ACCURACY AND PRECISION OF THE KINETIC ANALYSIS OF COUNTER MOVEMENT JUMP PERFORMANCE

The purpose of this study was to quantify the accuracy and precision of measuring counter movement jump (CMJ) performance kinetically (i.e. measuring impulse using a force plate). A 14-camera 3D motion analysis system and a force plate were used simultaneously to obtain vertical trajectories of centre of mass (CM) for comparison. Fifty-eight CMJs were analyzed from eleven physically active males. Jump height differences were trivial, and small bias was obtained thereby showing good accuracy as well as small typical errors for performance. Our study indicates that force plates can be used confidently for CMJ analysis

Melting of a Two-component Source beneath Iceland

New trace element and Hf-Nd isotope data on post-glacial basalts from Iceland's main rift zones are used in conjunction with literature data to evaluate the relative importance of source heterogeneity and the melting process for the final melt composition. Correlations between Hf and Nd isotope compositions and trace element ratios indicate that at least two source components are sampled systematically as a function of the degree and pressure of melting beneath Iceland. Strong depletion in Rb, Ba, U and Th and enrichment in Nb and Ta compared with La in the most enriched samples from the Reykjanes Peninsula and Western Rift Zone suggests that the enriched source component is similar to ancient recycled enriched mid-ocean ridge basalt (E-MORB) crust. Highly incompatible trace element ratios such as Nb/La and Nb/U and Pb isotope ratios are variable across Iceland. This observation suggests that either the enriched component is intrinsically heterogeneous, or that there is a larger proportion of the enriched source component beneath the Southwestern Rift Zone compared with the Northern Rift Zone. The relative effect of source heterogeneity and melting on the final melt composition was evaluated with a one-dimensional polybaric melt mixing model in which accumulated melts from a depleted MORB mantle and a recycled E-MORB crust are mixed in different ways. Two styles of melt mixing were simulated: (1) complete mixing of melts with variable proportions of the depleted mantle and recycled E-MORB components; (2) incomplete mixing with a fixed initial proportion of the two source components. Calculated pressure-dependent compositional changes using these simple two-component melting models can explain the observed trends in trace element ratio and isotope ratio diagrams for Icelandic basalts, even in cases where conventional binary mixing models would require more than two source components. The example of Iceland demonstrates that melt mixing during extraction from the mantle is a key process for controlling the trace element and isotope variability observed in basaltic lavas and must be evaluated before inferring the presence of multiple source component

Metabolomics reveals distinct neurochemical profiles associated with stress resilience

Acute social defeat represents a naturalistic form of conditioned fear and is an excellent model in which to investigate the biological basis of stress resilience. While there is growing interest in identifying biomarkers of stress resilience, until recently, it has not been feasible to associate levels of large numbers of neurochemicals and metabolites to stress-related phenotypes. The objective of the present study was to use an untargeted metabolomics approach to identify known and unknown neurochemicals in select brain regions that distinguish susceptible and resistant individuals in two rodent models of acute social defeat. In the first experiment, male mice were first phenotyped as resistant or susceptible. Then, mice were subjected to acute social defeat, and tissues were immediately collected from the ventromedial prefrontal cortex (vmPFC), basolateral/central amygdala (BLA/CeA), nucleus accumbens (NAc), and dorsal hippocampus (dHPC). Ultra-high performance liquid chromatography coupled with high resolution mass spectrometry (UPLC-HRMS) was used for the detection of water-soluble neurochemicals. In the second experiment, male Syrian hamsters were paired in daily agonistic encounters for 2 weeks, during which they formed stable dominant-subordinate relationships. Then, 24 h after the last dominance encounter, animals were exposed to acute social defeat stress. Immediately after social defeat, tissue was collected from the vmPFC, BLA/CeA, NAc, and dHPC for analysis using UPLC-HRMS. Although no single biomarker characterized stress-related phenotypes in both species, commonalities were found. For instance, in both model systems, animals resistant to social defeat stress also show increased concentration of molecules to protect against oxidative stress in the NAc and vmPFC. Additionally, in both mice and hamsters, unidentified spectral features were preliminarily annotated as potential targets for future experiments. Overall, these findings suggest that a metabolomics approach can identify functional groups of neurochemicals that may serve as novel targets for the diagnosis, treatment, or prevention of stress-related mental illness

KINEMATIC DIFFERENCES BETWEEN ‘ONE-FOOTED’ AND ‘TWO-FOOTED’ YOUNG SOCCER PLAYERS KICKING WITH THE NON-PREFERRED LEG

The purpose of this study was to examine kinematic differences between ‘one-footed’ and ‘two-footed’ players when kicking with the non-preferred leg at a target and with maximal effort. Eighteen highly-trained young soccer players were categorised as one-footed (n=9) and two-footed (n=9) based on results of a kicking test. Motion analysis data showed that two-footed players run-up straighter and have less pelvic rotation at ball-foot impact than one-footed players and the differences are likely to be meaningful (ES differences of 0.89 and 0.99 respectively). Run-up angle and pelvic rotation angle are significantly correlated (P < 0.1). The study found that two-footed players are significantly smaller in stature than one-footed players (P < 0.1). Practical implications for soccer coaches arose from the study

Metabolomic analysis of mouse prefrontal cortex reveals upregulated analytes during wakefulness compared to sleep

By identifying endogenous molecules in brain extracellular fluid metabolomics can provide insight into the regulatory mechanisms and functions of sleep. Here we studied how the cortical metabolome changes during sleep, sleep deprivation and spontaneous wakefulness. Mice were implanted with electrodes for chronic sleep/wake recording and with microdialysis probes targeting prefrontal and primary motor cortex. Metabolites were measured using ultra performance liquid chromatography-high resolution mass spectrometry. Sleep/wake changes in metabolites were evaluated using partial least squares discriminant analysis, linear mixed effects model analysis of variance, and machine-learning algorithms. More than 30 known metabolites were reliably detected in most samples. When used by a logistic regression classifier, the profile of these metabolites across sleep, spontaneous wake, and enforced wake was sufficient to assign mice to their correct experimental group (pair-wise) in 80–100% of cases. Eleven of these metabolites showed significantly higher levels in awake than in sleeping mice. Some changes extend previous findings (glutamate, homovanillic acid, lactate, pyruvate, tryptophan, uridine), while others are novel (D-gluconate, N-acetyl-beta-alanine, N-acetylglutamine, orotate, succinate/methylmalonate). The upregulation of the de novo pyrimidine pathway, gluconate shunt and aerobic glycolysis may reflect a wake-dependent need to promote the synthesis of many essential components, from nucleic acids to synaptic membranes

(N)-methanocarba-2MeSADP (MRS2365) is a subtype-specific agonist that induces rapid desensitization of the P2Y1 receptor of human platelets

Adenosine diphosphate (ADP) initiates and maintains sustained aggregation of platelets through simultaneous activation of both the Gq-coupled P2Y1 receptor and the Gi-coupled P2Y12 receptor. We recently described the synthesis and P2Y1 receptor-specific agonist activity of (N)-methano-carba-2MeSADP (MRS2365). Consequences of selective activation of the P2Y1 receptor by MRS2365 have been further examined in human platelets. Whereas MRS2365 alone only induced shape change, addition of MRS2365 following epinephrine treatment, which activates the Gi/z-linked, α2A-adrenergic receptor, resulted in sustained aggregation that was indistinguishable from that observed with ADP. Conversely, the platelet shape change promoted by ADP in the presence of the GPIIb/IIIa antagonist eptifibatide was similar to that promoted by MRS2365. Preaddition of the high affinity P2Y1 receptor antagonist MRS2500 inhibited the effect of MRS2365, whereas addition of MRS2500 subsequent to MRS2365 reversed the MRS2365-induced shape change. Preactivation of the P2Y1 receptor with MRS2365 for 2 min resulted in marked loss of capacity of ADP to induce aggregation as evidenced by a greater than 20-fold rightward shift in the concentration effect curve of ADP. This inhibitory effect of P2Y1 receptor activation was dependent on the concentration of MRS2365 (EC50 = 34 nM). The inhibitory effect of preincubation with MRS2365 was circumvented by activation of the Gq-coupled 5-HT2a receptor suggesting that MRS2365 induces loss of the ADP response as a consequence of desensitization of the Gq-coupled P2Y1 receptor. The time course of MRS2365-induced loss of aggregation response to epinephrine was similar to that observed with ADP. These results further demonstrate the P2Y1 receptor selectivity of MRS2365 and illustrate the occurrence of agonist-induced desensitization of the P2Y1 receptor of human platelets studied in the absence of P2Y12 receptor activation

Quantifying loopy network architectures

Biology presents many examples of planar distribution and structural networks having dense sets of closed loops. An archetype of this form of network organization is the vasculature of dicotyledonous leaves, which showcases a hierarchically-nested architecture containing closed loops at many different levels. Although a number of methods have been proposed to measure aspects of the structure of such networks, a robust metric to quantify their hierarchical organization is still lacking. We present an algorithmic framework, the hierarchical loop decomposition, that allows mapping loopy networks to binary trees, preserving in the connectivity of the trees the architecture of the original graph. We apply this framework to investigate computer generated graphs, such as artificial models and optimal distribution networks, as well as natural graphs extracted from digitized images of dicotyledonous leaves and vasculature of rat cerebral neocortex. We calculate various metrics based on the Asymmetry, the cumulative size distribution and the Strahler bifurcation ratios of the corresponding trees and discuss the relationship of these quantities to the architectural organization of the original graphs. This algorithmic framework decouples the geometric information (exact location of edges and nodes) from the metric topology (connectivity and edge weight) and it ultimately allows us to perform a quantitative statistical comparison between predictions of theoretical models and naturally occurring loopy graphs.Comment: 17 pages, 8 figures. During preparation of this manuscript the authors became aware of the work of Mileyko at al., concurrently submitted for publicatio

Metabolomic analysis of mouse prefrontal cortex reveals upregulated analytes during wakefulness compared to sleep

By identifying endogenous molecules in brain extracellular fluid metabolomics can provide insight into the regulatory mechanisms and functions of sleep. Here we studied how the cortical metabolome changes during sleep, sleep deprivation and spontaneous wakefulness. Mice were implanted with electrodes for chronic sleep/wake recording and with microdialysis probes targeting prefrontal and primary motor cortex. Metabolites were measured using ultra performance liquid chromatography-high resolution mass spectrometry. Sleep/wake changes in metabolites were evaluated using partial least squares discriminant analysis, linear mixed effects model analysis of variance, and machine-learning algorithms. More than 30 known metabolites were reliably detected in most samples. When used by a logistic regression classifier, the profile of these metabolites across sleep, spontaneous wake, and enforced wake was sufficient to assign mice to their correct experimental group (pair-wise) in 80–100% of cases. Eleven of these metabolites showed significantly higher levels in awake than in sleeping mice. Some changes extend previous findings (glutamate, homovanillic acid, lactate, pyruvate, tryptophan, uridine), while others are novel (D-gluconate, N-acetyl-beta-alanine, N-acetylglutamine, orotate, succinate/methylmalonate). The upregulation of the de novo pyrimidine pathway, gluconate shunt and aerobic glycolysis may reflect a wake-dependent need to promote the synthesis of many essential components, from nucleic acids to synaptic membranes

Integrating evolution into ecological modelling: accommodating phenotypic changes in agent based models.

PMCID: PMC3733718This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Evolutionary change is a characteristic of living organisms and forms one of the ways in which species adapt to changed conditions. However, most ecological models do not incorporate this ubiquitous phenomenon. We have developed a model that takes a 'phenotypic gambit' approach and focuses on changes in the frequency of phenotypes (which differ in timing of breeding and fecundity) within a population, using, as an example, seasonal breeding. Fitness per phenotype calculated as the individual's contribution to population growth on an annual basis coincide with the population dynamics per phenotype. Simplified model variants were explored to examine whether the complexity included in the model is justified. Outputs from the spatially implicit model underestimated the number of individuals across all phenotypes. When no phenotype transitions are included (i.e. offspring always inherit their parent's phenotype) numbers of all individuals are always underestimated. We conclude that by using a phenotypic gambit approach evolutionary dynamics can be incorporated into individual based models, and that all that is required is an understanding of the probability of offspring inheriting the parental phenotype