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Record W2809821989 · doi:10.1113/jp275560

Beta <sub>2</sub> ‐adrenoceptor agonist salbutamol increases protein turnover rates and alters signalling in skeletal muscle after resistance exercise in young men

2018· article· en· W2809821989 on OpenAlexfundno aff
Morten Hostrup, Søren Reitelseder, Søren Jessen, Anders Kalsen, Michael Nyberg, Jon Egelund, Michael Kreiberg, Caroline Maag Kristensen, Martin Thomassen, Henriette Pilegaard, Vibeke Backer, Glenn A. Jacobson, Lars Holm, Jens Bangsbo

Bibliographic record

VenueThe Journal of Physiology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPharmacological Effects and Assays
Canadian institutionsnot available
FundersKulturministerietWorld Anti-Doping Agency
KeywordsSalbutamolAgonistEndocrinologySkeletal muscleInternal medicineResistance trainingSignallingAdrenergic receptorReceptorChemistryMedicineBiologyCell biology

Abstract

fetched live from OpenAlex

Key points Animal models have shown that beta 2 ‐adrenoceptor stimulation increases protein synthesis and attenuates breakdown processes in skeletal muscle. Thus, the beta 2 ‐adrenoceptor is a potential target in the treatment of disuse‐, disease‐ and age‐related muscle atrophy. In the present study, we show that a few days of oral treatment with the commonly prescribed beta 2 ‐adrenoceptor agonist, salbutamol, increased skeletal muscle protein synthesis and breakdown during the first 5 h after resistance exercise in young men. Salbutamol also counteracted a negative net protein balance in skeletal muscle after resistance exercise. Changes in protein turnover rates induced by salbutamol were associated with protein kinase A‐signalling, activation of Akt2 and modulation of mRNA levels of growth‐regulating proteins in skeletal muscle. These findings indicate that protein turnover rates can be augmented by beta 2 ‐adrenoceptor agonist treatment during recovery from resistance exercise in humans. Abstract The effect of beta 2 ‐adrenoceptor stimulation on skeletal muscle protein turnover and intracellular signalling is insufficiently explored in humans, particularly in association with exercise. In a randomized, placebo‐controlled, cross‐over study investigating 12 trained men, the effects of beta 2 ‐agonist (6 × 4 mg oral salbutamol) on protein turnover rates, intracellular signalling and mRNA response in skeletal muscle were investigated 0.5–5 h after quadriceps resistance exercise. Each trial was preceded by a 4‐day lead‐in treatment period. Leg protein turnover rates were assessed by infusion of [ 13 C 6 ]‐phenylalanine and sampling of arterial and venous blood, as well as vastus lateralis muscle biopsies 0.5 and 5 h after exercise. Furthermore, myofibrillar fractional synthesis rate, intracellular signalling and mRNA response were measured in muscle biopsies. The mean (95% confidence interval) myofibrillar fractional synthesis rate was higher for salbutamol than placebo [0.079 (95% CI, 0.064 to 0.093) vs . 0.066 (95% CI, 0.056 to 0.075%) × h −1 ] ( P < 0.05). Mean net leg phenylalanine balance 0.5–5 h after exercise was higher for salbutamol than placebo [3.6 (95% CI, 1.0 to 6.2 nmol) × min −1 × 100 g Leg Lean Mass −1 ] ( P < 0.01). Phosphorylation of Akt2, cAMP response element binding protein and PKA substrate 0.5 and 5 h after exercise, as well as phosphorylation of eEF2 5 h after exercise, was higher ( P < 0.05) for salbutamol than placebo. Calpain‐1, Forkhead box protein O1, myostatin and Smad3 mRNA content was higher ( P < 0.01) for salbutamol than placebo 0.5 h after exercise, as well as Forkhead box protein O1 and myostatin mRNA content 5 h after exercise, whereas ActivinRIIB mRNA content was lower ( P < 0.01) for salbutamol 5 h after exercise. These observations suggest that beta 2 ‐agonist increases protein turnover rates in skeletal muscle after resistance exercise in humans, with concomitant cAMP/PKA and Akt2 signalling, as well as modulation of mRNA response of growth‐regulating proteins.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.227
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations64
Published2018
Admission routes1
Has abstractyes

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