The Impact Grit and Achievement Goal Orientation have on Athletic Training Students\u27 Persistence

Purpose: Athletic training education continues to evolve thereby increasing the importance of student retention. Understanding student motivation through achievement goal orientation and grit scores may help support student’s persistence in an athletic training program. The purpose was to determine if a relationship exists between achievement goal orientation and grit to help provide educators a better understanding of their students’ reasons for persisting to help improve retention. Methods: An achievement goal orientation survey and grit scale were administered, and quantitative data was analyzed statistically from Commission on Accreditation of Athletic Training Education- accredited programs in good standing for the 2018-2019 academic year. Results: A total of 520 professional athletic training students participated. There was a significant main effect (F(1,3)=690.0, pConclusions: Athletic training students have similar grit scores across all cohorts and classify higher with mastery goal orientation compared to performance-approach, performance-avoidant, and work-avoidant orientations. Educators should understand students’ motivation to provide support and challenging tasks for their passion and perseverance for athletic training. Key Words: grit, mastery, performance-approach, performance-avoidant, work-avoidant

Photo-physics and electronic structure of lateral graphene/MoS2 and metal/MoS2 junctions

Integration of semiconducting transition metal dichalcogenides (TMDs) into functional optoelectronic circuitries requires an understanding of the charge transfer across the interface between the TMD and the contacting material. Here, we use spatially resolved photocurrent microscopy to demonstrate electronic uniformity at the epitaxial graphene/molybdenum disulfide (EG/MoS2) interface. A 10x larger photocurrent is extracted at the EG/MoS2 interface when compared to metal (Ti/Au) /MoS2 interface. This is supported by semi-local density-functional theory (DFT), which predicts the Schottky barrier at the EG/MoS2 interface to be ~2x lower than Ti/MoS2. We provide a direct visualization of a 2D material Schottky barrier through combination of angle resolved photoemission spectroscopy with spatial resolution selected to be ~300 nm (nano-ARPES) and DFT calculations. A bending of ~500 meV over a length scale of ~2-3 micrometer in the valence band maximum of MoS2 is observed via nano-ARPES. We explicate a correlation between experimental demonstration and theoretical predictions of barriers at graphene/TMD interfaces. Spatially resolved photocurrent mapping allows for directly visualizing the uniformity of built-in electric fields at heterostructure interfaces, providing a guide for microscopic engineering of charge transport across heterointerfaces. This simple probe-based technique also speaks directly to the 2D synthesis community to elucidate electronic uniformity at domain boundaries alongside morphological uniformity over large areas

Decadal changes in fire frequencies shift tree communities and functional traits

Global change has resulted in chronic shifts in fire regimes. Variability in the sensitivity of tree communities to multi-decadal changes in fire regimes is critical to anticipating shifts in ecosystem structure and function, yet remains poorly understood. Here, we address the overall effects of fire on tree communities and the factors controlling their sensitivity in 29 sites that experienced multi-decadal alterations in fire frequencies in savanna and forest ecosystems across tropical and temperate regions. Fire had a strong overall effect on tree communities, with an average fire frequency (one fire every three years) reducing stem density by 48% and basal area by 53% after 50 years, relative to unburned plots. The largest changes occurred in savanna ecosystems and in sites with strong wet seasons or strong dry seasons, pointing to fire characteristics and species composition as important. Analyses of functional traits highlighted the impact of fire-driven changes in soil nutrients because frequent burning favoured trees with low biomass nitrogen and phosphorus content, and with more efficient nitrogen acquisition through ectomycorrhizal symbioses. Taken together, the response of trees to altered fire frequencies depends both on climatic and vegetation determinants of fire behaviour and tree growth, and the coupling between fire-driven nutrient losses and plant traits

Spectrum of PEX1 and PEX6 variants in Heimler syndrome

Heimler syndrome (HS) consists of recessively inherited sensorineural hearing loss, amelogenesis imperfecta (AI) and nail abnormalities, with or without visual defects. Recently HS was shown to result from hypomorphic mutations in PEX1 or PEX6, both previously implicated in Zellweger Syndrome Spectrum Disorders (ZSSD). ZSSD are a group of conditions consisting of craniofacial and neurological abnormalities, sensory defects and multi-organ dysfunction. The finding of HS-causing mutations in PEX1 and PEX6 shows that HS represents the mild end of the ZSSD spectrum, though these conditions were previously thought to be distinct nosological entities. Here, we present six further HS families, five with PEX6 variants and one with PEX1 variants, and show the patterns of Pex1, Pex14 and Pex6 immunoreactivity in the mouse retina. While Ratbi et al. found more HS-causing mutations in PEX1 than in PEX6, as is the case for ZSSD, in this cohort PEX6 variants predominate, suggesting both genes play a significant role in HS. The PEX6 variant c.1802G>A, p.(R601Q), reported previously in compound heterozygous state in one HS and three ZSSD cases, was found in compound heterozygous state in three HS families. Haplotype analysis suggests a common founder variant. All families segregated at least one missense variant, consistent with the hypothesis that HS results from genotypes including milder hypomorphic alleles. The clinical overlap of HS with the more common Usher syndrome and lack of peroxisomal abnormalities on plasma screening suggest that HS may be under-diagnosed. Recognition of AI is key to the accurate diagnosis of HS

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

A Combined Pathway and Regional Heritability Analysis Indicates NETRIN1 Pathway is Associated with Major Depressive Disorder

AbstractBackgroundGenome-wide association studies (GWASs) of major depressive disorder (MDD) have identified few significant associations. Testing the aggregation of genetic variants, in particular biological pathways, may be more powerful. Regional heritability analysis can be used to detect genomic regions that contribute to disease risk.MethodsWe integrated pathway analysis and multilevel regional heritability analyses in a pipeline designed to identify MDD-associated pathways. The pipeline was applied to two independent GWAS samples [Generation Scotland: The Scottish Family Health Study (GS:SFHS, N = 6455) and Psychiatric Genomics Consortium (PGC:MDD) (N = 18,759)]. A polygenic risk score (PRS) composed of single nucleotide polymorphisms from the pathway most consistently associated with MDD was created, and its accuracy to predict MDD, using area under the curve, logistic regression, and linear mixed model analyses, was tested.ResultsIn GS:SFHS, four pathways were significantly associated with MDD, and two of these explained a significant amount of pathway-level regional heritability. In PGC:MDD, one pathway was significantly associated with MDD. Pathway-level regional heritability was significant in this pathway in one subset of PGC:MDD. For both samples the regional heritabilities were further localized to the gene and subregion levels. The NETRIN1 signaling pathway showed the most consistent association with MDD across the two samples. PRSs from this pathway showed competitive predictive accuracy compared with the whole-genome PRSs when using area under the curve statistics, logistic regression, and linear mixed model.ConclusionsThese post-GWAS analyses highlight the value of combining multiple methods on multiple GWAS data for the identification of risk pathways for MDD. The NETRIN1 signaling pathway is identified as a candidate pathway for MDD and should be explored in further large population studies