The glyoxal budget and its contribution to organic aerosol for Los Angeles, California, during CalNex 2010

Recent laboratory and field studies have indicated that glyoxal is a potentially large contributor to secondary organic aerosol mass. We present in situ glyoxal measurements acquired with a recently developed, high sensitivity spectroscopic instrument during the CalNex 2010 field campaign in Pasadena, California. We use three methods to quantify the production and loss of glyoxal in Los Angeles and its contribution to organic aerosol. First, we calculate the difference between steady state sources and sinks of glyoxal at the Pasadena site, assuming that the remainder is available for aerosol uptake. Second, we use the Master Chemical Mechanism to construct a two-dimensional model for gas-phase glyoxal chemistry in Los Angeles, assuming that the difference between the modeled and measured glyoxal concentration is available for aerosol uptake. Third, we examine the nighttime loss of glyoxal in the absence of its photochemical sources and sinks. Using these methods we constrain the glyoxal loss to aerosol to be 0-5 × 10-5 s-1 during clear days and (1 ± 0.3) × 10-5 s-1 at night. Between 07:00-15:00 local time, the diurnally averaged secondary organic aerosol mass increases from 3.2 μg m-3 to a maximum of 8.8 μg m -3. The constraints on the glyoxal budget from this analysis indicate that it contributes 0-0.2 μg m-3 or 0-4% of the secondary organic aerosol mass. Copyright 2011 by the American Geophysical Union

Modeling regional aerosol variability over California and its sensitivity to emissions and long-range transport during the 2010 CalNex and CARES campaigns

Abstract. The performance of the Weather Research and Forecasting regional model with chemistry (WRF-Chem) in simulating the spatial and temporal variations in aerosol mass, composition, and size over California is quantified using measurements collected during the California Nexus of Air Quality and Climate Experiment (CalNex) and the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted during May and June of 2010. The extensive meteorological, trace gas, and aerosol measurements collected at surface sites and along aircraft and ship transects during CalNex and CARES were combined with operational monitoring network measurements to create a single dataset that was used to evaluate the one configuration of the model. Simulations were performed that examined the sensitivity of regional variations in aerosol concentrations to anthropogenic emissions and to long-range transport of aerosols into the domain obtained from a global model. The configuration of WRF-Chem used in this study is shown to reproduce the overall synoptic conditions, thermally-driven circulations, and boundary layer structure observed in region that controls the transport and mixing of trace gases and aerosols. However, sub-grid scale variability in the meteorology and emissions as well as uncertainties in the treatment of secondary organic aerosol chemistry likely contribute to errors at a primary surface sampling site located at the edge of the Los Angeles basin. Differences among the sensitivity simulations demonstrate that the aerosol layers over the central valley detected by lidar measurements likely resulted from lofting and recirculation of local anthropogenic emissions along the Sierra Nevada. Reducing the default emissions inventory by 50% led to an overall improvement in many simulated trace gases and black carbon aerosol at most sites and along most aircraft flight paths; however, simulated organic aerosol was closer to observed when there were no adjustments to the primary organic aerosol emissions. The model performance for some aerosol species was not uniform over the region, and we found that sulfate was better simulated over northern California whereas nitrate was better simulated over southern California. While the overall spatial and temporal variability of aerosols and their precursors were simulated reasonably well, we show cases where the local transport of some aerosol plumes were either too slow or too fast, which adversely affects the statistics regarding the differences between observed and simulated quantities. Comparisons with lidar and in-situ measurements indicate that long-range transport of aerosols from the global model was likely too high in the free troposphere even though their concentrations were relatively low. This bias led to an over-prediction in aerosol optical depth by as much as a factor of two that offset the under-predictions of boundary-layer extinction resulting primarily from local emissions. Lowering the boundary conditions of aerosol concentrations by 50% greatly reduced the bias in simulated aerosol optical depth for all regions of California. This study shows that quantifying regional-scale variations in aerosol radiative forcing and determining the relative role of emissions from local and distant sources is challenging during "clean" conditions and that a wide array of measurements are needed to ensure model predictions are correct for the right reasons. In this regard, the combined CalNex and CARES datasets are an ideal testbed that can be used to evaluate aerosol models in great detail and develop improved treatments for aerosol processes

Genetic variation in the HLA region is associated with susceptibility to herpes zoster.

Herpes zoster, commonly referred to as shingles, is caused by the varicella zoster virus (VZV). VZV initially manifests as chicken pox, most commonly in childhood, can remain asymptomatically latent in nerve tissues for many years and often re-emerges as shingles. Although reactivation may be related to immune suppression, aging and female sex, most inter-individual variability in re-emergence risk has not been explained to date. We performed a genome-wide association analyses in 22,981 participants (2280 shingles cases) from the electronic Medical Records and Genomics Network. Using Cox survival and logistic regression, we identified a genomic region in the combined and European ancestry groups that has an age of onset effect reaching genome-wide significance (P>1.0 × 10(-8)). This region tags the non-coding gene HCP5 (HLA Complex P5) in the major histocompatibility complex. This gene is an endogenous retrovirus and likely influences viral activity through regulatory functions. Variants in this genetic region are known to be associated with delay in development of AIDS in people infected by HIV. Our study provides further suggestion that this region may have a critical role in viral suppression and could potentially harbor a clinically actionable variant for the shingles vaccine

Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)

Introduction Our goal was to evaluate if traffic-light driven personalized care for COVID-19 was associated with improved survival in acute hospital settings. Methods Discharge outcomes were evaluated before and after prospective implementation of a real-time dashboard with feedback to ward-based clinicians. Thromboembolic categories were “medium-risk” (D-dimer >1000 ng/mL or CRP >200 mg/L); “high-risk” (D-dimer >3000 ng/mL or CRP >250 mg/L) or “suspected” (D-dimer >5000 ng/mL). Cytokine storm risk was categorized by ferritin. Results 939/1039 COVID-19 positive patients (median age 69 years, 563/939 (60%) male) completed hospital encounters to death or discharge by 21st May 2020. Thromboembolic flag criteria were reached by 568/939 (60.4%), including 238/275 (86.6%) of the patients who died, and 330/664 (49.7%) of the patients who survived to discharge, p < 0.0001. Cytokine storm flag criteria were reached by 212 (22.5%) of admissions, including 80/275 (29.0%) of the patients who died, and 132/664 (19.9%) of the patients who survived, p < 0.0001. The maximum thromboembolic flag discriminated completed encounter mortality (no flag: 37/371 [9.97%] died; medium-risk: 68/239 [28.5%]; high-risk: 105/205 [51.2%]; and suspected thromboembolism: 65/124 [52.4%], p < 0.0001). Flag criteria were reached by 535 consecutive COVID-19 positive patients whose hospital encounter completed before traffic-light introduction: 173/535 (32.3% [95% confidence intervals 28.0, 36.0]) died. For the 200 consecutive admissions after implementation of real-time traffic light flags, 46/200 (23.0% [95% confidence intervals 17.1–28.9]) died, p = 0.013. Adjusted for age and sex, the probability of death was 0.33 (95% confidence intervals 0.30–0.37) before traffic light implementation, 0.22 (0.17–0.27) after implementation, p < 0.001. In subgroup analyses, older patients, males, and patients with hypertension (p ≤ 0.01), and/or diabetes (p = 0.05) derived the greatest benefit from admission under the traffic light system. Conclusion Personalized early interventions were associated with a 33% reduction in early mortality. We suggest benefit predominantly resulted from early triggers to review/enhance anticoagulation management, without exposing lower-risk patients to potential risks of full anticoagulation therapy

Arctic marine secondary organic aerosol contributes significantly to summertime particle size distributions in the Canadian Arctic Archipelago

Summertime Arctic aerosol size distributions are strongly controlled by natural regional emissions. Within this context, we use a chemical transport model with sizeresolved aerosol microphysics (GEOS-Chem-TOMAS) to interpret measurements of aerosol size distributions from the Canadian Arctic Archipelago during the summer of 2016, as part of the "NETwork on Climate and Aerosols: Addressing key uncertainties in Remote Canadian Environments" (NETCARE) project. Our simulations suggest that condensation of secondary organic aerosol (SOA) from precursor vapors emitted in the Arctic and near Arctic marine (ice-free seawater) regions plays a key role in particle growth events that shape the aerosol size distributions observed at Alert (82.5° N, 62.3° W), Eureka (80.1° N, 86.4° W), and along a NETCARE ship track within the Archipelago. We refer to this SOA as Arctic marine SOA (AMSOA) to reflect the Arctic marine-based and likely biogenic sources for the precursors of the condensing organic vapors. AMSOA from a simulated flux (500 μgm-2 day-1, north of 50° N) of precursor vapors (with an assumed yield of unity) reduces the summertime particle size distribution model-observation mean fractional error 2- to 4-fold, relative to a simulation without this AMSOA. Particle growth due to the condensable organic vapor flux contributes strongly (30 %-50 %) to the simulated summertime-mean number of particles with diameters larger than 20 nm in the study region. This growth couples with ternary particle nucleation (sulfuric acid, ammonia, and water vapor) and biogenic sulfate condensation to account for more than 90% of this simulated particle number, which represents a strong biogenic influence. The simulated fit to summertime size-distribution observations is further improved at Eureka and for the ship track by scaling up the nucleation rate by a factor of 100 to account for other particle precursors such as gas-phase iodine and/or amines and/or fragmenting primary particles that could be missing from our simulations. Additionally, the fits to the observed size distributions and total aerosol number concentrations for particles larger than 4 nm improve with the assumption that the AMSOA contains semivolatile species: the model-observation mean fractional error is reduced 2- to 3-fold for the Alert and ship track size distributions. AMSOA accounts for about half of the simulated particle surface area and volume distributions in the summertime Canadian Arctic Archipelago, with climaterelevant simulated summertime pan-Arctic-mean top-of-theatmosphere aerosol direct (-0:04Wm-2) and cloud-albedo indirect (-0:4Wm-2) radiative effects, which due to uncertainties are viewed as an order of magnitude estimate. Future work should focus on further understanding summertime Arctic sources of AMSOA

Characterization of complex networks: A survey of measurements

Each complex network (or class of networks) presents specific topological features which characterize its connectivity and highly influence the dynamics of processes executed on the network. The analysis, discrimination, and synthesis of complex networks therefore rely on the use of measurements capable of expressing the most relevant topological features. This article presents a survey of such measurements. It includes general considerations about complex network characterization, a brief review of the principal models, and the presentation of the main existing measurements. Important related issues covered in this work comprise the representation of the evolution of complex networks in terms of trajectories in several measurement spaces, the analysis of the correlations between some of the most traditional measurements, perturbation analysis, as well as the use of multivariate statistics for feature selection and network classification. Depending on the network and the analysis task one has in mind, a specific set of features may be chosen. It is hoped that the present survey will help the proper application and interpretation of measurements.Comment: A working manuscript with 78 pages, 32 figures. Suggestions of measurements for inclusion are welcomed by the author

Effects of the number of markers per haplotype and clustering of haplotypes on the accuracy of QTL mapping and prediction of genomic breeding values

The aim of this paper was to compare the effect of haplotype definition on the precision of QTL-mapping and on the accuracy of predicted genomic breeding values. In a multiple QTL model using identity-by-descent (IBD) probabilities between haplotypes, various haplotype definitions were tested i.e. including 2, 6, 12 or 20 marker alleles and clustering base haplotypes related with an IBD probability of > 0.55, 0.75 or 0.95. Simulated data contained 1100 animals with known genotypes and phenotypes and 1000 animals with known genotypes and unknown phenotypes. Genomes comprising 3 Morgan were simulated and contained 74 polymorphic QTL and 383 polymorphic SNP markers with an average r2 value of 0.14 between adjacent markers. The total number of haplotypes decreased up to 50% when the window size was increased from two to 20 markers and decreased by at least 50% when haplotypes related with an IBD probability of > 0.55 instead of > 0.95 were clustered. An intermediate window size led to more precise QTL mapping. Window size and clustering had a limited effect on the accuracy of predicted total breeding values, ranging from 0.79 to 0.81. Our conclusion is that different optimal window sizes should be used in QTL-mapping versus genome-wide breeding value prediction

Religion's Role in Promoting Health and Reducing Risk Among American Youth

Although past research has long documented religion's salutary impact on adult health-related behaviors and outcomes, relatively little research has examined the relationship between religion and adolescent health. This study uses large, nationally representative samples of high school seniors to examine the relationship between religion and behavioral predictors of adolescent morbidity and mortality. Relative to their peers, religious youth are less likely to engage in behaviors that compromise their health (e.g., carrying weapons, getting into fights, drinking and driving) and are more likely to behave in ways that enhance their health (e.g., proper nutrition, exercise, and rest). Multivariate analyses suggest that these relationships persist even after controlling for demographic factors, and trend analyses reveal that they have existed over time. Particularly important is the finding that religious seniors have been relatively unaffected by past and recent increases in marijuana use.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66995/2/10.1177_109019819802500604.pd

Feedback as intervention for team learning in virtual teams: the role of team cohesion and personality

Scholars and practitioners agree that virtual teams (VTs) have become commonplace in today's digital workplace. Relevant literature argues that learning constitutes a significant contributor to team member satisfaction and performance, and that, at least in face-to-face teams, team cohesion fosters team learning. Given the additional challenges VTs face, e.g. geographical dispersion, which are likely have a negative influence on cohesion, in this paper we shed light on the relationship between team cohesion and team learning. We adopted a quantitative approach and studied 54 VTs in our quest to understand the role of feedback in mediating this relationship and, more specifically, the role of personality traits in moderating the indirect effect of team feedback and guided reflection intervention on TL through team cohesion within the VT context. Our findings highlight the importance of considering aspects related to the team composition when devising intervention strategies for VTs, and provide empirical support for an interactionist model between personality and emergent states such as cohesion. Implications for theory and practice are also discussed

Sensitivity of methods for estimating breeding values using genetic markers to the number of QTL and distribution of QTL variance

The objective of this simulation study was to compare the effect of the number of QTL and distribution of QTL variance on the accuracy of breeding values estimated with genomewide markers (MEBV). Three distinct methods were used to calculate MEBV: a Bayesian Method (BM), Least Angle Regression (LARS) and Partial Least Square Regression (PLSR). The accuracy of MEBV calculated with BM and LARS decreased when the number of simulated QTL increased. The accuracy decreased more when QTL had different variance values than when all QTL had an equal variance. The accuracy of MEBV calculated with PLSR was affected neither by the number of QTL nor by the distribution of QTL variance. Additional simulations and analyses showed that these conclusions were not affected by the number of individuals in the training population, by the number of markers and by the heritability of the trait. Results of this study show that the effect of the number of QTL and distribution of QTL variance on the accuracy of MEBV depends on the method that is used to calculate MEBV