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Record W2328108810 · doi:10.1242/jcs.093674

Skeletal muscle fatigue – regulation of excitation–contraction coupling to avoid metabolic catastrophe

2012· review· en· W2328108810 on OpenAlexafffund
Brian R. MacIntosh, Robert John Holash, Jean‐Marc Renaud

Bibliographic record

VenueJournal of Cell Science · 2012
Typereview
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRyanodine receptorBiologyMuscle contractionBiophysicsEndoplasmic reticulumContraction (grammar)MyosinATPaseCell biologyATP synthaseSkeletal muscleMyosin ATPaseAdenosine triphosphateBiochemistryAnatomyEndocrinologyEnzyme

Abstract

fetched live from OpenAlex

ATP provides the energy in our muscles to generate force, through its use by myosin ATPases, and helps to terminate contraction by pumping Ca(2+) back into the sarcoplasmic reticulum, achieved by Ca(2+) ATPase. The capacity to use ATP through these mechanisms is sufficiently high enough so that muscles could quickly deplete ATP. However, this potentially catastrophic depletion is avoided. It has been proposed that ATP is preserved not only by the control of metabolic pathways providing ATP but also by the regulation of the processes that use ATP. Considering that contraction (i.e. myosin ATPase activity) is triggered by release of Ca(2+), the use of ATP can be attenuated by decreasing Ca(2+) release within each cell. A lower level of Ca(2+) release can be accomplished by control of membrane potential and by direct regulation of the ryanodine receptor (RyR, the Ca(2+) release channel in the terminal cisternae). These highly redundant control mechanisms provide an effective means by which ATP can be preserved at the cellular level, avoiding metabolic catastrophe. This Commentary will review some of the known mechanisms by which this regulation of Ca(2+) release and contractile response is achieved, demonstrating that skeletal muscle fatigue is a consequence of attenuation of contractile activation; a process that allows avoidance of metabolic catastrophe.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.065
GPT teacher head0.356
Teacher spread0.291 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations130
Published2012
Admission routes2
Has abstractyes

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