Comparison of External Load across Multi-Day Tournaments in Female Youth Volleyball Athletes

Several youth volleyball tournaments are played across multiple consecutive days with athletes averaging 3–4 matches/day. This study evaluated the differences in workload of female youth volleyball athletes across days and by position during multi-day tournaments. Athletes (n = 22, 16.4 ± 0.4 years) wore an accelerometer during 12 two- and three-day tournaments. Workload was measured via kinetic energy (KE, J/lb), total jumps (TJ), high jumps (HJ, >51 cm), average jump height (cm), and percentage of high stress movements (%) via VERT accelerometers. Data were analyzed across days and by position as an average per day and analyzed via repeated measures analyses of variance. Across days, workload averages ranged 484.8–558.0 J/lb for KE, 27.3–31.2 TJ/match, 37.5–37.9 cm/jump, 5.2–6.5 HJ/match, and 20.1–20.7% high stress movements/match, with no difference (p = 0.300). Setters (49.2 ± 24.3 jumps) jumped more than liberos (13.0 ± 6.8 TJ, p = 0.005), and middles (45.8 ± 4.1 cm) jumped higher than all other positions (setters: 28.8 ± 3.6 cm, outside hitters: 41.3 ± 4.2 cm, and liberos: 27.0 ± 4.1 cm, p = 0.000–0.044). Athletes appeared to perform and recover sufficiently between days of play such that their external load was not affected. The level of competition tends to become more evenly matched as the tournament progresses, thus there may have been less physical demand early in the tournaments due to unequal competition levels compared to the final day of the tournament

Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g. cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale

FAIR for AI: An interdisciplinary and international community building perspective.

A foundational set of findable, accessible, interoperable, and reusable (FAIR) principles were proposed in 2016 as prerequisites for proper data management and stewardship, with the goal of enabling the reusability of scholarly data. The principles were also meant to apply to other digital assets, at a high level, and over time, the FAIR guiding principles have been re-interpreted or extended to include the software, tools, algorithms, and workflows that produce data. FAIR principles are now being adapted in the context of AI models and datasets. Here, we present the perspectives, vision, and experiences of researchers from different countries, disciplines, and backgrounds who are leading the definition and adoption of FAIR principles in their communities of practice, and discuss outcomes that may result from pursuing and incentivizing FAIR AI research. The material for this report builds on the FAIR for AI Workshop held at Argonne National Laboratory on June 7, 2022

FAIR for AI: An interdisciplinary and international community building perspective

A foundational set of findable, accessible, interoperable, and reusable (FAIR) principles were proposed in 2016 as prerequisites for proper data management and stewardship, with the goal of enabling the reusability of scholarly data. The principles were also meant to apply to other digital assets, at a high level, and over time, the FAIR guiding principles have been re-interpreted or extended to include the software, tools, algorithms, and workflows that produce data. FAIR principles are now being adapted in the context of AI models and datasets. Here, we present the perspectives, vision, and experiences of researchers from different countries, disciplines, and backgrounds who are leading the definition and adoption of FAIR principles in their communities of practice, and discuss outcomes that may result from pursuing and incentivizing FAIR AI research. The material for this report builds on the FAIR for AI Workshop held at Argonne National Laboratory on June 7, 2022

Statins: Antimicrobial resistance breakers or makers?

© 2017 Ko et al. Introduction. The repurposing of non-antibiotic drugs as adjuvant antibiotics may help break antimicrobial resistance (AMR). Statins are commonly prescribed worldwide to lower cholesterol. They also possess qualities of AMR 'breakers'', namely direct antibacterial activity, synergism with antibiotics, and ability to stimulate the host immune system. However, statins' role as AMR breakers may be limited. Their current extensive use for cardiovascular protection might result in selective pressures for resistance, ironically causing statins to be AMR'makers'' instead. This review examines statins' potential as AMR breakers, probable AMR makers, and identifies knowledge gaps in a statin-bacteria-human-environment continuum. The most suitable statin for repurposing is identified, and a mechanism of antibacterial action is postulated based on structure-activity relationship analysis. Methods. A literature search using keywords 'statin' or 'statins' combined with 'minimum inhibitory concentration'' (MIC) was performed in six databases on 7th April 2017. After screening 793 abstracts, 16 relevant studies were identified. Unrelated studies on drug interactions; antifungal or antiviral properties of statins; and antibacterial properties of mevastatin, cerivastatin, antibiotics, or natural products were excluded. Studies involving only statins currently registered for human use were included. Results. Against Gram-positive bacteria, simvastatin generally exerted the greatest an- tibacterial activity (lowest MIC) compared to atorvastatin, rosuvastatin, and fluvastatin. Against Gram-negative bacteria, atorvastatin generally exhibited similar or slightly better activity compared to simvastatin, but both were more potent than rosuvastatin and fluvastatin. Discussion. Statins may serve as AMR breakers by working synergistically with existing topical antibiotics, attenuating virulence factors, boosting human immunity, or aiding in wound healing. It is probable that statins' mechanism of antibacterial activity involves interference of bacterial cell regulatory functions via binding and disrupting cell surface structures such as wall teichoic acids, lipoteichoic acids, lipopolysaccharides, and/or surface proteins. The widespread use of statins for cardiovascular protection may favor selective pressures or co-selection for resistance, including dysbiosis of the human gut microbiota, sublethal plasma concentrations in bacteremic patients, and statin persistence in the environment, all possibly culminating in AMR. Conclusion. Simvastatin appears to be the most suitable statin for repurposing as a novel adjuvant antibiotic. Current evidence better supports statins as potential AMR breakers, but their role as plausible AMR makers cannot be excluded. Elucidating the mechanism of statins' antibacterial activity is perhaps the most important knowledge gap to address as this will likely clarify statins' role as AMR breakers or makers