Impact reduction during running: efficiency of simple acute interventions in recreational runners

International audienceRunning-related stress fractures have been associated with the overall impact intensity, which has recently been described through the loading rate (LR). Our purpose was to evaluate the effects of four acute interventions with specific focus on LR: wearing racing shoes (RACE), increasing step frequency by 10 % (FREQ), adopting a midfoot strike pattern (MIDFOOT) and combining these three interventions (COMBI). Nine rearfoot-strike subjects performed five 5-min trials during which running kinetics, kinematics and spring-mass behavior were measured for ten consecutive steps on an instrumented treadmill. Electromyographic activity of gastrocnemius lateralis, tibialis anterior, biceps femoris and vastus lateralis muscles was quantified over different phases of the stride cycle. LR was significantly and similarly reduced in MIDFOOT (37.4 ± 7.20 BW s(-1), -56.9 ± 50.0 %) and COMBI (36.8 ± 7.15 BW s(-1), -55.6 ± 29.2 %) conditions compared to NORM (56.3 ± 11.5 BW s(-1), both P<0.001). RACE (51.1 ± 9.81 BW s(-1)) and FREQ (52.7 ± 11.0 BW s(-1)) conditions had no significant effects on LR. Running with a midfoot strike pattern resulted in a significant increase in gastrocnemius lateralis pre-activation (208 ± 97.4 %, P<0.05) and in a significant decrease in tibialis anterior EMG activity (56.2 ± 15.5 %, P<0.05) averaged over the entire stride cycle. The acute attenuation of foot-ground impact seems to be mostly related to the use of a midfoot strike pattern and to a higher pre-activation of the gastrocnemius lateralis. Further studies are needed to test these results in prolonged running exercises and in the long term

Optimising sounds for the driving of sleep oscillations by closed‐loop auditory stimulation

Recent studies have shown that slow oscillations (SOs) can be driven by rhythmic auditory stimulation, which deepens slow‐wave sleep (SWS) and improves memory and the immune‐supportive hormonal milieu related to this sleep stage. While different attempts have been made to optimise the driving of the SOs by changing the number of click stimulations, no study has yet investigated the impact of applying more than five clicks in a row. Likewise, the importance of the type of sounds in eliciting brain responses is presently unclear. In a study of 12 healthy young participants (10 females; aged 18–26 years), we applied an established closed‐loop stimulation method, which delivered sequences of 10 pink noises, 10 pure sounds (B note of 247 Hz), 10 pronounced “a” vowels, 10 sham, 10 variable sounds, and 10 “oddball” sounds on the up phase of the endogenous SOs. By analysing area under the curve, amplitude, and event related potentials, we explored whether the nature of the sound had a differential effect on driving SOs. We showed that every stimulus in a 10‐click sequence, induces a SO response. Interestingly, all three types of sounds that we tested triggered SOs. However, pink noise elicited a more pronounced response compared to the other sounds, which was explained by a broader topographical recruitment of brain areas. Our data further suggest that varying the sounds may partially counteract habituation

Sprint Acceleration Mechanics in Fatigue Conditions: Compensatory Role of Gluteal Muscles in Horizontal Force Production and Potential Protection of Hamstring Muscles

Aim: Hamstring muscle injury is the main injury related to sports requiring sprint acceleration. In addition, hamstring muscles have been reported to play a role in horizontal force production during sprint acceleration performance. The aim of the present study was to analyze (i) the determinants of horizontal force production and (ii) the role of hip extensors, and hamstring muscles in particular, for horizontal force production during repeated sprint-induced fatigue conditions.Method: In this experimental laboratory setting study including 14 sprint-trained male athletes, we analyzed (i) the changes in sprint mechanics, peak torque of the knee and hip extensors and flexors, muscle activity of the vastus lateralis, rectus femoris, biceps femoris, and gluteus, and sagittal plane lower limb motion, before and after twelve 6-s sprints separated by 44 s rest on an instrumented motorized treadmill, and (ii) the determinants of horizontal force production (FH) during the sprint acceleration in a fatigue state (after 12 sprints).Results: The repeated-sprint protocol induced a decrease in maximal power output (Pmax) [-17.5 ± 8.9%; effect size (ES): 1.57, large] and in the contact-averaged horizontal force component (FH) (-8.6 ± 8.4%; ES: 0.86, moderate) but not meaningful changes in the contact-averaged resultant (total) force (FTot) (-3.4 ± 2.9%; ES: 0.55, small) and vertical force component (FV) (-3.1 ± 3.2%; ES: 0.49, small). A decrease was found in concentric peak torque of the knee flexors and extensors and in gluteus and vastus lateralis muscle activity during entire swing and end-of-swing phase. An increase was found in contact time and swing time, while step frequency and knee speed before ground contact decreased. Muscular determinants associated with FH and its decrease after the repeated-sprint protocol were concentric peak torque of the hip extensors (p = 0.033) and a decrease in gluteus maximus activity at the end-of-swing (p = 0.007), respectively.Conclusion: Sprint-induced fatigue lead to changes in horizontal force production muscular determinants: hamstring muscle seems not to have the same role than in non-fatigue condition. Horizontal force production seems to be more dependent on the hip extensors and gluteus maximus function. Given the fatigue-induced decrease in hamstring muscle strength, we can hypothesize that muscle compensatory and kinematic strategies reported in a fatigued state could be an adaptation to allow/maintain performance and a protective adaptation to limit hamstring muscles constraints

Leukocyte Expression of Type 1 and Type 2 Purinergic Receptors and Pro-Inflammatory Cytokines during Total Sleep Deprivation and/or Sleep Extension in Healthy Subjects

The purinergic type P1 (adenosine A1 and A2A) receptors and the type P2 (X7) receptor have been suggested to mediate physiological effects of adenosine and adenosine triphosphate on sleep. We aimed to determine gene expression of A1R (receptor), A2AR, and P2RX7 in leukocytes of healthy subjects during total sleep deprivation followed by sleep recovery. Expression of the pro-inflammatory cytokines IL-1β and TNF-α were also determined as they have been characterized as sleep regulatory substances, via P2RX7 activation. Blood sampling was performed on 14 young men (aged 31.9 ± 3.9) at baseline (B), after 24 h of sleep deprivation (24 h-SD), and after one night of sleep recovery (R). We compared gene expression levels after six nights of habitual (22.30–07.00) or extended (21.00–07.00) bedtimes. Using quantitative real-time PCR, the amount of mRNA for A1R, A2AR, P2RX7, TNF-α, and IL-1β was analyzed. After 24 h-SD compared to B, whatever prior sleep condition, a significant increase of A2AR expression was observed that returned to basal level after sleep recovery [day main effect, F(2, 26) = 10.8, p &lt; 0.001]. In both sleep condition, a day main effect on P2RX7 mRNA was observed [F(2, 26) = 6.7, p = 0.005] with significant increases after R compared with 24 h-SD. TNF-α and IL-1β expressions were not significantly altered. Before 24 h-SD (baseline), the A2AR expression was negatively correlated with the latency of stage 3 sleep during the previous night, while that of the A1R positively. This was not observed after sleep recovery following 24 h-SD. This is the first study showing increased A2AR and not A1 gene expression after 24 h-SD in leukocytes of healthy subjects, and this even if bedtime was initially increased by 1.5 h per night for six nights. In conclusion, prolonged wakefulness induced an up-regulation of the A2A receptor gene expression in leukocytes from healthy subjects. Significant correlations between baseline expression of A1 and A2A receptors in peripheral cells and stage 3 sleep suggested their involvement in mediating the effects of adenosine on sleep

Cognitive functions and cerebral oxygenation changes during acute and prolonged hypoxic exposure

International audienceno abstrac

DOSED: A deep learning approach to detect multiple sleep micro-events in EEG signal

International audienceBackground: Electroencephalography (EEG) monitors brain activity during sleep and is used to identify sleep disorders. In sleep medicine, clinicians interpret raw EEG signals in so-called sleep stages, which are assigned by experts to every 30 s window of signal. For diagnosis, they also rely on shorter prototypical micro-architecture events which exhibit variable durations and shapes, such as spindles, K-complexes or arousals. Annotating such events is traditionally performed by a trained sleep expert, making the process time consuming, tedious and subject to inter-scorer variability. To automate this procedure, various methods have been developed, yet these are event-specific and rely on the extraction of hand-crafted features.New method: We propose a novel deep learning architecure called Dreem One Shot Event Detector (DOSED). DOSED jointly predicts locations, durations and types of events in EEG time series. The proposed approach, applied here on sleep related micro-architecture events, is inspired by object detectors developed for computer vision such as YOLO and SSD. It relies on a convolutional neural network that builds a feature representation from raw EEG signals, as well as two modules performing localization and classification respectively.Results and comparison with other methods: The proposed approach is tested on 4 datasets and 3 types of events (spindles, K-complexes, arousals) and compared to the current state-of-the-art detection algorithms.Conclusions: Results demonstrate the versatility of this new approach and improved performance compared to the current state-of-the-art detection method

Sleep habits and strategies of ultramarathon runners

<div><p>Among factors impacting performance during an ultramarathon, sleep is an underappreciated factor that has received little attention. The aims of this study were to characterize habitual sleep behaviors in ultramarathon runners and to examine strategies they use to manage sleep before and during ultramarathons. Responses from 636 participants to a questionnaire were considered. This population was found to sleep more on weekends and holidays (7–8 h to 8–9 h) than during weekdays (6–7 h to 7–8 h; p < 0.001). Work was a mediator of napping habits since 19–25% reported napping on work days and 37–56% on non-work days. There were 24.5% of the participants reporting sleep disorders, with more women (38.9%) reporting sleep problems than men (22.0%; p < 0.005). Mean (±SD) sleepiness score on the Epworth Sleepiness Scale was 8.9 ± 4.3 with 37.6% of respondents scoring higher than 10, reflecting excessive daytime sleepiness. Most of the study participants (73.9%) had a strategy to manage sleep preceding an ultramarathon, with 54.7% trying to increase their opportunities for sleep. Only 21% of participants reported that they had a strategy to manage sleep during ultramarathons, with micronaps being the most common strategy specified. Sub-analyses from 221 responses indicated that sleep duration during an ultramarathon was correlated with finish time for races lasting 36–60 h (r = 0.48; p < 0.01) or > 60 h (r = 0.44; p < 0.001). We conclude that sleep duration among ultramarathon runners was comparable to the general population and other athletic populations, yet they reported a lower prevalence of sleep disorders. Daytime sleepiness was among the lowest rates encountered in athletic populations, which may be related to the high percentage of nappers in our population. Sleep extension, by increasing sleep time at night and daytime napping, was the main sleep strategy to prepare for ultramarathons.</p></div

Sleep strategies used during ultramarathons among subjects indicating they had slept during an ultramarathon.

<p>Sleep strategies used during ultramarathons among subjects indicating they had slept during an ultramarathon.</p