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.

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: 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.

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.

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.

Wildfire smoke exposure is increasing across the U.S., but the long-term neurological effects of smoke-specific fine particulate matter (PM2.5) and its carbonaceous components remain uncertain. Using Medicare data from 2002 through 2019, we examined incident Alzheimer's disease (AD) and Alzheimer's disease and related dementias (ADRD) among 39,678,630 fee-for-service Medicare beneficiaries followed from 2005 through 2019. We identified 3,501,414 incident AD cases over 258.5 million person-years and 8,377,416 incident ADRD cases over 248.6 million person-years. We linked the cohort with annual, high-resolution estimates of smoke and non-smoke PM2.5 mass and carbonaceous components (elemental and organic carbon) and fitted stratified Cox proportional hazards models. Per 1 g/m3 increase, smoke PM2.5 was associated with incident AD (hazard ratio [HR], 1.015, 95% confidence interval [CI], 1.005-1.026) and ADRD (1.029 [1.024-1.035]). Smoke carbonaceous fraction was also associated with AD (1.063 [1.042-1.085]) and ADRD (1.090 [1.077-1.103]). Within the ADRD endpoint, smoke-related associations exceeded their corresponding non-smoke associations on a per-unit-mass basis. Per interquartile range, associations were smaller for smoke PM2.5 (AD, 1.005 [1.002-1.008]; ADRD, 1.009 [1.008-1.011]) than for non-smoke PM2.5 (AD, 1.086 [1.079-1.094]; ADRD, 1.048 [1.043-1.053]). Associations varied across geographic, racial, socioeconomic, and clinical subgroups. Long-term wildfire smoke exposure, particularly its carbonaceous fraction, was associated with higher incidence of AD and ADRD among older U.S. adults. The associations correspond to 2,284 and 11,142 incident cases per year of AD and ADRD attributable to smoke PM2.5 among older Medicare beneficiaries, with the carbonaceous fraction accounting for most of this burden. These findings support the use of source-resolved and composition-specific smoke metrics in dementia research and wildfire-smoke health-impact assessments.

Urban green infrastructure is increasingly promoted as a public-health intervention, yet the biological features that determine exposure to potentially beneficial plant-derived volatile compounds remain poorly understood. Here we quantified airborne terpenes and terpenoids across five contrasting urban greenspaces in Oxford, UK, and related chemical profiles to plant diversity, vegetation structure and surrounding habitat characteristics. Ambient air samples collected across spring and summer were analysed by thermal-desorption gas chromatography-mass spectrometry, alongside field surveys of taxonomic richness, canopy cover, vegetation volume and ground composition. Terpene and terpenoid scentscapes differed strongly among sites and through time, with monoterpenes dominating detected profiles. Sites with greater plant richness and greater vegetation volume below 1.5 m consistently showed higher terpene/terpenoid abundance, whereas total vegetation volume, canopy cover and tree abundance were weaker and less consistent predictors. These relationships were specific to plant-associated chemical classes and were not observed for predominantly anthropogenic volatile compounds. These patterns were resolved across only five independent sampling sites, and the relationships reported here should therefore be considered exploratory. Our findings suggest that human exposure to plant-derived volatiles in cities may be maximised not simply by increasing tree cover, but by designing biodiverse, structurally complex lower-to-mid-storey vegetation within the breathing zone. These results provide an empirical basis for incorporating scentscape ecology into health-oriented urban greenspace design.

Researchers must often rely on observational data to draw conclusions about the causal relationship between an exposure and an outcome. This is common in environmental epidemiology research, where the assignment to an exposure can be unethical or impossible. Consider a setting in which we seek to estimate excess mortality during heat waves, but are unable to randomize individuals to moderate or extreme heat. We propose to follow a causal framework for non-randomized time series that uses what we call historical time series matching to construct hypothetical randomized experiments, in which background covariates are balanced. We applied this framework and assessed the following causal question: Are daily mortality counts among elderly Americans higher during hot versus warm summer time periods? We addressed this causal question by drawing frequentist, Fisherian, and Bayesian inferences for five American cities. We estimated the average treatment effect of heat on three-day mortality with 95% Fisherian intervals to be 0.5 [-3.6, 4.4] deaths in Pittsburgh, 3.7 [0.7, 6.6] deaths in Seattle, 12.5 [6.1, 18.9] deaths in Chicago, 8.5 [1.4, 15.6] deaths in Los Angeles, and 20.3 [11.2, 29.5] deaths in New York.

Total serum perfluorooctane sulfonate (PFOS) concentration and its isomer composition describe different aspects of internal exposure, but their respective associations with depressive symptoms remain uncertain. We examined adults aged 18-25 years in NHANES August 2021-August 2023 using survey-weighted models of the Patient Health Questionnaire-9 (PHQ-9). Total measured PFOS was the sum of linear PFOS and pooled monomethyl-branched PFOS; composition was their log-ratio. The analytic cohort included 169 participants, with 147 complete cases for core adjustment. Median total PFOS was 1.70 ng/mL, the median linear fraction was 72.2%, and the weighted prevalence of PHQ-9 [≥]10 was 22.6%. In the joint adjusted model, a doubling of total PFOS at fixed composition corresponded to -0.49 PHQ-9 points (95% CI, -1.65 to 0.68); a doubling of the linear-to-branched ratio at fixed total corresponded to 0.21 points (-1.94 to 2.36). Algebraic rescaling across the reported interquartile ranges yielded differences of -0.58 points (-1.95 to 0.81) for total PFOS and 0.13 points (-1.16 to 1.41) for composition. The inverse continuous-score association weakened with adjustment, whereas the screening odds ratio primarily lost precision. Excluding three observations with an isomer below detection shifted both joint coefficients. The data therefore do not establish an independent composition association or equivalent isomer effects. Experimental evidence supports candidate oxidative, inflammatory, and synaptic pathways, but differential protein binding and elimination prevent a serum composition ratio from being interpreted directly as brain dose or toxicity. Larger longitudinal analyses with isomer-resolved exposure and toxicokinetic measurements are needed to test these pathways.

Background. Public-health use of influenza surveillance - situational awareness, planning for clinical surge, and issuing advisories or warnings - needs more than an accurate point estimate of next week's count. What matters operationally is whether a rise is caught early, whether the direction of change is right, and whether an alert threshold is about to be crossed, all with honest uncertainty. For such use a forecast must also respect reporting delay, later data revision, and the calibration of its prediction intervals. Using Japan's sentinel surveillance, we evaluated short-term probabilistic forecasts that respect the data release history, and we measured what adding other surveillance series contributes, focusing on the properties that matter for public-health decisions. Methods. The target was the number of influenza reports per sentinel site in each of the 47 prefectures. For each forecast we predicted, as quantiles, the value 1-4 weeks after the most recent observed week. We compared three models: a ridge regression trained jointly across prefectures; a gradient-boosting quantile regression (GBQR) that learns from many surveillance series; and their equal-weight combination on the log scale. Six seasons were used to develop the models. The 2025/26 season was held out as a temporal evaluation period after the specification was fixed; because its epidemic profile had already been seen, it is not a fully independent prospective test. We scored forecasts with the weighted interval score (WIS) and checked prediction-interval coverage. For the Japanese target series we used the value first published for each week; some auxiliary series were taken as retrieved and therefore include later revisions. Results. In 2025/26, the combination's WIS relative to a persistence forecast was 0.841, 0.811, 0.794 and 0.818 at horizons of 1-4 observed weeks - that is, 16-21% lower than persistence. Coverage of the 80% prediction interval was 79.7%, 77.1%, 74.5% and 75.1%, and of the 95% interval 94.3%, 93.4%, 92.6% and 91.8%. Adding auxiliary series improved the GBQR over the development period. However, on the original scale the combination's edge over ridge regression was not statistically clear, and in some low-level rising phases the combination did worse than ridge. Conclusions. Over the period studied, models that share information across regions scored better than a persistence forecast. For public-health use, however, the operative questions are the real lead time once reporting delay is accounted for, whether rises from low levels and threshold exceedances are caught in time, and whether the upper prediction intervals are wide enough; on these, the present evidence is not yet sufficient. The 2025 change to the sentinel system also means that pre-change advisory and warning thresholds cannot be read mechanically. A prospective evaluation with strictly controlled data availability is needed before such forecasts are used to support advisories or planning.

Wearable light loggers are increasingly used to assess light exposure in everyday environments in studies of circadian physiology and sleep, yet their accuracy under diverse lighting conditions remains insufficiently understood. This study evaluated three commonly used wearable light loggers (ActLumus, Lido and OcuWEAR) by comparing measurements of photopic illuminance, melanopic equivalent daylight illuminance (m-EDI), and correlated colour temperature (CCT) against a reference spectroradiometer under controlled laboratory conditions and in the field. Measurements were conducted across fluorescent, incandescent, and multiple LED sources, as well as under dynamic daylight exposure. Device performance depended strongly on both light source characteristics and metric type. Illuminance exhibited lower variability, whereas m-EDI and CCT showed substantial device- and condition-specific biases, particularly under spectrally atypical illumination conditions. These differences were consistent with spectral mismatch effects arising from standard photometric calibration practices. Importantly, the impact of measurement bias varied by exposure context: under dim light conditions, small absolute deviations led to substantial misclassification relative to currently recommended thresholds, whereas brighter electric light and daylight conditions were more robust. These findings highlight that device- and context-dependent biases can influence the interpretation of light exposure in circadian and sleep research, underscoring the need for careful device selection and data interpretation.

Current health risk assessments from thirdhand exposure to methamphetamine (meth) to occupants of contaminated residences when no cooking or use is still occurring assume that inhalation exposure is insignificant. After Wright et al. (2021) reported substantial meth concentrations in a contaminated residence, the present study was conducted to further test the hypothesis that concentrations were high enough to contribute to total occupant dose. Air sampling was conducted in contaminated residences that had been previously sampled for surface contamination. Samples were collected on personal sampling pumps in fixed locations on treated glass fiber filters is cassettes and analyzed by gas or liquid chromatography with mass spectroscopy. Sixty-nine samples were collected from eighteen residences for the study. Meth concentrations ranged from 0.02 to 15 ug/m3. Concentrations in supply air vents were significantly higher than in return vents or in ambient air. Residences with no HVAC systems (baseboard heat) had airborne concentrations similar to residences with HVAC systems turned off, and lower than when HVAC was on. Whether a residence was occupied or not did not show differences. All data from residences with HVAC had a significant correlation with surface concentrations (R2 = 0.61) but some factors that affected results were not determined in the study. In the context of the risk assessment and regulatory standard established by California and adopted in several other states, the inhalation exposure would approximately double total occupant dose for infants, and this population would exceed the California reference dose by approximately 100%. Further studies should be conducted to refine these estimates and determine the factors that influence airborne concentrations.

Chromosome was "self-assembled" into a complex three-dimensional topology in the nucleus, which provided the structural basis for important biological processes such as gene expression regulation and cell differentiation. The current understanding of the three-dimensional organization of the genome is based on high-throughput sequencing and imaging technologies to visualize the conformation of chromatin in its native environment. This study proposes a new research perspective and technical means to use fusion genes to determine the interaction information and three-dimensional structure of chromosomes. This three-dimensional information provided by the fusion gene spectrum not only shows the universality of the spatial layout of chromosomes, but also increases the interpretability of the occurrence of fusion genes. The chromatin conformation capture data of multiple tissues and periods is significantly correlated with the strength of fusion genes. For example, the frequency of trans-interaction between chromosomes 11 and 17 was the highest, and the frequency of fusion gene occurrence corresponding to KMT2A on chromosome 11 was the highest. Therefore, we infer that this structural universality is a common feature of the human genome, which provides a theoretical basis and data for predicting chromosome fusion events.

In 2024, Chicago experienced a measles virus outbreak. Air samples collected as part of routine respiratory virus surveillance from three hospitals that received measles patients were retrospectively analyzed. Measles virus was detected in air samples from one emergency department across five weeks when measles patients were present and another when no known cases were present. Two of three viral sequences derived from air samples were identical to measles patients. The source of one diverging sequence could not be identified and may represent a case not identified by traditional surveillance methods. Air sampling may supplement measles investigation, surveillance and response.

Japanese encephalitis virus (JEV) is a leading cause of viral encephalitis in humans in Asia. Prior to 2021, only sporadic outbreaks had been detected in Australia's tropical northern extremes. However, during 2021-23, JEV infection was identified in 45 people and in more than 85 piggeries, together with many detections in feral pigs, mosquitoes, and other livestock across Australia, including in the temperate far south. Here we estimated the spatial extent of virus transmission during the outbreak (the realised niche) and the area environmentally suitable for transmission (the potential niche). We collated a national dataset of JEV surveillance and detection in humans, mosquitoes, domestic pigs, feral pigs, and sentinel chickens from 2021-23. We combined these data with (1) previously published predictions of habitat suitability for vertebrate host and vector species, and (2) estimated densities of humans, domestic pigs, and feral pigs, in a multipart assessment of spatial risk. Our model projected broad potential environmental suitability over much of northern and eastern Australia during the outbreak period, but floodplain wetland areas in the north and the inland east of Australia had both the highest estimated environmental suitability for transmission, and the strongest evidence for virus circulation.

Background: Commercial spaceflight now carries civilians on short missions, yet their stress-axis physiology is poorly described. Earlier shuttle data suggest that sympathetic responses predominate after short flights and glucocorticoid responses after long ones. The neutrophil-to-lymphocyte ratio (NLR) is a low-cost readout of both. Methods: Preregistered secondary analysis of open clinical laboratory data (NASA Open Science Data Repository OSD-569 and OSD-575) from the four Inspiration4 crew members, each sampled seven times: three draws before launch, one the day after return (R+1) and three during recovery (R+45 to R+194). Log-transformed NLR was modelled with a linear mixed model with a random intercept per crew member and Kenward-Roger inference. Lymphocyte and eosinophil counts and C-reactive protein were secondary outcomes with false discovery rate correction. Results: All 28 draws were analysed. NLR at R+1 did not differ from pre-flight (fold change 1.04; 95% CI 0.81 to 1.34; p = 0.73); two crew members increased (+25% and +46%) and two decreased (-27% and -11%). During recovery NLR was 23% lower than pre-flight (fold change 0.77; 95% CI 0.64 to 0.92; p = 0.005). No secondary outcome changed after correction; lymphocytes were 18% lower at R+1 (95% CI -35% to +4%; q = 0.31). Between-person differences explained 58% of the variance. An ordinary regression ignoring repeated measures missed the recovery effect (p = 0.08). Conclusions: A 3-day orbital flight produced no consistent leukocyte stress signature one day after return. The lower NLR during recovery suggests that pre-flight values, not recovery values, deviate from the resting state, which has implications for how baselines are defined in short-duration spaceflight studies.