Literature DB >> 31999527

Muscle fiber typology substantially influences time to recover from high-intensity exercise.

Eline Lievens1, Malgorzata Klass2, Tine Bex1, Wim Derave1.   

Abstract

Human fast-twitch muscle fibers generate high power in a short amount of time but are easily fatigued, whereas slow-twitch fibers are more fatigue resistant. The transfer of this knowledge to coaching is hampered by the invasive nature of the current evaluation of muscle typology by biopsies. Therefore, a noninvasive method was developed to estimate muscle typology through proton magnetic resonance spectroscopy in the gastrocnemius. The aim of this study was to investigate whether male subjects with an a priori-determined fast typology (FT) are characterized by a more pronounced Wingate exercise-induced fatigue and delayed recovery compared with subjects with a slow typology (ST). Ten subjects with an estimated higher percentage of fast-twitch fibers and 10 subjects with an estimated higher percentage of slow-twitch fibers underwent the test protocol, consisting of three 30-s all-out Wingate tests. Recovery of knee extension torque was evaluated by maximal voluntary contraction combined with electrical stimulation up to 5 h after the Wingate tests. Although both groups delivered the same mean power across all Wingates, the power drop was higher in the FT group (-61%) compared with the ST group (-41%). The torque at maximal voluntary contraction had fully recovered in the ST group after 20 min, whereas the FT group had not yet recovered 5 h into recovery. This noninvasive estimation of muscle typology can predict the extent of fatigue and time to recover following repeated all-out exercise and may have applications as a tool to individualize training and recovery cycles.NEW & NOTEWORTHY A one-fits-all training regime is present in most sports, though the same training implies different stimuli in athletes with a distinct muscle typology. Individualization of training based on this muscle typology might be important to optimize performance and to lower the risk for accumulated fatigue and potentially injury. When conducting research, one should keep in mind that the muscle typology of participants influences the severity of fatigue and might therefore impact the results.

Entities:  

Keywords:  Wingate testing; fatigue; muscle fiber type composition; training-recovery cycles

Mesh:

Year:  2020        PMID: 31999527     DOI: 10.1152/japplphysiol.00636.2019

Source DB:  PubMed          Journal:  J Appl Physiol (1985)        ISSN: 0161-7567


  16 in total

1.  Skeletal Muscle Phenotype in Patients Undergoing Long-Term Hemodialysis Awaiting Kidney Transplantation.

Authors:  Jean-Sébastien Souweine; Fares Gouzi; Éric Badia; Pascal Pomies; Valérie Garrigue; Marion Morena; Maurice Hayot; Jacques Mercier; Bronia Ayoub; Moglie Le Quintrec; Fabrice Raynaud; Jean-Paul Cristol
Journal:  Clin J Am Soc Nephrol       Date:  2021-11       Impact factor: 8.237

2.  Anaerobic Speed/Power Reserve and Sport Performance: Scientific Basis, Current Applications and Future Directions.

Authors:  Gareth N Sandford; Paul B Laursen; Martin Buchheit
Journal:  Sports Med       Date:  2021-08-16       Impact factor: 11.928

3.  High-throughput muscle fiber typing from RNA sequencing data.

Authors:  Nikolay Oskolkov; Malgorzata Santel; Hemang M Parikh; Ola Ekström; Gray J Camp; Eri Miyamoto-Mikami; Kristoffer Ström; Bilal Ahmad Mir; Dmytro Kryvokhyzha; Mikko Lehtovirta; Hiroyuki Kobayashi; Ryo Kakigi; Hisashi Naito; Karl-Fredrik Eriksson; Björn Nystedt; Noriyuki Fuku; Barbara Treutlein; Svante Pääbo; Ola Hansson
Journal:  Skelet Muscle       Date:  2022-07-02       Impact factor: 5.063

Review 4.  Using Field Based Data to Model Sprint Track Cycling Performance.

Authors:  Hamish A Ferguson; Chris Harnish; J Geoffrey Chase
Journal:  Sports Med Open       Date:  2021-03-16

5.  Association of muscle fiber composition with health and exercise-related traits in athletes and untrained subjects.

Authors:  Elliott C R Hall; Ekaterina A Semenova; Elvira A Bondareva; Oleg V Borisov; Oleg N Andryushchenko; Liliya B Andryushchenko; Piotr Zmijewski; Edward V Generozov; Ildus I Ahmetov
Journal:  Biol Sport       Date:  2021-02-05       Impact factor: 4.606

6.  Prediction of muscle fiber composition using multiple repetition testing.

Authors:  Elliott C R Hall; Evgeny A Lysenko; Ekaterina A Semenova; Oleg V Borisov; Oleg N Andryushchenko; Liliya B Andryushchenko; Tatiana F Vepkhvadze; Egor M Lednev; Piotr Zmijewski; Daniil V Popov; Edward V Generozov; Ildus I Ahmetov
Journal:  Biol Sport       Date:  2020-10-22       Impact factor: 2.806

Review 7.  The Hamstrings: Anatomic and Physiologic Variations and Their Potential Relationships With Injury Risk.

Authors:  José Afonso; Sílvia Rocha-Rodrigues; Filipe M Clemente; Michele Aquino; Pantelis T Nikolaidis; Hugo Sarmento; Alberto Fílter; Jesús Olivares-Jabalera; Rodrigo Ramirez-Campillo
Journal:  Front Physiol       Date:  2021-07-07       Impact factor: 4.566

Review 8.  Maximal muscular power: lessons from sprint cycling.

Authors:  Jamie Douglas; Angus Ross; James C Martin
Journal:  Sports Med Open       Date:  2021-07-15

9.  Response to Three Weeks of Sprint Interval Training Cannot Be Explained by the Exertional Level.

Authors:  Raulas Krusnauskas; Nerijus Eimantas; Neringa Baranauskiene; Tomas Venckunas; Audrius Snieckus; Marius Brazaitis; Hakan Westerblad; Sigitas Kamandulis
Journal:  Medicina (Kaunas)       Date:  2020-08-07       Impact factor: 2.430

10.  Recovery from Different High-Intensity Interval Training Protocols: Comparing Well-Trained Women and Men.

Authors:  Laura Hottenrott; Martin Möhle; Alexander Ide; Sascha Ketelhut; Oliver Stoll; Kuno Hottenrott
Journal:  Sports (Basel)       Date:  2021-03-02
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