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BACKGROUND: Epidemiological findings regarding the association of particulate matter ≤2.5 μm (PM2.5) exposure with hypertensive disorders in pregnancy (HDP) are inconsistent; evidence for HDP risk related to PM2.5 components, mixture effects, and windows of susceptibility is limited. We aimed to investigate the relationships between HDP and exposure to PM2.5 during pregnancy. METHODS AND FINDINGS: A large retrospective cohort study was conducted among mothers with singleton pregnancies in Kaiser Permanente Southern California from 2008 to 2017. HDP were defined by International Classification of Diseases-9/10 (ICD-9/10) diagnostic codes and were classified into 2 subcategories based on the severity of HDP: gestational hypertension (GH) and preeclampsia and eclampsia (PE-E). Monthly averages of PM2.5 total mass and its constituents (i.e., sulfate, nitrate, ammonium, organic matter, and black carbon) were estimated using outputs from a fine-resolution geoscience-derived model. Multilevel Cox proportional hazard models were used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of PM2.5 constituents. The distributed lag model was applied to estimate the association between monthly PM2.5 exposure and HDP risk. This study included 386,361 participants (30.3 ± 6.1 years) with 4.8% (17,977/373,905) GH and 5.0% (19,381/386,361) PE-E cases, respectively. In single-pollutant models, we observed increased relative risks for PE-E associated with exposures to PM2.5 total mass [adjusted hazard ratio (HR) per interquartile range: 1.07, 95% confidence interval (CI) [1.04, 1.10] p < 0.001], black carbon [HR = 1.12 (95% CI [1.08, 1.16] p < 0.001)] and organic matter [HR = 1.06 (95% CI [1.03, 1.09] p < 0.001)], but not for GH. The population attributable fraction for PE-E corresponding to the standards of the US Environmental Protection Agency (9 μg/m3) was 6.37%. In multi-pollutant models, the PM2.5 mixture was associated with an increased relative risk of PE-E ([HR = 1.05 (95% CI [1.03, 1.07] p < 0.001)], simultaneous increase in PM2.5 constituents of interest by a quartile) and PM2.5 black carbon gave the greatest contribution of the overall mixture effects (71%) among all individual constituents. The susceptible window is the late first trimester and second trimester. Furthermore, the risks of PE-E associated with PM2.5 exposure were significantly higher among Hispanic and African American mothers and mothers who live in low- to middle-income neighborhoods (p < 0.05 for Cochrans Q test). Study limitations include potential exposure misclassification solely based on residential outdoor air pollution, misclassification of disease status defined by ICD codes, the date of diagnosis not reflecting the actual time of onset, and lack of information on potential covariates and unmeasured factors for HDP. CONCLUSIONS: Our findings add to the literature on associations between air pollution exposure and HDP. To our knowledge, this is the first study reporting that specific air pollution components, mixture effects, and susceptible windows of PM2.5 may affect GH and PE-E differently.

BackgroundPrior studies suggested that air pollution exposure may increase the risk of Parkinson's Disease (PD). We investigated the long-term impacts of traffic-related and multiple sources of particulate air pollution on PD in central California.MethodsOur case-control analysis included 761 PD patients and 910 population controls. We assessed exposure at residential and occupational locations from 1981 to 2016, estimating annual average carbon monoxide (CO) concentrations - a traffic pollution marker - based on the California Line Source Dispersion Model, version 4. Additionally, particulate matter (PM2.5) concentrations were based on a nationwide geospatial chemical transport model. Exposures were assessed as 10-year averages with a 5-year lag time prior to a PD diagnosis for cases and an interview date for controls, subsequently categorized into tertiles. Logistic regression models were used, adjusting for various factors.ResultsTraffic-related CO was associated with an increased odds ratio for PD at residences (OR for T3 vs. T1: 1.58; 95% CI: 1.20, 2.10; p-trend = 0.02) and workplaces (OR for T3 vs. T1: 1.91; 95% CI: 1.22, 3.00; p-trend

Breast cancer metastasis to the brain is a clinical challenge rising in prevalence. However, the underlying mechanisms, especially how cancer cells adapt a distant brain niche to facilitate colonization, remain poorly understood. A unique metabolic feature of the brain is the coupling between neurons and astrocytes through glutamate, glutamine, and lactate. Here we show that extracellular vesicles from breast cancer cells with a high potential to develop brain metastases carry high levels of miR-199b-5p, which shows higher levels in the blood of breast cancer patients with brain metastases comparing to those with metastatic cancer in other organs. miR-199b-5p targets solute carrier transporters (SLC1A2/EAAT2 in astrocytes and SLC38A2/SNAT2 and SLC16A7/MCT2 in neurons) to hijack the neuron-astrocyte metabolic coupling, leading to extracellular retention of these metabolites and promoting cancer cell growth. Our findings reveal a mechanism through which cancer cells of a non-brain origin reprogram neural metabolism to fuel brain metastases.

The Farm Animal Genotype-Tissue Expression (FarmGTEx) project has been established to develop a public resource of genetic regulatory variants in livestock, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biological discovery and exploitation in animal breeding and human biomedicine. Here we show results from the pilot phase of PigGTEx by processing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples passing quality control from pigs. We build a pig genotype imputation panel and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We evaluate tissue specificity of regulatory effects and elucidate molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying 207 pig complex phenotypes and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, supporting the importance of pigs as a human biomedical model.

Inhaled particles and gases can harm health by promoting chronic inflammation in the body. Few studies have investigated the relationship between outdoor air pollution and inflammation by race and ethnicity, socioeconomic status, and lifestyle risk factors. We examined associations of particulate matter (PM) and other markers of traffic-related air pollution with circulating levels of C-reactive protein (CRP), a biomarker of systemic inflammation. CRP was measured from blood samples obtained in 1994-2016 from 7,860 California residents participating in the Multiethnic Cohort (MEC) Study. Exposure to PM (aerodynamic diameter ≤2.5 μm [PM2.5], ≤10 μm [PM10], and between 2.5 and 10 μm [PM10-2.5]), nitrogen oxides (NOx, including nitrogen dioxide [NO2]), carbon monoxide (CO), ground-level ozone (O3), and benzene averaged over one or twelve months before blood draw were estimated based on participants' addresses. Percent change in geometric mean CRP levels and 95% confidence intervals (CI) per standard concentration increase of each pollutant were estimated using multivariable generalized linear regression. Among 4,305 females (55%) and 3,555 males (45%) (mean age 68.1 [SD 7.5] years at blood draw), CRP levels increased with 12-month exposure to PM10 (11.0%, 95% CI: 4.2%, 18.2% per 10 μg/m3), PM10-2.5 (12.4%, 95% CI: 1.4%, 24.5% per 10 μg/m3), NOx (10.4%, 95% CI: 2.2%, 19.2% per 50 ppb), and benzene (2.9%, 95% CI: 1.1%, 4.6% per 1 ppb). In subgroup analyses, these associations were observed in Latino participants, those who lived in low socioeconomic neighborhoods, overweight or obese participants, and never or former smokers. No consistent patterns were found for 1-month pollutant exposures. This investigation identified associations of primarily traffic-related air pollutants, including PM, NOx, and benzene, with CRP in a multiethnic population. The diversity of the MEC across demographic, socioeconomic, and lifestyle factors allowed us to explore the generalizability of the effects of air pollution on inflammation across subgroups.

Gestational diabetes mellitus (GDM) is a major pregnancy complication affecting approximately 14.0% of pregnancies around the world. Air pollution exposure, particularly exposure to PM2.5, has become a major environmental issue affecting health, especially for vulnerable pregnant women. Associations between PM2.5 exposure and adverse birth outcomes are generally assumed to be the same throughout a large geographical area. However, the effects of air pollution on health can very spatially in subpopulations. Such spatially varying effects are likely due to a wide range of contextual neighborhood and individual factors that are spatially correlated, including SES, demographics, exposure to housing characteristics and due to different composition of particulate matter from different emission sources. This combination of elevated environmental hazards in conjunction with socioeconomic-based disparities forms what has been described as a double jeopardy for marginalized sub-populations. In this manuscript our analysis combines both an examination of spatially varying effects of a) unit-changes in exposure and examines effects of b) changes from current exposure levels down to a fixed compliance level, where compliance levels correspond to the Air Quality Standards (AQS) set by the U.S. Environmental Protection Agency (EPA) and World Health Organization (WHO) air quality guideline values. Results suggest that exposure reduction policies should target certain hotspot areas where size and effects of potential reductions will reap the greatest rewards in terms of health benefits, such as areas of southeast Los Angeles County which experiences high levels of PM2.5 exposures and consist of individuals who may be particularly vulnerable to the effects of air pollution on the risk of GDM.

We assessed whether neighborhood socioeconomic disadvantage, as measured by the Area Deprivation Index (ADI), was associated with an increased risk of postpartum readmission. This is a secondary analysis from nuMoM2b (Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be), a prospective cohort of nulliparous pregnant individuals from 2010 to 2013. The exposure was the ADI in quartiles, and the outcome was postpartum readmission; Poisson regression was used. Among 9,061 assessed individuals, 154 (1.7%) were readmitted postpartum within 2 weeks of delivery. Individuals living with the most neighborhood deprivation (ADI quartile 4) were at increased risk of postpartum readmission compared with those living with the lowest neighborhood deprivation (ADI quartile 1) (adjusted risk ratio 1.80, 95% CI 1.11-2.93). Measures of community-level adverse social determinants of health, such as the ADI, may inform postpartum care after delivery discharge.

BACKGROUND: Significant mortality and morbidity in pregnant women and their offspring are linked to premature rupture of membranes (PROM). Epidemiological evidence for heat-related PROM risk is extremely limited. We investigated associations between acute heatwave exposure and spontaneous PROM. METHODS: We conducted this retrospective cohort study among mothers in Kaiser Permanente Southern California who experienced membrane ruptures during the warm season (May-September) from 2008 to 2018. Twelve definitions of heatwaves with different cut-off percentiles (75th, 90th, 95th, and 98th) and durations (≥ 2, 3, and 4 consecutive days) were developed using the daily maximum heat index, which incorporates both daily maximum temperature and minimum relative humidity in the last gestational week. Cox proportional hazards models were fitted separately for spontaneous PROM, term PROM (TPROM), and preterm PROM (PPROM) with zip codes as the random effect and gestational week as the temporal unit. Effect modification by air pollution (i.e., PM2.5 and NO2), climate adaptation measures (i.e., green space and air conditioning [AC] penetration), sociodemographic factors, and smoking behavior was examined. RESULTS: In total, we included 190,767 subjects with 16,490 (8.6%) spontaneous PROMs. We identified a 9-14% increase in PROM risks associated with less intense heatwaves. Similar patterns as PROM were found for TPROM and PPROM. The heat-related PROM risks were greater among mothers exposed to a higher level of PM2.5 during pregnancy, under 25 years old, with lower education and household income level, and who smoked. Even though climate adaptation factors were not statistically significant effect modifiers, mothers living with lower green space or lower AC penetration were at consistently higher heat-related PROM risks compared to their counterparts. CONCLUSION: Using a rich and high-quality clinical database, we detected harmful heat exposure for spontaneous PROM in preterm and term deliveries. Some subgroups with specific characteristics were more susceptible to heat-related PROM risk.

Major wildfires and their smoke pose a threat to public health and are becoming more frequent in the United States, particularly in California and other populated, fire-prone states. Therefore, it is crucial to understand how California residents view wildfires and engage in risk-reducing behaviors during wildfire events. Currently, there is a knowledge gap concerning this area of inquiry. We disseminated a 40-question cross-sectional survey to explore wildfire perception and knowledge along with related risk-reducing measures and policies among 807 adult residents in the fire-prone region of Orange County, California. Results demonstrated that nearly all (>95%) participants had (or knew someone who had) previously experienced a wildfire. Female gender, knowing a wildfire victim and reporting to have a general interest/passion for environmental issues were the three factors most strongly associated with (1) wildfires (and smoke) being reported as a threat, (2) participants' willingness to evacuate if threatened by a nearby wildfire, and (3) participants' willingness to support a wildfire-related tax increase (p < 0.05). The majority (57.4%) of participants agreed that the occurrence of wildfires is influenced by climate change, with the most commonly reported risk-reducing actions (by 44% of participants) being informational actions (e.g., tracking the news) rather than self-motivated physical safety actions (e.g., using an air purifier) (29%). The results of this study can help to inform decision- and policy-making regarding future wildfire events as well as allow more targeted and effective public health messaging and intervention measures, in turn helping to reduce the risk associated with future wildfire/smoke episodes.

Rationale: Although the contribution of air pollution to lung cancer risk is well characterized, few studies have been conducted in racially, ethnically, and socioeconomically diverse populations. Objectives: To examine the association between traffic-related air pollution and risk of lung cancer in a racially, ethnically, and socioeconomically diverse cohort. Methods: Among 97,288 California participants of the Multiethnic Cohort Study, we used Cox proportional hazards regression to examine associations between time-varying traffic-related air pollutants (gaseous and particulate matter pollutants and regional benzene) and lung cancer risk (n = 2,796 cases; average follow-up = 17 yr), adjusting for demographics, lifetime smoking, occupation, neighborhood socioeconomic status (nSES), and lifestyle factors. Subgroup analyses were conducted for race, ethnicity, nSES, and other factors. Measurements and Main Results: Among all participants, lung cancer risk was positively associated with nitrogen oxide (hazard ratio [HR], 1.15 per 50 ppb; 95% confidence interval [CI], 0.99-1.33), nitrogen dioxide (HR, 1.12 per 20 ppb; 95% CI, 0.95-1.32), fine particulate matter with aerodynamic diameter  0.21), although participants residing in low-SES neighborhoods had increased lung cancer risk associated with nitrogen oxides, and no association was observed among those in high-SES neighborhoods. Conclusions: These findings in a large multiethnic population reflect an association between lung cancer and the mixture of traffic-related air pollution and not a particular individual pollutant. They are consistent with the adverse effects of air pollution that have been described in less racially, ethnically, and socioeconomically diverse populations. Our results also suggest an increased risk of lung cancer among those residing in low-SES neighborhoods.

This paper investigates the historical sources of soil-lead contamination in Santa Ana, California. Even though dangerous levels of soil-lead have been found in a wide variety of communities across the United States, public health institutions lack clarity on the historical origins of these crises. This study uses geo-spatial data collected through archival research to estimate the impact of two potential sources of lead contamination in the past -- lead-paint and leaded gasoline. It examines, through a combination of statistical and historical methods, the association between lead concentrations in contemporary soil samples and patterns in the evolution of the city's physical features, such as the growth of urbanized areas and the historical flow of traffic. We emphasize the value of historical data collected through archival research for understanding the sources of environmental lead, particularly leaded gasoline, which our study found to be the most likely and most prominent contributor to soil-lead in Santa Ana's environment. This research contributes to environmental-justice advocacy efforts to reframe lead poisoning as a systemic environmental issue and outlines the path forward to community-level remediation strategies.

BackgroundWithin the Multiethnic Cohort (MEC), we examined the association between air pollution and mortality among African American, European American, Japanese American, and Latina American women diagnosed with breast cancer.MethodsWe used a land use regression (LUR) model and kriging interpolation to estimate nitrogen oxides (NOx , NO2) and particulate matter (PM2.5, PM10) exposures for 3,089 breast cancer cases in the MEC, who were diagnosed from 1993 through 2013 and resided largely in Los Angeles County, California. Cox proportional hazards models were used to examine the association of time-varying air pollutants with all-cause, breast cancer, cardiovascular disease (CVD), and non-breast cancer/non-CVD mortality, accounting for key covariates.ResultsWe identified 1,125 deaths from all causes (474 breast cancer, 272 CVD, 379 non-breast cancer/non-CVD deaths) among the 3,089 breast cancer cases with 8.1 years of average follow-up. LUR and kriged NOX (per 50 ppb) and NO2 (per 20 ppb), PM2.5 (per 10 µg/m3), and PM10 (per 10 µg/m3) were positively associated with risks of all-cause (Hazard Ratio (HR) range = 1.13-1.25), breast cancer (HR range = 1.19-1.45), and CVD mortality (HR range = 1.37-1.60). Associations were statistically significant for LUR NOX and CVD mortality (HR = 1.60; 95% CI: 1.08-2.37) and kriged NO2 and breast cancer mortality (HR = 1.45; 95% CI 1.02-2.07). Gaseous and PM pollutants were positively associated with breast cancer mortality across racial/ethnic group.ConclusionIn this study, air pollutants have a harmful impact on breast cancer survival. Additional studies should evaluate potential confounding by socioeconomic factors. These data support maintaining clean air laws to improve survival for women with breast cancer.

BackgroundEpidemiological findings are inconsistent regarding the associations between air pollution exposure during pregnancy and gestational diabetes mellitus (GDM). Several limitations exist in previous studies, including potential outcome and exposure misclassification, unassessed confounding, and lack of simultaneous consideration of air pollution mixtures and particulate matter (PM) constituents.ObjectivesTo assess the association between GDM and maternal residential exposure to air pollution, and the joint effect of the mixture of air pollutants and PM constituents.MethodsDetailed clinical data were obtained for 395,927 pregnancies in southern California (2008-2018) from Kaiser Permanente Southern California (KPSC) electronic health records. GDM diagnosis was based on KPSC laboratory tests. Monthly average concentrations of fine particulate matter

Background: Traffic and industrial emissions are associated with increased pediatric asthma morbidity. However, few studies have examined the influence of city industrial zoning on pediatric asthma outcomes among minoritized communities with limited access to air monitoring. Methods: In this cross-sectional analysis of 39,974 school-aged students in Santa Ana, CA, we investigated the effect of proximity to areas zoned for industrial use on pediatric asthma prevalence, physical fitness, school attendance, and standardized test scores. Results: The study population was 80.6% Hispanic, with 88.2% qualifying for free/reduced lunch. Compared to students living more than 1 km away from industrial zones, those living within 0.5 km had greater odds of having asthma (adjusted OR 1.21, 95% CI 1.09 to 1.34, p < 0.001). Among children with asthma, those living between 0.5−1.0 km had greater odds of being overweight or obese (aOR 1.47, 95% CI 1.00, 2.15, p = 0.047). Industrial zone proximity was not significantly associated with worse fitness and academic outcomes for students with asthma. Conclusion: These findings suggest that industrial zone proximity is associated with increased pediatric asthma in a predominantly Latino community in Southern California.

BackgroundMaternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and childhood disorders. High-resolution metabolomics (HRM) has previously been employed to identify metabolic responses to traffic-related air pollution in adults, including pregnant women. Thus far, no studies have examined metabolic effects of air pollution exposure in utero on neonates.MethodsWe retrieved stored neonatal blood spots for 241 children born in California between 1998 and 2007. These children were randomly selected from all California birth rolls to serve as birth-year matched controls for children with retinoblastoma identified from the California cancer registry for a case control study of childhood cancer. We estimated prenatal traffic-related air pollution exposure (particulate matter less than 2.5 μm (PM2.5)) during the third-trimester using the California Line Source Dispersion Model, version 4 (CALINE4) based on residential addresses recorded at birth. We employed untargeted HRM to obtain metabolic profiles, and metabolites associated with air pollution exposure were identified using partial least squares (PLS) regression and linear regressions. Biological effects were characterized using pathway enrichment analyses adjusting for potential confounders including maternal age, race/ethnicity, and education.ResultsIn total we extracted 4038 and 4957 metabolite features from neonatal blood spots in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 reverse phase columns (negative ion mode), respectively. After controlling for confounding factors, partial least square regression (Variable Importance in Projection (VIP) ≥ 2) selected 402 HILIC positive and 182 C18 negative features as statistically significantly associated with increasing third trimester PM2.5 exposure. Using pathway enrichment analysis, we identified metabolites in oxidative stress and inflammation pathways as being altered, primarily involving lipid metabolism.ConclusionThe metabolite features and pathways associated with air pollution exposure in neonates suggest that maternal exposure during late pregnancy contributes to oxidative stress and inflammation in newborn children.

BackgroundPrior studies examining the association between ambient air pollutants and pancreatic cancer have been conducted in racially/ethnically homogeneous samples and have produced mixed results, with some studies supporting evidence of an association with fine particulate matter.MethodsTo further investigate these findings, we estimated exposure levels of particulate matter (PM2.5, PM10) and oxides of nitrogen (NOX, and NO2) using kriging interpolation for 100,527 men and women from the Multiethnic Cohort Study, residing largely in Los Angeles County from 1993 through 2013. We measured the association between these air pollutants and incident pancreatic cancer using Cox proportional hazards models with time-varying pollutant measures, with adjustment for confounding factors.ResultsA total of 821 incident pancreatic cancer and 1,660,488 person-years accumulated over the study period, with an average follow-up time of over 16 years. PM2.5 (per 10 μg/m3) was associated with incident pancreatic cancer (hazard ratio [HR] = 1.61; 95% CI, 1.09, 2.37). This PM2.5 -association was strongest among Latinos (HR = 3.59; 95% CI, 1.60, 8.06) and ever smokers (HR = 1.76; 95% CI, 1.05, 2.94). There was no association for PM10 (HR = 1.12; 95% CI, 0.94, 1.32, per 10 μg/m3), NOx (HR = 1.14; 95% CI, 0.88, 1.48, per 50 ppb), or NO2 (HR = 1.14; 95% CI, 0.85, 1.54, per 20 ppb).ConclusionsOur findings support prior research identifying an association between fine particulate matter, PM2.5, and pancreatic cancer. Although not statistically heterogeneous, this association was most notable among Latinos and smokers. Future studies are needed to replicate these results in an urban setting and in a racially/ethnically diverse population.

To cope with unrepaired DNA lesions, cells are equipped with DNA damage tolerance mechanisms, including translesion synthesis (TLS). While TLS polymerases are well documented in facilitating replication across damaged DNA templates, it remains unknown whether TLS polymerases participate in transcriptional bypass of DNA lesions in cells. Herein, we employed the competitive transcription and adduct bypass assay to examine the efficiencies and fidelities of transcription across N2-alkyl-2-deoxyguanosine (N2-alkyl-dG, alkyl = methyl, ethyl, n-propyl, or n-butyl) lesions in HEK293T cells. We found that N2-alkyl-dG lesions strongly blocked transcription and elicited CC → AA tandem mutations in nascent transcripts, where adenosines were misincorporated opposite the lesions and their adjacent 5 nucleoside. Additionally, genetic ablation of Pol η, but not Pol κ, Pol ι, or Pol ζ, conferred marked diminutions in the transcriptional bypass efficiencies of the N2-alkyl-dG lesions, which is exacerbated by codepletion of Rev1 in Pol η-deficient background. We also observed that the repair of N2-nBu-dG was not pronouncedly affected by genetic depletion of Pol η or Rev1. Hence, our results provided insights into transcriptional perturbations induced by N2-alkyl-dG lesions and expanded the biological functions of TLS DNA polymerases.

BackgroundCompared to commonly-used green space indicators from downward-facing satellite imagery, street view-based green space may capture different types of green space and represent how environments are perceived and experienced by people on the ground, which is important to elucidate the underlying mechanisms linking green space and health.ObjectivesThis study aimed to evaluate machine learning models that can classify the type of vegetation (i.e., tree, low-lying vegetation, grass) from street view images; and to investigate the associations between street green space and socioeconomic (SES) factors, in Los Angeles County, California.MethodsSES variables were obtained from the CalEnviroScreen3.0 dataset. Microsoft Bing Maps images in conjunction with deep learning were used to measure total and types of street view green space, which were compared to normalized difference vegetation index (NDVI) as commonly-used satellite-based green space measure. Generalized linear mixed model was used to examine associations between green space and census tract SES, adjusting for population density and rural/urban status.ResultsThe accuracy of the deep learning model was high with 92.5% mean intersection over union. NDVI were moderately correlated with total street view-based green space and tree, and weakly correlated with low-lying vegetation and grass. Total and three types of green space showed significant negative associations with neighborhood SES. The percentage of total green space decreased by 2.62 [95% confidence interval (CI): -3.02, -2.21, p < 0.001] with each interquartile range increase in CalEnviroScreen3.0 score. Disadvantaged communities contained approximately 5% less average street green space than other communities.ConclusionStreet view imagery coupled with deep learning approach can accurately and efficiently measure eye-level street green space and distinguish vegetation types. In Los Angeles County, disadvantaged communities had substantively less street green space. Governments and urban planners need to consider the type and visibility of street green space from pedestrian's perspective.

BackgroundType 2 diabetes is a leading contributor to the global burden of morbidity and mortality. Ozone (O3) exposure has previously been linked to diabetes.ObjectiveWe studied the impact of O3 exposure on incident diabetes risk in elderly Mexican Americans and investigated whether outdoor physical activity modifies the association.MethodsWe selected 1,090 Mexican American participants from the Sacramento Area Latino Study on Aging conducted from 1998 to 2007. Ambient O3 exposure levels were modeled with a land-use regression built with saturation monitoring data collected at 49 sites across the Sacramento metropolitan area. Using Cox proportional hazard models, we estimated the risk of developing incident diabetes based on average O3 exposure modeled for 5-y prior to incident diabetes diagnosis or last follow-up. Further, we estimated outdoor leisure-time physical activity at baseline and investigated whether higher vs. lower levels modified the association between O3 exposure and diabetes.ResultsIn total, 186 incident diabetes cases were identified during 10-y follow-up. Higher levels of physical activity were negatively associated with incident diabetes [hazard ratio (HR)=0.64 (95% CI: 0.43, 0.95)]. The estimated HRs for incident diabetes was 1.13 (95% CI: 1.00, 1.28) per 10-ppb increment of 5-y average O3 exposure; also, this association was stronger among those physically active outdoors [HR=1.52 (95% CI: 1.21, 1.90)], and close to null for those reporting lower levels of outdoor activity [HR=1.04 (95% CI: 0.90, 1.20), pinteraction=0.01].ConclusionsOur findings suggest that ambient O3 exposure contributes to the development of type 2 diabetes, particularly among those with higher levels of leisure-time outdoor physical activity. Policies and strategies are needed to reduce O3 exposure to guarantee that the health benefits of physical activity are not diminished by higher levels of O3 pollution in susceptible populations such as older Hispanics. https://doi.org/10.1289/EHP8620.

Ultrafine particles (UFP; diameter less than or equal to 100 nm) may reach the brain via systemic circulation or the olfactory tract and have been implicated in the risk of brain tumors. The effects of airport-related UFP on the risk of brain tumors are not known. Here we determined the association between airport-related UFP and risk of incident malignant brain cancer (n = 155) and meningioma (n = 420) diagnosed during 16.4 years of follow-up among 75,936 men and women residing in Los Angeles County from the Multiethnic Cohort study. UFP exposure from aircrafts was estimated for participants who lived within a 53 km × 43 km grid area around the Los Angeles International Airport (LAX) from date of cohort entry (1993-1996) through December 31, 2013. Cox proportional hazards models were used to estimate the effects of time-varying, airport-related UFP exposure on risk of malignant brain cancer and meningioma, adjusting for sex, race/ethnicity, education, and neighborhood socioeconomic status. Malignant brain cancer risk in all subjects combined increased 12% [95% confidence interval (CI), 0.98-1.27] per interquartile range (IQR) of airport-related UFP exposure (∼6,700 particles/cm3) for subjects with any address in the grid area surrounding the LAX airport. In race/ethnicity-stratified analyses, African Americans, the subgroup who had the highest exposure, showed a HR of 1.32 (95% CI, 1.07-1.64) for malignant brain cancer per IQR in UFP exposure. UFP exposure was not related to risk of meningioma overall or by race/ethnicity. These results support the hypothesis that airport-related UFP exposure may be a risk factor for malignant brain cancers. SIGNIFICANCE: Malignant brain cancer risk increases with airport-related UFP exposure, particularly among African Americans, suggesting UFP exposure may be a modifiable risk factor for malignant brain cancer.

Since spring 2020, the human world seems to be exceptionally silent due to mobility reduction caused by the COVID-19 pandemic. To better measure the real-time decline of human mobility and changes in socio-economic activities in a timely manner, we constructed a silent index (SI) based on Google's mobility data. We systematically investigated the relations between SI, new COVID-19 cases, government policy, and the level of economic development. Results showed a drastic impact of the COVID-19 pandemic on increasing SI. The impact of COVID-19 on human mobility varied significantly by country and place. Bi-directional dynamic relationships between SI and the new COVID-19 cases were detected, with a lagging period of one to two weeks. The travel restriction and social policies could immediately affect SI in one week; however, could not effectively sustain in the long run. SI may reflect the disturbing impact of disasters or catastrophic events on the activities related to the global or national economy. Underdeveloped countries are more affected by the COVID-19 pandemic.

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.

Fireworks are often used in celebration, causing short term, extremely high particulate matter air pollution. In recent years, the rapid development and expansion of low-cost air quality sensors by companies such as PurpleAir has enabled an understanding of air pollution at a much higher spatiotemporal resolution compared to traditional monitoring networks. In this study, real-time PM2.5 measurements from 751 PurpleAir sensors operating from June to July in 2019 and 2020 were used to examine the impact of 4th of July fireworks on hourly and daily PM2.5 concentrations at the census tract and county levels in California. American Community Survey (ACS) and CalEnviroScreen 3.0 data were used to identify correlations between PM2.5 measurements and socioeconomic status (SES). A two-step method was implemented to assure the quality of raw PM2.5 sensor data and sensor calibration against co-located reference instruments. The results showed that over 67% and 81% of counties experienced immediate impacts related to fireworks in 2019 and 2020, respectively. Relative to 2019, the peak PM2.5 concentrations on July 4th and 5th 2020 were, on average, over 50% higher in California, likely due to the COVID-19-related increase in the use of household-level fireworks. This increase was most pronounced in southern counties, which tend to have less strict firework-related regulations and a greater use of illegal fireworks. Los Angeles County experienced the highest July 4th daily PM2.5 levels both in 2019 (29.9 µg·m-3) and 2020 (42.6 µg·m-3). Spatial hot spot analyses generally showed these southern counties (e.g., Los Angeles County) to be regional air pollution hotspots, whereas the opposite pattern was seen in the north (e.g., San Francisco). The results also showed PM2.5 peaks that were over two-times higher among communities with lower SES, higher minority group populations, and higher asthma rates. Our findings highlight the important role that policy and enforcement can play in reducing firework-related air pollution and protecting public health, as exemplified by southern California, where policy was more relaxed and air pollution was higher (especially in 2020 when the 4th of July coincided with the COVID-19-lockdown period), and in disadvantaged communities where disparities were greatest.

Although evidences showed an overall reduction in outdoor air pollution levels across the globe due to COVID-19-related lockdown, no comprehensive assessment was available for indoor air quality during the period of stay-at-home orders, despite that the residential indoor environment contributes most to personal exposures. We examined temporal and diurnal variations of indoor PM2.5 based on real-time measurements from 139 indoor-outdoor co-located low-cost PurpleAir sensor sets across California for pre-, during, and post-lockdown periods in 2020 and "business-as-usual" periods in 2019. A two-step method was implemented to systematically control the quality of raw sensor data and calibrate the sensor data against co-located reference instruments. During the lockdown period, 17-24% higher indoor PM2.5 concentrations were observed in comparison to those in the 2019 business-as-usual period. In residential sites, a clear peak in PM2.5 concentrations in the afternoon and elevated evening levels toping at roughly 10 μg·m-3 was observed, which reflects enhanced human activity during lunch and dinner time (i.e., cooking) and possibly more cleaning and indoor movement that increase particle generation and resuspension in homes. The contribution of indoor-generated PM2.5 to total indoor concentrations increased as high as 80% during and post-lockdown periods compared to before lockdown.

Wildfires can be detrimental to urban and rural communities, causing impacts in the form of psychological stress, direct physical injury, and smoke-related morbidity and mortality. This study examined the area burned by wildfires over the entire state of California from the years 2000 to 2020 in order to quantify and identify whether burned area and fire frequency differed across Census tracts according to socioeconomic indicators over time. Wildfire data were obtained from the California Fire and Resource Assessment Program (FRAP) and National Interagency Fire Center (NIFC), while demographic data were obtained from the American Community Survey. Results showed a doubling in the number of Census tracts that experienced major wildfires and a near doubling in the number of people residing in wildfire-impacted Census tracts, mostly due to an over 23,000 acre/year increase in the area burned by wildfires over the last two decades. Census tracts with a higher fire frequency and burned area had lower proportions of minority groups on average. However, when considering Native American populations, a greater proportion resided in highly impacted Census tracts. Such Census tracts also had higher proportions of older residents. In general, high-impact Census tracts tended to have higher proportions of low-income residents and lower proportions of high-income residents, as well as lower median household incomes and home values. These findings are important to policymakers and state agencies as it relates to environmental justice and the allocation of resources before, during, and after wildfires in the state of California.

BackgroundRecently, it has been suggested that environmental exposures from traffic sources including noise may play a role in cognitive impairment in the elderly. The objective of the study was to investigate the association between local traffic-related noise pollution and incident dementia or cognitive impairment without dementia (CIND) during a 10-year follow-up period.Methods1612 Mexican-American participants from the Sacramento Area Latino Study on Aging (SALSA) were followed every 12-15 months via home visits from 1998 to 2007. We used the SoundPLAN software package to estimate noise originating from local traffic with the input of Annual Average Daily Traffic (AADT) data from Metropolitan Planning Organizations (MPO) based on geocoded residential addresses at baseline (1998-1999). We estimated the risks of incident dementia or CIND from 24-hour and nighttime noise exposure using Cox proportional hazard models.ResultsDuring the follow-up, we identified 159 incident dementia or CIND cases in total. Per 11.6 dB (interquartile range width) increase in 24-hour noise, the hazard of developing dementia or CIND increased (hazard ratio = 1.3 [1.0, 1.6]) during follow-up; estimates were slightly lower (hazard ratio = 1.2 [0.97, 1.6]) when adjusting for modeled local air pollution exposure from traffic sources. Overall, the risk of dementia/CIND was elevated when 24-hour and nighttime noise were higher than 75 and 65 dB respectively. See video Abstract: http://links.lww.com/EDE/B728.ConclusionsIn our study, traffic-related noise exposure was associated with increased risk of dementia or CIND in elderly Mexican-Americans. Future studies taking into account other noise sources and occupational noise exposure before retirement are needed.

BackgroundLead (Pb) exposure is a problem that disproportionately impacts low-income communities and communities of color. We applied a community-based participatory research approach to assess the distribution of soil Pb concentrations and related social vulnerabilities across Census tracts in Santa Ana, CA.MethodsSoil Pb samples (n = 1528) were collected by the ¡Plo-NO! Santa Ana! Lead-Free Santa Ana! partnership in 2018 across Santa Ana, CA, at a high spatial resolution and measured using XRF analysis. Pb concentrations were mapped and spatial interpolation was conducted to generate a continuous smoothed map of soil Pb concentrations across the city. American Community Survey data was used to examine Pb across Census tracts based on social and economic factors, and to allow for the development of a Cumulative Risk Index to identify areas at high risk of health impacts.ResultsSoil Pb concentrations varied by landuse type and socioeconomic factors. Census tracts with a median household income below $50,000 had over five times higher soil Pb concentrations than high-income Census tracts. Soil samples collected in tertiles with the highest percent children, residents without health insurance, renter-occupied housing units, and lowest percent college educated residents had 90.0%, 96.1%, 75.2%, and 87.0% higher Pb concentrations on average, respectively, compared to their counterparts. Overall, 52.7% of residential samples had Pb concentrations in excess of the 80 ppm California EPA recommendation, and 11 Census tracts were characterized as high risk according to our Cumulative Risk Index.DiscussionThis study underscores the need for precautionary measures relating to disturbances of the soil, particularly for areas where children play outside, given children's higher absorption of lead. It also informs environmental justice initiatives and identifies vulnerable subpopulations at greater risk of Pb exposure, thus warranting community-driven recommendations for policies and initiatives to remediate soil Pb and protect public health and health equity.

BackgroundThe role of omega-3 fatty acid in multiple sclerosis (MS) susceptibility is unclear.ObjectiveTo determine whether fish/seafood intake or genetic factors that regulate omega-3 fatty acids levels are associated with MS risk.MethodsWe examined the association of fish and shrimp consumption and 13 tag single nucleotide polymorphisms (SNPs) in FADS1, FADS2, and ELOV2 with risk of MS in 1153 individuals from the MS Sunshine Study, a case-control study of incident MS or clinically isolated syndrome (CIS), recruited from Kaiser Permanente Southern California.ResultsConsuming fish/seafood at least once a week or at least once a month with regular fish oil use was associated with 44% reduced odds of MS/CIS (adjusted OR = 0.56; 95% CI = 0.41-0.76; p = 0.0002) compared with consuming fish/seafood less than once a month and no fish oil supplementation. Two FADS2 SNPs (rs174611 and rs174618) were independently associated with a lower risk of MS (adjusted ORs = 0.74, 0.79, p = 0.0056, 0.0090, respectively). Association of FADS2 SNPs with MS risk was confirmed in an independent dataset.ConclusionThese findings suggest that omega-3 fatty acid intake may be an important modifiable risk factor for MS. This is consistent with the other known health benefits of fish consumption and complementary genetic studies supporting a key role for omega-3 regulation.

BACKGROUND: Recent studies have reported inconsistent associations between maternal residential green space and preterm birth (PTB, born

BackgroundRecent studies have reported inconsistent associations between maternal residential green space and preterm birth (PTB, born

Exogenous and endogenous chemicals can react with DNA to produce DNA lesions that may block DNA replication. Not much is known about the roles of polymerase (Pol) ν and Pol θ in translesion synthesis (TLS) in cells. Here we examined the functions of these two polymerases in bypassing major-groove O6-alkyl-2-deoxyguanosine (O6-alkyl-dG) and minor-groove N2-alkyl-dG lesions in human cells, where the alkyl groups are ethyl, n-butyl (nBu), and, for O6-alkyl-dG, pyridyloxobutyl. We found that Pol ν and Pol θ promote TLS across major-groove O6-alkyl-dG lesions. O6-alkyl-dG lesions mainly induced G→A mutations that were modulated by the two TLS polymerases and the structures of the alkyl groups. Simultaneous ablation of Pol ν and Pol θ resulted in diminished mutation frequencies for all three O6-alkyl-dG lesions. Depletion of Pol ν alone reduced mutations only for O6-nBu-dG, and sole loss of Pol θ attenuated the mutation rates for O6-nBu-dG and O6-pyridyloxobutyl-dG. Replication across the two N2-alkyl-dG lesions was error-free, and Pol ν and Pol θ were dispensable for their replicative bypass. Together, our results provide critical knowledge about the involvement of Pol ν and Pol θ in bypassing alkylated guanine lesions in human cells.

Previous studies using different exposure methods to assess air pollution and breast cancer risk among primarily whites have been inconclusive. Air pollutant exposures of particulate matter and oxides of nitrogen were estimated by kriging (NOx , NO2 , PM10 , PM2.5 ), land use regression (LUR, NOx , NO2 ) and California Line Source Dispersion model (CALINE4, NOx , PM2.5 ) for 57,589 females from the Multiethnic Cohort, residing largely in Los Angeles County from recruitment (1993-1996) through 2010. Cox proportional hazards models were used to examine the associations between time-varying air pollution and breast cancer incidence adjusting for confounding factors. Stratified analyses were conducted by race/ethnicity and distance to major roads. Among all women, breast cancer risk was positively but not significantly associated with NOx (per 50 parts per billion [ppb]) and NO2 (per 20 ppb) determined by kriging and LUR and with PM2.5 and PM10 (per 10 μg/m3 ) determined by kriging. However, among women who lived within 500 m of major roads, significantly increased risks were observed with NOx (hazard ratio [HR] = 1.35, 95% confidence interval [95% CI]: 1.02-1.79), NO2 (HR = 1.44, 95% CI: 1.04-1.99), PM10 (HR = 1.29, 95% CI: 1.07-1.55) and PM2.5 (HR = 1.85, 95% CI: 1.15-2.99) determined by kriging and NOx (HR = 1.21, 95% CI:1.01-1.45) and NO2 (HR = 1.26, 95% CI: 1.00-1.59) determined by LUR. No overall associations were observed with exposures assessed by CALINE4. Subgroup analyses suggested stronger associations of NOx and NO2 among African Americans and Japanese Americans. Further studies of multiethnic populations to confirm the effects of air pollution, particularly near-roadway exposures, on the risk of breast cancer is warranted.

BackgroundAmbient air pollution exposure has been associated with dementia. Additionally, epidemiologic evidence supports associations between air pollution and diabetes as well as diabetes and dementia. Thus, an indirect pathway between air pollution and dementia may exist through metabolic dysfunction.ObjectiveTo investigate whether local traffic-related air pollution (TRAP) influences incident dementia and cognitive impairment, non-dementia (CIND) in a cohort of older Mexican Americans. We also assess how much of this estimated effect might be mediated through type 2 diabetes (T2DM).MethodsIn a 10-year, prospective study of Latinos (n = 1,564), we generated TRAP-NOx as a surrogate for pollution from local traffic sources at participants' residences during the year prior to enrollment. We used Cox proportional hazards modeling and mediation analysis to estimate the effects of TRAP-NOx on dementia and/or CIND and indirect pathways operating through T2DM.ResultsHigher TRAP-NOx was associated with incident dementia (HR = 1.55 for the highest versus lower tertiles, 95% CI = 1.04, 2.55). Higher TRAP-NOx was also associated with T2DM (OR = 1.62, 95% CI = 1.27, 2.05); furthermore, T2DM was associated with dementia (HR = 1.94, 95% CI = 1.42, 2.66). Mediation analysis indicated that 20% of the estimated effect of TRAP-NOx on dementia/CIND was mediated through T2DM.ConclusionOur results suggest that exposure to local traffic-related air pollution is associated with incident dementia. We also estimated that 20% of this effect is mediated through T2DM. Thus, ambient air pollution might affect brain health via direct damage as well as through indirect pathways related to diabetes and metabolic dysfunction.

BackgroundPrevious studies suggested that air pollutants may increase the incidence of metabolic syndrome, but the potential impact from traffic sources is not well-understood. This study aimed to investigate associations between traffic-related nitrogen oxides (NOx) or noise pollution and risk of incident metabolic syndrome and its components in an elderly Mexican-American population.MethodsA total of 1,554 Mexican-American participants of the Sacramento Area Latino Study on Aging (SALSA) cohort were followed from 1998 to 2007. We used anthropometric measures and biomarkers to define metabolic syndrome according to the recommendations of the Third Adult Treatment Panel of the National Cholesterol Education Program (NCEP ATP III). Based on participants' residential addresses at baseline, estimates of local traffic-related NOx were generated using the California Line Source Dispersion Model version 4 (CALINE4), and of noise employing the SoundPLAN software package. We used Cox regression models with calendar time as the underlying time scale to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations of air pollution or noise with metabolic syndrome or its components.ResultsEach per unit increase of traffic-related NOx (2.29 parts per billion (ppb)) was associated with a 15% (HR = 1.15, 95% CI: 1.04-1.28) lower level of high-density lipoprotein cholesterol (HDL-cholesterol), and each 11.6 decibels (dB) increase in noise increased the risk of developing metabolic syndrome by 17% (HR = 1.17, 95% CI: 1.01-1.35).ConclusionPolicies aiming to reduce traffic-related air pollution and noise might mitigate the risk of metabolic syndrome and its components in vulnerable populations.

OBJECTIVE. We investigated in Liver Imaging Reporting and Data System category 5 (LR-5) observations whether imaging features, including LI-RADS imaging features, could predict microvascular invasion (MVI) and posthepatectomy recurrence in high-risk adult patients with hepatocellular carcinoma (HCC). MATERIALS AND METHODS. We retrospectively identified 149 high-risk patients who underwent 3-T MRI within 1 month before hepatectomy for HCC; 81 of 149 patients with no HCC recurrence were followed for more than 1 year. Tumors with clear surgical margins were confirmed in each hepatectomy specimen. MVI was evaluated histologically by a histopathologist. Tumor recurrence was determined by clinical and imaging follow-up. Two independent radiologists reviewed the prehepatectomy MR images and assessed LI-RADS v2018 imaging features as well as some non-LI-RADS features in all LR-5 observations in consensus. Alpha-fetoprotein level, tumor number, and imaging features were analyzed as potential predictors for MVI and posthepatectomy recurrence using multivariate logistic regression and Cox proportional hazards models. RESULTS. One hundred forty-nine patients with pathologically confirmed HCC were included; 64 of 149 (43.0%) patients had MVI, whereas 48 of 129 (37.2%) patients had tumor recurrence within 3 years after hepatectomy. Mosaic architecture (odds ratio, 3.420; p < 0.001) and nonsmooth tumor margin (odds ratio, 2.554; p = 0.011) were independent predictors of MVI. Multifocal tumors (hazard ratio, 2.101; p = 0.034), absence of fat in mass (hazard ratio, 2.109; p = 0.015), and nonsmooth tumor margin (hazard ratio, 2.415; p = 0.005) were independent predictors of posthepatectomy recurrence. CONCLUSION. In high-risk patients with LR-5 HCC, mosaic architecture and non-smooth tumor margin independently predicted MVI. Multifocal tumors, absence of fat in mass, and nonsmooth tumor margin independently predicted recurrence.

In vivo genome editing represents a powerful strategy for both understanding basic biology and treating inherited diseases. However, it remains a challenge to develop universal and efficient in vivo genome-editing tools for tissues that comprise diverse cell types in either a dividing or non-dividing state. Here, we describe a versatile in vivo gene knock-in methodology that enables the targeting of a broad range of mutations and cell types through the insertion of a minigene at an intron of the target gene locus using an intracellularly linearized single homology arm donor. As a proof-of-concept, we focused on a mouse model of premature-aging caused by a dominant point mutation, which is difficult to repair using existing in vivo genome-editing tools. Systemic treatment using our new method ameliorated aging-associated phenotypes and extended animal lifespan, thus highlighting the potential of this methodology for a broad range of in vivo genome-editing applications.

BackgroundMaternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and neurodevelopmental disorders. By utilizing high-resolution metabolomics (HRM), we investigated perturbations of the maternal serum metabolome in response to traffic-related air pollution to identify biological mechanisms.MethodsWe retrieved stored mid-pregnancy serum samples from 160 mothers who lived in the Central Valley of California known for high air particulate levels. We estimated prenatal traffic-related air pollution exposure (carbon monoxide, nitric oxides, and particulate matter

Chromatin architecture has been implicated in cell type-specific gene regulatory programs, yet how chromatin remodels during development remains to be fully elucidated. Here, by interrogating chromatin reorganization during human pluripotent stem cell (hPSC) differentiation, we discover a role for the primate-specific endogenous retrotransposon human endogenous retrovirus subfamily H (HERV-H) in creating topologically associating domains (TADs) in hPSCs. Deleting these HERV-H elements eliminates their corresponding TAD boundaries and reduces the transcription of upstream genes, while de novo insertion of HERV-H elements can introduce new TAD boundaries. The ability of HERV-H to create TAD boundaries depends on high transcription, as transcriptional repression of HERV-H elements prevents the formation of boundaries. This ability is not limited to hPSCs, as these actively transcribed HERV-H elements and their corresponding TAD boundaries also appear in pluripotent stem cells from other hominids but not in more distantly related species lacking HERV-H elements. Overall, our results provide direct evidence for retrotransposons in actively shaping cell type- and species-specific chromatin architecture.

Endogenous metabolites and exogenous chemicals can induce covalent modifications on DNA, producing DNA lesions. The N2 of guanine was shown to be a common alkylation site in DNA; however, not much is known about the influence of the size of the alkyl group in N2-alkyldG lesions on cellular DNA replication or how translesion synthesis (TLS) polymerases modulate DNA replication past these lesions in human cells. To answer these questions, we employ a robust shuttle vector method to investigate the impact of four N2-alkyldG lesions (i.e., with the alkyl group being a methyl, ethyl, n-propyl, or n-butyl group) on DNA replication in human cells. We find that replication through the N2-alkyldG lesions was highly efficient and accurate in HEK293T cells or isogenic CRISPR-engineered cells with deficiency in polymerase (Pol) ζ or Pol η. Genetic ablation of Pol ι, Pol κ, or Rev1, however, results in decreased bypass efficiencies and elicits substantial frequencies of G → A transition and G → T transversion mutations for these lesions. Moreover, further depletion of Pol ζ in Pol κ- or Pol ι-deficient cells gives rise to elevated rates of G → A and G → T mutations and substantially decreased bypass efficiencies. Cumulatively, we demonstrate that the error-free replication past the N2-alkyldG lesions is facilitated by a specific subset of TLS polymerases, and we find that longer alkyl chains in these lesions induce diminished bypass efficiency and fidelity in DNA replication.

BackgroundZika virus (ZIKV) is an emerging mosquito-borne arbovirus that can produce serious public health consequences. In 2016, ZIKV caused an epidemic in many countries around the world, including the United States. ZIKV surveillance and vector control is essential to combating future epidemics. However, challenges relating to the timely publication of case reports significantly limit the effectiveness of current surveillance methods. In many countries with poor infrastructure, established systems for case reporting often do not exist. Previous studies investigating the H1N1 pandemic, general influenza and the recent Ebola outbreak have demonstrated that time- and geo-tagged Twitter data, which is immediately available, can be utilized to overcome these limitations.MethodsIn this study, we employed a recently developed system called Cloudberry to filter a random sample of Twitter data to investigate the feasibility of using such data for ZIKV epidemic tracking on a national and state (Florida) level. Two auto-regressive models were calibrated using weekly ZIKV case counts and zika tweets in order to estimate weekly ZIKV cases 1 week in advance.ResultsWhile models tended to over-predict at low case counts and under-predict at extreme high counts, a comparison of predicted versus observed weekly ZIKV case counts following model calibration demonstrated overall reasonable predictive accuracy, with an R2 of 0.74 for the Florida model and 0.70 for the U.S.ModelTime-series analysis of predicted and observed ZIKV cases following internal cross-validation exhibited very similar patterns, demonstrating reasonable model performance. Spatially, the distribution of cumulative ZIKV case counts (local- & travel-related) and zika tweets across all 50 U.S. states showed a high correlation (r = 0.73) after adjusting for population.ConclusionsThis study demonstrates the value of utilizing Twitter data for the purposes of disease surveillance. This is of high value to epidemiologist and public health officials charged with protecting the public during future outbreaks.

BackgroundIncreasingly ensemble learning-based spatiotemporal models are being used to estimate residential air pollution exposures in epidemiological studies. While these machine learning models typically have improved performance, they suffer from exposure measurement error that is inherent in all models. Our objective is to develop a framework to formally assess shared, multiplicative measurement error (SMME) in our previously published three-stage, ensemble learning-based nitrogen oxides (NOx) model to identify its spatial and temporal patterns and predictors.MethodsBy treating the ensembles as an external dosimetry system, we quantified shared and unshared, multiplicative and additive (SUMA) measurement error components in our exposure model. We used generalized additive models (GAMs) with a smooth term for location to identify geographic locations with significantly elevated SMME and explain their spatial and temporal determinants.ResultsWe found evidence of significant shared and unshared multiplicative error (p

Although lead has been removed from paint and gasoline sold in the U.S., lead exposures persist, with communities of color and residents in urban and low-income areas at greatest risk for exposure. The persistence of and inequities in lead exposures raise questions about the scope and implementation of policies that address lead as a public health concern. To understand the multi-level nature of lead policies, this paper and case study reviews lead policies at the national level, for the state of California, and for Santa Ana, CA, a dense urban city in Southern California. Through a community-academic partnership process, this analysis examines lead exposure pathways represented, the level of intervention (e.g., prevention, remediation), and whether policies address health inequities. Results indicate that most national and state policies focus on establishing hazardous lead exposure levels in settings and consumer products, disclosing lead hazards, and remediating lead paint. Several policies focus on mitigating exposures rather than primary prevention. The persistence of lead exposures indicates the need to identify sustainable solutions to prevent lead exposures in the first place. We close with recommendations to reduce lead exposures across the life course, consider multiple lead exposure pathways, and reduce and eliminate health inequities related to lead.

The establishment of HIV-1 latency gives rise to persistent chronic infection that requires life-long treatment. To reverse latency for viral eradiation, the HIV-1 Tat protein and its associated ELL2-containing Super Elongation Complexes (ELL2-SECs) are essential to activate HIV-1 transcription. Despite efforts to identify effective latency-reversing agents (LRA), avenues for exposing latent HIV-1 remain inadequate, prompting the need to identify novel LRA targets. Here, by conducting a CRISPR interference-based screen to reiteratively enrich loss-of-function genotypes that increase HIV-1 transcription in latently infected CD4+ T cells, we have discovered a key role of the proteasome in maintaining viral latency. Downregulating or inhibiting the proteasome promotes Tat-transactivation in cell line models. Furthermore, the FDA-approved proteasome inhibitors bortezomib and carfilzomib strongly synergize with existing LRAs to reactivate HIV-1 in CD4+ T cells from antiretroviral therapy-suppressed individuals without inducing cell activation or proliferation. Mechanistically, downregulating/inhibiting the proteasome elevates the levels of ELL2 and ELL2-SECs to enable Tat-transactivation, indicating the proteasome-ELL2 axis as a key regulator of HIV-1 latency and promising target for therapeutic intervention.

Iron-related disorders are among the most prevalent diseases worldwide. Systemic iron homeostasis requires hepcidin, a liver-derived hormone that controls iron mobilization through its molecular target ferroportin (FPN), the only known mammalian iron exporter. This pathway is perturbed in diseases that cause iron overload. Additionally, intestinal HIF-2α is essential for the local absorptive response to systemic iron deficiency and iron overload. Our data demonstrate a hetero-tissue crosstalk mechanism, whereby hepatic hepcidin regulated intestinal HIF-2α in iron deficiency, anemia, and iron overload. We show that FPN controlled cell-autonomous iron efflux to stabilize and activate HIF-2α by regulating the activity of iron-dependent intestinal prolyl hydroxylase domain enzymes. Pharmacological blockade of HIF-2α using a clinically relevant and highly specific inhibitor successfully treated iron overload in a mouse model. These findings demonstrate a molecular link between hepatic hepcidin and intestinal HIF-2α that controls physiological iron uptake and drives iron hyperabsorption during iron overload.

The climate-violence relationship has been debated for decades, and yet most of the supportive evidence has come from ecological or cross-sectional analyses with very limited long-term exposure data. We conducted an individual-level, longitudinal study to investigate the association between ambient temperature and externalizing behaviors of urban-dwelling adolescents. Participants (n = 1,287) in the Risk Factors for Antisocial Behavior Study, in California, were examined during 2000-2012 (aged 9-18 years) with repeated assessments of their externalizing behaviors (e.g., aggression, delinquency). Ambient temperature data were obtained from the local meteorological information system. In adjusted multilevel models, aggressive behaviors significantly increased with rising average temperatures (per 1°C increment) in the preceding 1, 2, or 3 years (respectively, β = 0.23, 95% confidence interval (CI): 0.00, 0.46; β = 0.35, 95% CI: 0.06, 0.63; or β = 0.41, 95% CI: 0.08, 0.74), equivalent to 1.5-3.0 years of delay in age-related behavioral maturation. These associations were slightly stronger among girls and families of lower socioeconomic status but greatly diminished in neighborhoods with more green space. No significant associations were found with delinquency. Our study provides the first individual-level epidemiologic evidence supporting the adverse association of long-term ambient temperature and aggression. Similar approaches to studying meteorology and violent crime might further inform scientific debates on climate change and collective violence.

Animal experiments and cross-sectional human studies have linked particulate matter (PM) with increased behavioral problems. We conducted a longitudinal study to examine whether the trajectories of delinquent behavior are affected by PM2.5 (PM with aerodynamic diameter ≤ 2.5 μm) exposures before and during adolescence. We used the parent-reported Child Behavior Checklist at age 9-18 with repeated measures every ~2-3 years (up to 4 behavioral assessments) on 682 children from the Risk Factors for Antisocial Behavior Study conducted in a multi-ethnic cohort of twins born in 1990-1995. Based on prospectively-collected residential addresses and a spatiotemporal model of ambient air concentrations in Southern California, monthly PM2.5 estimates were aggregated to represent long-term (1-, 2-, 3-year average) exposures preceding baseline and cumulative average exposure until the last assessment. Multilevel mixed-effects models were used to examine the association between PM2.5 exposure and individual trajectories of delinquent behavior, adjusting for within-family/within-individual correlations and potential confounders. We also examined whether psychosocial factors modified this association. The results sμggest that PM2.5 exposure at baseline and cumulative exposure during follow-up was significantly associated (p

Multiple sclerosis (MS) incidence and serum 25-hydroxyvitamin D (25OHD) levels vary by race/ethnicity. We examined the consistency of beneficial effects of 25OHD and/or sun exposure for MS risk across multiple racial/ethnic groups. We recruited incident MS cases and controls (blacks 116 cases/131 controls; Hispanics 183/197; whites 247/267) from the membership of Kaiser Permanente Southern California into the MS Sunshine Study to simultaneously examine sun exposure and 25OHD, accounting for genetic ancestry and other factors. Higher lifetime ultraviolet radiation exposure (a rigorous measure of sun exposure) was associated with a lower risk of MS independent of serum 25OHD levels in blacks (adjusted OR = 0.53, 95% CI = 0.31-0.83; p = 0.007) and whites (OR = 0.68, 95% CI = 0.48-0.94; p = 0.020) with a similar magnitude of effect that did not reach statistical significance in Hispanics (OR = 0.66, 95% CI = 0.42-1.04; p = 0.071). Higher serum 25OHD levels were associated with a lower risk of MS only in whites. No association was found in Hispanics or blacks regardless of how 25OHD was modeled. Lifetime sun exposure appears to reduce the risk of MS regardless of race/ethnicity. In contrast, serum 25OHD levels are not associated with MS risk in blacks or Hispanics. Our findings challenge the biological plausibility of vitamin D deficiency as causal for MS and call into question the targeting of specific serum 25OHD levels to achieve health benefits, particularly in blacks and Hispanics.

Blacks have different dominant polymorphisms in the vitamin D-binding protein (DBP) gene that result in higher bioavailable vitamin D than whites. This study tested whether the lack of association between 25-hydroxyvitamin D (25OHD) and multiple sclerosis (MS) risk in blacks and Hispanics is due to differences in these common polymorphisms (rs7041, rs4588). We recruited incident MS cases and controls (blacks 116 cases/131 controls; Hispanics 183/197; whites 247/267) from Kaiser Permanente Southern California. AA is the dominant rs7041 genotype in blacks (70.0%) whereas C is the dominant allele in whites (79.0% AC/CC) and Hispanics (77.1%). Higher 25OHD levels were associated with a lower risk of MS in whites who carried at least one copy of the C allele but not AA carriers. No association was found in Hispanics or blacks regardless of genotype. Higher ultraviolet radiation exposure was associated with a lower risk of MS in blacks (OR = 0.06), Hispanics and whites who carried at least one copy of the C allele but not in others. Racial/ethnic variations in bioavailable vitamin D do not explain the lack of association between 25OHD and MS in blacks and Hispanics. These findings further challenge the biological plausibility of vitamin D deficiency as causal for MS.

BackgroundRacial/ethnic disparities in preterm birth (PTB) are well documented in the epidemiological literature, but little is known about the relative contribution of different social and environmental determinants of such disparities in birth outcome. Furthermore, increased focus has recently turned toward modifiable aspects of the environment, including physical characteristics, such as neighborhood air pollution, to reduce disparities in birth outcomes.ObjectivesTo apply decomposition methods to understand disparities in preterm birth (PTB) prevalence between births of non-Hispanic black individuals and births of non-Hispanic white individuals in California, according to individual demographics, neighborhood socioeconomic environment, and neighborhood air pollution.MethodsWe used all live singleton births in California spanning 2005 to 2010 and estimated PTBs and other adverse birth outcomes for infants borne by non-Hispanic black mothers and white mothers. To compare individual-level, neighborhood-level, and air pollution [Particulate Matter, 2.5 micrometers or less (PM2.5) and nitrogen dioxide (NO2)] predictors, we conducted a nonlinear extension of the Blinder-Oaxaca method to decompose racial/ethnic disparities in PTB.ResultsThe predicted differences in probability of PTB between black and white infants was 0.056 (95% CI: 0.054, 0.058). All included predictors explained 37.8% of the black-white disparity. Overall, individual (17.5% for PTB) and neighborhood-level variables (16.1% for PTB) explained a greater proportion of the black-white difference in birth outcomes than air pollution (5.7% for PTB).ConclusionsOur results suggest that, although the role of individual and neighborhood factors remains prevailing in explaining black-white differences in birth outcomes, the individual contribution of PM2.5 is comparable in magnitude to any single individual- or neighborhood-level factor. https://doi.org/10.1289/EHP490.