A need for speed: Objectively identifying full-body kinematic and neuromuscular features associated with faster sprint velocities

Sprinting is multifactorial and dependent on a variety of kinematic, kinetic, and neuromuscular features. A key objective in sprinting is covering a set amount of distance in the shortest amount of time. To achieve this, sprinters are required to coordinate their entire body to achieve a fast sprint velocity. This suggests that a whole-body kinematic and neuromuscular coordinative strategy exists which is associated with improved sprint performance. The purpose of this study was to leverage inertial measurement units (IMUs) and wireless surface electromyography (sEMG) to find coordinative strategies associated with peak over-ground sprint velocity using machine learning. We recruited 40 healthy university age sprint-based athletes from a variety of athletic backgrounds. IMU and sEMG data were used as inputs into a principal components analysis (PCA) to observe major modes of variation (i.e., PC scores). PC scores were then used as inputs into a stepwise multivariate linear regression model to derive associations of each mode of variation with peak sprint velocity. Both the kinematic (R2 = 0.795) and sEMG data (R2 = 0.586) produced significant multivariate linear regression models. The PCs that were selected as inputs into the multivariate linear regression model were reconstructed using multi-component reconstruction to produce a representation of the whole-body movement pattern and changes in the sEMG waveform associated with faster sprint velocities. The findings of this work suggest that distinct features are associated with faster sprint velocity. These include the timing of the contralateral arm and leg swing, stance leg kinematics, dynamic trunk extension at toe-off, asymmetry between the right and left swing side leg and a phase shift feature of the posterior chain musculature. These results demonstrate the utility of data-driven frameworks in identifying different coordinative features that are associated with a movement outcome. Using our framework, coaches and biomechanists can make decisions based on objective movement information, which can ultimately improve an athlete’s performance.Natural Sciences and Engineering Research Council (NSERC) of Canada & Brock Library Open Access Publishing Fun

Tihonov theory and center manifolds for inhibitory mechanisms in enzyme kinetics

Abstract In this paper we study the chemical reaction of inhibition, determine the appropriate parameter ε for the application of Tihonov's Theorem, compute explicitly the equations of the center manifold of the system and find sufficient conditions to guarantee that in the phase space the curves which relate the behavior of the complexes to the substrates by means of the tQSSA are asymptotically equivalent to the center manifold of the system. Some numerical results are discussed

An evaluation of the Goddard Space Flight Center Library

The character and degree of coincidence between the current and future missions, programs, and projects of the Goddard Space Flight Center and the current and future collection, services, and facilities of its library were determined from structured interviews and discussions with various classes of facility personnel. In addition to the tabulation and interpretation of the data from the structured interview survey, five types of statistical analyses were performed to corroborate (or contradict) the survey results and to produce useful information not readily attainable through survey material. Conclusions reached regarding compatability between needs and holdings, services and buildings, library hours of operation, methods of early detection and anticipation of changing holdings requirements, and the impact of near future programs are presented along with a list of statistics needing collection, organization, and interpretation on a continuing or longitudinal basis

Selective Enrichment and Identification of Azide-tagged Cross-Linked Peptides Using Chemical Ligation and Mass Spectrometry

Protein-protein interaction is one of the key regulatory mechanisms for controlling protein function in various cellular processes. Chemical cross-linking coupled with mass spectrometry has proven to be a powerful method not only for mapping protein-protein interactions of all natures, including weak and transient ones, but also for determining their interaction interfaces. One critical challenge remaining in this approach is how to effectively isolate and identify cross-linked products from a complex peptide mixture. In this work, we have developed a novel strategy using conjugation chemistry for selective enrichment of cross-linked products. An azide-tagged cross-linker along with two biotinylated conjugation reagents were designed and synthesized. Cross-linking of model peptides and cytochrome c as well as enrichment of the resulting cross-linked peptides has been assessed. Selective conjugation of azide-tagged cross-linked peptides has been demonstrated using two strategies: copper catalyzed cycloaddition and Staudinger ligation. While both methods are effective, Staudinger ligation is better suited for enriching the cross-linked peptides since there are fewer issues with sample handling. LC MSn analysis coupled with database searching using the Protein Prospector software package allowed identification of 58 cytochrome c cross-linked peptides after enrichment and affinity purification. The new enrichment strategy developed in this work provides useful tools for facilitating identification of cross-linked peptides in a peptide mixture by MS, thus presenting a step forward in future studies of protein-protein interactions of protein complexes by cross-linking and mass spectrometry

Glycine Signaling in the Framework of Dopamine-Glutamate Interaction and Postsynaptic Density. Implications for Treatment-Resistant Schizophrenia

Treatment-resistant schizophrenia (TRS) or suboptimal response to antipsychotics affects almost 30% of schizophrenia (SCZ) patients, and it is a relevant clinical issue with significant impact on the functional outcome and on the global burden of disease. Among putative novel treatments, glycine-centered therapeutics (i.e. sarcosine, glycine itself, D-Serine, and bitopertin) have been proposed, based on a strong preclinical rationale with, however, mixed clinical results. Therefore, a better appraisal of glycine interaction with the other major players of SCZ pathophysiology and specifically in the framework of dopamine – glutamate interactions is warranted. New methodological approaches at cutting edge of technology and drug discovery have been applied to study the role of glycine in glutamate signaling, both at presynaptic and post-synaptic level and have been instrumental for unveiling the role of glycine in dopamine-glutamate interaction. Glycine is a non-essential amino acid that plays a critical role in both inhibitory and excitatory neurotransmission. In caudal areas of central nervous system (CNS), such as spinal cord and brainstem, glycine acts as a powerful inhibitory neurotransmitter through binding to its receptor, i.e. the Glycine Receptor (GlyR). However, glycine also works as a co-agonist of the N-Methyl-D-Aspartate receptor (NMDAR) in excitatory glutamatergic neurotransmission. Glycine concentration in the synaptic cleft is finely tuned by glycine transporters, i.e. GlyT1 and GlyT2, that regulate the neurotransmitter's reuptake, with the first considered a highly potential target for psychosis therapy. Reciprocal regulation of dopamine and glycine in forebrain, glycine modulation of glutamate, glycine signaling interaction with postsynaptic density proteins at glutamatergic synapse, and human genetics of glycinergic pathways in SCZ are tackled in order to highlight the exploitation of this neurotransmitters and related molecules in SCZ and TRS

Assessing the potential benefits of the geostationary vantage point for generating daily chlorophyll-a Maps in the Baltic Sea

Currently, observations from low-Earth orbit (LEO) ocean color sensors represent one of the most used tools to study surface optical and biogeochemical properties of the ocean. LEO observations are available at daily temporal resolution, and are often combined into weekly, monthly, seasonal, and annual averages in order to obtain sufficient spatial coverage. Indeed, daily satellite maps of the main oceanic variables (e.g., surface phytoplankton chlorophyll-a) generally have many data gaps, mainly due to clouds, which can be filled using either Optimal Interpolation or the Empirical Orthogonal Functions approach. Such interpolations, however, may introduce large uncertainties in the final product. Here, our goal is to quantify the potential benefits of having high-temporal resolution observations from a geostationary (GEO) ocean color sensor to reduce interpolation errors in the reconstructed hourly and daily chlorophyll-a products. To this aim, we used modeled chlorophyll-a fields from the Copernicus Marine Environment Monitoring Service's (CMEMS) Baltic Monitoring and Forecasting Centre (BAL MFC) and satellite cloud observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor (on board the geostationary satellite METEOSAT). The sampling of a GEO was thus simulated by combining the hourly chlorophyll fields and clouds masks, then hourly and daily chlorophyll-a products were generated after interpolation from neighboring valid data using the Multi-Channel Singular Spectral Analysis (M-SSA). Two cases are discussed: (i) A reconstruction based on the typical sampling of a LEO and, (ii) a simulation of a GEO sampling with hourly observations. The results show that the root mean square and interpolation bias errors are significantly reduced using hourly observations

Increase of dissolved inorganic carbon and decrease in pH in near-surface waters in the Mediterranean Sea during the past two decades

Two 3-year time series of hourly measurements of the fugacity of CO2 (fCO2) in the upper 10 m of the surface layer of the northwestern Mediterranean Sea have been recorded by CARIOCA sensors almost two decades apart, in 1995–1997 and 2013–2015. By combining them with the alkalinity derived from measured temperature and salinity, we calculate changes in pH and dissolved inorganic carbon (DIC). DIC increased in surface seawater by ∼25 µmol kg−1 and fCO2 by 40 µatm, whereas seawater pH decreased by ∼0.04 (0.0022 yr−1). The DIC increase is about 15 % larger than expected from the equilibrium with atmospheric CO2. This could result from natural variability, e.g. the increase between the two periods in the frequency and intensity of winter convection events. Likewise, it could be the signature of the contribution of the Atlantic Ocean as a source of anthropogenic carbon to the Mediterranean Sea through the Strait of Gibraltar. We then estimate that the part of DIC accumulated over the last 18 years represents ∼30 % of the total inventory of anthropogenic carbon in the Mediterranean Sea

DAMEWARE - Data Mining & Exploration Web Application Resource

Astronomy is undergoing through a methodological revolution triggered by an unprecedented wealth of complex and accurate data. DAMEWARE (DAta Mining & Exploration Web Application and REsource) is a general purpose, Web-based, Virtual Observatory compliant, distributed data mining framework specialized in massive data sets exploration with machine learning methods. We present the DAMEWARE (DAta Mining & Exploration Web Application REsource) which allows the scientific community to perform data mining and exploratory experiments on massive data sets, by using a simple web browser. DAMEWARE offers several tools which can be seen as working environments where to choose data analysis functionalities such as clustering, classification, regression, feature extraction etc., together with models and algorithms

Metasurface dome for above-the-horizon grating lobes reduction in 5G-NR systems

The use of fifth-generation (5G) new radio (NR) spectrum around 26 GHz is currently raising the quest on its compatibility with the well-established Earth exploration-satellite service, which may be blinded by the spurious radiation emitted above the horizon (AtH) by base station (BS) antennas. Indeed, AtH grating lobes are often present during cell scanning due to the large interelement spacing in BS array antennas for achieving higher gains with a reduced number of RF chains. In this letter, we propose an approach based on an electrically thin metasurface-based dome for the reduction of AtH grating lobes in 5G-NR BS antennas. The proposed scanning range shifting approach exploits the natural lower amplitude of the grating lobes when the antenna array scans in an angular region closer to the broadside direction. The grating lobe reduction is here demonstrated considering a 1x4 phased linear antenna array operating under dual-liner +/- 45 degrees-slant polarization. A simple design procedure for designing the metasurface dome is reported, together with the antenna performances, evaluated through a proper set of numerical experiments. It is shown that the grating lobe radiation toward the satellite region is significantly reduced, whereas the overall insertion loss is moderate

Guselkumab for treatment of moderate-to-severe plaque psoriasis: real-life effectiveness and drug-survival for up to 148 weeks

Background: Real-world data are useful to guide the management of psoriasis. Here, we present data on the effectiveness and survival of guselkumab in moderate-to-severe chronic plaque psoriasis for up to 148 weeks. Research design and methods: Cross-sectional study of 122 patients receiving guselkumab (100 mg at weeks 0 and 4, and then every 8 weeks thereafter) for>12 weeks, from November 2018 to April 2022. Main outcome measures: Clinical features and drug survival were analyzed up to 148 weeks. Results: Obese patients (32.8%) and those receiving prior biologics (64.8%) were included. Guselkumab treatment was associated with a rapid decrease in PASI, from 16.2 to 3.2 at week 12, and long-term improvements in all subgroups (97.6%, 82.9%, and 63.4% of patients, respectively, achieved PASI 75, 90, and 100 after 148 weeks). More non-obese than obese patients achieved PASI 100 at week 148 (86.4% vs 38.9%), as did bio-naïve vs bio-experienced patients (86.7% vs 50.0%). Previous biologic therapy was a negative prognostic factor for achieving PASI 100 over the long-term by multivariate analysis (p = 0.005). Overall, 96% of patients were on treatment after 2 years. Conclusions: Real-world data confirm the long-term effectiveness of guselkumab in patients with psoriasis