The peroxisome proliferator-activated receptor (PPAR)-␥ coactivator-1 (PGC-1) can induce mitochondria biogenesis and has been implicated in the development of oxidative type I muscle fibers. The PPAR isoforms ␣, ␤/␦, and ␥ control the transcription of genes involved in fatty acid and glucose metabolism. As endurance training increases skeletal muscle mitochondria and type I fiber content and fatty acid oxidative capacity, our aim was to determine whether these increases could be mediated by possible effects on PGC-1 or PPAR-␣, -␤/␦, and -␥. Seven healthy men performed 6 weeks of endurance training and the expression levels of PGC-1 and PPAR-␣, -␤/␦, and -␥ mRNA as well as the fiber type distribution of the PGC-1 and PPAR-␣ proteins were measured in biopsies from their vastus lateralis muscle. PGC-1 and PPAR-␣ mRNA expression increased by 2.7-and 2.2-fold (P < 0.01), respectively, after endurance training. PGC-1 expression was 2.2-and 6-fold greater in the type IIa than in the type I and IIx fibers, respectively. It increased by 2.8-fold in the type IIa fibers and by 1.5-fold in both the type I and IIx fibers after endurance training (P < 0.015). PPAR-␣ was 1.9-fold greater in type I than in the II fibers and increased by 3.0-fold and 1.5-fold in these respective fibers after endurance training (P < 0.001). The increases in PGC-1 and PPAR-␣ levels reported in this study may play an important role in the changes in muscle mitochondria content, oxidative phenotype, and sensitivity to insulin known to be induced by endurance training. Diabetes 52:2874 -2881, 2003

While intermittent hypoxic training (IHT) has been reported to evoke cellular responses via hypoxia inducible factors (HIFs) but without substantial performance benefits in endurance athletes, we hypothesized that repeated sprint training in hypoxia could enhance repeated sprint ability (RSA) performed in normoxia via improved glycolysis and O2 utilization. 40 trained subjects completed 8 cycling repeated sprint sessions in hypoxia (RSH, 3000 m) or normoxia (RSN, 485 m). Before (Pre-) and after (Post-) training, muscular levels of selected mRNAs were analyzed from resting muscle biopsies and RSA tested until exhaustion (10-s sprint, work-to-rest ratio 1∶2) with muscle perfusion assessed by near-infrared spectroscopy. From Pre- to Post-, the average power output of all sprints in RSA was increased (p<0.01) to the same extent (6% vs 7%, NS) in RSH and in RSN but the number of sprints to exhaustion was increased in RSH (9.4±4.8 vs. 13.0±6.2 sprints, p<0.01) but not in RSN (9.3±4.2 vs. 8.9±3.5). mRNA concentrations of HIF-1α (+55%), carbonic anhydrase III (+35%) and monocarboxylate transporter-4 (+20%) were augmented (p<0.05) whereas mitochondrial transcription factor A (−40%), peroxisome proliferator-activated receptor gamma coactivator 1α (−23%) and monocarboxylate transporter-1 (−36%) were decreased (p<0.01) in RSH only. Besides, the changes in total hemoglobin variations (Δ[tHb]) during sprints throughout RSA test increased to a greater extent (p<0.01) in RSH. Our findings show larger improvement in repeated sprint performance in RSH than in RSN with significant molecular adaptations and larger blood perfusion variations in active muscles.

Mitochondrial impairment is hypothesized to contribute to the pathogenesis of insulin resistance. Mitofusin (Mfn) proteins regulate the biogenesis and maintenance of the mitochondrial network, and when inactivated, cause a failure in the mitochondrial architecture and decreases in oxidative capacity and glucose oxidation. Exercise increases muscle mitochondrial content, size, oxidative capacity and aerobic glucose oxidation. To address if Mfn proteins are implicated in these exercise-induced responses, we measured Mfn1 and Mfn2 mRNA levels, pre-, post-, 2 and 24 h post-exercise. Additionally, we measured the expression levels of transcriptional regulators that control mitochondrial biogenesis and functions, including PGC-1α, NRF-1, NRF-2 and the recently implicated ERRα. We show that Mfn1, Mfn2, NRF-2 and COX IV mRNA were increased 24 h post-exercise, while PGC-1α and ERRα mRNA increased 2 h post-exercise. Finally, using in vitro cellular assays, we demonstrate that Mfn2 gene expression is driven by a PGC-1α programme dependent on ERRα. The PGC-1α/ERRα-mediated induction of Mfn2 suggests a role of these two factors in mitochondrial fusion. Our results provide evidence that PGC-1α not only mediates the increased expression of oxidative phosphorylation genes but also mediates alterations in mitochondrial architecture in response to aerobic exercise in humans.

Skeletal muscle size is tightly regulated by the synergy between anabolic and catabolic signalling pathways which, in humans, have not been well characterized. Akt has been suggested to play a pivotal role in the regulation of skeletal muscle hypertrophy and atrophy in rodents and cells. Here we measured the amount of phospho-Akt and several of its downstream anabolic targets (glycogen synthase kinase-3β (GSK-3β), mTOR, p70 s6k and 4E-BP1) and catabolic targets (Foxo1, Foxo3, atrogin-1 and MuRF1). All measurements were performed in human quadriceps muscle biopsies taken after 8 weeks of both hypertrophy-stimulating resistance training and atrophy-stimulating de-training. Following resistance training a muscle hypertrophy (∼10%) and an increase in phospho-Akt, phospho-GSK-3β and phospho-mTOR protein content were observed. This was paralleled by a decrease in Foxo1 nuclear protein content. Following the de-training period a muscle atrophy (5%), relative to the post-training muscle size, a decrease in phospho-Akt and GSK-3β and an increase in Foxo1 were observed. Atrogin-1 and MuRF1 increased after the hypertrophy and decreased after the atrophy phases. We demonstrate, for the first time in human skeletal muscle, that the regulation of Akt and its downstream signalling pathways GSK-3β, mTOR and Foxo1 are associated with both the skeletal muscle hypertrophy and atrophy processes.

In this paper, we characterize the Ninapro database and its use as a benchmark for hand prosthesis evaluation. The database is a publicly available resource that aims to support research on advanced myoelectric hand prostheses. The database is obtained by jointly recording surface electromyography signals from the forearm and kinematics of the hand and wrist while subjects perform a predefined set of actions and postures. Besides describing the acquisition protocol, overall features of the datasets and the processing procedures in detail, we present benchmark classification results using a variety of feature representations and classifiers. Our comparison shows that simple feature representations such as mean absolute value and waveform length can achieve similar performance to the computationally more demanding marginal discrete wavelet transform. With respect to classification methods, the nonlinear support vector machine was found to be the only method consistently achieving high performance regardless of the type of feature representation. Furthermore, statistical analysis of these results shows that classification accuracy is negatively correlated with the subject's Body Mass Index. The analysis and the results described in this paper aim to be a strong baseline for the Ninapro database. Thanks to the Ninapro database (and the characterization described in this paper), the scientific community has the opportunity to converge to a common position on hand movement recognition by surface electromyography, a field capable to strongly affect hand prosthesis capabilities.

Lower ventilatory responses to a similar hypoxic stimulus during rest and exercise in HH versus NH were sustained for 24 h and associated with lower plasma pH level, exaggerated oxidative stress, and impaired NO bioavailability.

Abstract-This paper is about (self-powered) advanced hand prosthetics and their control via surface electromyography (sEMG). We hereby introduce to the biorobotics community the first version of the NINAPRO database, containing kinematic and sEMG data from the upper limbs of 27 intact subjects while performing 52 finger, hand and wrist movements of interest. The setup and experimental protocol are distilled from existing literature and thoroughly described; the data are then analysed and the results are discussed. In particular, it is clear that standard analysis techniques are no longer enough when so many subjects and movements are taken into account. The database is publicly available to download in standard ASCII format.The database is an ongoing work lasting several years, which is planned to contain data from more than 100 intact subjects and 50 trans-radial amputees; characteristics of the amputations, phantom limbs and prosthesis usage will be stored. We therefore hope that it will constitute a standard, widely accepted benchmark for all novel myoelectric hand prosthesis control methods, as well as a fundamental tool to deliver insight into the needs of trans-radial amputees.

BackgroundMotorized treadmills are widely used in research or in clinical therapy. Small kinematics, kinetics and energetics changes induced by Treadmill Walking (TW) as compared to Overground Walking (OW) have been reported in literature. The purpose of the present study was to characterize the differences between OW and TW in terms of stride-to-stride variability. Classical (Standard Deviation, SD) and non-linear (fractal dynamics, local dynamic stability) methods were used. In addition, the correlations between the different variability indexes were analyzed.MethodsTwenty healthy subjects performed 10 min TW and OW in a random sequence. A triaxial accelerometer recorded trunk accelerations. Kinematic variability was computed as the average SD (MeanSD) of acceleration patterns among standardized strides. Fractal dynamics (scaling exponent α) was assessed by Detrended Fluctuation Analysis (DFA) of stride intervals. Short-term and long-term dynamic stability were estimated by computing the maximal Lyapunov exponents of acceleration signals.ResultsTW did not modify kinematic gait variability as compared to OW (multivariate T2, p = 0.87). Conversely, TW significantly modified fractal dynamics (t-test, p = 0.01), and both short and long term local dynamic stability (T2 p = 0.0002). No relationship was observed between variability indexes with the exception of significant negative correlation between MeanSD and dynamic stability in TW (3 × 6 canonical correlation, r = 0.94).ConclusionsTreadmill induced a less correlated pattern in the stride intervals and increased gait stability, but did not modify kinematic variability in healthy subjects. This could be due to changes in perceptual information induced by treadmill walking that would affect locomotor control of the gait and hence specifically alter non-linear dependencies among consecutive strides. Consequently, the type of walking (i.e. treadmill or overground) is important to consider in each protocol design.