The effectiveness of constraint-led training on skill development in interceptive sports: a systematic review (Clark, McEwan and Christie) – a commentary

Clark, McEwan and Christie's systematic review1 offers a timely examination of current literature assessing effects of a constraints-led approach (CLA) to training on ‘technical and cognitive skill in sport’, in comparison to traditional training methods. They concluded that, currently, there is strong evidence to advocate for the effects of training interventions that espouse benefits of constraints-led training on acquiring skill in interceptive actions. Clark, McEwan and Christie reported that 18 studies satisfied their proposed inclusion criteria and, of these studies, 77% provided evidence of the effectiveness of the CLA. Consequently, Clark, McEwan and Christie argued that a ‘the implementation of the constraints-led approach within interceptive sport can be advocated’ (p. 17). This is a revealing insight, which supports their claims that this finding ‘provides the opportunity for researchers to collect more compelling evidence to answer the question: “Does constraint-led training assist with the development of technical skills within interceptive sport?”’. While we endorse their call for more empirical evidence on the effectiveness of a CLA to practice and training design, we qualify it by highlighting some limitations of Clark, McEwan and Christie's systematic review

Simple, Fast and Accurate Implementation of the Diffusion Approximation Algorithm for Stochastic Ion Channels with Multiple States

The phenomena that emerge from the interaction of the stochastic opening and closing of ion channels (channel noise) with the non-linear neural dynamics are essential to our understanding of the operation of the nervous system. The effects that channel noise can have on neural dynamics are generally studied using numerical simulations of stochastic models. Algorithms based on discrete Markov Chains (MC) seem to be the most reliable and trustworthy, but even optimized algorithms come with a non-negligible computational cost. Diffusion Approximation (DA) methods use Stochastic Differential Equations (SDE) to approximate the behavior of a number of MCs, considerably speeding up simulation times. However, model comparisons have suggested that DA methods did not lead to the same results as in MC modeling in terms of channel noise statistics and effects on excitability. Recently, it was shown that the difference arose because MCs were modeled with coupled activation subunits, while the DA was modeled using uncoupled activation subunits. Implementations of DA with coupled subunits, in the context of a specific kinetic scheme, yielded similar results to MC. However, it remained unclear how to generalize these implementations to different kinetic schemes, or whether they were faster than MC algorithms. Additionally, a steady state approximation was used for the stochastic terms, which, as we show here, can introduce significant inaccuracies. We derived the SDE explicitly for any given ion channel kinetic scheme. The resulting generic equations were surprisingly simple and interpretable - allowing an easy and efficient DA implementation. The algorithm was tested in a voltage clamp simulation and in two different current clamp simulations, yielding the same results as MC modeling. Also, the simulation efficiency of this DA method demonstrated considerable superiority over MC methods.Comment: 32 text pages, 10 figures, 1 supplementary text + figur

Consequences of converting graded to action potentials upon neural information coding and energy efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a ‘footprint’ in the generator potential that obscures incoming signals. These three processes reduce information rates by ~50% in generator potentials, to ~3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation

Estimating the Continuous-Time Dynamics of Energy and Fat Metabolism in Mice

The mouse has become the most popular organism for investigating molecular mechanisms of body weight regulation. But understanding the physiological context by which a molecule exerts its effect on body weight requires knowledge of energy intake, energy expenditure, and fuel selection. Furthermore, measurements of these variables made at an isolated time point cannot explain why body weight has its present value since body weight is determined by the past history of energy and macronutrient imbalance. While food intake and body weight changes can be frequently measured over several weeks (the relevant time scale for mice), correspondingly frequent measurements of energy expenditure and fuel selection are not currently feasible. To address this issue, we developed a mathematical method based on the law of energy conservation that uses the measured time course of body weight and food intake to estimate the underlying continuous-time dynamics of energy output and net fat oxidation. We applied our methodology to male C57BL/6 mice consuming various ad libitum diets during weight gain and loss over several weeks and present the first continuous-time estimates of energy output and net fat oxidation rates underlying the observed body composition changes. We show that transient energy and fat imbalances in the first several days following a diet switch can account for a significant fraction of the total body weight change. We also discovered a time-invariant curve relating body fat and fat-free masses in male C57BL/6 mice, and the shape of this curve determines how diet, fuel selection, and body composition are interrelated

Disarming the guarded prognosis: predicting survival in newly referred patients with incurable cancer

People affected by cancer want information about their prognosis but clinicians have trouble estimating and talking about it. We sought to determine the nature and accuracy of medical oncologists' estimates of life expectancy in newly referred patients with incurable cancer. With reference to each patient, medical oncologists estimated how long they thought 90, 50, and 10% of similar patients would live. These proportions were chosen to reflect worst case, predicted, and best case scenarios suitable for discussions. After a median follow-up of 35 months, 86 of the 102 patients had died with an observed median survival of 12 months. Oncologists' estimates of each patient's worst case, predicted and best case scenarios were well-calibrated: 10% of patients lived for fewer months than estimated for the worst 10% of similar patients; 50% lived for at least as long as estimated for 50% of similar patients (predicted survival), and 17% lived for more months than estimated for the best 10% of similar patients. Oncologists' estimates of each patient's predicted survival were imprecise: 29% were within 0.67–1.33 times the patient's actual survival, 35% were too optimistic (>1.33 times the actual survival), and 39% were too pessimistic (<0.67 times the actual survival). The proportions of patients with actual survival times bounded by simple multiples of their predicted survival were as follows: 61% between half to double their predicted, 6% at least three to four times their predicted, and 4% no more than 1/6 of their predicted; similar to the proportions in an exponential distribution (about 50%, 10% and 10% respectively). Ranges based on simple multiples of the predicted survival time appropriately convey prognosis and its uncertainty in newly referred people with incurable cancer

Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr × Holstein F2 population

Now a days, an important and interesting alternative in the control of tick-infestation in cattle is to select resistant animals, and identify the respective quantitative trait loci (QTLs) and DNA markers, for posterior use in breeding programs. The number of ticks/animal is characterized as a discrete-counting trait, which could potentially follow Poisson distribution. However, in the case of an excess of zeros, due to the occurrence of several noninfected animals, zero-inflated Poisson and generalized zero-inflated distribution (GZIP) may provide a better description of the data. Thus, the objective here was to compare through simulation, Poisson and ZIP models (simple and generalized) with classical approaches, for QTL mapping with counting phenotypes under different scenarios, and to apply these approaches to a QTL study of tick resistance in an F2 cattle (Gyr × Holstein) population. It was concluded that, when working with zero-inflated data, it is recommendable to use the generalized and simple ZIP model for analysis. On the other hand, when working with data with zeros, but not zero-inflated, the Poisson model or a data-transformation-approach, such as square-root or Box-Cox transformation, are applicable

Identification of New Genetic Risk Variants for Type 2 Diabetes

Although more than 20 genetic susceptibility loci have been reported for type 2 diabetes (T2D), most reported variants have small to moderate effects and account for only a small proportion of the heritability of T2D, suggesting that the majority of inter-person genetic variation in this disease remains to be determined. We conducted a multistage, genome-wide association study (GWAS) within the Asian Consortium of Diabetes to search for T2D susceptibility markers. From 590,887 SNPs genotyped in 1,019 T2D cases and 1,710 controls selected from Chinese women in Shanghai, we selected the top 2,100 SNPs that were not in linkage disequilibrium (r2<0.2) with known T2D loci for in silico replication in three T2D GWAS conducted among European Americans, Koreans, and Singapore Chinese. The 5 most promising SNPs were genotyped in an independent set of 1,645 cases and 1,649 controls from Shanghai, and 4 of them were further genotyped in 1,487 cases and 3,316 controls from 2 additional Chinese studies. Consistent associations across all studies were found for rs1359790 (13q31.1), rs10906115 (10p13), and rs1436955 (15q22.2) with P-values (per allele OR, 95%CI) of 6.49×10−9 (1.15, 1.10–1.20), 1.45×10−8 (1.13, 1.08–1.18), and 7.14×10−7 (1.13, 1.08–1.19), respectively, in combined analyses of 9,794 cases and 14,615 controls. Our study provides strong evidence for a novel T2D susceptibility locus at 13q31.1 and the presence of new independent risk variants near regions (10p13 and 15q22.2) reported by previous GWAS

Accurate and Fast Simulation of Channel Noise in Conductance-Based Model Neurons by Diffusion Approximation

Stochastic channel gating is the major source of intrinsic neuronal noise whose functional consequences at the microcircuit- and network-levels have been only partly explored. A systematic study of this channel noise in large ensembles of biophysically detailed model neurons calls for the availability of fast numerical methods. In fact, exact techniques employ the microscopic simulation of the random opening and closing of individual ion channels, usually based on Markov models, whose computational loads are prohibitive for next generation massive computer models of the brain. In this work, we operatively define a procedure for translating any Markov model describing voltage- or ligand-gated membrane ion-conductances into an effective stochastic version, whose computer simulation is efficient, without compromising accuracy. Our approximation is based on an improved Langevin-like approach, which employs stochastic differential equations and no Montecarlo methods. As opposed to an earlier proposal recently debated in the literature, our approximation reproduces accurately the statistical properties of the exact microscopic simulations, under a variety of conditions, from spontaneous to evoked response features. In addition, our method is not restricted to the Hodgkin-Huxley sodium and potassium currents and is general for a variety of voltage- and ligand-gated ion currents. As a by-product, the analysis of the properties emerging in exact Markov schemes by standard probability calculus enables us for the first time to analytically identify the sources of inaccuracy of the previous proposal, while providing solid ground for its modification and improvement we present here

Management control systems in innovation companies: A literature based framework

Past research has traditionally argued that management control systems (MCSs) may present a hindrance to the creativity of innovation companies. This theoretical paper surveys the literature to focus an investigation on the MCSs of innovation companies. Within the object of control paradigm the paper develops and presents a theoretical model of the impact of eleven external, organisational and innovation related contingency factors on the MCSs in companies that engage in innovation activities. We also suggest measures for further empirical research. By formulating hypotheses on 43 potential interactions the model predicts contradictory influences on two direct control categories, results and action control, but stresses the importance of two indirect categories, personnel and cultural control. More specifically, the high levels of technological complexity and innovation capability in this type of company are expected to be negatively associated with the application of results and action control, whereas personnel and cultural seem to be more appropriate. Furthermore, important sources of finance, venture capital and public funding, are both hypothesised to be positively associated with the application of results, action and personnel control; whereas only public funding is predicted to be positively related to the application of cultural control. The principal contribution of this paper lies in synthesising the literature to provide a model of the impact of a unique set of eleven contingency factors for innovation companies on a broad scope of controls. In addition, the contingency model, if empirically validated, would add value by inferring the particular forms of management control which would be beneficial in innovative company settings. © 2014 Springer-Verlag Berlin Heidelberg