A Historical Sketch and an Evaluation of the Utah State Agricultural Coaching School and its Results in Terms of the Judgment of Coaches who Participated in 1948

The 1st Annual Utah State Agricultural College Coaching School was held in 1927. The originator and director of the school is E. L. Romney, professor of physical education, director of athletics, and head football coach, Utah State Agricultural College. He has directed this school from its beginning and has consistently obtained leading coaches in the United States as instructors. The school was begun by Coach Romney because he felt that high school and college coaches needed to learn, through specialized instruction by outstanding authorities, the latest developments in coaching principal sports. The purpose of the present study is to determine (1) the areas from which coaches come to attend the Utah State Agricultural College Coaching School, (2) whether or not the people attending the 22nd Annual Coaching School at the Utah State Agricultural College attend regularly, (3) to what extent information and material available at the school are used in the coach\u27s own coaching program, (4) if the school is answering the needs of the coaches attending, and (5) whether or not there is any social value in attending the school, (6) a comparison of all Utah State coaching schools, (7) what, if any, instructional methods need to be used more in the instructor\u27s presentation of material. This information should prove valuable (1) as a guide to Directors of Coaching Schools in building their programs for their particular coaching school, (2) to coaches in determining the value of the coaching school

The Role of Heating and Enrichment in Galaxy Formation

We show that the winds identified with high-redshift low-mass galaxies may strongly affect the formation of stars in more massive galaxies that form later. With 3D realizations of a simple linear growth model we track gas shocking, metal enrichment, and cooling, together with dark halo formation. We show that outflows typically strip baryonic material out of collapsing intermediate mass halos, suppressing star formation. More massive halos can trap the heated gas but collapse late, leading to a broad bimodal redshift distribution, with a larger characteristic mass associated with the lower redshift peak. This scenario accounts for the observed bell-shaped luminosity function of early type galaxies, explains the small number of Milky Way satellite galaxies relative to Cold Dark Matter models predictions, and provides a possible explanation for the lack of metal poor G-dwarfs in the solar neighborhood and the more general lack of low-metallicity stars in massive galaxies relative to ``closed-box'' models of chemical enrichment. Intergalactic medium heating from outflows should produce spectral distortions in the cosmic microwave background that will be measurable with the next generation of experiments.Comment: 19 pages, 12 figures, accepted to ApJ, models refined and minor revisions mad

Real-Time PyMOL Visualization for Rosetta and PyRosetta

Computational structure prediction and design of proteins and protein-protein complexes have long been inaccessible to those not directly involved in the field. A key missing component has been the ability to visualize the progress of calculations to better understand them. Rosetta is one simulation suite that would benefit from a robust real-time visualization solution. Several tools exist for the sole purpose of visualizing biomolecules; one of the most popular tools, PyMOL (Schrödinger), is a powerful, highly extensible, user friendly, and attractive package. Integrating Rosetta and PyMOL directly has many technical and logistical obstacles inhibiting usage. To circumvent these issues, we developed a novel solution based on transmitting biomolecular structure and energy information via UDP sockets. Rosetta and PyMOL run as separate processes, thereby avoiding many technical obstacles while visualizing information on-demand in real-time. When Rosetta detects changes in the structure of a protein, new coordinates are sent over a UDP network socket to a PyMOL instance running a UDP socket listener. PyMOL then interprets and displays the molecule. This implementation also allows remote execution of Rosetta. When combined with PyRosetta, this visualization solution provides an interactive environment for protein structure prediction and design

Neuroimaging-Based Classification of PTSD Using Data-Driven Computational Approaches:A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality.RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60% test AUC for s-MRI, 59% for rs-fMRI and 56% for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75% AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance.CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.</p

Pre-detection history of extensively drug-resistant tuberculosis in KwaZulu-Natal, South Africa

Antimicrobial-resistant (AMR) infections pose a major threat to global public health. Similar to other AMR pathogens, both historical and ongoing drug-resistant tuberculosis (TB) epidemics are characterized by transmission of a limited number of predominant Mycobacterium tuberculosis (Mtb) strains. Understanding how these predominant strains achieve sustained transmission, particularly during the critical period before they are detected via clinical or public health surveillance, can inform strategies for prevention and containment. In this study, we employ whole-genome sequence (WGS) data from TB clinical isolates collected in KwaZulu-Natal, South Africa to examine the pre-detection history of a successful strain of extensively drug-resistant (XDR) TB known as LAM4/KZN, first identified in a widely reported cluster of cases in 2005. We identify marked expansion of this strain concurrent with the onset of the generalized HIV epidemic 12 y prior to 2005, localize its geographic origin to a location in northeastern KwaZulu-Natal ∼400 km away from the site of the 2005 outbreak, and use protein structural modeling to propose a mechanism for how strain-specific rpoB mutations offset fitness costs associated with rifampin resistance in LAM4/KZN. Our findings highlight the importance of HIV coinfection, high preexisting rates of drug-resistant TB, human migration, and pathoadaptive evolution in the emergence and dispersal of this critical public health threat. We propose that integrating wholegenome sequencing into routine public health surveillance can enable the early detection and local containment of AMR pathogens before they achieve widespread dispersal.The National Institute of Allergy and Infectious Disease and National Institutes of Health.https://www.pnas.orgpm2020Medical Microbiolog

The MassiveBlack-II simulation: the evolution of haloes and galaxies to z 0

(Abridged for arXiv)We investigate the properties of halos, galaxies and blackholes to z=0 in the high resolution hydrodynamical simulation MassiveBlack-II (MBII) which evolves a LCDM cosmology in a comoving volume Vbox=100(Mpc/h)^3. MBII is the highest resolution simulation of this size which includes a self-consistent model for star formation, black hole accretion and associated feedback. We provide a simulation browser web application which enables interactive search and tagging of halos, subhalos and their properties and publicly release our galaxy catalogs. Our analysis of the halo mass function (MF) in MBII reveals that baryons have strong effects, with changes in the halo abundance of 20-35% below the knee of the MF (Mhalo < 10^13.2 Msun/h at z=0) when compared to fits based on dark matter only simulations. We provide a fitting function for the halo MF out to redshift z=11 and discuss how the onset of non-universality in the MF limits the accuracy of our fit. We study the halo occupation distribution and clustering of galaxies, in particular the evolution and scale dependence of stochasticity and bias finding reasonable agreement with observational data. The shape of the cosmic spectral energy distribution predicted by MBII is consistent with observations, but lower in amplitude. The Galaxy Stellar Mass Function (GSMF) function is broadly consistent with observations at z>=2. At z<2, the population of passive low mass (for M*<10^9 Msun) galaxies in MBII makes the GSMF too steep compared to observations whereas at the high mass end (M*>10^11 Msun) galaxies hosting bright AGNs make significant contributions to the GSMF. The quasar bolometric luminosity function is also largely consistent with observations. We note however that more efficient AGN feedback (beyond simple thermal coupling used here) is likely necessary for the largest, rarest objects/clusters at low redshifts.Comment: 26 pages, 25 figures. Submitted to MNRAS. High-resolution version and MBII galaxy catalogs can be found at http://mbii.phys.cmu.edu/data

Defining the genotypic and phenotypic spectrum of X-linked MSL3-related disorder

Purpose We sought to delineate the genotypic and phenotypic spectrum of female and male individuals with X-linked, MSL3-related disorder (Basilicata-Akhtar syndrome). Methods Twenty-five individuals (15 males, 10 females) with causative variants in MSL3 were ascertained through exome or genome sequencing at ten different sequencing centers. Results We identified multiple variant types in MSL3 (ten nonsense, six frameshift, four splice site, three missense, one in-frame-deletion, one multi-exon deletion), most proven to be de novo, and clustering in the terminal eight exons suggesting that truncating variants in the first five exons might be compensated by an alternative MSL3 transcript. Three-dimensional modeling of missense and splice variants indicated that these have a deleterious effect. The main clinical findings comprised developmental delay and intellectual disability ranging from mild to severe. Autism spectrum disorder, muscle tone abnormalities, and macrocephaly were common as well as hearing impairment and gastrointestinal problems. Hypoplasia of the cerebellar vermis emerged as a consistent magnetic resonance image (MRI) finding. Females and males were equally affected. Using facial analysis technology, a recognizable facial gestalt was determined. Conclusion Our aggregated data illustrate the genotypic and phenotypic spectrum of X-linked, MSL3-related disorder (Basilicata-Akhtar syndrome). Our cohort improves the understanding of disease related morbidity and allows us to propose detailed surveillance guidelines for affected individuals

Defining the genotypic and phenotypic spectrum of X-linked MSL3-related disorder

PURPOSE: We sought to delineate the genotypic and phenotypic spectrum of female and male individuals with X-linked, MSL3-related disorder (Basilicata-Akhtar syndrome). METHODS: Twenty-five individuals (15 males, 10 females) with causative variants in MSL3 were ascertained through exome or genome sequencing at ten different sequencing centers. RESULTS: We identified multiple variant types in MSL3 (ten nonsense, six frameshift, four splice site, three missense, one in-frame-deletion, one multi-exon deletion), most proven to be de novo, and clustering in the terminal eight exons suggesting that truncating variants in the first five exons might be compensated by an alternative MSL3 transcript. Three-dimensional modeling of missense and splice variants indicated that these have a deleterious effect. The main clinical findings comprised developmental delay and intellectual disability ranging from mild to severe. Autism spectrum disorder, muscle tone abnormalities, and macrocephaly were common as well as hearing impairment and gastrointestinal problems. Hypoplasia of the cerebellar vermis emerged as a consistent magnetic resonance image (MRI) finding. Females and males were equally affected. Using facial analysis technology, a recognizable facial gestalt was determined. CONCLUSION: Our aggregated data illustrate the genotypic and phenotypic spectrum of X-linked, MSL3-related disorder (Basilicata-Akhtar syndrome). Our cohort improves the understanding of disease related morbidity and allows us to propose detailed surveillance guidelines for affected individuals

Remodeling of the Cortical Structural Connectome in Posttraumatic Stress Disorder:Results from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Posttraumatic stress disorder (PTSD) is accompanied by disrupted cortical neuroanatomy. We investigated alteration in covariance of structural networks associated with PTSD in regions that demonstrate the case-control differences in cortical thickness (CT) and surface area (SA). METHODS: Neuroimaging and clinical data were aggregated from 29 research sites in >1,300 PTSD cases and >2,000 trauma-exposed controls (age 6.2-85.2 years) by the ENIGMA-PGC PTSD working group. Cortical regions in the network were rank-ordered by effect size of PTSD-related cortical differences in CT and SA. The top-n (n = 2 to 148) regions with the largest effect size for PTSD > non-PTSD formed hypertrophic networks, the largest effect size for PTSD < non-PTSD formed atrophic networks, and the smallest effect size of between-group differences formed stable networks. The mean structural covariance (SC) of a given n-region network was the average of all positive pairwise correlations and was compared to the mean SC of 5,000 randomly generated n-region networks. RESULTS: Patients with PTSD, relative to non-PTSD controls, exhibited lower mean SC in CT-based and SA-based atrophic networks. Comorbid depression, sex and age modulated covariance differences of PTSD-related structural networks. CONCLUSIONS: Covariance of structural networks based on CT and cortical SA are affected by PTSD and further modulated by comorbid depression, sex, and age. The structural covariance networks that are perturbed in PTSD comport with converging evidence from resting state functional connectivity networks and networks impacted by inflammatory processes, and stress hormones in PTSD

A Comparison of Methods to Harmonize Cortical Thickness Measurements Across Scanners and Sites

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants’ demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LME INT), (2) LME that models both site-specific random intercepts and age-related random slopes (LME INT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2–81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3–85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ 2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ 2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ 2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects