ArticleEuropean journal of applied physiology2020
Resistance training upregulates skeletal muscle Na
Article in European journal of applied physiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Six weeks of high-load resistance and low-load blood flow restricted training increase Na/K-ATPase sub-units α2 and β1 equally, but does not alter ClC-1 abundance in untrained human skeletal muscle.Journal of muscle research and cell motility · 2023Trial
- A century of exercise physiology: effects of muscle contraction and exercise on skeletal muscle NaEuropean journal of applied physiology · 2024Review
- Phase angle, muscle tissue, and resistance training.Reviews in endocrine & metabolic disorders · 2023Review
- Review
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe Na
methodsTwenty-one healthy young males (22.9 ± 4.6 year; 1.80 ± 0.70 m, 85.1 ± 17.8 kg, mean ± SD) underwent 7 weeks of resistance training, training three times per week (RT, n = 16) or control (CON, n = 5). The training program was effective with a 39% gain in leg press muscle strength (p = 0.001). A resting vastus lateralis muscle biopsy was taken before and following RT or CON and assayed for NKA content ([
resultsAfter RT, each of NKA content (12%, 311 ± 76 vs 349 ± 76 pmol g wet weight
conclusionsResistance training increased muscle NKA content through upregulation of both α
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.