Optimal stride frequencies in running at different speeds

During running at a constant speed, the optimal stride frequency (SF) can be derived from the u-shaped relationship between SF and heart rate (HR). Changing SF towards the optimum of this relationship is beneficial for energy expenditure and may positively change biomechanics of running. In the current study, the effects of speed on the optimal SF and the nature of the u-shaped relation were empirically tested using Generalized Estimating Equations. To this end, HR was recorded from twelve healthy (4 males, 8 females) inexperienced runners, who completed runs at three speeds. The three speeds were 90%, 100% and 110% of self-selected speed. A self-selected SF (SFself) was determined for each of the speeds prior to the speed series. The speed series started with a free-chosen SF condition, followed by five imposed SF conditions (SFself, 70, 80, 90, 100 strides·min-1) assigned in random order. The conditions lasted 3 minutes with 2.5 minutes of walking in between. SFself increased significantly (p<0.05) with speed with averages of 77, 79, 80 strides·min-1 at 2.4, 2.6, 2.9 m·s-1, respectively). As expected, the relation between SF and HR could be described by a parabolic curve for all speeds. Speed did not significantly affect the curvature, nor did it affect optimal SF. We conclude that over the speed range tested, inexperienced runners may not need to adapt their SF to running speed. However, since SFself were lower than the SFopt of 83 strides·min-1, the runners could reduce HR by increasing their SFself

Significance of the model parameters.

<p>Significance of the model parameters.</p

Hypothetical models to evaluate the effect of speed on the relation between stride frequency and heart rate.

<p>The dashed line (V90%), dash-dot (V100%) and solid line (V110%) respectively represent three increasing speed conditions.</p

The relation between SF and HR for each speed series based on Model 1.

<p>From bottom to top V_90%, V_100%, V_110%. The central line in the boxplot represents the median, the edges of the box are the 25th and 75th percentiles, and the whiskers extend to ±1.5 of the interquartile range. The outliers (+) beyond this range belong to a single participant. An optimum of 83 strides·min^-1 was calculated using the parameters of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0184273#pone.0184273.e001" target="_blank">Model 1</a>.</p

Average error scores calculated from the observed stride frequency (SF) relative to the imposed SF.

<p>The asterisk denotes the average self-selected SF.</p

A reference genome for pea provides insight into legume genome evolution

International audienceWe report the first annotated chromosome-level reference genome assembly for pea, Gregor Mendel’s original genetic model. Phylogenetics and paleogenomics show genomic rearrangements across legumes and suggest a major role for repetitive elements in pea genome evolution. Compared to other sequenced Leguminosae genomes, the pea genome shows intense gene dynamics, most likely associated with genome size expansion when the Fabeae diverged from its sister tribes. During Pisum evolution, translocation and transposition differentially occurred across lineages. This reference sequence will accelerate our understanding of the molecular basis of agronomically important traits and support crop improvement