Theory of Work Adjustment and Student-Athletes\u27 Transition out of Collegiate Sport

While there are several person-environment fit vocational theories, Theory of Work Adjustment (TWA; Lofquist & Dawis, 1969) distinguishes itself by emphasizing the role of the work environment, not just the individual characteristics, in order to establish mutual responsiveness through career transitions. One particular population found both in popular media and peer-reviewed research to have potentially troublesome transitions are student-athletes and their transition out of collegiate sport, despite having the ability to plan for it before graduation. Some researchers have used TWA for those preparing for retirement (Harper & Shoffner, 2004; Hesketh et al. 2011), but no research to date has examined the use of TWA\u27s elements with student-athletes retiring from sport. The purpose of the study was to explore the opinions of those who work with collegiate student-athletes and gain a consensus on the importance, applicability, and potential use of core elements of TWA. A three-round modified online Delphi panel was used and included experts (those with at least 10 years) in the fields of academic advising, sport psychology, and counseling psychology. The resulting data explored what is currently being discussed and generated a collective expert opinion on the use of TWA with student-athletes

Hematopoietic Defects in rps29 Mutant Zebrafish Depend Upon p53 Activation

Disruption of ribosomal proteins is associated with hematopoietic phenotypes in cell culture and animal models. Mutations in ribosomal proteins are seen in patients with Diamond Black- fan anemia, a rare congenital disease characterized by red cell aplasia and distinctive cranio- facial anomalies. A zebrafish screen uncovered decreased hematopoietic stem cells in embryos with mutations in ribosomal protein rps29. Here, we determined that rps29L/L embryos also have red blood cell defects and increased apoptosis in the head. As the p53 pathway has been shown to play a role in other ribosomal protein mutants, we studied the genetic relationship of rps29 and p53. Transcriptional profiling revealed that genes upregulated in the rps29 mutant are enriched for genes upregulated by p53 after irradiation. p53 mutation near completely rescues the rps29 morphological and hematopoietic phenotypes, demonstrating that p53 medi- ates the effects of rps29 knockdown. We also identified neuronal gene orthopedia protein a (otpa) as one whose expression correlates with rps29 expression, suggesting that levels of expression of some genes are dependent on rps29 levels. Together, our studies demonstrate a role of p53 in mediating the cellular defects associated with rps29 and establish a role for rps29 and p53 in hematopoietic stem cells and red blood cell development.Stem Cell and Regenerative Biolog

Transportation Energy Pathways LDRD.

This report presents a system dynamics based model of the supply-demand interactions between the USlight-duty vehicle (LDV) fleet, its fuels, and the corresponding primary energy sources through the year2050. An important capability of our model is the ability to conduct parametric analyses. Others have reliedupon scenario-based analysis, where one discrete set of values is assigned to the input variables and used togenerate one possible realization of the future. While these scenarios can be illustrative of dominant trendsand tradeoffs under certain circumstances, changes in input values or assumptions can have a significantimpact on results, especially when output metrics are associated with projections far into the future. Thistype of uncertainty can be addressed by using a parametric study to examine a range of values for the inputvariables, offering a richer source of data to an analyst.The parametric analysis featured here focuses on a trade space exploration, with emphasis on factors thatinfluence the adoption rates of electric vehicles (EVs), the reduction of GHG emissions, and the reduction ofpetroleum consumption within the US LDV fleet. The underlying model emphasizes competition between13 different types of powertrains, including conventional internal combustion engine (ICE) vehicles, flex-fuel vehicles (FFVs), conventional hybrids(HEVs), plug-in hybrids (PHEVs), and battery electric vehicles(BEVs).We find that many factors contribute to the adoption rates of EVs. These include the pace of technologicaldevelopment for the electric powertrain, battery performance, as well as the efficiency improvements inconventional vehicles. Policy initiatives can also have a dramatic impact on the degree of EV adoption. Theconsumer effective payback period, in particular, can significantly increase the market penetration rates ifextended towards the vehicle lifetime.Widespread EV adoption can have noticeable impact on petroleum consumption and greenhouse gas(GHG) emission by the LDV fleet. However, EVs alone cannot drive compliance with the most aggressiveGHG emission reduction targets, even as the current electricity source mix shifts away from coal and towardsnatural gas. Since ICEs will comprise the majority of the LDV fleet for up to forty years, conventional vehicleefficiency improvements have the greatest potential for reductions in LDV GHG emissions over this time.These findings seem robust even if global oil prices rise to two to three times current projections. Thus,investment in improving the internal combustion engine might be the cheapest, lowest risk avenue towardsmeeting ambitious GHG emission and petroleum consumption reduction targets out to 2050.3 AcknowledgmentThe authors would like to thank Dr. Andrew Lutz, Dr. Benjamin Wu, Prof. Joan Ogden and Dr. ChristopherYang for their suggestions over the course of this project. This work was funded by the Laboratory DirectedResearch and Development program at Sandia National Laboratories.

Evaluation of whole- genome sequence data analysis approaches for short- and long- read sequencing of Mycobacterium tuberculosis

Whole-genome sequencing (WGS) of Mycobacterium tuberculosis (MTB) isolates can be used to get an accurate diagnosis, to guide clinical decision making, to control tuberculosis (TB) and for outbreak investigations. We evaluated the performance of long-read (LR) and/or short-read (SR) sequencing for anti-TB drug-resistance prediction using the TBProfiler and Mykrobe tools, the fraction of genome recovery, assembly accuracies and the robustness of two typing approaches based on core-genome SNP (cgSNP) typing and core-genome multi-locus sequence typing (cgMLST). Most of the discrepancies between phenotypic drug-susceptibility testing (DST) and drug-resistance prediction were observed for the first-line drugs rifampicin, isoniazid, pyrazinamide and ethambutol, mainly with LR sequence data. Resistance prediction to second-line drugs made by both TBProfiler and Mykrobe tools with SR- and LR-sequence data were in complete agreement with phenotypic DST except for one isolate. The SR assemblies were more accurate than the LR assemblies, having significantly (P<0.05) fewer indels and mismatches per 100 kbp. However, the hybrid and LR assemblies had slightly higher genome fractions. For LR assemblies, Canu followed by Racon, and Medaka polishing was the most accurate approach. The cgSNP approach, based on either reads or assemblies, was more robust than the cgMLST approach, especially for LR sequence data. In conclusion, anti-TB drug-resistance prediction, particularly with only LR sequence data, remains challenging, especially for first-line drugs. In addition, SR assemblies appear more accurate than LR ones, and reproducible phylogeny can be achieved using cgSNP approaches

Drug discovery for Diamond-Blackfan anemia using reprogrammed hematopoietic progenitors

Diamond-Blackfan anemia (DBA) is a congenital disorder characterized by the failure of erythroid progenitor differentiation, severely curtailing red blood cell production. Because many DBA patients fail to respond to corticosteroid therapy, there is considerable need for therapeutics for this disorder. Identifying therapeutics for DBA requires circumventing the paucity of primary patient blood stem and progenitor cells. To this end, we adopted a reprogramming strategy to generate expandable hematopoietic progenitor cells from induced pluripotent stem cells (iPSCs) from DBA patients. Reprogrammed DBA progenitors recapitulate defects in erythroid differentiation, which were rescued by gene complementation. Unbiased chemical screens identified SMER28, a small-molecule inducer of autophagy, which enhanced erythropoiesis in a range of in vitro and in vivo models of DBA. SMER28 acted through autophagy factor ATG5 to stimulate erythropoiesis and up-regulate expression of globin genes. These findings present an unbiased drug screen for hematological disease using iPSCs and identify autophagy as a therapeutic pathway in DBA.National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (Grant R24-DK092760)National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (Grant R24-DK49216)National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (Grant U54DK110805)National Heart, Lung, and Blood Institute (Grant UO1-HL100001)National Heart, Lung, and Blood Institute (Grant U01HL134812)National Heart, Lung, and Blood Institute (Grant R01HL04880)National Institutes of Health (U.S.) (Grant R24OD017870-01

T cell antigen discovery via trogocytosis

T cell receptor (TCR) ligand discovery is essential for understanding and manipulating immune responses to tumors. We developed a cell-based selection platform for TCR ligand discovery that exploits a membrane transfer phenomenon called trogocytosis. We discovered that T cell membrane proteins are transferred specifically to target cells that present cognate peptide–major histocompatibility complex (MHC) molecules. Co-incubation of T cells expressing an orphan TCR with target cells collectively presenting a library of peptide–MHCs led to specific labeling of cognate target cells, enabling isolation of these target cells and sequencing of the cognate TCR ligand. We validated this method for two clinically employed TCRs and further used the platform to identify the cognate neoepitope for a subject-derived neoantigen-specific TCR. Thus, target cell trogocytosis is a robust tool for TCR ligand discovery that will be useful for studying basic tumor immunology and identifying new targets for immunotherapy

Reverberation Mapping of the Kepler-Field AGN KA1858+4850

KA1858+4850 is a narrow-line Seyfert 1 galaxy at redshift 0.078 and is among the brightest active galaxies monitored by the Kepler mission. We have carried out a reverberation mapping campaign designed to measure the broad-line region size and estimate the mass of the black hole in this galaxy. We obtained 74 epochs of spectroscopic data using the Kast Spectrograph at the Lick 3-m telescope from February to November of 2012, and obtained complementary V-band images from five other ground-based telescopes. We measured the H-beta light curve lag with respect to the V-band continuum light curve using both cross-correlation techniques (CCF) and continuum light curve variability modeling with the JAVELIN method, and found rest-frame lags of lag_CCF = 13.53 (+2.03, -2.32) days and lag_JAVELIN = 13.15 (+1.08, -1.00) days. The H-beta root-mean-square line profile has a width of sigma_line = 770 +/- 49 km/s. Combining these two results and assuming a virial scale factor of f = 5.13, we obtained a virial estimate of M_BH = 8.06 (+1.59, -1.72) x 10^6 M_sun for the mass of the central black hole and an Eddington ratio of L/L_Edd ~ 0.2. We also obtained consistent but slightly shorter emission-line lags with respect to the Kepler light curve. Thanks to the Kepler mission, the light curve of KA1858+4850 has among the highest cadences and signal-to-noise ratios ever measured for an active galactic nucleus; thus, our black hole mass measurement will serve as a reference point for relations between black hole mass and continuum variability characteristics in active galactic nuclei

Characteristics and Predictive Value of Blood Transcriptome Signature in Males with Autism Spectrum Disorders

Autism Spectrum Disorders (ASD) is a spectrum of highly heritable neurodevelopmental disorders in which known mutations contribute to disease risk in 20% of cases. Here, we report the results of the largest blood transcriptome study to date that aims to identify differences in 170 ASD cases and 115 age/sex-matched controls and to evaluate the utility of gene expression profiling as a tool to aid in the diagnosis of ASD. The differentially expressed genes were enriched for the neurotrophin signaling, long-term potentiation/depression, and notch signaling pathways. We developed a 55-gene prediction model, using a cross-validation strategy, on a sample cohort of 66 male ASD cases and 33 age-matched male controls (P1). Subsequently, 104 ASD cases and 82 controls were recruited and used as a validation set (P2). This 55-gene expression signature achieved 68% classification accuracy with the validation cohort (area under the receiver operating characteristic curve (AUC): 0.70 [95% confidence interval [CI]: 0.62–0.77]). Not surprisingly, our prediction model that was built and trained with male samples performed well for males (AUC 0.73, 95% CI 0.65–0.82), but not for female samples (AUC 0.51, 95% CI 0.36–0.67). The 55-gene signature also performed robustly when the prediction model was trained with P2 male samples to classify P1 samples (AUC 0.69, 95% CI 0.58–0.80). Our result suggests that the use of blood expression profiling for ASD detection may be feasible. Further study is required to determine the age at which such a test should be deployed, and what genetic characteristics of ASD can be identified

Persistent anthrax as a major driver of wildlife mortality in a tropical rainforest

Anthrax is a globally important animal disease and zoonosis. Despite this, our current knowledge of anthrax ecology is largely limited to arid ecosystems, where outbreaks are most commonly reported. Here we show that the dynamics of an anthrax-causing agent, Bacillus cereus biovar anthracis, in a tropical rainforest have severe consequences for local wildlife communities. Using data and samples collected over three decades, we show that rainforest anthrax is a persistent and widespread cause of death for a broad range of mammalian hosts. We predict that this pathogen will accelerate the decline and possibly result in the extirpation of local chimpanzee (Pan troglodytes verus) populations. We present the epidemiology of a cryptic pathogen and show that its presence has important implications for conservation