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Record W2525933343 · doi:10.1038/srep33944

Mitochondrial ROS regulate oxidative damage and mitophagy but not age-related muscle fiber atrophy

2016· article· en· W2525933343 on OpenAlexfundno aff
Giorgos K. Sakellariou, Tim Pearson, Adam P. Lightfoot, Gareth Nye, Nicola Wells, Ifigeneia Giakoumaki, Aphrodite Vasilaki, Richard Griffiths, Malcolm J. Jackson, Anne McArdle

Bibliographic record

VenueScientific Reports · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsnot available
FundersNational Institute on AgingMedical Research CouncilMcGill University Health CentreBuck Institute for Research on AgingOklahoma Medical Research FoundationMcGill University
KeywordsMitophagySarcopeniaOxidative stressAtrophySkeletal muscleMuscle atrophyMitochondrionOxidative phosphorylationBiologyMuscle weaknessCell biologyInternal medicineMedicineEndocrinologyAnatomyBiochemistryAutophagyApoptosis

Abstract

fetched live from OpenAlex

Age-related loss of skeletal muscle mass and function is a major contributor to morbidity and has a profound effect on the quality of life of older people. The potential role of age-dependent mitochondrial dysfunction and cumulative oxidative stress as the underlying cause of muscle aging remains a controversial topic. Here we show that the pharmacological attenuation of age-related mitochondrial redox changes in muscle with SS31 is associated with some improvements in oxidative damage and mitophagy in muscles of old mice. However, this treatment failed to rescue the age-related muscle fiber atrophy associated with muscle atrophy and weakness. Collectively, these data imply that the muscle mitochondrial redox environment is not a key regulator of muscle fiber atrophy during sarcopenia but may play a key role in the decline of mitochondrial organelle integrity that occurs with muscle aging.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.532

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 studies0.0000.001
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 head0.007
GPT teacher head0.221
Teacher spread0.215 · 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

Citations135
Published2016
Admission routes1
Has abstractyes

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