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Record W3163820360 · doi:10.3390/ijms22105179

Mitochondrial Bioenergetics and Turnover during Chronic Muscle Disuse

2021· review· en· W3163820360 on OpenAlexafffund
Jonathan M. Memme, Mikhaela Slavin, Neushaw Moradi, David A. Hood

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMuscle atrophyMitophagyMitochondrial biogenesisBioenergeticsMitochondrionAtrophyBiologymitochondrial fusionMyocyteMFN2Cell biologyInternal medicineMitochondrial DNAMedicineAutophagyBiochemistryGeneticsGene

Abstract

fetched live from OpenAlex

Periods of muscle disuse promote marked mitochondrial alterations that contribute to the impaired metabolic health and degree of atrophy in the muscle. Thus, understanding the molecular underpinnings of muscle mitochondrial decline with prolonged inactivity is of considerable interest. There are translational applications to patients subjected to limb immobilization following injury, illness-induced bed rest, neuropathies, and even microgravity. Studies in these patients, as well as on various pre-clinical rodent models have elucidated the pathways involved in mitochondrial quality control, such as mitochondrial biogenesis, mitophagy, fission and fusion, and the corresponding mitochondrial derangements that underlie the muscle atrophy that ensues from inactivity. Defective organelles display altered respiratory function concurrent with increased accumulation of reactive oxygen species, which exacerbate myofiber atrophy via degradative pathways. The preservation of muscle quality and function is critical for maintaining mobility throughout the lifespan, and for the prevention of inactivity-related diseases. Exercise training is effective in preserving muscle mass by promoting favourable mitochondrial adaptations that offset the mitochondrial dysfunction, which contributes to the declines in muscle and whole-body metabolic health. This highlights the need for further investigation of the mechanisms in which mitochondria contribute to disuse-induced atrophy, as well as the specific molecular targets that can be exploited therapeutically.

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 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 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 score0.990
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

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 science0.0010.000
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 head0.321
Teacher spread0.304 · 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 teacher head, 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

Citations53
Published2021
Admission routes2
Has abstractyes

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