PEAK RATE OF TRUNK ENERGY OUTFLOW DIFFERS BETWEEN PITCH TYPES IN SOFTBALL PITCHERS

In softball players, it is unclear how certain pitch types may increase the risk of injury. The purpose of this study was to determine energy flow differences in the trunk and upper-arm segments between pitch types. Twenty-three softball pitchers participated. Absolute values of trunk energy inflow (IF) and outflow (OF), and upper arm IF, as well as segment energy flow when normalized to pitch speed were assessed in three pitch types. Differences between trunk energy OF were found between fastballs compared to curveballs and dropballs. When normalized to pitch speed, trunk energy OF only differed between fastballs and dropballs. For the upper arm, absolute differences were found between the fastball and curveball. Similar rates of humerus IF between the fastball and dropball and less trunk outflow in the dropball may indicate increased upper extremity demands in the dropball

EFFICIENCY INDEX USED TO ASSESS SHOULDER STRESS IN COLLEGE SOFTBALL PITCHERS THROUGHOUT A SIMULATED GAME

Shoulder distraction forces in softball pitching are known to have a positive impact on performance yet a negative impact on musculoskeletal health. The purpose of this study was to assess changes in shoulder stress across innings pitched using Efficiency Arm-Stress Index (EASI) scores. Motion capture was used on collegiate softball pitchers pitching a simulated game. Peak shoulder distraction force was obtained using inverse dynamics procedures and used to calculate an EASI score (fastball velocity divided by peak shoulder distraction force in percent body weight). A RM·ANOVA revealed inning had no effect on EASI score (F[6,7]=1.28, p=0.286). Understanding a pitcher’s efficiency score may help shape individual pitching loads. Future work should investigate clinically meaningful changes in efficiency scores and mechanisms behind low efficiencies

Successful and unsuccessful cannabis quitters: Comparing group characteristics and quitting strategies

<p>Abstract</p> <p>Background</p> <p>In order to improve treatments for cannabis use disorder, a better understanding of factors associated with successful quitting is required.</p> <p>Method</p> <p>This study examined differences between successful (<it>n </it>= 87) and unsuccessful (<it>n </it>= 78) cannabis quitters. Participants completed a questionnaire addressing demographic, mental health, and cannabis-related variables, as well as quitting strategies during their most recent quit attempt.</p> <p>Results</p> <p>Eighteen strategies derived from cognitive behavioral therapy were entered into a principal components analysis. The analysis yielded four components, representing (1) Stimulus Removal, (2) Motivation Enhancement, (3) (lack of) Distraction, and (4) (lack of) Coping. Between groups comparisons showed that unsuccessful quitters scored significantly higher on Motivation Enhancement and (lack of) Coping. This may indicate that unsuccessful quitters focus on the desire to quit, but do not sufficiently plan strategies for coping. Unsuccessful quitters also had significantly more symptoms of depression and stress; less education; lower exposure to formal treatment; higher day-to-day exposure to other cannabis users; and higher cannabis dependence scores.</p> <p>Conclusions</p> <p>The findings suggest that coping, environmental modification, and co-morbid mental health problems may be important factors to emphasize in treatments for cannabis use disorder.</p

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

Standardisation framework for the Maudsley staging method for treatment resistance in depression

Background: Treatment-resistant depression (TRD) is a serious and relatively common clinical condition. Lack of consensus on defining and staging TRD remains one of the main barriers to understanding TRD and approaches to intervention. The Maudsley Staging Method (MSM) is the first multidimensional model developed to define and stage treatment-resistance in “unipolar depression”. The model is being used increasingly in treatment and epidemiological studies of TRD and has the potential to support consensus. Yet, standardised methods for rating the MSM have not been described adequately. The aim of this report is to present standardised approaches for rating or completing the MSM. Method: Based on the initial development of the MSM and a narrative review of the literature, the developers of the MSM provide explicit guidance on how the three dimensions of the MSM–treatment failure, severity of depressive episode and duration of depressive episode– may be rated. Result: The core dimension of the MSM, treatment failure, may be assessed using the Maudsley Treatment Inventory (MTI), a new method developed for the purposes of completing the MSM. The MTI consists of a relatively comprehensive list of medications with options for rating doses and provisions treatment for multiple episodes. The second dimension, severity of symptoms, may be assessed using simple instruments such as the Clinical Global Impression, the Psychiatric Status Rating or checklist from a standard diagnostic checklist. The standardisation also provides a simple rating scale for scoring the third dimension, duration of depressive episode. Conclusion: The approaches provided should have clinical and research utility in staging TRD. However, in proposing this model, we are fully cognisant that until the pathophysiology of depression is better understood, staging methods can only be tentative approximations. Future developments should attempt to incorporate other biological/ pathophysiological dimensions for staging

The DUNE Far Detector Interim Design Report, Volume 3: Dual-Phase Module

The DUNE IDR describes the proposed physics program and technical designs of the DUNE far detector modules in preparation for the full TDR to be published in 2019. It is intended as an intermediate milestone on the path to a full TDR, justifying the technical choices that flow down from the high-level physics goals through requirements at all levels of the Project. These design choices will enable the DUNE experiment to make the ground-breaking discoveries that will help to answer fundamental physics questions. Volume 3 describes the dual-phase module's subsystems, the technical coordination required for its design, construction, installation, and integration, and its organizational structure

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice