Muscle hypertrophy and muscle strength: dependent or independent variables? A provocative review

Reggiani, C; Schiaffino, Stefano

doi:10.4081/ejtm.2020.9311

Cited by 50 publications

(38 citation statements)

References 76 publications

(101 reference statements)

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“…The need of sports-specic measure is highlighted for example by the possible counterintuitive eects of hypertrophy to strength levels described in recent research. Reggiani et al [664] showed that the increase in muscle mass did not necessarily lead to increase in strength and vice versa [664], and in worst case, the increase in muscle mass was shown to decrease strength production [664,718]. There also seems to exist multiple types of muscle hypertrophy [664,820], with the concept of task-specic hypertrophy [820] becoming relevant when trying to transfer the gains from strength training program to improvements in the particular sport of the athlete [906].…”

Section: Precision Strength Trainingmentioning

confidence: 99%

“…Reggiani et al [664] showed that the increase in muscle mass did not necessarily lead to increase in strength and vice versa [664], and in worst case, the increase in muscle mass was shown to decrease strength production [664,718]. There also seems to exist multiple types of muscle hypertrophy [664,820], with the concept of task-specic hypertrophy [820] becoming relevant when trying to transfer the gains from strength training program to improvements in the particular sport of the athlete [906]. For instance sports as dierent as combat sports [485,765] and ballet [16,180,818], can be beneted for similar plyometric/ballistic training for explosive force production [906] mixed with some maximum strength training.…”

Section: Precision Strength Trainingmentioning

confidence: 99%

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Precision strength training: Data-driven artificial intelligence approach to strength and conditioning

Teikari¹,

Pietrusz²

2021

Preprint

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In strength training, personalised strength training (autoregulation) approaches have been used to individualise exercise programs with monitoring an for dynamic adjustment based on their responses to training. While this transition from tradition-based training to evidence-based training framework has been an improvement in training practices, we argue that the future of strength training will also incorporate deep learning models powered by data. We refer to this data-driven framework as precision strength training inspired by the similar modeling frameworks used in precision medicine. In contrast to current personalised training in which the acquired athlete data is often subject to human expert decision-making, we are anticipating the rise of human-in-the-loop systems with an augmented coach who will be doing decisions collaboratively with the machine. Similar to other precision frameworks, such as precision health, we envision such a future to take decades to be realised and we focus here on practical short-term targets on a way to long-term realisation. In this chapter, we will review the measurement technology needed for continuous data acquisition from an individual during training/physical activity, how to acquire these datasets for the development of such systems and, how a proof-of-concept system could be developed for powerlifting training with applicability to general strength and conditioning (S&C) and physical rehabilitation purposes. Additionally, we will evaluate how the user experience (UX) of the system feedback and visualisation could be designed.

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Section: Precision Strength Trainingmentioning

confidence: 99%

Section: Precision Strength Trainingmentioning

confidence: 99%

Precision strength training: Data-driven artificial intelligence approach to strength and conditioning

Teikari¹,

Pietrusz²

2021

Preprint

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“…Resistance training increases variables associated with muscle hypertrophy and strength (reviewed in [1]). However, the morphological adaptations that occur in myofibers during resistance training have not been fully elucidated [2,3]. It is generally assumed that increases in muscle fiber cross-sectional area (fCSA) with weeks to months of training coincides with the proportional expansion of all intracellular components (i.e., conventional hypertrophy).…”

Section: Introductionmentioning

confidence: 99%

Myofibril and Mitochondrial Area Changes in Type I and II Fibers Following 10 Weeks of Resistance Training in Previously Untrained Men

Ruple

Godwin

Mesquita

et al. 2021

Preprint

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Resistance training increases myofiber hypertrophy, but the morphological adaptations that occur within myofibers remain largely unresolved. Fifteen males with minimal training experience (24±4 years, 17.9±1.4 kg/m2 lean body mass index) performed 10 weeks of conventional, full-body resistance training (2x weekly). Body composition, the radiological density of the vastus lateralis muscle using peripheral quantitative computed tomography (pQCT), and vastus lateralis muscle biopsies were obtained one week prior to and 72 hours following the last training bout. Fiber typing and the quantification of myofibril and mitochondrial areas per fiber were performed using histology/immunohistochemistry (IHC) techniques. Relative myosin heavy chain and actin protein abundances per wet muscle weight as well as citrate synthase (CS) activity assays were also obtained on tissue lysates. Training increased whole-body lean mass, mid-thigh muscle cross-sectional area, various strength metrics, and mean and type II fiber cross sectional areas (fCSA) (p<0.05). Myofibril areas in type I or II fibers were not altered with training, suggesting a proportional expansion with fCSA increases. Relative myosin heavy chain and actin protein abundances also did not change with training. IHC indicated training increased mitochondrial areas in both fiber types (p=0.018). However, CS activity levels remained unaltered with training. Interestingly, although pQCT-derived muscle density increased with training (p=0.036), suggestive of myofibril packing, a positive association existed between training-induced changes in this metric and changes in type I+II myofibril areas (r=0.600, p=0.018). Shorter-term resistance training seemingly involves a proportional expansion of myofibrils and an accelerated expansion of mitochondria in type I and II fibers. Additionally, histological and biochemical techniques should be viewed independently from one another given the lack of agreement between the variables assessed herein. Finally, the pQCT may be a viable tool to non-invasively track morphological changes in muscle tissue.

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“…Epigenetic mechanisms might also be related to the observation that some individuals seem to have less malleable muscles than others, i.e. exercise resistance (17)(18)(19)).…”

Section: Introductionmentioning

confidence: 99%

The epigenetic landscape in purified myonuclei from fast and slow muscles

Bengtsen

Eftestøl

et al. 2021

Preprint

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Muscle cells have different phenotypes adapted to different usage and can be grossly divided into fast/glycolytic and slow/oxidative types. While most muscles contain a mixture of such fiber types, we aimed at providing a genome-wide analysis of chromatin environment by ChIP-Seq in two muscle extremes, the almost completely fast/glycolytic extensor digitorum longus (EDL) and slow/oxidative soleus muscles. Muscle is a heterogeneous tissue where less than 60% of the nuclei are inside muscle fibers. Since cellular homogeneity is critical in epigenome-wide association studies we devised a new method for purifying skeletal muscle nuclei from whole tissue based on the nuclear envelope protein Pericentriolar material 1 (PCM1) being a specific marker for myonuclei. Using antibody labeling and a magnetic-assisted sorting approach we were able to sort out myonuclei with 95% purity. The sorting eliminated influence from other cell types in the tissue and improved the myo-specific signal. A genome-wide comparison of the epigenetic landscape in EDL and soleus reflected the functional properties of the two muscles each with a distinct regulatory program involving distal enhancers, including a glycolytic super-enhancer in the EDL. The two muscles are also regulated by different sets of transcription factors; e.g. in soleus binding sites for MEF2C, NFATC2 and PPARA were enriched, while in EDL MYOD1 and SOX1 binding sites were found to be overrepresented. In addition, novel factors for muscle regulation such as MAF, ZFX and ZBTB14 were identified.

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Muscle hypertrophy and muscle strength: dependent or independent variables? A provocative review

Cited by 50 publications

References 76 publications

Precision strength training: Data-driven artificial intelligence approach to strength and conditioning

Precision strength training: Data-driven artificial intelligence approach to strength and conditioning

Myofibril and Mitochondrial Area Changes in Type I and II Fibers Following 10 Weeks of Resistance Training in Previously Untrained Men

The epigenetic landscape in purified myonuclei from fast and slow muscles

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