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Record W4405374407 · doi:10.1042/bsr20240137

Recycle, repair, recover: the role of autophagy in modulating skeletal muscle repair and post-exercise recovery

2024· review· en· W4405374407 on OpenAlex

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

VenueBioscience Reports · 2024
Typereview
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsUniversity of Toronto
FundersAcademy of Medical Sciences
KeywordsSkeletal muscleCell biologyAutophagyBiologyContext (archaeology)OrganelleApoptosisAnatomyBiochemistry

Abstract

fetched live from OpenAlex

Skeletal muscle is a highly plastic tissue that can adapt relatively rapidly to a range of stimuli. In response to novel mechanical loading, e.g. unaccustomed resistance exercise, myofibers are disrupted and undergo a period of ultrastructural remodeling to regain full physiological function, normally within 7 days. The mechanisms that underpin this remodeling are believed to be a combination of cellular processes including ubiquitin-proteasome/calpain-mediated degradation, immune cell infiltration, and satellite cell proliferation/differentiation. A relatively understudied system that has the potential to be a significant contributing mechanism to repair and recovery is the autophagolysosomal system, an intracellular process that degrades damaged and redundant cellular components to provide constituent metabolites for the resynthesis of new organelles and cellular structures. This review summarizes our current understanding of the autophagolysosomal system in the context of skeletal muscle repair and recovery. In addition, we also provide hypothetical models of how this system may interact with other processes involved in skeletal muscle remodeling and provide avenues for future research to improve our understanding of autophagy in human skeletal muscle.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.309
Teacher spread0.292 · 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