Rapid single-particle chemical imaging of nanoplastics by SRS microscopy.

Plastics are now omnipresent in our daily lives. The existence of microplastics (1 µm to 5 mm in length) and possibly even nanoplastics (<1 µm) has recently raised health concerns. In particular, nanoplastics are believed to be more toxic since their smaller size renders them much more amenable, compared to microplastics, to enter the human body. However, detecting nanoplastics imposes tremendous analytical challenges on both the nano-level sensitivity and the plastic-identifying specificity, leading to a knowledge gap in this mysterious nanoworld surrounding us. To address these challenges, we developed a hyperspectral stimulated Raman scattering (SRS) imaging platform with an automated plastic identification algorithm that allows micro-nano plastic analysis at the single-particle level with high chemical specificity and throughput. We first validated the sensitivity enhancement of the narrow band of SRS to enable high-speed single nanoplastic detection below 100 nm. We then devised a data-driven spectral matching algorithm to address spectral identification challenges imposed by sensitive narrow-band hyperspectral imaging and achieve robust determination of common plastic polymers. With the established technique, we studied the micro-nano plastics from bottled water as a model system. We successfully detected and identified nanoplastics from major plastic types. Micro-nano plastics concentrations were estimated to be about 2.4 ± 1.3 × 105 particles per liter of bottled water, about 90% of which are nanoplastics. This is orders of magnitude more than the microplastic abundance reported previously in bottled water. High-throughput single-particle counting revealed extraordinary particle heterogeneity and nonorthogonality between plastic composition and morphologies; the resulting multidimensional profiling sheds light on the science of nanoplastics.

Multiple imputation of more than one environmental exposure with nondifferential measurement error.

Measurement error is common in environmental epidemiologic studies, but methods for correcting measurement error in regression models with multiple environmental exposures as covariates have not been well investigated. We consider a multiple imputation approach, combining external or internal calibration samples that contain information on both true and error-prone exposures with the main study data of multiple exposures measured with error. We propose a constrained chained equations multiple imputation (CEMI) algorithm that places constraints on the imputation model parameters in the chained equations imputation based on the assumptions of strong nondifferential measurement error. We also extend the constrained CEMI method to accommodate nondetects in the error-prone exposures in the main study data. We estimate the variance of the regression coefficients using the bootstrap with two imputations of each bootstrapped sample. The constrained CEMI method is shown by simulations to outperform existing methods, namely the method that ignores measurement error, classical calibration, and regression prediction, yielding estimated regression coefficients with smaller bias and confidence intervals with coverage close to the nominal level. We apply the proposed method to the Neighborhood Asthma and Allergy Study to investigate the associations between the concentrations of multiple indoor allergens and the fractional exhaled nitric oxide level among asthmatic children in New York City. The constrained CEMI method can be implemented by imposing constraints on the imputation matrix using the mice and bootImpute packages in R.

Interface states and optical coupling functionalities in the super-SSH lattices.

We theoretically address the coupling between trimer lattices and reveal the existence of stable multiple edge and interface states. It is shown the superlattice can provides a tunable number of topologically protected edge and interface states depending on the coupling strength and topological phase of the connecting lattices. Dynamics and transport properties of interface states are also investigated, Due to the interference of linear modes with different propagation constants, stable oscillations resulted from the coupling of interface states in finite trimerized waveguide arrays are observed and can give rise to optical coupling functionalities, including directional coupling, beam splitting and beam oscillator.

Changing adolescent activity patterns and the correlation of self-esteem and externalizing mental health symptoms across time: results from the USA from 1991 through 2020.

BACKGROUND: Common adolescent psychiatric symptoms cluster into two dominant domains: internalizing and externalizing. Both domains are linked to self-esteem, which serves as a protective factor against a wide range of internalizing and externalizing problems. This study examined trends in US adolescents' self-esteem and externalizing symptoms, and their correlation, by sex and patterns of time use. METHODS: Using Monitoring the Future data (N = 338 896 adolescents, grades:8/10/12, years:1991-2020), we generated six patterns of time use using latent profile analysis with 17 behavior items (e.g. sports participation, parties, paid work). Groups were differentiated by high/low engagement in sports and either paid work or high/low peer socialization. Within each group, we mapped annual, sex-stratified means of (and correlation between) self-esteem and externalizing factors. We also examined past-decade rates of change for factor means using linear regression and mapped proportions with top-quartile levels of poor self-esteem, externalizing symptoms, or both. RESULTS: We found consistent increases in poor self-esteem, decreases in externalizing symptoms, and a positive correlation between the two across nearly all activity groups. We also identified a relatively constant proportion of those with high levels of both in every group. Increases in poor self-esteem were most pronounced for female adolescents with low levels of socializing, among whom externalizing symptoms also increased. CONCLUSIONS: Rising trends in poor self-esteem are consistent across time use groups, as is the existence of a group facing poor self-esteem and externalizing symptoms. Effective interventions for adolescents' poor self-esteem/co-occurring symptoms are needed broadly, but especially among female adolescents with low peer socialization.

Using leave-one-out cross validation (LOO) in a multilevel regression and poststratification (MRP) workflow: A cautionary tale.

In recent decades, multilevel regression and poststratification (MRP) has surged in popularity for population inference. However, the validity of the estimates can depend on details of the model, and there is currently little research on validation. We explore how leave-one-out cross validation (LOO) can be used to compare Bayesian models for MRP. We investigate two approximate calculations of LOO: Pareto smoothed importance sampling (PSIS-LOO) and a survey-weighted alternative (WTD-PSIS-LOO). Using two simulation designs, we examine how accurately these two criteria recover the correct ordering of model goodness at predicting population and small-area estimands. Focusing first on variable selection, we find that neither PSIS-LOO nor WTD-PSIS-LOO correctly recovers the models' order for an MRP population estimand, although both criteria correctly identify the best and worst model. When considering small-area estimation, the best model differs for different small areas, highlighting the complexity of MRP validation. When considering different priors, the models' order seems slightly better at smaller-area levels. These findings suggest that, while not terrible, PSIS-LOO-based ranking techniques may not be suitable to evaluate MRP as a method. We suggest this is due to the aggregation stage of MRP, where individual-level prediction errors average out. We validate these results by applying to the real world National Health and Nutrition Examination Survey (NHANES) data in the United States. Altogether, these results show that PSIS-LOO-based model validation tools need to be used with caution and might not convey the full story when validating MRP as a method.

Exploring Chemical Reaction Space with Machine Learning Models: Representation and Feature Perspective.

Chemical reactions serve as foundational building blocks for organic chemistry and drug design. In the era of large AI models, data-driven approaches have emerged to innovate the design of novel reactions, optimize existing ones for higher yields, and discover new pathways for synthesizing chemical structures comprehensively. To effectively address these challenges with machine learning models, it is imperative to derive robust and informative representations or engage in feature engineering using extensive data sets of reactions. This work aims to provide a comprehensive review of established reaction featurization approaches, offering insights into the selection of representations and the design of features for a wide array of tasks. The advantages and limitations of employing SMILES, molecular fingerprints, molecular graphs, and physics-based properties are meticulously elaborated. Solutions to bridge the gap between different representations will also be critically evaluated. Additionally, we introduce a new frontier in chemical reaction pretraining, holding promise as an innovative yet unexplored avenue.

Trajectory analysis of rhinitis in a birth cohort from lower-income New York City neighborhoods.

BACKGROUND: Rhinitis is a prevalent, chronic nasal condition associated with asthma. However, its developmental trajectories remain poorly characterized. OBJECTIVE: We sought to describe the course of rhinitis from infancy to adolescence and the association between identified phenotypes, asthma-related symptoms, and physician-diagnosed asthma. METHODS: We collected rhinitis data from questionnaires repeated across 22 time points among 688 children from infancy to age 11 years and used latent class mixed modeling (LCMM) to identify phenotypes. Once children were between ages 5 and 12, a study physician determined asthma diagnosis. We collected information on the following asthma symptoms: any wheeze, exercise-induced wheeze, nighttime coughing, and emergency department visits. For each, we used LCMM to identify symptom phenotypes. Using logistic regression, we described the association between rhinitis phenotype and asthma diagnosis and each symptom overall and stratified by atopic predisposition and sex. RESULTS: LCMM identified 5 rhinitis trajectory groups: never/infrequent; transient; late onset, infrequent; late onset, frequent; and persistent. LCMM identified 2 trajectories for each symptom, classified as frequent and never/infrequent. Participants with persistent and late onset, frequent phenotypes were more likely to be diagnosed with asthma and to have the frequent phenotype for all symptoms (P < .01). We identified interaction between seroatopy and rhinitis phenotype for physician-diagnosed asthma (P = .04) and exercise-induced wheeze (P = .08). Severe seroatopy was more common among children with late onset, frequent and persistent rhinitis, with nearly 25% of these 2 groups exhibiting sensitivity to 4 or 5 of the 5 allergens tested. CONCLUSIONS: In this prospective, population-based birth cohort, persistent and late onset, frequent rhinitis phenotypes were associated with increased risk of asthma diagnosis and symptoms during adolescence.

Comparison of Influenza-Like Illness (ILI) incidence data from the novel LeCellPHIA participatory surveillance system with COVID-19 case count data, Lesotho, July 2020 - July 2021.

BACKGROUND: While laboratory testing for infectious diseases such as COVID-19 is the surveillance gold standard, it is not always feasible, particularly in settings where resources are scarce. In the small country of Lesotho, located in sub-Saharan Africa, COVID-19 testing has been limited, thus surveillance data available to local authorities are limited. The goal of this study was to compare a participatory influenza-like illness (ILI) surveillance system in Lesotho with COVID-19 case count data, and ultimately to determine whether the participatory surveillance system adequately estimates the case count data. METHODS: A nationally-representative sample was called on their mobile phones weekly to create an estimate of incidence of ILI between July 2020 and July 2021. Case counts from the website Our World in Data (OWID) were used as the gold standard to which our participatory surveillance data were compared. We calculated Spearman's and Pearson's correlation coefficients to compare the weekly incidence of ILI reports to COVID-19 case count data. RESULTS: Over course of the study period, an ILI symptom was reported 1,085 times via participatory surveillance for an average annual cumulative incidence of 45.7 per 100 people (95% Confidence Interval [CI]: 40.7 - 51.4). The cumulative incidence of reports of ILI symptoms was similar among males (46.5, 95% CI: 39.6 - 54.4) and females (45.1, 95% CI: 39.8 - 51.1). There was a slightly higher annual cumulative incidence of ILI among persons living in peri-urban (49.5, 95% CI: 31.7 - 77.3) and urban settings compared to rural areas. The January peak of the participatory surveillance system ILI estimates correlated significantly with the January peak of the COVID-19 case count data (Spearman's correlation coefficient = 0.49; P < 0.001) (Pearson's correlation coefficient = 0.67; P < 0.0001). CONCLUSIONS: The ILI trends captured by the participatory surveillance system in Lesotho mirrored trends of the COVID-19 case count data from Our World in Data. Public health practitioners in geographies that lack the resources to conduct direct surveillance of infectious diseases may be able to use cell phone-based data collection to monitor trends.

Nicotine Vaping and Co-occurring Substance Use Among Adolescents in the United States from 2017-2019.

Background: The use of electronic cigarettes (or "vaping") among adolescents remains a public health concern given exposure to harmful substances, plus potential association with cannabis and alcohol. Understanding vaping as it intersects with combustible cigarette use and other substance use can inform nicotine prevention efforts. Methods: Data were drawn from 51,872 US adolescents (grades 8, 10, 12, years: 2017-2019) from Monitoring the Future. Multinomial logistic regression analyses assessed links of past 30-day nicotine use (none, smoking-only, vaping-only, and any smoking plus vaping) with both past 30-day cannabis use and past two-week binge drinking. Results: Nicotine use patterns were strongly associated with greater likelihood of cannabis use and binge drinking, particularly for the highest levels of each. For instance, those who smoked and vaped nicotine had 36.53 [95% CI:16.16, 82.60] times higher odds of having 10+ past 2-week binge drinking instances compared to non-users of nicotine. Discussion: Given the strong associations between nicotine use and both cannabis use and binge drinking, there is a need for sustained interventions, advertising and promotion restrictions, and national public education efforts to reduce adolescent nicotine vaping, efforts that acknowledge co-occurring use.

Age, Period, and Cohort Effects of Internalizing Symptoms Among US Students and the Influence of Self-Reported Frequency of Attaining 7 or More Hours of Sleep: Results From the Monitoring the Future Survey 1991-2019.

Adolescent internalizing symptoms have increased since 2010, whereas adequate sleep has declined for several decades. It remains unclear how self-reported sleep attainment has affected internalizing-symptoms trends. Using 1991-2019 data from the Monitoring the Future Study (n ~ 390,000), we estimated age-period-cohort effects in adolescent internalizing symptoms (e.g., loneliness, self-esteem, self-derogation, depressive affect) and the association with yearly prevalence of a survey-assessed, self-reported measure of attaining ≥7 hours of sleep most nights. We focused our main analysis on loneliness and used median odds ratios to measure variance in loneliness associated with period differences. We observed limited signals for cohort effects and modeled only period effects. The feeling of loneliness increased by 0.83% per year; adolescents in 2019 had 0.68 (95% CI: 0.49, 0.87) increased log odds of loneliness compared with the mean, which was consistent by race/ethnicity and parental education. Girls experienced steeper increases in loneliness than boys (P < 0.0001). The period-effect median odds ratio for loneliness was 1.16 (variance = 0.09; 95% CI: 0.06, 0.17) before adjustment for self-reported frequency of getting ≥7 hours sleep versus 1.07 (variance = 0.02; 95% CI: 0.01, 0.03) after adjustment. Adolescents across cohorts are experiencing worsening internalizing symptoms. Self-reported frequency of <7 hours sleep partially explains increases in loneliness, indicating the need for feasibility trials to study the effect of increasing sleep attainment on internalizing symptoms.

Rectified Bloch oscillations in dynamically modulated waveguide arrays.

We study the dynamics of excitations in dynamically modulated waveguide arrays with an external spatial linear potential. Longitudinally periodic modulation may cause a significant change in the width of the quasi-energy band and leads to the dynamical band suppression with a linear dispersion relation. This substantially affects the Bloch oscillation dynamics. Novel dynamical phenomena with no analogue in ordinary discrete waveguides, named rectified Bloch oscillations, are highlighted. Due to the interplay between directional coupling between adjacent waveguides and diffraction suppression by the introduced onsite energy difference, at odd times of half Bloch oscillations period, the new submodes are continuously excited along two opposite rectification directions and experience same oscillation evolution, and eventually lead to the formation of a diamondlike intensity network. Both the amplitude and direction of the rectified Bloch oscillations strongly depend on the coupling strength. When coupling strength passes the critical value at which dynamical band suppression with a linear dispersion relation occurs, the direction of Bloch oscillations is inverted.

Temporal trends in alcohol, cannabis, and simultaneous use among 12th-grade U.S. adolescents from 2000 to 2020: Differences by sex, parental education, and race and ethnicity.

BACKGROUND: Simultaneous use of alcohol and cannabis to enhance each other's effect can cause potential harm. Time trends are diverging in adolescent use of alcohol, which is declining, and cannabis, which is increasing among certain subgroups. However, little is known about trends in their simultaneous and non-simultaneous use. Racial and socioeconomic disparities are emerging in cannabis use, which may portend consequences to public health. METHODS: The 2000 to 2020 Monitoring the Future surveys included approximately 38,000 U.S. 12th-grade students with information on simultaneous use and pertinent demographic factors. A 5-level alcohol/cannabis measure included past-year simultaneous use (i.e., alcohol and cannabis use at the same time), non-simultaneous alcohol and cannabis use, alcohol-use-only, cannabis-use-only, and no use. Multinomial logistic regressions estimated associations (adjusted relative risk ratios; aRRR) with time period (2000 to 2004, 2005 to 2009, 2010 to 2014, 2015 to 2020). Models were adjusted and included interactions with sex, race/ethnicity, and parental education. RESULTS: Between 2000 and 2020, simultaneous alcohol/cannabis use among 12th graders decreased from 24.4% to 18.7%. From 2015 to 2020 compared to 2000 to 2004, the odds of simultaneous use (adjusted relative risk ratio (aRRR) vs. no use = 0.57, 95% CI [0.50, 0.66]) and alcohol-use-only (aRRR = 0.55, 95% CI [0.49, 0.61]) decreased, while cannabis-use-only odds increased (aRRR = 2.59, 95% CI [1.87, 3.59]). Notably, the prevalence of cannabis-use-only more than doubled from 2011 to 2019. The odds of simultaneous use, alcohol-use-only, and non-simultaneous use of alcohol and cannabis declined more rapidly among males than females, whereas the odds for cannabis-use-only increased faster for females than males. Increases in cannabis-use-only were faster for non-white adolescents. CONCLUSION: Simultaneous use of alcohol and cannabis is declining among U.S. adolescents, but the decline is slower among females than males. Declines in simultaneous use are largely concomitant with historical declines in alcohol use, indicating that a continued focus on reducing alcohol use among adolescents and young adults has extended benefits to other adolescent substance use. However, cannabis use without any reported past-year alcohol use more than doubled in the last decade, a concerning trend.

Adolescents' Use of Free Time and Associations with Substance Use from 1991 to 2019.

Background: Understanding time trends in risk factors for substance use may contextualize and explain differing time trends in substance use. Methods: We examined data (N = 536,291; grades 8/10/12) from Monitoring the Future, years 1991-2019. Using Latent Profile Analyses, we identified six time use patterns: one for those working at a paid job and the other five defined by levels of socialization (low/high) and engagement in structured activities like sports (engaged/disengaged), with the high social/engaged group split further by levels of unsupervised social activities. We tested associations between time use profiles and past two-week binge drinking as well as past-month alcohol use, cigarette use, cannabis use, other substance use, and vaping. We examined trends and group differences overall and by decade (or for vaping outcomes, year). Results: Prevalence of most substance use outcomes decreased over time among all groups. Cannabis use increased, with the largest increase in the group engaged in paid employment. Vaping substantially increased, with the highest nicotine vaping increase in the high social/engaged group with less supervision and the highest cannabis vaping increase in the highly social but otherwise disengaged group. Substance use was lowest in the low social groups, highest in the high social and employed groups. Conclusions: While alcohol, cigarette, and other substance use have declined for all groups, use remained elevated given high levels of social time, especially with low engagement in structured activities or low supervision, or paid employment. Cannabis use and vaping are increasing across groups, suggesting the need for enhanced public health measures.

Explaining US Adolescent Depressive Symptom Trends Through Declines in Religious Beliefs and Service Attendance.

Over the past decade, US adolescents' depressive symptoms have increased, and changing religious beliefs and service attendance may be contributing factors. We examined the contribution of religious factors to depressive symptoms among 417,540 US adolescents (grades: 8, 10, 12), years:1991-2019, in survey-weighted logistic regressions. Among adolescents who felt religion was personally important, those who never attended services had 2.23 times higher odds of reporting depressive symptoms compared to peers attending weekly. Among adolescents who did not feel that religion was important, the pattern was reversed. Among adolescents, concordance between importance of religion and religious service attendance may lower risk of depressive symptoms. Overall, we estimate that depressive symptom trends would be 28.2% lower if religious factors had remained at 1991 levels.

Alcohol-involved motor vehicle crashes and the size and duration of random breath testing checkpoints.

OBJECTIVE: Sobriety checkpoints have strong empirical and theoretical support as an intervention to reduce alcohol-involved motor vehicle crashes. The purpose of this study was to examine whether checkpoint size (the number of police officers) and checkpoint duration (the amount of time in operation) affect associations between individual checkpoints and subsequent alcohol-related crash incidence. METHOD: Queensland Police Service provided latitude-longitude coordinates and date and time data for all breath tests that occurred in Brisbane, Australia, from January 2012 to June 2018. We applied hierarchical cluster analysis to the latitude-longitude coordinates for breath tests, identifying checkpoints as clusters of ≥25 breath tests conducted by ≥3 breath testing devices over a duration of 3 to 8 hours. Generalized linear autoregressive moving average (GLARMA) models related counts of alcohol-involved motor vehicle crashes to the number of checkpoints conducted per week, as well as 1 week prior and 2 weeks prior. RESULTS: A total of 3420 alcohol-related crashes occurred and 2069 checkpoints were conducted in Brisbane over the 6.5-year (339-week) study period. On average, checkpoints included a mean of 266.0 breath tests (SD = 216.3), 16.4 devices (SD = 13.7), and were 286.3 minutes in duration (SD = 104.2). Each 10 additional checkpoints were associated with a 12% decrease in crash incidence at a lag of 1 week (IRR = 0.88; 95%CI: 0.80, 0.97). We detected no differential associations according to checkpoint size or duration. CONCLUSIONS: Sobriety checkpoints are associated with fewer alcohol-related motor vehicle crashes for around 1 week. Checkpoint size and duration do not appear to affect this relationship.

Not all posttraumatic stress disorder symptoms are equal: fear, dysphoria, and risk of developing hypertension in trauma-exposed women.

BACKGROUND: Posttraumatic stress disorder (PTSD) is associated with higher risk of incident hypertension, but it is unclear whether specific aspects of PTSD are particularly cardiotoxic. PTSD is a heterogeneous disorder, comprising dimensions of fear and dysphoria. Because elevated fear after trauma may promote autonomic nervous system dysregulation, we hypothesized fear would predict hypertension onset, and associations with hypertension would be stronger with fear than dysphoria. METHODS: We examined fear and dysphoria symptom dimensions in relation to incident hypertension over 24 years in 2709 trauma-exposed women in the Nurses' Health Study II. Posttraumatic fear and dysphoria symptom scores were derived from a PTSD diagnostic interview. We used proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for each symptom dimension (quintiles) with new-onset hypertension events (N = 925), using separate models. We also considered lower-order symptom dimensions of fear and dysphoria. RESULTS: Higher levels of fear (P-trend = 0.02), but not dysphoria (P-trend = 0.22), symptoms were significantly associated with increased hypertension risk after adjusting for socio-demographics and family history of hypertension. Women in the highest v. lowest fear quintile had a 26% higher rate of developing hypertension [HR = 1.26 (95% CI 1.02-1.57)]; the increased incidence associated with greater fear was similar when further adjusted for biomedical and health behavior covariates (P-trend = 0.04) and dysphoria symptoms (P-trend = 0.04). Lower-order symptom dimension analyses provided preliminary evidence that the re-experiencing and avoidance components of fear were particularly associated with hypertension. CONCLUSIONS: Fear symptoms associated with PTSD may be a critical driver of elevated cardiovascular risk in trauma-exposed individuals.

Independent Relationship of Changes in Death Rates with Changes in US Presidential Voting.

BACKGROUND: The outcome of the 2016 presidential election is commonly attributed to socioeconomic and ethnic/racial issues, but health issues, including "deaths of despair," may also have contributed. OBJECTIVE: To assess whether changes in age-adjusted death rates were independently associated with changes in presidential election voting in 2016 vs. 2008. DESIGN: We used publicly available data in each of 3112 US counties to correlate changes in a county's presidential voting in 2016 compared with 2008 with recent changes in its age-adjusted death rate, after controlling for population and rural-urban status, median age, race/ethnicity, income, education, unemployment rate, and health insurance rate. DESIGN SETTING: Cross-sectional analysis of county-specific data. SETTING/PARTICIPANTS: All 3112 US counties. MAIN MEASURES: The independent correlation of a county's change in age-adjusted death rate between 2000 and 2015 with its net percentage Republican gain or loss in the presidential election of 2016 vs. 2008. KEY RESULTS: In 2016, President Trump increased the Republican presidential vote percentage in 83.8% of counties compared with Senator McCain in 2008. Counties with an increased Republican vote percentage in 2016 vs. 2008 had a 15% higher 2015 age-adjusted death rate than counties with an increased Democratic vote percentage. Since 2000, overall death rates declined by less than half as much, and death rates from drugs, alcohol, and suicide increased 2.5 times as much in counties with Republican gains compared with counties with Democratic gains. In multivariable analyses, Republican net presidential gain in 2016 vs. 2008 was independently correlated with slower reductions in a county's age-adjusted death rate. Although correlation cannot infer causality, modest reductions in death rates might theoretically have shifted Pennsylvania, Michigan, and Wisconsin to Secretary Clinton. CONCLUSIONS: Less of a reduction in age-adjusted death rates was an independent correlate of an increased Republican percentage vote in 2016 vs. 2008. Death rates may be markers of dissatisfactions and fears that influenced the 2016 Presidential election outcomes.

Posttraumatic stress disorder and incidence of thyroid dysfunction in women.

BACKGROUND: Abnormal thyroid function is prevalent among women and has been linked to increased risk of chronic disease. Posttraumatic stress disorder (PTSD) has been linked to thyroid dysfunction in some studies; however, the results have been inconsistent. Thus, we evaluated trauma exposure and PTSD symptoms in relation to incident thyroid dysfunction in a large longitudinal cohort of civilian women. METHODS: We used data from 45 992 women from the ongoing Nurses' Health Study II, a longitudinal US cohort study that began in 1989. In 2008, history of trauma and PTSD were assessed with the Short Screening Scale for Diagnostic and Statistical Manual of Mental Disorders, fourth edition, PTSD, and incident thyroid dysfunction was determined by participants' self-report in biennial questionnaires of physician-diagnosed hypothyroidism and Graves' hyperthyroidism. The study period was from 1989 to 2013. Proportional hazard models were used to estimate multivariable-adjusted hazard ratios and 95% confidence intervals (CIs) for incident hypothyroidism and Graves' hyperthyroidism. RESULTS: In multivariable-adjusted models, we found significant associations for PTSD only with hypothyroidism [p-trend <0.001; trauma with no PTSD symptoms, 1.08 (95% CI 1.02-1.15); 1-3 PTSD symptoms, 1.12 (95% CI 1.04-1.21); 4-5 PTSD symptoms, 1.23 (95% CI 1.13-1.34); and 6-7 PTSD symptoms, 1.26 (95% CI 1.14-1.40)]. PTSD was not associated with risk of Graves' hyperthyroidism (p-trend = 0.34). Associations were similar in sensitivity analyses restricted to outcomes with onset after 2008, when PTSD was assessed. CONCLUSIONS: PTSD was associated with higher risk of hypothyroidism in a dose-dependent fashion. Highlighted awareness for thyroid dysfunction may be especially important in women with PTSD.

Brain MR Imaging Findings and Associated Outcomes in Carriers of the Reciprocal Copy Number Variation at 16p11.2.

Purpose To identify developmental neuroradiologic findings in a large cohort of carriers who have deletion and duplication at 16p11.2 (one of the most common genetic causes of autism spectrum disorder [ASD]) and assess how these features are associated with behavioral and cognitive outcomes. Materials and Methods Seventy-nine carriers of a deletion at 16p11.2 (referred to as deletion carriers; age range, 1-48 years; mean age, 12.3 years; 42 male patients), 79 carriers of a duplication at 16p11.2 (referred to as duplication carriers; age range, 1-63 years; mean age, 24.8 years; 43 male patients), 64 unaffected family members (referred to as familial noncarriers; age range, 1-46 years; mean age, 11.7 years; 31 male participants), and 109 population control participants (age range, 6-64 years; mean age, 25.5 years; 64 male participants) were enrolled in this cross-sectional study. Participants underwent structural magnetic resonance (MR) imaging and completed cognitive and behavioral tests. MR images were reviewed for development-related abnormalities by neuroradiologists. Differences in frequency were assessed with a Fisher exact test corrected for multiple comparisons. Unsupervised machine learning was used to cluster radiologic features and an association between clusters and cognitive and behavioral scores from IQ testing, and parental measures of development were tested by using analysis of covariance. Volumetric analysis with automated segmentation was used to confirm radiologic interpretation. Results For deletion carriers, the most prominent features were dysmorphic and thicker corpora callosa compared with familial noncarriers and population control participants (16%; P < .001 and P < .001, respectively) and a greater likelihood of cerebellar tonsillar ectopia (30.7%; P < .002 and P < .001, respectively) and Chiari I malformations (9.3%; P < .299 and P < .002, respectively). For duplication carriers, the most salient findings compared with familial noncarriers and population control participants were reciprocally thinner corpora callosa (18.6%; P < .003 and P < .001, respectively), decreased white matter volume (22.9%; P < .001, and P < .001, respectively), and increased ventricular volume (24.3%; P < .001 and P < .001, respectively). By comparing cognitive assessments to imaging findings, the presence of any imaging feature associated with deletion carriers indicated worse daily living, communication, and social skills compared with deletion carriers without any radiologic abnormalities (P < .005, P < .002, and P < .004, respectively). For the duplication carriers, presence of decreased white matter, callosal volume, and/or increased ventricle size was associated with decreased full-scale and verbal IQ scores compared with duplication carriers without these findings (P < .007 and P < .004, respectively). Conclusion In two genetically related cohorts at high risk for ASD, reciprocal neuroanatomic abnormalities were found and determined to be associated with cognitive and behavioral impairments. © RSNA, 2017 Online supplemental material is available for this article.

Posttraumatic stress disorder onset and inflammatory and endothelial function biomarkers in women.

BACKGROUND: Research has linked posttraumatic stress disorder (PTSD) with higher circulating levels of inflammatory and endothelial function (EF) biomarkers, and effects may be bidirectional. We conducted the first investigation of new-onset PTSD and changes in inflammatory and EF biomarkers. METHODS: Data were from women in the Nurses' Health Study II. Biomarkers obtained at two blood draws, 10-16 years apart, included C-reactive protein (CRP), tumor necrosis factor-alpha receptor-II (TNFRII), intercellular adhesion molecule-1 (ICAM-1), and vascular cell adhesion molecule-1 (VCAM-1). PTSD was assessed via interview. Analyses compared biomarker levels in women with PTSD that onset between draws (n = 175) to women with no history of trauma (n = 175) and to women with history of trauma at draw 1 and no PTSD at either draw (n = 175). We examined if PTSD onset was associated with biomarker change over time and if pre-PTSD-onset biomarker levels indicated risk of subsequent PTSD using linear mixed models and linear regression, respectively. Biomarkers were log-transformed. RESULTS: Compared to women without trauma, women in the PTSD onset group had larger increases in VCAM-1 over time (b = 0.003, p = .068). They also had higher TNFRII (b = 0.05, p = .049) and ICAM-1 (b = 0.04, p = .060) levels at draw 1 (prior to trauma and PTSD onset). However, pre-PTSD-onset biomarker levels did not predict onset of more severe PTSD. CONCLUSIONS: PTSD onset (vs. no trauma) was associated with increases in one inflammation-related biomarker. Effects may be small and cumulative; longer follow-up periods with larger samples are needed. We did not observe strong support that pre-PTSD-onset biomarkers predicted risk of subsequent PTSD.