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Record W4388446849 · doi:10.1113/jp285129

The potassium–glycogen interaction on force and excitability in mouse skeletal muscle: implications for fatigue

2023· article· en· W4388446849 on OpenAlexafffund
Simeon P. Cairns, Jean‐Marc Renaud

Bibliographic record

VenueThe Journal of Physiology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Ottawa
FundersGovernment of Canada
KeywordsGlycogenIsometric exerciseInternal medicineEndocrinologyChemistrySkeletal muscleDepolarizationBiologyMedicine

Abstract

fetched live from OpenAlex

Abstract A reduced muscle glycogen content and potassium (K+) disturbances across muscle membranes occur concomitantly during repeated intense exercise and together may contribute to skeletal muscle fatigue. Therefore, we examined whether raised extracellular K+ concentration ([K+]o) (4 to 11 mM) interacts with lowered glycogen to reduce force production. Isometric contractions were evoked in isolated mouse soleus muscles (37°C) using direct supramaximal field stimulation. (1) Glycogen declined markedly in non‐fatigued muscle with >2 h exposure in glucose‐free physiological saline compared with control solutions (11 mM glucose), i.e. to <45% control. (2) Severe glycogen depletion was associated with increased 5′‐AMP‐activated protein kinase activity, indicative of metabolic stress. (3) The decline of peak tetanic force at 11 mM [K+]o was exacerbated from 67% initial at normal glycogen to 22% initial at lowered glycogen. This was due to a higher percentage of inexcitable fibres (71% vs. 43%), yet without greater sarcolemmal depolarisation or smaller amplitude action potentials. (4) Returning glucose while at 11 mM [K+]o increased both glycogen and force. (5) Exposure to 4 mM [K+]o glucose‐free solutions (15 min) did not increase fatiguability during repeated tetani; however, after recovery there was a greater force decline at 11 mM [K+]o at lower than normal glycogen. (6) An important exponential relationship was established between relative peak tetanic force at 11 mM [K+]o and muscle glycogen content. These findings provide direct evidence of a synergistic interaction between raised [K+]o and lowered muscle glycogen as the latter shifts the peak tetanic force–resting EM relationship towards more negative resting EM due to lowered sarcolemmal excitability, which hence may contribute to muscle fatigue. image Key points Diminished muscle glycogen levels and raised extracellular potassium concentrations ([K+]o) occur simultaneously during intense exercise and together may contribute to muscle fatigue. Prolonged exposure of isolated non‐fatigued soleus muscles of mice to glucose‐free physiological saline solutions markedly lowered muscle glycogen levels, as does fatigue then recovery in glucose‐free solutions. For both approaches, the subsequent decline of maximal force at 11 mM [K+]o, which mimics interstitial [K+] levels during intense exercise, was exacerbated at lowered compared with normal glycogen. This was mainly due to many more muscle fibres becoming inexcitable. We established an important relationship that provides evidence of a synergistic interaction between raised [K+]o and lowered glycogen content to reduce force production. This paper indicates that partially lowered muscle glycogen (and/or metabolic stress) together with elevated interstitial [K+] interactively lowers muscle force, and hence may diminish performance especially during repeated high‐intensity exercise.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.026
GPT teacher head0.308
Teacher spread0.283 · 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

Citations14
Published2023
Admission routes2
Has abstractyes

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