Neural influences on sprint running - Training adaptations and acute responses

Performance in sprint exercise is determined by the ability to accelerate, the magnitude of maximal velocity and the ability to maintain velocity against the onset of fatigue. These factors are strongly influenced by metabolic and anthropometric components. Improved temporal sequencing of muscle activation and/or improved fast twitch fibre recruitment may contribute to superior sprint performance. Speed of impulse transmission along the motor axon may also have implications on sprint performance. Nerve conduction velocity (NCV) has been shown to increase in response to a period of sprint training. However, it is difficult to determine if increased NCV is likely to contribute to improved sprint performance. An increase in motoneuron excitability, as measured by the Hoffman reflex (H-reflex), has been reported to produce a more powerful muscular contraction, hence maximising motoneuron excitability would be expected to benefit sprint performance. Motoneuron excitability can be raised acutely by an appropriate stimulus with obvious implications for sprint performance. However, at rest reflex has been reported to be lower in athletes trained for explosive events compared with endurance-trained athletes. This may be caused by the relatively high, fast twitch fibre percentage and the consequent high activation thresholds of such motor units in power-trained populations. In contrast, stretch reflexes appear to be enhanced in sprint athletes possibly because of increased muscle spindle sensitivity as a result of sprint training. With muscle in a contracted state, however, there is evidence to suggest greater reflex potentiation among both sprint and resistance-trained populations compared with controls. Again this may be indicative of the predominant types of motor units in these populations, but may also mean an enhanced reflex contribution to force production during running in sprint-trained athletes. Fatigue of neural origin both during and following sprint exercise has implications with respect to optimising training frequency and volume. Research suggests athletes are unable to maintain maximal firing frequencies for the full duration of, for example, a 100m sprint. Fatigue after a single training session may also have a neural manifestation with some athletes unable to voluntarily fully activate muscle or experiencing stretch reflex inhibition after heavy training. This may occur in conjunction with muscle damage. Research investigating the neural influences on sprint performance is limited. Further longitudinal research is necessary to improve our understanding of neural factors that contribute to training-induced improvements in sprint performance.

Optimising high-intensity treadmill training using the running speed at maximal O-2 uptake and the time for which this can be maintained

The aim of this study was to compare the effects of two high-intensity, treadmill interval-training programs on 3000-m and 5000-m running performance. Maximal oxygen uptake ((V) over dot O-2max), the running speed associated with (V) over dot O-2max (nu (V) over dot O-2max), the time for which nu (V) over dot O-2max can be maintained (T-max), running economy (RE), ventilatory threshold (VT) and 3000-m and 5000-m running times were determined in 27 well-trained runners. Subjects were then randomly assigned to three groups; (1) 60% T-max (2) 70% T-max and (3) control. Subjects in the control group continued their normal training and subjects in the two T-max groups undertook a 4-week treadmill interval-training program with the intensity set at nu (V) over dot O-2max and the interval duration at the assigned T-max. These subjects completed two interval-training sessions per week (60% T-max = six intervals/session, 70% T-max group = five intervals/session). Subjects were re-tested on all parameters at the completion of the training program. There was a significant improvement between pre- and post-training values in 3000-m time trial (TT) performance in the 60% T-max group compared to the 70% T,,a, and control groups [mean (SE); 60% T-max = 17.6 (3.5) s, 70% T-max = 6.3 (4.2) s, control = 0.5 (7.7) s]. There was no significant effect of the training program on 5000-m TT performance [60% T-max = 25.8 (13.8) s, 70% T-max = 3.7 (11.6) s, control = 9.9 (13.1) s]. Although there were no significant improvements in (V) over dot O-2max, nu (V) over dot (2max) and RE between groups, changes in (V) over dot O-2max and RE were significantly correlated with the improvement in the 3000-m TT. Furthermore, VT and T-max were significantly higher in the 60% Tmax group post-compared to pre-training. In conclusion, 3000-m running performance can be significantly improved in a group of well-trained runners, using a 4-week treadmill interval training program at nu (V) over dot O-2max with interval durations of 60% T-max.

(Virtual) Agents for running electricity markets

This paper describes a multi-agent based simulation (MABS) framework to construct an artificial electric power market populated with learning agents. The artificial market, named TEMMAS (The Electricity Market Multi-Agent Simulator), explores the integration of two design constructs: (i) the specification of the environmental physical market properties and (ii) the specification of the decision-making (deliberative) and reactive agents. TEMMAS is materialized in an experimental setup involving distinct power generator companies that operate in the market and search for the trading strategies that best exploit their generating units' resources. The experimental results show a coherent market behavior that emerges from the overall simulated environment.

Makespan computation for GPU threads running on a single streaming multiprocessor

Graphics processors were originally developed for rendering graphics but have recently evolved towards being an architecture for general-purpose computations. They are also expected to become important parts of embedded systems hardware -- not just for graphics. However, this necessitates the development of appropriate timing analysis techniques which would be required because techniques developed for CPU scheduling are not applicable. The reason is that we are not interested in how long it takes for any given GPU thread to complete, but rather how long it takes for all of them to complete. We therefore develop a simple method for finding an upper bound on the makespan of a group of GPU threads executing the same program and competing for the resources of a single streaming multiprocessor (whose architecture is based on NVIDIA Fermi, with some simplifying assunptions). We then build upon this method to formulate the derivation of the exact worst-case makespan (and corresponding schedule) as an optimization problem. Addressing the issue of tractability, we also present a technique for efficiently computing a safe estimate of the worstcase makespan with minimal pessimism, which may be used when finding an exact value would take too long.

Changes in Running Mechanics and Spring-Mass Behaviour during a 5-km Time Trial

Research into the biomechanical manifestation of fatigue during exhaustive runs is increasingly popular but additional understanding of the adaptation of the spring-mass behaviour during the course of strenuous, self-paced exercises continues to be a challenge in order to develop optimized training and injury prevention programs. This study investigated continuous changes in running mechanics and spring-mass behaviour during a 5-km run. 12 competitive triathletes performed a 5-km running time trial (mean performance: 17 min 30 s) on a 200 m indoor track. Vertical and anterior-posterior ground reaction forces were measured every 200 m by a 5-m long force platform system, and used to determine spring-mass model characteristics. After a fast start, running velocity progressively decreased (- 11.6%; P<0.001) in the middle part of the race before an end spurt in the final 400-600 m. Stride length (- 7.4%; P<0.001) and frequency (- 4.1%; P=0.001) decreased over the 25 laps, while contact time (+ 8.9%; P<0.001) and total stride duration (+ 4.1%; P<0.001) progressively lengthened. Peak vertical forces (- 2.0%; P<0.01) and leg compression (- 4.3%; P<0.05), but not centre of mass vertical displacement (+ 3.2%; P>0.05), decreased with time. As a result, vertical stiffness decreased (- 6.0%; P<0.001) during the run, whereas leg stiffness changes were not significant (+ 1.3%; P>0.05). Spring-mass behaviour progressively changes during a 5-km time trial towards deteriorated vertical stiffness, which alters impact and force production characteristics.

Time is Running Out: The 2°C Target and Optimal Climate Policies

The quintessence of recent natural science studies is that the 2 degrees C target can only be achieved with massive emission reductions in the next few years. The central twist of this paper is the addition of this limited time to act into a non-perpetual real options framework analysing optimal climate policy under uncertainty. The window-of-opportunity modelling setup shows that the limited time to act may spark a trend reversal in the direction of low-carbon alternatives. However, the implementation of a climate policy is evaded by high uncertainty about possible climate pathways.

Physiological differences between cycling and running: lessons from triathletes

The purpose of this review was to provide a synopsis of the literature concerning the physiological differences between cycling and running. By comparing physiological variables such as maximal oxygen consumption (V O(2max)), anaerobic threshold (AT), heart rate, economy or delta efficiency measured in cycling and running in triathletes, runners or cyclists, this review aims to identify the effects of exercise modality on the underlying mechanisms (ventilatory responses, blood flow, muscle oxidative capacity, peripheral innervation and neuromuscular fatigue) of adaptation. The majority of studies indicate that runners achieve a higher V O(2max) on treadmill whereas cyclists can achieve a V O(2max) value in cycle ergometry similar to that in treadmill running. Hence, V O(2max) is specific to the exercise modality. In addition, the muscles adapt specifically to a given exercise task over a period of time, resulting in an improvement in submaximal physiological variables such as the ventilatory threshold, in some cases without a change in V O(2max). However, this effect is probably larger in cycling than in running. At the same time, skill influencing motor unit recruitment patterns is an important influence on the anaerobic threshold in cycling. Furthermore, it is likely that there is more physiological training transfer from running to cycling than vice versa. In triathletes, there is generally no difference in V O(2max) measured in cycle ergometry and treadmill running. The data concerning the anaerobic threshold in cycling and running in triathletes are conflicting. This is likely to be due to a combination of actual training load and prior training history in each discipline. The mechanisms surrounding the differences in the AT together with V O(2max) in cycling and running are not largely understood but are probably due to the relative adaptation of cardiac output influencing V O(2max) and also the recruitment of muscle mass in combination with the oxidative capacity of this mass influencing the AT. Several other physiological differences between cycling and running are addressed: heart rate is different between the two activities both for maximal and submaximal intensities. The delta efficiency is higher in running. Ventilation is more impaired in cycling than in running. It has also been shown that pedalling cadence affects the metabolic responses during cycling but also during a subsequent running bout. However, the optimal cadence is still debated. Central fatigue and decrease in maximal strength are more important after prolonged exercise in running than in cycling.

Differences in whole-body fat oxidation kinetics between cycling and running.

This study aimed to quantitatively describe and compare whole-body fat oxidation kinetics in cycling and running using a sinusoidal mathematical model (SIN). Thirteen moderately trained individuals (7 men and 6 women) performed two graded exercise tests, with 3-min stages and 1 km h(-1) (or 20 W) increment, on a treadmill and on a cycle ergometer. Fat oxidation rates were determined using indirect calorimetry and plotted as a function of exercise intensity. The SIN model, which includes three independent variables (dilatation, symmetry and translation) that account for main quantitative characteristics of kinetics, provided a mathematical description of fat oxidation kinetics and allowed for determination of the intensity (Fat(max)) that elicits maximal fat oxidation (MFO). While the mean fat oxidation kinetics in cycling formed a symmetric parabolic curve, the mean kinetics during running was characterized by a greater dilatation (i.e., widening of the curve, P < 0.001) and a rightward asymmetry (i.e., shift of the peak of the curve to higher intensities, P = 0.01). Fat(max) was significantly higher in running compared with cycling (P < 0.001), whereas MFO was not significantly different between modes of exercise (P = 0.36). This study showed that the whole-body fat oxidation kinetics during running was characterized by a greater dilatation and a rightward asymmetry compared with cycling. The greater dilatation may be mainly related to the larger muscle mass involved in running while the rightward asymmetry may be induced by the specific type of muscle contraction.

Alteration in neuromuscular function after a 5 km running time trial.

The aim of this study was to characterize the effect of a 5 km running time trial on the neuromuscular properties of the plantar flexors. Eleven well-trained triathletes performed a series of neuromuscular tests before and immediately after the run on a 200 m indoor track. Muscle activation (twitch interpolation) and normalized EMG activity were assessed during maximal voluntary contraction (MVC) of plantar flexors. Maximal soleus H-reflexes and M-waves were evoked at rest (i.e. H (MAX) and M (MAX), respectively) and during MVC (i.e. H (SUP) and M (SUP), respectively). MVC significantly declined (-27%; P < 0.001) after the run, due to decrease in muscle activation (-8%; P < 0.05) and M (MAX)-normalized EMG activity (-13%; P < 0.05). Significant reductions in M-wave amplitudes (M (MAX): -13% and M (SUP): -16%; P < 0.05) as well as H (MAX)/M (MAX) (-37%; P < 0.01) and H (SUP)/M (SUP) (-25%; P < 0.05) ratios occurred with fatigue. Following exercise, the single twitch was characterized by lower peak torque (-16%; P < 0.001) as well as shorter contraction (-19%; P < 0.001) and half-relaxation (-24%; P < 0.001) times. In conclusion, the reduction in plantar flexors strength induced by a 5 km running time trial is caused by peripheral adjustments, which are attributable to a failure of the neuromuscular transmission and excitation-contraction coupling. Fatigue also decreased the magnitude of efferent motor outflow from spinal motor neurons to the plantar flexors and part of this suboptimal neural drive is the result of an inhibition of soleus motoneuron pool reflex excitability.

Is the GraftConnector a valid alternative to running suture in end-to-side coronary arteries anastomoses?

BACKGROUND: An animal study was carried out to compare long-term patency rates of coronary anastomoses performed with the GraftConnector versus running suture technique. METHODS: 10 sheep, 45 to 55 kg, underwent off-pump coronary artery bypass grafting (right internal mammary artery to left anterior descending artery). In 5 animals, the anastomosis was performed with a GraftConnector and in 5 animals with 7-0 running suture. Intraoperative fluoroscopy and a fluoroscopic control at 6 months were performed. After 6 months, the animals were sacrificed and the anastomoses were examined histologically. RESULTS: All animals survived at 6 months with 100% anastomosis patency rates in both groups. In the GraftConnector group, the anastomosis diameter at 6 months fluoroscopy was 118% of native left anterior descending artery versus 97% of the control group. Luminal anastomotic width at histology was 1.7 +/- 0.2 mm in the device group versus 1.6 +/- 0.1 mm in the control group. Mean intimal hyperplasia thickness was 0.21 +/- 0.1 mm in the device group versus 0.01 mm in the control group. CONCLUSIONS: The GraftConnector provides a consistent and reproducible coronary artery anastomosis and reduces technical demand and manual dexterity in coronary operations. Long-term results demonstrate that off-pump coronary artery bypass grafting performed with the GraftConnector had the same patency rate and luminal width as those performed with running suture.

Cardiorespiratory responses during running and sport-specific exercises in handball players

To determine whether a 4-a-side handball (HB) game is an appropriate aerobic stimulus to reach and potentially enhance maximal oxygen uptake (V O(2)max), and whether heart rate (HR) is a valid index of V O(2) during a handball game. Nine skilled players (21.0+/-2.9 yr) underwent a graded maximal aerobic test (GT) where V O(2)max and HR-V O(2) relationship were determined. V O(2), HR and blood lactate ([La](b)) were recorded during a 2 x 225 s (interspersed with 30s rest) 4-a-side handball game and were compared to those measured during an 480-s running intermittent exercise (IE). Mean V O(2) tended to be higher in handball compared to IE (93.9+/-8.5 vs. 87.6+/-7.4% O(2)max, p=0.06), whereas HR was similar (92.3+/-4.9 vs. 93.9+/-3.9% of the peak of HR, p=0.10). [La](b) was lower for handball than for IE (8.9+/-3.5 vs. 11.6+/-2.1 mmol l(-1), p=0.04). Time spent over 90% of V O(2)max was higher for handball than for IE (336.1+/-139.6s vs. 216.1+/-124.7s; p=0.03). The HR-V O(2) relationship during GT was high (r(2)=0.96, p<0.001) but estimated V O(2) from HR was lower to that measured (p=0.03) in handball, whereas there was no difference in IE. 4-a-side handball game can be used as a specific alternative to IE for enhancing aerobic fitness in handball players. Nevertheless, the accuracy of HR measures for estimating V O(2) during handball is poor.

Does the mechanical work in running change during the VO2 slow component?

PURPOSE: The origin of the slow component is not fully understood. The mechanical hypothesis is one of the potential factors, because an increase in external mechanical work with fatigue was previously reported for a constant velocity run. The purpose of this study was to determine whether a change in mechanical work could occur during the development of the VO2 slow component under the effect of fatigue. METHODS: Twelve regional-level competitive runners performed a square-wave transition, corresponding to 95% of the speed associated with peak VO2 obtained during an incremental test. The VO2 response was fit with a classical model including two exponential functions. A specific treadmill with three-dimensional force transducers was used to measure the ground reaction force. Kinetic work (W(kin)), potential work (W(pot)), external work (W(ext)), and an index of internal work (W(int)) per unit of distance were quantified continuously. RESULTS: During the slow component of VO2, a significant increase in W (P< 0.01), no change in W, and a significant decrease in W and W index (P< 0.05, P< 0.001, respectively) were observed. CONCLUSION: The present study showed that the slow component of VO2 did not result partly from a change in mechanical work under the effect of fatigue. Nevertheless, the decrease in stride frequency (P< 0.001) and contact time (P< 0.001) suggested an alternative mechanical explanation. The slow component during running may be due to the cost of generating force or to alterations in the storage and recoil of elastic energy, and not to the external mechanical work.