Stray Light Modeling of the James Webb Space Telescope (JWST) Integrated Science Instrument Module (ISIM)

This paper describes an integrated stray light model of each Science Instrument (SI) in the Integrated Science Instrument Module (ISIM) of the James Webb Space Telescope (JWST) and the Optical Telescope Element Simulator (OSIM), the light source used to characterize the performance of ISIM in cryogenic-vacuum tests at the Goddard Space Flight Center (GSFC). We present three cases where this stray light model was integral to solving questions that arose during the testing campaign - 1) ghosting and coherent diffraction from hardware surfaces in the Near Infrared Imager and Slitless Spectrograph (NIRISS) GR700XD grism mode, 2) ghost spots in the Near Infrared Camera (NIRCam) GRISM modes, and 3) scattering from knife edges of the NIRCam focal plane array masks

Teaching Group Processes Through Multiple Group Leadership Opportunities in a Masters Level Counselor Education Program

Utilizing an experiential component in group work training is a prominent feature in Counselor Education programs. Although numerous models have been proposed, the vast majority offer limited explanations of incorporating the number of hours of group participation and observation recommended by the Professional Standards for the Training of Group Workers (ASGW, 2000). This article presents an experiential group training model with multiple opportunities for group leadership in a masters level Counselor Education program, and provides a description of common themes experienced by group-leaders-in-training as they progressed through the culminating feature which served as the capstone of this approach

Sickle cell trait and risk of cognitive impairment in African-Americans: The REGARDS cohort

Background: Sickle cell anemia may be associated with cognitive dysfunction, and some complications of sickle cell anemia might affect those with sickle cell trait (SCT), so we hypothesized that SCT is a risk factor for cognitive impairment. Methods: The Reasons for Geographic and Racial Differences in Stroke (REGARDS) study enrolled a national cohort of 30,239 white and black Americans from 2003 to 7, who are followed every 6 months. Baseline and annual global cognitive function testing used the Six-Item Screener (SIS), a validated instrument (scores range 0-6; ≤ 4 indicates cognitive impairment). Participants with baseline cognitive impairment and whites were excluded. Logistic regression was used to calculate the association of SCT with incident cognitive impairment, adjusted for risk factors. Linear mixed models assessed multivariable-adjusted change in test scores on a biennially administered 3-test battery measuring learning, memory, and semantic and phonemic fluency. Findings: Among 7743 participants followed for a median of 7·1 years, 85 of 583 participants with SCT (14·6%) developed incident cognitive impairment compared to 902 of 7160 (12·6%) without SCT. In univariate analysis, the odds ratio (OR) of incident cognitive impairment was 1·18 (95% CI: 0·93, 1·51) for those with SCT vs. those without. Adjustment did not impact the OR. There was no difference in change on 3-test battery scores by SCT status (all p > 0·11). Interpretation: In this prospective cohort study of black Americans, SCT was not associated with incident cognitive impairment or decline in test scores of learning, memory and executive function. Funding: National Institutes of Health, American Society of Hematology

Characterization of a Reverse-Phase Perfluorocarbon Emulsion for the Pulmonary Delivery of Tobramycin

Background: Aerosolized delivery of antibiotics is hindered by poor penetration within distal and plugged airways. Antibacterial perfluorocarbon ventilation (APV) is a proposed solution in which the lungs are partially or totally filled with perfluorocarbon (PFC) containing emulsified antibiotics. The purpose of this study was to evaluate emulsion stability and rheological, antibacterial, and pharmacokinetic characteristics. Methods: This study examined emulsion aqueous droplet diameter and number density over 24?hr and emulsion and neat PFC viscosity and surface tension. Additionally, Pseudomonas aeruginosa biofilm growth was measured after 2-hr exposure to emulsion with variable aqueous volume percentages (0.25, 1, and 2.5%) and aqueous tobramycin concentrations (Ca=0.4, 4, and 40?mg/mL). Lastly, the time course of serum and pulmonary tobramycin concentrations was evaluated following APV and conventional aerosolized delivery of tobramycin in rats. Results: The initial aqueous droplet diameter averaged 1.9±0.2??m with little change over time. Initial aqueous droplet number density averaged 3.5±1.7?109 droplets/mL with a significant (p<0.01) decrease over time. Emulsion and PFC viscosity were not significantly different, averaging 1.22±0.03?10?3 Pa·sec. The surface tensions of PFC and emulsion were 15.0±0.1?10?3 and 14.6±0.6?10?3 N/m, respectively, and the aqueous interfacial tensions were 46.7±0.3?10?3 and 26.9±11.0?10?3 N/m (p<0.01), respectively. Biofilm growth decreased markedly with increasing Ca and, to a lesser extent, aqueous volume percentage. Tobramycin delivered via APV yielded 2.5 and 10 times larger pulmonary concentrations at 1 and 4?hr post delivery, respectively, and significantly (p<0.05) lower serum concentrations compared with aerosolized delivery. Conclusions: The emulsion is bactericidal, retains the rheology necessary for pulmonary delivery, is sufficiently stable for this application, and results in increased pulmonary retention of the antibiotic.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140105/1/jamp.2013.1058.pd

Novel designs for minimizing diffraction effects of large segmented mirror telescopes

Diffraction effects of large segmented mirror gaps and secondary mirror support struts produce diffraction peaks or flares that are a detriment to exoplanet detection. In this paper we present a detailed diffraction analysis of innovative segmented mirror concepts utilizing curved segment gaps and secondary support struts that eliminate these diffraction spikes that can obscure the faint exoplanet image. The resulting diffraction performance will be quantitatively compared to that of both monolithic circular pupils and classical hexagonally segmented mirrors. We will utilize performance-based merit functions consisting of both radial and azimuthal profiles of the resulting telescope point spread function

Diffraction analysis of large segmented mirror concepts for exoplanet exploration

Diffraction effects of large segmented mirror gaps and secondary mirror support struts produce diffraction peaks or flares that are a detriment to exoplanet detection. In this paper we present detailed parametric diffraction analyses of an innovative “Pinwheel Pupil” segmented mirror concept utilizing curved segment gaps and secondary support struts that can potentially eliminate these diffraction flares that can obscure a faint exoplanet image. The resulting numerical diffraction performance predictions are quantitatively compared to that of both ideal monolithic circular pupils and classical annular pupils with straight secondary mirror struts. We utilize performance – based merit functions consisting of both radial and azimuthal profiles of the resulting telescope point spread function

Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: a pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction &gt; 5.0×10−8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD

Identification of Novel and Rare Variants Associated with Handgrip Strength Using Whole Genome Sequence Data from the NHLBI Trans-Omics in Precision Medicine (TOPMed) Program

Handgrip strength is a widely used measure of muscle strength and a predictor of a range of morbidities including cardiovascular diseases and all-cause mortality. Previous genome-wide association studies of handgrip strength have focused on common variants primarily in persons of European descent. We aimed to identify rare and ancestry-specific genetic variants associated with handgrip strength by conducting whole-genome sequence association analyses using 13,552 participants from six studies representing diverse population groups from the Trans-Omics in Precision Medicine (TOPMed) Program. By leveraging multiple handgrip strength measures performed in study participants over time, we increased our effective sample size by 7-12%. Single-variant analyses identified ten handgrip strength loci among African-Americans: four rare variants, five low-frequency variants, and one common variant. One significant and four suggestive genes were identified associated with handgrip strength when aggregating rare and functional variants; all associations were ancestry-specific. We additionally leveraged the different ancestries available in the UK Biobank to further explore the ancestry-specific association signals from the single-variant association analyses. In conclusion, our study identified 11 new loci associated with handgrip strength with rare and/or ancestry-specific genetic variations, highlighting the added value of whole-genome sequencing in diverse samples. Several of the associations identified using single-variant or aggregate analyses lie in genes with a function relevant to the brain or muscle or were reported to be associated with muscle or age-related traits. Further studies in samples with sequence data and diverse ancestries are needed to confirm these findings

Gap-filling eddy covariance methane fluxes : Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting halfhourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).Peer reviewe

Contribution of Common Genetic Variants to Risk of Early-Onset Ischemic Stroke

Background and Objectives Current genome-wide association studies of ischemic stroke have focused primarily on late-onset disease. As a complement to these studies, we sought to identify the contribution of common genetic variants to risk of early-onset ischemic stroke. Methods We performed a meta-analysis of genome-wide association studies of early-onset stroke (EOS), ages 18-59 years, using individual-level data or summary statistics in 16,730 cases and 599,237 nonstroke controls obtained across 48 different studies. We further compared effect sizes at associated loci between EOS and late-onset stroke (LOS) and compared polygenic risk scores (PRS) for venous thromboembolism (VTE) between EOS and LOS. Results We observed genome-wide significant associations of EOS with 2 variants in ABO, a known stroke locus. These variants tag blood subgroups O1 and A1, and the effect sizes of both variants were significantly larger in EOS compared with LOS. The odds ratio (OR) for rs529565, tagging O1, was 0.88 (95% confidence interval [CI]: 0.85-0.91) in EOS vs 0.96 (95% CI: 0.92-1.00) in LOS, and the OR for rs635634, tagging A1, was 1.16 (1.11-1.21) for EOS vs 1.05 (0.99-1.11) in LOS; p-values for interaction = 0.001 and 0.005, respectively. Using PRSs, we observed that greater genetic risk for VTE, another prothrombotic condition, was more strongly associated with EOS compared with LOS (p = 0.008). Discussion The ABO locus, genetically predicted blood group A, and higher genetic propensity for venous thrombosis are more strongly associated with EOS than with LOS, supporting a stronger role of prothrombotic factors in EOS.Peer reviewe