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Sprint performance can be characterized through the centre of mass (COM) velocity over time. In-field computation of the COM is key in sprint training.To compare the stance-averaged COM velocity computation from a Magneto-Inertial Measurement Units (MIMU) to a reference system: force platforms (FP), over the early acceleration phase in both straight and curve sprinting.Nineteen experienced-to-elite track sprinters performed 1 maximal sprint on both the straight and the curve (radius = 41.58 m) in a randomized order. Utilizing a MIMU-based system (Xsens MVN Link) and compared to FP (Kistler), COM velocity was computed with both systems. Averaged stance-by-stance COM velocity over straight-line and curve sprinting following the vertical axis (respectively V148 stances were analyzed. V

The maximal total power (Pmax) is one of the major determinants of sprint performance. It can be calculated using a simple model based on the runner’s velocity. This velocity has already been measured with force plates, video cameras or a radar system, but not with an inertial system. The purpose of this study was to compare Pmax measured with a radar system and with a multiple inertial sensors system. Seven participants (174.0 ± 6.9 cm; 67.7 ± 10.1 kg; 22.3 ± 1.7 years) realized two maximal 40-m sprints. Each athlete was equipped with an instrumented suit composed of 17 inertial measurement units (IMU) (Xsens), and a radar (Stalker ATS) was placed behind them. Both systems measured the athletes’ instantaneous horizontal velocity during the acceleration phase. Using an exponential model, Pmax, maximal velocity (Vmax), the slope of the exponential model (τ), maximal force (F0) and the slope of the force, the velocity relationship (SFV) was calculated. The results showed that Pmax, Vmax, τ, F0 and SFV were not significantly different between the radar and the Xsens system (p > 0.13). Pmax, Vmax and F0 measured with the radar were correlated with the same parameters measured with Xsens (r > 0.81 and p ≤ 0.03). The IMU system can be accurately used to measure the main parameters that determine the sprint running performance: Pmax, Vmax and F0. Moreover, contrary to the radar system, multiple inertial sensors will allow for an understanding of the role of the segments in maximal sprint running.

In boxing, an efficient punch requires a combination of force, velocity and stability of the athlete. Being able to monitor these parameters has the potential to better inform training practices required to reach high performance. Hence, the aim of this study was to investigate the differences in punching execution between two groups of elite boxers (senior vs. junior) using three biomechanical indicators of performance in boxing. Each athlete was equipped with an instrumented suit composed of 17 inertial measurement units (IMU) and were asked to perform several series of punches with 3 standardized punching techniques (cross, hook and uppercut) on a punching bag with maximal force. Linear velocity, stability and punch forces were computed from the different sensors. Our findings show that senior boxers systematically produced more force and at a higher velocity for the three punching techniques compared to juniors. The IMU analysis also reveals differences of joint contributions between seniors and juniors, juniors presenting a higher contribution of the shoulder for the three punching techniques.

The purpose of this study was to investigate the effect of a 16-day training camp at moderate altitude on running energetics and biomechanics in an elite female 3,000-m steeplechase athlete (personal best: 9 min 36.15 s). The 16-day intervention included living and training at 1,600 m altitude. A maximal incremental test was performed at sea level to determine the maximal oxygen uptake ( V ∙ O 2 max ). Before (pre-) and after (post-) intervention, the participant performed a specific training session consisting of 10 × 400 m with 5 hurdles with oxygen uptake ( V ∙ O 2 ), blood lactate, stride length and stride rate being measured. A video analysis determined take-off distance and landing around the hurdle (DTH and DLH), take-off velocity and landing around the hurdle (VTH and VLH), and the maximal height over the hurdle (MH). The results demonstrated that the mean V ∙ O 2 maintained during the ten 400 m trials represented 84-86% of V ∙ O 2 max and did not change from pre- to post-intervention (p = 0.22). Mean blood lactate measured on the 6 last 400-m efforts increased significantly (12.0 ± 2.2 vs. 17.0 ± 1.6 mmol.l-1; p < 0.05). On the other hand, post-intervention maximal lactate decreased from 20.1 to 16.0 mmol.l-1. Biomechanical analysis revealed that running velocity increased from 5.12 ± 0.16 to 5.49 ± 0.19 m.s-1 (p < 0.001), concomitantly with stride length (1.63 ± 0.05 vs. 1.73 ± 0.06 m; p < 0.001). However, stride rate did not change (3.15 ± 0.03 vs. 3.16 ± 0.02 Hz; p = 0.14). While DTH was not significantly different from pre- to post- (1.34 ± 0.08 vs. 1.40 ± 0.07 m; p = 0.09), DLH was significantly longer (1.17 ± 0.07 vs. 1.36 ± 0.05 m; p < 0.01). VTH and VLH significantly improved after intervention (5.00 ± 0.14 vs. 5.33 ± 0.16 m.s-1 and 5.18 ± 0.13 vs. 5.51 ± 0.22 m.s-1, respectively; both p < 0.01). Finally, MH increased from pre- to post- (52.5 ± 3.8 vs. 54.9 ± 2.1 cm; p < 0.05). A 16-day moderate altitude training camp allowed an elite female 3,000-m steeplechase athlete to improve running velocity through a greater glycolytic-but not aerobic-metabolism.

The upstream regulatory regions of the mouse and rabbit whey acidic protein (WAP) genes have been used extensively to target the efficient expression of foreign genes into the mammary gland of transgenic animals. Therefore both regions have been studied to elucidate fully the mechanisms controlling WAP gene expression. Three DNase I-hypersensitive sites (HSS0, HSS1 and HSS2) have been described upstream of the rabbit WAP gene in the lactating mammary gland and correspond to important regulatory regions. These sites are surrounded by variable chromatin structures during mammary-gland development. In the present study, we describe the upstream sequence of the mouse WAP gene. Analysis of genomic sequences shows that the mouse WAP gene is situated between two widely expressed genes (Cpr2 and Ramp3). We show that the hypersensitive sites found upstream of the rabbit WAP gene are also detected in the mouse WAP gene. Further, they encompass functional signal transducer and activator of transcription 5-binding sites, as has been observed in the rabbit. A new hypersensitive site (HSS3), not specific to the mammary gland, was mapped 8 kb upstream of the rabbit WAP gene. Unlike the three HSSs described above, HSS3 is also detected in the liver, but similar to HSS1, it does not depend on lactogenic hormone treatments during cell culture. The region surrounding HSS3 encompasses a potential matrix attachment region, which is also conserved upstream of the mouse WAP gene and contains a functional transcription factor Ets-1 (E26 transformation-specific-1)-binding site. Finally, we demonstrate for the first time that variations in the chromatin structure are dependent on prolactin alone.