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This study aims to validate the use of contralateral designs in studies of effects of resistance exercise. It will recruit healthy young (18-35 years) individuals, which will be allocated to 4 experimental groups. In two of the experimental groups, 3x10 or 6x10 repetitions of heavy resistance exercise on one leg will be combined with no training of the other leg for 7 weeks. In the third group, 3x10 repetitions of heavy resistance exercise on one leg will be combined with 6x10 repetitions of heavy resistance exercise on the other leg for 7 weeks. In the fourth group, which serves as a control group, a period of no training (similar in length to the training period of groups 1-3; 7 weeks), before both legs will train 3x10 repetitions of heavy resistance exercise in an unilateral manner.
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Our understanding of how exercise affects muscular adaptations at the cellular and molecular level comes from the use of skeletal muscle biopsies. Such studies are met by several challenges, including its invasive nature, costs of muscle analyses, large inter-participant variability in response to exercise and a limited number of subjects (related to ethical concerns regarding exposing participants to biopsies). Consequently, studies often include small sample sizes, resulting in low statistical power. This poses a great challenge to the field of exercise physiology. While increasing sample size may not always be feasible, employing alternative designs may offer a way to increase the statistical power. An example of such a design is the so-called cross-over design, wherein participants serve as their own control thereby reducing the inter-participant variation. An interesting variant of the cross-over design is the unilateral or contralateral exercise model. In such designs, each of the participant's limbs (e.g. legs) are randomly allocated to perform different types of training/treatments in close temporal proximity. This design obliterates the need for a wash-out period and removes the potential effects of confounding factors such as diet, activity and sleep decreases. Thus, resources, time spent and variability can be reduced. However, validation of such studies is lacking.
In an effort to validate a contralateral training design, the investigators will recruit young (18-35 years) healthy individuals to 4 groups performing unilateral progressive strength training; (1) one leg with no training and one leg with 3x10 maximal repetitions, (2) one leg with no training and one leg with 6x10 maximal repetitions, (3) one leg with 3x10 maximal repetitions and one leg with 6x10 maximal repetitions and (4) a control group with an initial period of no training (similar in length to the training period of groups 1-3) followed by a period of 3x10 maximal repetitions on each leg. Leg training will consist of one-legged leg press and one-legged knee extensions. All groups, except the control group (during the no-training control period), will train the upper body by 3x10 maximal repetitions in bench press and lying rowing. Prior to the 7 week training intervention, all four groups will go through a 3-week period of familiarization to training and repeated testing (4 test time points for performance measures).
This design allows us to investigate the benefits of a contralateral design compared to the more common two-group design, the intra-individual variation vs the inter-individual variation, the potential contralateral effect of training one leg on the physiology and functional abilities of the non-trained leg, and whether or not these perspective are affected by training volume. We will also investigate whether participant classification into low or high responders is universal across several measures of muscle mass and strength, and between different training volumes. Further, by measuring several hypertrophy-related outcomes (e.g. changes in ribosome volume, activation of satellite cells and transcriptional changes), the investigators will extend previous findings regarding the effects of training volume on these variables and their ability to predict training outcomes.
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38 participants in 4 patient groups
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Data sourced from clinicaltrials.gov
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