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Record W2892194479 · doi:10.1139/apnm-2018-0369

Effects of myostatin on the mechanical properties of muscles during repeated active lengthening in the mouse

2018· article· en· W2892194479 on OpenAlexvenueno aff
Danguolė Satkunskienė, Aivaras Ratkevičius, Sigitas Kamandulis, Tomas Venckūnas

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMyostatinBiologyChemistryMuscle hypertrophyEndocrinology

Abstract

fetched live from OpenAlex

The aim of the present study was to investigate how myostatin dysfunction affects fast and slow muscle stiffness and viscosity during severe repeated loading. Isolated extensor digitorum longus (EDL) and soleus muscles of young adult female mice of the BEH (dysfunctional myostatin) and BEH+/+ (functional myostatin) strains were subjected to 100 contraction-stretching loading cycles during which contractile and mechanical properties were assessed. BEH mice exhibited greater exercise-induced muscle damage, although the effect was muscle- and age-dependent and limited to the early phases of simulated exercise. The relative reduction of the EDL muscle isometric force recorded during the initial 10-30 loading cycles was greater in BEH mice than in BEH+/+ mice and exceeded that of the soleus muscle of either strain. The induced damage was associated with lower muscle stiffness. The effects of myostatin on the mechanical properties of muscles depend on muscle type and maturity.

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 score0.003

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 integrity0.0000.001
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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

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