Using synthetic tracers as a proxy for summertime PM2.5 air quality over the Northeastern United States in physical climate models

Fine particulate matter (PM2.5) is a criteria pollutant. Its sensitivity to meteorology implies its distribution will likely change with climate shifts. Limited availability of global climate models with full chemistry complicates efforts to assess rigorously the uncertainties in the PM2.5 response to a warming climate. We evaluate the potential for PM2.5 distributions in a chemistry-climate model under current-day and warmer climate conditions over the Northeastern United States to be represented by a Synthetic Aerosol tracer (SAt). The SAt implemented into the Geophysical Fluid Dynamics Laboratory chemistry-climate model (AM3) follows the protocol of a recent multimodel community effort (HTAP), with CO emissions, 25-day chemical lifetime, and wet deposition rate of sulfate. Over the Northeastern United States, the summer daily time series of SAt correlates strongly with that of PM2.5, with similar cumulative density functions under both present and future climate conditions. With a linear regression model derived from PM2.5 and SAt in the current-day simulation, we reconstruct both the current-day and future PM2.5 daily time series from the simulated SAt. This reconstruction captures the summer mean PM2.5, the incidence of days above the 24-h mean PM2.5 NAAQS, and PM2.5 responses to climate change. This reconstruction also works over other polluted Northern Hemispheric regions and in spring. Our proof-of-concept study demonstrates that simple tracers can be developed to mimic PM2.5, including its response to climate change, as an easy-to-implement and low-cost addition to physical climate models that should help air quality managers to reap the benefits of climate models that have no chemistry

Local and Remote Mean and Extreme Temperature Response to Regional Aerosol Emissions Reductions

The climatic implications of regional aerosol and precursor emissions reductions implemented to protect human health are poorly understood. We investigate the mean and extreme temperature response to regional changes in aerosol emissions using three coupled chemistryclimate models: NOAA GFDL CM3, NCAR CESM1, and NASA GISS-E2. Our approach contrasts a long present-day control simulation from each model (up to 400 years with perpetual year 2000 or 2005 emissions) with 14 individual aerosol emissions perturbation simulations (160240 years each). We perturb emissions of sulfur dioxide (SO2) and/or carbonaceous aerosol within six world regions and assess the statistical significance of mean and extreme temperature responses relative to internal variability determined by the control simulation and across the models. In all models, the global mean surface temperature response (perturbation minus control) to SO2 and/or carbonaceous aerosol is mostly positive (warming) and statistically significant and ranges from +0.17 K (Europe SO2) to -0.06 K (US BC). The warming response to SO2 reductions is strongest in the US and Europe perturbation simulations, both globally and regionally, with Arctic warming up to 1 K due to a removal of European anthropogenic SO2 emissions alone; however, even emissions from regions remote to the Arctic, such as SO2 from India, significantly warm the Arctic by up to 0.5 K. Arctic warming is the most robust response across each model and several aerosol emissions perturbations. The temperature response in the Northern Hemisphere midlatitudes is most sensitive to emissions perturbations within that region. In the tropics, however, the temperature response to emissions perturbations is roughly the same in magnitude as emissions perturbations either within or outside of the tropics. We find that climate sensitivity to regional aerosol perturbations ranges from 0.5 to 1.0 K (W m(exp -2))(exp -1) depending on the region and aerosol composition and is larger than the climate sensitivity to a doubling of CO2 in two of three models. We update previous estimates of regional temperature potential (RTP), a metric for estimating the regional temperature responses to a regional emissions perturbation that can facilitate assessment of climate impacts with integrated assessment models without requiring computationally demanding coupled climate model simulations. These calculations indicate a robust regional response to aerosol forcing within the Northern Hemisphere midlatitudes, regardless of where the aerosol forcing is located longitudinally. We show that regional aerosol perturbations can significantly increase extreme temperatures on the regional scale. Except in the Arctic in the summer, extreme temperature responses largely mirror mean temperature responses to regional aerosol perturbations through a shift of the temperature distributions and are mostly dominated by local rather than remote aerosol forcing

Serial Observations and Mutational Analysis of an Adoptee with Family History of Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is an inherited cardiac disease with an autosomal dominant mode of transmission. Comprehensive genetic screening of several genes frequently found mutated in HCM is recommended for first-degree relatives of HCM patients. Genetic testing provides the means to identify those at risk of developing HCM and to institute measures to prevent sudden cardiac death (SCD). Here, we present an adoptee whose natural mother and maternal relatives were known be afflicted with HCM and SCD. The proband was followed closely from age 6 to 17 years, revealing a natural history of the progression of clinical findings associated with HCM. Genetic testing of the proband and her natural mother, who is affected by HCM, revealed that they were heterozygous for both the R719Q and T1513S variants in the cardiac beta-myosin heavy chain (MYH7) gene. The proband's ominous family history indicates that the combination of the R719Q and T1513S variants in cis may be a “malignant” variant that imparts a poor prognosis in terms of the disease progression and SCD risk

Multiscale Estimation of Cell Kinetics

We introduce a methodology based on the Luria–Delbrück fluctuation model for estimating the cell kinetics of clonally expanding populations. In particular, this approach allows estimation of the net cell proliferation rate, the extinction coefficient and the initial (viable) population size. We present a systematic approach based on spatial partitioning, which captures the local fluctuations of the number and sizes of individual clones. However, partitioning introduces measurement error by inflating the number of clones, which is dependent on time and the degree of cell migration. We perform various in silico experiments to explore the properties of the estimators and we show that there exists a direct relationship between precision and observation time. We also explore the trade-off between the measurement error and the estimation accuracy. By exploring different scales of cellular fluctuations, from the entire population down to those of individual clones, we show that this methodology is useful for inferring important parameters in neoplastic progression

Observational constraints on the chemistry of isoprene nitrates over the eastern United States

The formation of organic nitrates during the oxidation of the biogenic hydrocarbon isoprene can strongly affect boundary layer concentrations of ozone and nitrogen oxides (NOx = NO + NO2). We constrain uncertainties in the chemistry of these isoprene nitrates using chemical transport model simulations in conjunction with observations over the eastern United States from the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) field campaign during summer 2004. The model best captures the observed boundary layer concentrations of organic nitrates and their correlation with ozone using a 4% yield of isoprene nitrate production from the reaction of isoprene hydroxyperoxy radicals with NO, a recycling of 40% NOx when isoprene nitrates react with OH and ozone, and a fast dry deposition rate of isoprene nitrates. Simulated boundary layer concentrations are only weakly sensitive to the rate of photochemical loss of the isoprene nitrates. An 8% yield of isoprene nitrates degrades agreement with the observations somewhat, but concentrations are still within 50% of observations and thus cannot be ruled out by this study. Our results indicate that complete recycling of NOx from the reactions of isoprene nitrates and slow rates of isoprene nitrate deposition are incompatible with the observations. We find that ∼50% of the isoprene nitrate production in the model occurs via reactions of isoprene (or its oxidation products) with the NO3 radical, but note that the isoprene nitrate yield from this pathway is highly uncertain. Using recent estimates of rapid reaction rates with ozone, 20–24% of isoprene nitrates are lost via this pathway, implying that ozonolysis is an important loss process for isoprene nitrates. Isoprene nitrates are shown to have a major impact on the nitrogen oxide (NOx = NO + NO2) budget in the summertime U.S. continental boundary layer, consuming 15–19% of the emitted NOx, of which 4–6% is recycled back to NOx and the remainder is exported as isoprene nitrates (2–3%) or deposited (8–10%). Our constraints on reaction rates, branching ratios, and deposition rates need to be confirmed through further laboratory and field measurements. The model systematically underestimates free tropospheric concentrations of organic nitrates, indicating a need for future investigation of the processes controlling the observed distribution

Community-based interventions to improve and sustain antiretroviral therapy adherence, retention in HIV care and clinical outcomes in low- and middle-income countries for achieving the UNAIDS 90-90-90 targets

Little is known about the effect of community versus health facility-based interventions to improve and sustain antiretroviral therapy (ART) adherence, virologic suppression, and retention in care among HIV-infected individuals in low- and middle-income countries (LMICs). We systematically searched four electronic databases for all available randomized controlled trials (RCTs) and comparative cohort studies in LMICs comparing community versus health facility-based interventions. Relative risks (RRs) for pre-defined adherence, treatment engagement (linkage and retention in care), and relevant clinical outcomes were pooled using random effect models. Eleven cohort studies and eleven RCTs (N = 97,657) were included. Meta-analysis of the included RCTs comparing community- versus health facility-based interventions found comparable outcomes in terms of ART adherence (RR = 1.02, 95 % CI 0.99 to 1.04), virologic suppression (RR = 1.00, 95 % CI 0.98 to 1.03), and all-cause mortality (RR = 0.93, 95 % CI 0.73 to 1.18). The result of pooled analysis from the RCTs (RR = 1.03, 95 % CI 1.01 to 1.06) and cohort studies (RR  = 1.09, 95 % CI 1.03 to 1.15) found that participants assigned to community-based interventions had statistically significantly higher rates of treatment engagement. Two studies found community-based ART delivery model either cost-saving or cost-effective. Community- versus facility-based models of ART delivery resulted in at least comparable outcomes for clinically stable HIV-infected patients on treatment in LMICs and are likely to be cost-effective

Negative symptoms and impaired social functioning predict later psychosis in Latino youth at clinical high risk in the North American prodromal longitudinal studies consortium

AIM: Examining ethnically related variables in evaluating those at risk for psychosis is critical. This study investigated sociodemographic and clinical characteristics of Latino versus non-Latino clinical high-risk (CHR) subjects and healthy control (HC) subjects in the first North American Prodrome Longitudinal Study. METHODS: Fifty-six Latino CHR subjects were compared to 25 Latino HC and 423 non-Latino CHR subjects across clinical and demographic variables. Thirty-nine of the 56 CHR subjects completed at least one subsequent clinical evaluation over the 2.5-year period with 39% developing a psychotic illness. Characteristics of Latino CHR subjects who later converted to psychosis (‘converters’) were compared to those who did not (‘non-converters’). RESULTS: Latino CHR subjects were younger than non-Latino CHR subjects and had less education than Latino HC subjects and non-Latino CHR counterparts. Latino CHR converters had higher scores than Latino non-converters on the Structured Interview for Prodromal Syndromes total negative symptoms that were accounted for by decreased expression of emotion and personal hygiene/social attentiveness subsections. Latino CHR converters scored lower on the global functioning:social scale, indicating worse social functioning than Latino non-converters. CONCLUSION: Based on this sample, Latino CHR subjects may seek treatment earlier and have less education than non-Latino CHR subjects. Deficits in social functioning and impaired personal hygiene/social attentiveness among Latino CHR subjects predicted later psychosis and may represent important areas for future study. Larger sample sizes are needed to more thoroughly investigate the observed ethnic differences and risk factors for psychosis in Latino youth

Functional development in clinical high risk youth: Prediction of schizophrenia versus other psychotic disorders

This study evaluates premorbid social and academic functioning in clinical high-risk individuals as predictors of transition to schizophrenia versus another psychotic disorder. Participants were 54 individuals enrolled in phase one of the North American Prodrome Longitudinal Study who over two and a half years of follow-up met criteria for schizophrenia/schizophreniform disorder (n=28) or another psychotic disorder (n=26). Social and academic functioning in childhood, early adolescence, and late adolescence was assessed at baseline using the Cannon-Spoor Premorbid Adjustment Scale. Social maladjustment in late adolescence predicted significantly higher odds of transition to schizophrenia versus another psychotic disorder independent of childhood and early adolescent adjustment (OR = 4.02) and conveyed unique risk over academic maladjustment (O R= 5.64). Premorbid academic maladjustment was not associated with psychotic disorder diagnosis. Results support diagnostic specificity of premorbid social dysfunction to schizophrenia in clinical high-risk youth and underscore an important role for social maladjustment in the developmental pathology of schizophrenia and its prediction. (C) 2013 Elsevier Ireland Ltd. All rights reserved

An Individualized Risk Calculator for Research in Prodromal Psychosis

About 20–35% of individuals aged 12–30 years who meet criteria for a prodromal risk syndrome convert to psychosis within two years. However, this estimate ignores the fact that clinical high-risk (CHR) cases vary considerably in risk. Here we sought to create a risk calculator that can ascertain the probability of conversion to psychosis in individual patients based on profiles of risk indicators. The high risk category predicted by this calculator can inform research criteria going forward

Relation between cannabis use and subcortical volumes in people at clinical high risk of psychosis

Among people at genetic risk of schizophrenia, those who use cannabis show smaller thalamic and hippocampal volumes. We evaluated this relationship in people at clinical high risk (CHR) of psychosis. The Alcohol and Drug Use Scale was used to identify 132 CHR cannabis users, the majority of whom were non-dependent cannabis users, 387 CHR non-users, and 204 healthy control non-users, and all participants completed magnetic resonance imaging scans. Volumes of the thalamus, hippocampus and amygdala were extracted with FreeSurfer, and compared across groups. Comparing all CHR participants with healthy control participants revealed no significant differences in volumes of any ROI. However, when comparing CHR users to CHR non-users, a significant ROI × Cannabis group effect emerged: CHR users showed significantly smaller amygdala compared to CHR non-users. However, when limiting analysis to CHR subjects who reported using alcohol at a ‘use without impairment’ severity level, the amygdala effect was non-significant; rather, smaller hippocampal volumes were seen in CHR cannabis users compared to non-users. Controlling statistically for effects of alcohol and tobacco use rendered all results non-significant. These results highlight the importance of controlling for residual confounding effects of other substance use when examining the relationship between cannabis use and neural structure