050, while DALYs rose from 1.5 million to 2.6 million. Conclusions In the absence of strengthened alcohol control policies, ALD will impose a substantial and growing burden on China's health system by 2050, with marked increases in HCC incidence, LT demand, and liver-related mortality.

Background: Observational studies have linked air pollution to otitis media, but confounding and reverse causation preclude causal inference. We used two-sample Mendelian randomization (MR) to assess genetic causal effects of six air pollutants on non-suppurative otitis media, represented by otitis media with effusion (OME). Methods: Exposure GWAS for PM2.5, PM2.5 absorbance, PM2.5-10, PM10, NO2 and NOx were obtained from UK Biobank (MRC-IEU), and the outcome was FinnGen R13 H8_NONSUPPNAS (12,397 cases, 464,237 controls). Inverse-variance weighting was primary, with MR-Egger, weighted median and mode, MR-PRESSO, leave-one-out and Steiger analyses, reverse MR and exploratory multivariable MR (MVMR). Asthma, allergic rhinitis and chronic rhinosinusitis served as positive controls, and three suppurative otitis media phenotypes served as negative controls. Results: After false-discovery-rate correction, none of the six pollutants was significantly associated with OME; the sole nominal signal was PM10 (OR=1.555, 95% CI 0.947-2.553, P=0.081), which reversed with the 88-SNP pooled set (OR=0.64, 0.24-1.69, P=0.365). At 80% power, minimum detectable ORs ranged widely from 1.69 to 32.09; only PM2.5-10 and PM10 had values near 2, so moderate effects (OR 1.2-1.5) cannot be excluded. Confirmatory positive controls using phenotype-specific instruments were strongly positive, whereas negative-control outcomes showed no associations (all FDR>0.85). Every nominal reverse-MR signal had a significant MR-Egger intercept (the PM2.5 absorbance signal also showed significant heterogeneity and MR-PRESSO tests), indicating horizontal pleiotropy rather than reverse causation. MVMR was exploratory only, as conditional F statistics were below 10. Conclusions: We found no evidence for large-effect genetic causal associations between the six air pollutants and OME. These null findings argue against large, lifetime-average causal effects, and the associations reported in observational studies may instead reflect residual confounding, shared comorbidity or differences in exposure windows.

Long-term PM2.5 exposure is associated with increased mortality and is usually represented by annual mean concentration, which does not capture how concentrations are distributed across days. We tested whether the prespecified PM2.5 magnitude-rank index (PMRI), a summary of within-year daily concentration structure, improves mortality prediction beyond the annual mean. Daily modeled PM2.5 estimates were linked to age-adjusted mortality rates for 27,289 county-years from 3,064 U.S. counties during 2003-2011. PMRI is the largest k for which at least k days reached k micrograms per cubic meter. County-grouped 10-fold cross-validation compared models with annual mean alone versus annual mean plus PMRI, with additional geographic, temporal, cause-specific, and specification analyses. Annual mean PM2.5 had the highest standalone predictive performance. Adding PMRI increased county-held-out R-squared from 0.0802 to 0.1391 (increase in R-squared = 0.0589; 95% CI, 0.0499-0.0677) and reduced RMSE and MAE. Improvement persisted across geographic and temporal validations and all six cause-specific mortality outcomes. Within-year PM2.5 exposure structure therefore contains reproducible mortality-predictive information not captured by annual mean concentration.

Background: Children spend more than 90% of their time indoors, and early childhood education settings (ECEs) are an understudied, high-occupant-density indoor microenvironment where exposure to volatile organic compounds, particulate matter, and other toxicants has been documented. Limited knowledge exists on ECE-specific exposures affecting young children and how they compare to exposures in the home. Methods: This prospective, repeated-measures pilot study targeted enrollment of 44 preschool-aged children and 8 ECE staff across two geographically and sociodemographically distinct ECEs in metropolitan Atlanta, Georgia. Paired silicone wristbands, one home-designated and one ECE-designated, were exchanged between settings across three consecutive days and nights beginning at enrollment to characterize microenvironment-specific exposure. A single spot urine sample was also collected from each child. Continuous indoor air quality monitoring was conducted in two classrooms per site. Caregivers and ECE staff completed structured questionnaires assessing home and ECE environmental characteristics, child respiratory risk, and protocol feasibility and acceptability. Feasibility was evaluated using eight pre-specified indicators spanning recruitment and enrollment, wristband wear duration and loss by microenvironment, urine sample collection completeness, and survey completion by instrument and respondent group. Conclusion: This pilot will establish feasibility and acceptability parameters for a paired, multi-matrix silicone wristband protocol across home and ECE microenvironments. Findings will inform the design, sample size, and power calculations for a subsequent study testing indoor air interventions and pediatric respiratory outcomes in ECEs. Feasibility outcomes are reported in a companion manuscript.

A minority of asbestos-exposed individuals develop Pleural mesothelioma (PM), suggesting a role for inherited genetic factors. We performed germline whole-exome sequencing of blood from 127 EPIC participants who developed PM and controls. Rare pathogenic/likely pathogenic variants were assessed in 193 cancer-associated genes and were evaluated for association with PM risk and overall survival. Exome-wide gene-based rare-variant aggregation analyses were performed using SKAT-O and Firth logistic regression. A PM polygenic risk score (PRS) was integrated with PTV status and asbestos exposure. Protein Truncating Variants (PTVs) were enriched in cases and associated with increased PM risk (OR=3.5, 95% CI 1.3-11.2, p-value = 0.01). PTV carriers had improved survival and lower mortality after adjustment for age at diagnosis and sex (HR=0.54, 95% CI 0.32-0.92, p-value = 0.023). PTV carriers had lower PRS values, and among individuals with low asbestos exposure, they were associated with increased PM risk (OR=5.75, 95% CI 1.09-58.2, p-value = 0.023). Gene-based analyses identified four novel loci. Rare variants and polygenic background may jointly influence PM risk, however validation in larger cohorts is warranted.

Despite significant advancements in microsurgical techniques in recent years, the treatment and prognosis of craniopharyngiomas remain unsatisfactory. As a central nervous system tumor located adjacent to important brain structures such as the hypothalamus-pituitary axis and accompanied by a highly inflammatory microenvironment, the tumor heterogeneity and tumor microenvironment characteristics of papillary craniopharyngiomas (PCPs) remain unclear. In this study, we integrated multimodal single-cell and spatial profiling from PCP tissue and peripheral blood mononuclear cells (PBMCs) to elucidate the tumor heterogeneity and microenvironment characteristics of PCP. Our single-cell and spatial analyses defined four specific tumor cell states in PCP, representing specific transcriptional regulatory programs and spatial heterogeneity characteristics during tumor progression. By constructing a spatial niche composed of tumor, immune, and stromal cells, we analyzed the cellular and spatial ecosystem of PCP at multiple levels to further assess the communication relationships between different tumor cell states and microenvironment cells. This study established a multidimensional molecular atlas of PCP from the perspectives of cell state, spatial structure, and microenvironment interactions, providing a foundation for understanding its biological behavior and exploring new intervention strategies.

Background: Multiple factors can drive heat susceptibility, but are typically analyzed individually. This study investigates high-dimensional heterogeneity across multiple domains in the effect of hot days on emergency hospitalizations across German districts. Methods: We obtained emergency hospitalization rates per 1,000 in 3-day windows for the summers of 2005-2023 from the German Diagnosis-Related Groups-Statistic, linked with spatio-temporal temperature information. A hot day was defined as at least one day above the district-level 98th percentile heat index. Multiple characteristics of the demographic, health/social, and environmental domains were selected as potential effect modifiers. We implemented a generalized random forest, where outcome and propensity scores were modeled with fixed effects estimators to control for seasonality and district-level confounding. We divided the conditional average treatment effects (CATE) into quartiles to map their spatial distribution and identify key effect modifiers via the variable importance and observed indicator profiles across quartiles. Results: We found substantial variation across districts regarding heat-related emergency hospitalizations. The top three indicators for predicting this effect heterogeneity were the percentage of people seeking protection, population below age 6, and air pollution levels. The observed indicator profile for the most susceptible districts was characterized by a larger percentage of vulnerable populations, higher car density, and fewer hospital beds. Conclusion: There is substantial variation in heat susceptibility across and within districts in Germany. We propose an approach that can help understanding such complex interplay of indicators from different domains driving heterogeneity.

Low pathogenic avian influenza A(H7N7) virus detected in a poultry worker in Taiwan, 2026 was related to viruses circulating in Asian wild birds and possessed PB2 E627K, a mammalian adaptation marker. Enhanced surveillance for H7 viruses in poultry and rapid characterization of human cases are essential to assess pandemic potential.

Coal-fired power plants remain a major source of fine particulate matter (PM2.5) exposure and mortality in the United States. Announced retirement dates mark when those burdens are expected to end, but rising electricity demand, partly from data centers supporting cloud computing and artificial intelligence, has led utilities and regulators to revisit them. Of 50 coal plants scheduled in January 2024 to retire before 2035, 20 had later or removed dates by January 2026. Projecting coal PM2.5 and mortality among Medicare beneficiaries from the 20 plants for 2026-2035, we estimate the revised schedule would result in 1,256 additional deaths (1,136 to 1,376), raising mortality to 3.1 times the original burden. Eighteen plants operate in balancing authorities with hyperscale data-center demand, and federal orders and utility filings supporting several plants' operation cited data-center growth. Retirement schedules are revised faster than health consequences are assessed, and those delays carry a measurable mortality cost.

Background: Cardiovascular disease is an important competing cause of death in men with metastatic prostate cancer, and ambient air pollution may increase cardiovascular vulnerability. We evaluated associations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) with all-cause, cardiovascular, and prostate cancer-specific mortality, including joint associations with androgen deprivation therapy (ADT). Methods: We analyzed 33,384 men from 11 US state registries diagnosed with metastatic prostate cancer during 2000-2015 and followed through 2018. Residential PM2.5 and NO2 concentrations at diagnosis were assigned using 1-km exposure models. Multivariable Cox models estimated all-cause mortality, and inverse-probability-weighted Cox models assessed cause-specific mortality. Results: Each interquartile-range increase in PM2.5 was associated with higher cardiovascular mortality (HR 1.04, 95% CI 1.02-1.07; p-trend=0.008). Cardiovascular mortality was also higher in the fourth and fifth PM2.5 quintiles versus the first (HR 1.18 and 1.21, respectively). Higher NO2 was associated with prostate cancer-specific mortality in the highest quintile (HR 1.07, 95% CI 1.01-1.13). In joint analyses, ADT-treated men with high versus low PM2.5 exposure had higher cardiovascular mortality (HR 1.19, 95% CI 1.05-1.34), without clear evidence of effect modification (p-interaction=0.051). Conclusions: In men with metastatic prostate cancer, higher PM2.5 exposure was associated with cardiovascular mortality, particularly among ADT-treated patients, supporting further study of environmental exposures and systemic therapy in cardio-oncology.

Hepatocellular carcinoma (HCC) is particularly aggressive and difficult to treat. Due to the lack of early clinical diagnosis and the unsatisfactory clinical treatment effect, it is particularly important to identify novel markers that can predict tumor behavior in HCC. biogenesis of ribosomes BRX1 (BRIX1) is abundant in various tissues of the human body. However, the regulatory mechanisms and its role in various tissues are not fully understood. Here, we analyzed the expression pattern of BRIX1 in HCC from public gene expression databases and tissue samples from clinical HCC. We confirmed that BRIX1 was upregulated in both HCC cell lines and HCC paraffin section samples. BRIX1 depletion significantly dicreased the capacity of cells to grow and migrate in vitro, and knockdown BRIX1 suppressed tumor growth in xenograft tumor model. Mechanistically, BRIX1 depletion suppressed the MAPK/ERK pathway, as reflected by reduced phosphorylated ERK (p-ERK) levels. In summary, we provide a rational clue for the further investigation of BRIX1 as an invaluable biological marker for diagnosing and predicting prognosis of patients with HCC.