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Record W1847176293 · doi:10.3389/fphys.2015.00283

Satellite cells in human skeletal muscle plasticity

2015· review· en· W1847176293 on OpenAlex
Tim Snijders, Joshua P. Nederveen, Bryon R. McKay, Sophie Joanisse, Lex B. Verdijk, Luc J. C. van Loon, Gianni Parise

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Physiology · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsMcMaster University Medical CentreMcMaster University
Fundersnot available
KeywordsSkeletal muscleSatelliteBiologyContext (archaeology)Cell biologyNeuroscienceCellRegeneration (biology)AnatomyGeneticsEngineering

Abstract

fetched live from OpenAlex

Skeletal muscle satellite cells are considered to play a crucial role in muscle fiber maintenance, repair and remodeling. Our knowledge of the role of satellite cells in muscle fiber adaptation has traditionally relied on in vitro cell and in vivo animal models. Over the past decade, a genuine effort has been made to translate these results to humans under physiological conditions. Findings from in vivo human studies suggest that satellite cells play a key role in skeletal muscle fiber repair/remodeling in response to exercise. Mounting evidence indicates that aging has a profound impact on the regulation of satellite cells in human skeletal muscle. Yet, the precise role of satellite cells in the development of muscle fiber atrophy with age remains unresolved. This review seeks to integrate recent results from in vivo human studies on satellite cell function in muscle fiber repair/remodeling in the wider context of satellite cell biology whose literature is largely based on animal and cell models.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.288
Teacher spread0.270 · 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