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Mechanisms of Exercise‐Induced Mitochondrial Biogenesis in Skeletal Muscle: Implications for Health and Disease

2011· article· en· W4409087816 on OpenAlexaff
David A. Hood, Giulia Uguccioni, Anna Vainshtein, Donna M. D’Souza

Bibliographic record

VenueComprehensive physiology · 2011
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsYork University
Fundersnot available
KeywordsMitochondrial biogenesisDiseaseSkeletal muscleBiogenesisMitochondrionMedicineBiologyCell biologyInternal medicineGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Mitochondria have paradoxical functions within cells. Essential providers of energy for cellular survival, they are also harbingers of cell death (apoptosis). Mitochondria exhibit remarkable dynamics, undergoing fission, fusion, and reticular expansion. Both nuclear and mitochondrial DNA (mtDNA) encode vital sets of proteins which, when incorporated into the inner mitochondrial membrane, provide electron transport capacity for ATP production, and when mutated lead to a broad spectrum of diseases. Acute exercise can activate a set of signaling cascades in skeletal muscle, leading to the activation of the gene expression pathway, from transcription, to post‐translational modifications. Research has begun to unravel the important signals and their protein targets that trigger the onset of mitochondrial adaptations to exercise. Exercise training leads to an accumulation of nuclear‐ and mtDNA‐encoded proteins that assemble into functional complexes devoted to mitochondrial respiration, reactive oxygen species (ROS) production, the import of proteins and metabolites, or apoptosis. This process of biogenesis has important consequences for metabolic health, the oxidative capacity of muscle, and whole body fitness. In contrast, the chronic muscle disuse that accompanies aging or muscle wasting diseases provokes a decline in mitochondrial content and function, which elicits excessive ROS formation and apoptotic signaling. Research continues to seek the molecular underpinnings of how regular exercise can be used to attenuate these decrements in organelle function, maintain skeletal muscle health, and improve quality of life. © 2011 American Physiological Society. Compr Physiol 1:1119‐1134, 2011.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.971
Threshold uncertainty score0.468

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 science0.0000.000
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 head0.063
GPT teacher head0.324
Teacher spread0.261 · 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 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

Citations20
Published2011
Admission routes1
Has abstractyes

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