Effect of creatine malate supplementation on physical performance, body composition and selected hormone levels in spinters and long-distance runners

Purpose The aim of the study was to determine whether creatine malate (CML) supplementation results in similar ergogenic effect in sprinters and long-distance runners. The other goal was to compare changes in body composition, physical performance and hormone levels after six-week training in athletes, divided into subgroups supplemented with creatine malate or taking placebo. Results Six-week supplementation combined with physical training induced different effects in athletes. Significantly higher increases in relative and absolute peak power and total work (p < 0.05) were found in sprinters compared to other groups. Except for growth hormone, post-exercise venous blood serum hormone levels exhibited no statistically significant differences in athletes. After CML loading period, a significant increase in growth hormone was found in the group of sprinters. Conclusions A significant ergogenic effect was found in sprinters, which was reflected by the increase in anaerobic exercise indices and morphological indices and elevated growth hormone level, after graded exercise testing. The significant increase in the distance covered during graded test was only observed in supplemented long-distance runners, whereas no significant changes in maximal oxygen uptake, relative peak power and relative total work were noticed. This could be caused by later anaerobic threshold appearance in exercise test to exhaustion

Modeling Disordered Regions in Proteins Using Rosetta

Protein structure prediction methods such as Rosetta search for the lowest energy conformation of the polypeptide chain. However, the experimentally observed native state is at a minimum of the free energy, rather than the energy. The neglect of the missing configurational entropy contribution to the free energy can be partially justified by the assumption that the entropies of alternative folded states, while very much less than unfolded states, are not too different from one another, and hence can be to a first approximation neglected when searching for the lowest free energy state. The shortcomings of current structure prediction methods may be due in part to the breakdown of this assumption. Particularly problematic are proteins with significant disordered regions which do not populate single low energy conformations even in the native state. We describe two approaches within the Rosetta structure modeling methodology for treating such regions. The first does not require advance knowledge of the regions likely to be disordered; instead these are identified by minimizing a simple free energy function used previously to model protein folding landscapes and transition states. In this model, residues can be either completely ordered or completely disordered; they are considered disordered if the gain in entropy outweighs the loss of favorable energetic interactions with the rest of the protein chain. The second approach requires identification in advance of the disordered regions either from sequence alone using for example the DISOPRED server or from experimental data such as NMR chemical shifts. During Rosetta structure prediction calculations the disordered regions make only unfavorable repulsive contributions to the total energy. We find that the second approach has greater practical utility and illustrate this with examples from de novo structure prediction, NMR structure calculation, and comparative modeling

The dawn of the dead : (improbable) art after aI-zombie apocalypse

In recent years there has been growing interest in artificial neural networks (ANNs) which are quickly becoming the primary device for machine learning. Used for finding patterns in large data sets, ANNs were also recently employed in many artistic contexts: as tools for artists, semi-independent creators of content, and even as invisible "critics" which / who predict our aesthetic preferences. The aim of this paper is to speculate about the disruptive effect of these ‘alien agencies’ on the (modernist) aesthetic regime of art centred around the notion of autonomy. The author examines how neural networks and connectionist epistemologies may potentially affect the most common ways of producing, circulating, and valorising art. He claims that the possibility of automatizing creativity and art criticism may lead to the emergence of a new aesthetic regime based on forms of dynamic, distributed and probabilistic governance

RosettaScripts: A Scripting Language Interface to the Rosetta Macromolecular Modeling Suite

Macromolecular modeling and design are increasingly useful in basic research, biotechnology, and teaching. However, the absence of a user-friendly modeling framework that provides access to a wide range of modeling capabilities is hampering the wider adoption of computational methods by non-experts. RosettaScripts is an XML-like language for specifying modeling tasks in the Rosetta framework. RosettaScripts provides access to protocol-level functionalities, such as rigid-body docking and sequence redesign, and allows fast testing and deployment of complex protocols without need for modifying or recompiling the underlying C++ code. We illustrate these capabilities with RosettaScripts protocols for the stabilization of proteins, the generation of computationally constrained libraries for experimental selection of higher-affinity binding proteins, loop remodeling, small-molecule ligand docking, design of ligand-binding proteins, and specificity redesign in DNA-binding proteins

Combining Experiments and Simulations Using the Maximum Entropy Principle

A key component of computational biology is to compare the results of computer modelling with experimental measurements. Despite substantial progress in the models and algorithms used in many areas of computational biology, such comparisons sometimes reveal that the computations are not in quantitative agreement with experimental data. The principle of maximum entropy is a general procedure for constructing probability distributions in the light of new data, making it a natural tool in cases when an initial model provides results that are at odds with experiments. The number of maximum entropy applications in our field has grown steadily in recent years, in areas as diverse as sequence analysis, structural modelling, and neurobiology. In this Perspectives article, we give a broad introduction to the method, in an attempt to encourage its further adoption. The general procedure is explained in the context of a simple example, after which we proceed with a real-world application in the field of molecular simulations, where the maximum entropy procedure has recently provided new insight. Given the limited accuracy of force fields, macromolecular simulations sometimes produce results that are at not in complete and quantitative accordance with experiments. A common solution to this problem is to explicitly ensure agreement between the two by perturbing the potential energy function towards the experimental data. So far, a general consensus for how such perturbations should be implemented has been lacking. Three very recent papers have explored this problem using the maximum entropy approach, providing both new theoretical and practical insights to the problem. We highlight each of these contributions in turn and conclude with a discussion on remaining challenges

Search for anisotropic gravitational-wave backgrounds using data from Advanced LIGO and Advanced Virgo's first three observing runs

We report results from searches for anisotropic stochastic gravitational-wave backgrounds using data from the first three observing runs of the Advanced LIGO and Advanced Virgo detectors. For the first time, we include Virgo data in our analysis and run our search with a new efficient pipeline called {\tt PyStoch} on data folded over one sidereal day. We use gravitational-wave radiometry (broadband and narrow band) to produce sky maps of stochastic gravitational-wave backgrounds and to search for gravitational waves from point sources. A spherical harmonic decomposition method is employed to look for gravitational-wave emission from spatially-extended sources. Neither technique found evidence of gravitational-wave signals. Hence we derive 95\% confidence-level upper limit sky maps on the gravitational-wave energy flux from broadband point sources, ranging from $F_{\alpha, \Theta} < {\rm (0.013 - 7.6)} \times 10^{-8} {\rm erg \, cm^{-2} \, s^{-1} \, Hz^{-1}},$ and on the (normalized) gravitational-wave energy density spectrum from extended sources, ranging from $\Omega_{\alpha, \Theta} < {\rm (0.57 - 9.3)} \times 10^{-9} \, {\rm sr^{-1}}$, depending on direction ($\Theta$) and spectral index ($\alpha$). These limits improve upon previous limits by factors of $2.9 - 3.5$. We also set 95\% confidence level upper limits on the frequency-dependent strain amplitudes of quasimonochromatic gravitational waves coming from three interesting targets, Scorpius X-1, SN 1987A and the Galactic Center, with best upper limits range from $h_0 < {\rm (1.7-2.1)} \times 10^{-25},$ a factor of $\geq 2.0$ improvement compared to previous stochastic radiometer searches.Comment: 23 Pages, 9 Figure

Diving below the spin-down limit:constraints on gravitational waves from the energetic young pulsar PSR J0537-6910

We present a search for continuous gravitational-wave signals from the young, energetic X-ray pulsar PSR J0537-6910 using data from the second and third observing runs of LIGO and Virgo. The search is enabled by a contemporaneous timing ephemeris obtained using NICER data. The NICER ephemeris has also been extended through 2020 October and includes three new glitches. PSR J0537-6910 has the largest spin-down luminosity of any pulsar and is highly active with regards to glitches. Analyses of its long-term and inter-glitch braking indices provided intriguing evidence that its spin-down energy budget may include gravitational-wave emission from a time-varying mass quadrupole moment. Its 62 Hz rotation frequency also puts its possible gravitational-wave emission in the most sensitive band of LIGO/Virgo detectors. Motivated by these considerations, we search for gravitational-wave emission at both once and twice the rotation frequency. We find no signal, however, and report our upper limits. Assuming a rigidly rotating triaxial star, our constraints reach below the gravitational-wave spin-down limit for this star for the first time by more than a factor of two and limit gravitational waves from the l = m = 2 mode to account for less than 14% of the spin-down energy budget. The fiducial equatorial ellipticity is limited to less than about 3 x 10⁻⁵, which is the third best constraint for any young pulsar