Increased Risk of Gestational Hypertension by Periconceptional Exposure to Ambient Air Pollution and Effect Modification by Prenatal Depression.

BACKGROUND: Air pollution has been associated with gestational hypertension (GH) and preeclampsia, but susceptible windows of exposure and potential vulnerability by comorbidities, such as prenatal depression, remain unclear. METHODS: We ascertained GH and preeclampsia cases in a prospective pregnancy cohort in Los Angeles, CA. Daily levels of ambient particles (with a diameter of ≤10 µm [PM10] or ≤2.5 µm [PM2.5]), nitrogen dioxide, and ozone were averaged for each week from 12 weeks preconception to 20 gestational weeks. We used distributed lag models to identify susceptible exposure windows, adjusting for potential confounders. Analyses were additionally stratified by probable prenatal depression to explore population vulnerability. RESULTS: Among 619 participants, 60 developed preeclampsia and 42 developed GH. We identified a susceptible window for exposure to PM2.5 from 1 week preconception to 11 weeks postconception: higher exposure (5 µg/m3) within this window was associated with an average of 8% (95% CI, 1%-15%) higher risk of GH. Among participants with probable prenatal depression (n=179; 32%), overlapping sensitive windows were observed for all pollutants from 8 weeks before to 10 weeks postconception with increased risk of GH (PM2.5, 16% [95% CI, 3%-31%]; PM10, 39% [95% CI, 13%-72%]; nitrogen dioxide, 65% [95% CI, 17%-134%]; and ozone, 45% [95% CI, 9%-93%]), while the associations were close to null among those without prenatal depression. Air pollutants were not associated with preeclampsia in any analyses. CONCLUSIONS: We identified periconception through early pregnancy as a susceptible window of air pollution exposure with an increased risk of GH. Prenatal depression increases vulnerability to air pollution exposure and GH.

Perceived Stress From Childhood to Adulthood and Cardiometabolic End Points in Young Adulthood: An 18-Year Prospective Study.

BACKGROUND: We investigated how childhood-to-adulthood perceived stress patterns predict adult cardiometabolic risk. METHODS AND RESULTS: This study included 276 participants from the Southern California Children's Health Study (2003-2014), and a follow-up assessment (2018-2021). Perceived stress (Perceived Stress Scale) was initially reported by participants' parents for themselves during early childhood (mean age, 6.3 years), and later self-reported during adolescence (13.3 years) and young adulthood (23.6 years). Participants were grouped into 4 stress patterns: consistently high, decreasing, increasing, and consistently low. Cardiometabolic risk was assessed in young adulthood by carotid artery intima-media thickness, systolic and diastolic blood pressure, obesity, percent body fat, android/gynoid ratio, and glycated hemoglobin. A cardiometabolic risk score was generated by summing the clinically abnormal markers. Multivariable linear and logistic regression models were used to (1) examine the associations between Perceived Stress Scale at 3 time points and adult cardiometabolic risk, and (2) assess the impact of stress pattern on adult cardiometabolic risk. Findings suggested that in adulthood, higher Perceived Stress Scale score was associated with increased overall cardiometabolic risk (ß=0.12 [95% CI, 0.01-0.22]), carotid artery intima-media thickness (ß=0.01 [95% CI, 0.0003-0.02]), systolic blood pressure (ß=1.27 [95% CI, 0.09-2.45]), and diastolic blood pressure (ß=0.94 [95% CI, 0.13-1.75]). Individuals with a consistently high adolescence-to-adulthood stress pattern had greater overall cardiometabolic risk (ß=0.31 [95% CI, 0.02-0.60]), android/gynoid ratio (ß=0.07 [95% CI, 0.02-0.13]), percent body fat (ß=2.59 [95% CI, 0.01-5.17]), and greater odds of obesity (odds ratio, 5.57 [95% CI, 1.62-19.10]) in adulthood, compared with those with a consistently low Perceived Stress Scale score. CONCLUSIONS: Consistently high perceived stress from adolescence to adulthood may contribute to greater cardiometabolic risk in young adulthood.

True-color and super-resolution imaging using an optical axis shiftable liquid crystal lens.

This study explores the utilization of a liquid crystal lens with a shiftable axis for true-color and super-resolution imaging. By maintaining the optical power and shifting the axis of the liquid crystal lens, precise sub-pixel level shifts are applied to the images formed on the sensor, enabling the construction of true-color and super-resolution images. A comparative analysis with the traditional interpolation-based demosaicing method reveals that true-color imaging not only enhances clarity and effective pixel count, but also significantly reduces occurrences of false color, edge aliasing, and color moiré artifacts.

Prenatal exposures to organophosphate ester metabolites and early motor development in the MADRES cohort.

Organophosphate esters (OPEs) are increasingly considered neurotoxicants which may impact gross and fine motor development. We evaluated associations between prenatal OPE exposures and infant motor development. Third trimester urinary concentrations of nine OPE metabolites were measured in 329 mother-infant dyads participating in the Maternal And Developmental Risks from Environmental and Social Stressors (MADRES) cohort. Child gross and fine motor development at 6, 9, 12, and 18-months were assessed with the Ages and Stages Questionnaire-3 (ASQ-3) and operationalized in models using dichotomous instrument-specific cutoffs for typical motor development. Five OPE metabolites with >60% detection were specific-gravity-adjusted, natural log-transformed, and modeled continuously, while four metabolites with <60% detection were modeled dichotomously (detected/not-detected). We fit mixed effects logistic regression between OPE metabolites and fine/gross motor development and assessed sex-specific effects using a statistical interaction term and sex-stratified models. Among children, 31% and 23% had gross and fine motor scores, respectively, below the ASQ-3 at-risk cutoffs at least once across infancy. A doubling in prenatal diphenyl phosphate (DPHP) exposure was associated with 26% increased odds of potential fine motor delays (ORfine = 1.26, 95% CI: 1.02, 1.57, p = 0.04). We also observed significant interactions by infant sex for associations of detected dipropyl phosphate (DPRP) with gross motor development (pinteraction = 0.048) and detected bis(1-chloro-2-propyl) phosphate (BCIPP) with fine motor development (pinteraction = 0.02). Females had greater odds of potential motor delays for both detected DPRP (females vs males ORgross (95% CI) = 1.48 (0.71, 3.09), p = 0.30 vs 0.27 (0.06, 1.29), p = 0.10) and detected BCIPP (females vs males ORfine (95% CI) = 2.72 (1.27, 5.85), p = 0.01 vs 0.76 (0.31, 1.90), p = 0.56). There were no other significant associations between other metabolites and motor development, despite similar patterns. We found evidence of adverse effects of prenatal OPE exposures on infant motor development with greater adverse effects among female infants with some OPE metabolites.

Prenatal exposures to organophosphate ester metabolite mixtures and children's neurobehavioral outcomes in the MADRES pregnancy cohort.

BACKGROUND: Evidence suggests organophosphate esters (OPEs) are neurotoxic; however, the epidemiological literature remains scarce. We investigated whether prenatal exposures to OPEs were associated with child neurobehavior in the MADRES cohort. METHODS: We measured nine OPE metabolites in 204 maternal urine samples (gestational age at collection: 31.4 ± 1.8 weeks). Neurobehavior problems were assessed among 36-month-old children using the Child Behavior Checklist's (CBCL) three composite scales [internalizing, externalizing, and total problems]. We examined associations between tertiles of prenatal OPE metabolites (> 50% detection) and detect/non-detect categories (< 50% detection) and CBCL composite scales using linear regression and generalized additive models. We also examined mixtures for widely detected OPEs (n = 5) using Bayesian kernel machine regression. RESULTS: Maternal participants with detectable versus non-detectable levels of bis(2-methylphenyl) phosphate (BMPP) had children with 42% (95% CI: 4%, 96%) higher externalizing, 45% (-2%, 114%) higher internalizing, and 35% (3%, 78%) higher total problems. Participants in the second versus first tertile of bis(butoxethyl) phosphate (BBOEP) had children with 43% (-1%, 109%) higher externalizing scores. Bis(1-chloro-2-propyl) phosphate (BCIPP) and child sex had a statistically significant interaction in internalizing (p = 0.02) and total problems (p = 0.03) models, with 120% (23%, 295%) and 57% (6%, 134%) higher scores in the third versus first BCIPP tertile among males. Among females, detectable vs non-detectable levels of prenatal BMPP were associated with 69% higher externalizing scores (5%, 170%) while the third versus first tertile of prenatal BBOEP was associated with 45% lower total problems (-68%, -6%). Although the metabolite mixture and each CBCL outcome had null associations, we observed marginal associations between di-n-butyl phosphate and di-isobutyl phosphate (DNBP + DIBP) and higher internalizing scores (0.15; 95% CrI: -0.02, 0.32), holding other metabolites at their median. CONCLUSIONS: Our results generally suggest adverse and sex-specific effects of prenatal exposure to previously understudied OPEs on neurobehavioral outcomes in 36-month children, providing evidence of potential OPE neurotoxicity.

Drug repositioning candidates identified using in-silico quasi-quantum molecular simulation demonstrate reduced COVID-19 mortality in 1.5M patient records.

Background: Drug repositioning is a key component of COVID-19 pandemic response, through identification of existing drugs that can effectively disrupt COVID-19 disease processes, contributing valuable insights into disease pathways. Traditional non in silico drug repositioning approaches take substantial time and cost to discover effect and, crucially, to validate repositioned effects. Methods: Using a novel in-silico quasi-quantum molecular simulation platform that analyzes energies and electron densities of both target proteins and candidate interruption compounds on High Performance Computing (HPC), we identified a list of FDA-approved compounds with potential to interrupt specific SARS-CoV-2 proteins. Subsequently we used 1.5M patient records from the National COVID Cohort Collaborative to create matched cohorts to refine our in-silico hits to those candidates that show statistically significant clinical effect. Results: We identified four drugs, Metformin, Triamcinolone, Amoxicillin and Hydrochlorothiazide, that were associated with reduced mortality by 27%, 26%, 26%, and 23%, respectively, in COVID-19 patients. Conclusions: Together, these findings provide support to our hypothesis that in-silico simulation of active compounds against SARS-CoV-2 proteins followed by statistical analysis of electronic health data results in effective therapeutics identification.