The Influence of CrossFit Training on Running Mechanics

Introduction 40 million Americans run regularly.1 Contrary to many runner’s beliefs, increased strength may be beneficial while not adding body mass. An increase in strength in specific muscles may improve running gait and performance. 9,6 Strength training may also play an important role in preventing common overuse injuries in running 11,12 Depending on the style of strength training, it may also have an enhanced benefit on running economy.4,16 Participation in CrossFit is also widely popular, with an increase in participation of 923% in the past ten years.2 CrossFit is a type of strength training in which most movements performed utilize the hip to generate a majority of the power for successful completion.8 Muscles of the hip and knee are imperative during many CrossFit movements, but also during running. Purpose The purpose of this study is to investigate the influence that CrossFit training has on running mechanics. Methods 18 recreational runners between the ages of 18-65 were recruited in each of two groups: 9 runners that also participate in CrossFit 3 times per week, and 9 runners that do not do any strength training. Inclusion criteria included running at least 10 miles a week. Participants gave written consent and completed a demographic questionnaire and Physical Activity Readiness Questionnaire. Following consent, InBody (570, InBody USA, Cerritos, CA) bioelectric impedance body composition was collected. Participants then completed a 5-minute treadmill warm-up. Retro-reflective markers were placed bilaterally on the shoulders and hips and unilaterally on the leg and foot. Data collection was completed over ground along a 10-meter runway with three embedded force platforms (1000 Hz, AMTI Optima, Watertown, MA). Preferred running velocity was then determined. Participants performed two separate conditions; preferred running velocity (C1) and a set velocity of 3.5 m/s (C2). Trials were collected via three-dimensional motion capture system (200 Hz, Vicon, MX and Vantage, Oxfordshire, UK) and photoelectric timing gates. Eight successful trials were collected for each condition. Participants then performed strength testing of the hip and knee to determine peak torque using the isokinetic dynamometer (Biodex System 3, Biodex Medical Systems Shirley, NY) each consisting of one set of five reps at 120 °/s . Data Analysis Following collection, trials were individually processed using Vicon Nexus software (version 2.2.3, Oxfrodshire, UK). Trials were then exported to Visual 3D (version 5, Germantown, MD) and further processed. Statistics Kinematic and kinetic variables were analyzed with a 2x2 repeated measures ANOVA. Strength variables were analyzed with independent t-tests. Alpha level was set to 0.05. Results There was a significant difference between the CF group and the RO group in all of the strength measures, with the CF group having greater strength. For hip ROM, there were no significant differences between the groups, but there was a significant difference between the conditions. Discussion Although there were few differences between the two groups, the main finding of this study is that the CrossFit group was significantly stronger than the run-only group. This is of importance because it demonstrates that even though the CrossFit group was stronger, the running mechanics of the two groups were similar

Relative Bioavailability and Bioaccessibility and Speciation of Arsenic in Contaminated Soils

Background: Assessment of soil arsenic (As) bioavailability may profoundly affect the extent of remediation required at contaminated sites by improving human exposure estimates. Because small adjustments in soil As bioavailability estimates can significantly alter risk assessments and remediation goals, convenient, rapid, reliable, and inexpensive tools are needed to determine soil As bioavailability

PHANGS-JWST First Results: Spurring on Star Formation: JWST Reveals Localized Star Formation in a Spiral Arm Spur of NGC 628

We combine JWST observations with Atacama Large Millimeter/submillimeter Array CO and Very Large Telescope MUSE Hα data to examine off-spiral arm star formation in the face-on, grand-design spiral galaxy NGC 628. We focus on the northern spiral arm, around a galactocentric radius of 3-4 kpc, and study two spurs. These form an interesting contrast, as one is CO-rich and one CO-poor, and they have a maximum azimuthal offset in MIRI 21 μm and MUSE Hα of around 40° (CO-rich) and 55° (CO-poor) from the spiral arm. The star formation rate is higher in the regions of the spurs near spiral arms, but the star formation efficiency appears relatively constant. Given the spiral pattern speed and rotation curve of this galaxy and assuming material exiting the arms undergoes purely circular motion, these offsets would be reached in 100-150 Myr, significantly longer than the 21 μm and Hα star formation timescales (both < 10 Myr). The invariance of the star formation efficiency in the spurs versus the spiral arms indicates massive star formation is not only triggered in spiral arms, and cannot simply occur in the arms and then drift away from the wave pattern. These early JWST results show that in situ star formation likely occurs in the spurs, and that the observed young stars are not simply the “leftovers” of stellar birth in the spiral arms. The excellent physical resolution and sensitivity that JWST can attain in nearby galaxies will well resolve individual star-forming regions and help us to better understand the earliest phases of star formation

The Lantern, 2017-2018

On Dissociation • Untouchable • After Rocket Man • The Science Fair • Cardinal Rule at Stephen J. Memorial • Quentin & Sylvie • Cabello • The Get Out • Painting Day • Black, White and Grey • Family Pruning • How to Remove a Stain • Becoming Ourselves • Wonderbread U • Overture • Pescadero • Gross • Stage Fright • Lucky Daddy • Sarah • Rumble • Silvermine • The Green Iguana • A Poem for Ghost Children • A Poem for Lost Boys • Mother • Drop of Grease • Don\u27t Wanna be White • I • Amelia Earhart Disappeared Into My Vagina: An Ode to Cunts, Menstrual Cups and All Things Woman • Suburban Summer • Nightmares and Dreams Induced by My Mother • Teacups, Skins, etc. • Three Thoughts About My Bedroom • Dear Siri • 2 Queens (Beyonce in Reference to Sonia Sanchez) • Voyeurs • In Front of the Bathroom Mirror • To a Rose • Howl • Mice • Mirror • Language Accordion Volcano Mouth • Lucky Woman • Butterscotch • To Persephone • Wolf • Notes Never Passed • Topple • Bust • Kyoto • Identity • Sunflower • Tornabuoni Bubbles • Olympia • Decayed Hall • Perspectivehttps://digitalcommons.ursinus.edu/lantern/1186/thumbnail.jp

brainlife.io: A decentralized and open source cloud platform to support neuroscience research

Neuroscience research has expanded dramatically over the past 30 years by advancing standardization and tool development to support rigor and transparency. Consequently, the complexity of the data pipeline has also increased, hindering access to FAIR data analysis to portions of the worldwide research community. brainlife.io was developed to reduce these burdens and democratize modern neuroscience research across institutions and career levels. Using community software and hardware infrastructure, the platform provides open-source data standardization, management, visualization, and processing and simplifies the data pipeline. brainlife.io automatically tracks the provenance history of thousands of data objects, supporting simplicity, efficiency, and transparency in neuroscience research. Here brainlife.io's technology and data services are described and evaluated for validity, reliability, reproducibility, replicability, and scientific utility. Using data from 4 modalities and 3,200 participants, we demonstrate that brainlife.io's services produce outputs that adhere to best practices in modern neuroscience research

Comparative Genomics of the Apicomplexan Parasites Toxoplasma gondii and Neospora caninum: Coccidia Differing in Host Range and Transmission Strategy

Toxoplasma gondii is a zoonotic protozoan parasite which infects nearly one third of the human population and is found in an extraordinary range of vertebrate hosts. Its epidemiology depends heavily on horizontal transmission, especially between rodents and its definitive host, the cat. Neospora caninum is a recently discovered close relative of Toxoplasma, whose definitive host is the dog. Both species are tissue-dwelling Coccidia and members of the phylum Apicomplexa; they share many common features, but Neospora neither infects humans nor shares the same wide host range as Toxoplasma, rather it shows a striking preference for highly efficient vertical transmission in cattle. These species therefore provide a remarkable opportunity to investigate mechanisms of host restriction, transmission strategies, virulence and zoonotic potential. We sequenced the genome of N. caninum and transcriptomes of the invasive stage of both species, undertaking an extensive comparative genomics and transcriptomics analysis. We estimate that these organisms diverged from their common ancestor around 28 million years ago and find that both genomes and gene expression are remarkably conserved. However, in N. caninum we identified an unexpected expansion of surface antigen gene families and the divergence of secreted virulence factors, including rhoptry kinases. Specifically we show that the rhoptry kinase ROP18 is pseudogenised in N. caninum and that, as a possible consequence, Neospora is unable to phosphorylate host immunity-related GTPases, as Toxoplasma does. This defense strategy is thought to be key to virulence in Toxoplasma. We conclude that the ecological niches occupied by these species are influenced by a relatively small number of gene products which operate at the host-parasite interface and that the dominance of vertical transmission in N. caninum may be associated with the evolution of reduced virulence in this species

How to Detect an Astrophysical Nanohertz Gravitational-Wave Background

Analysis of pulsar timing data have provided evidence for a stochastic gravitational wave background in the nHz frequency band. The most plausible source of such a background is the superposition of signals from millions of supermassive black hole binaries. The standard statistical techniques used to search for such a background and assess its significance make several simplifying assumptions, namely: i) Gaussianity; ii) isotropy; and most often iii) a power-law spectrum. However, a stochastic background from a finite collection of binaries does not exactly satisfy any of these assumptions. To understand the effect of these assumptions, we test standard analysis techniques on a large collection of realistic simulated datasets. The dataset length, observing schedule, and noise levels were chosen to emulate the NANOGrav 15-year dataset. Simulated signals from millions of binaries drawn from models based on the Illustris cosmological hydrodynamical simulation were added to the data. We find that the standard statistical methods perform remarkably well on these simulated datasets, despite their fundamental assumptions not being strictly met. They are able to achieve a confident detection of the background. However, even for a fixed set of astrophysical parameters, different realizations of the universe result in a large variance in the significance and recovered parameters of the background. We also find that the presence of loud individual binaries can bias the spectral recovery of the background if we do not account for them.Comment: 14 pages, 8 figure

Crowdsourcing hypothesis tests: Making transparent how design choices shape research results

To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer fiveoriginal research questions related to moral judgments, negotiations, and implicit cognition. Participants from two separate large samples (total N > 15,000) were then randomly assigned to complete one version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: materials from different teams renderedstatistically significant effects in opposite directions for four out of five hypotheses, with the narrowest range in estimates being d = -0.37 to +0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for two hypotheses, and a lack of support for three hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, while considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim.</div

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery