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Record W2151136828 · doi:10.1093/gerona/61.7.675

No Decline in Skeletal Muscle Oxidative Capacity With Aging in Long-Term Calorically Restricted Rats: Effects Are Independent of Mitochondrial DNA Integrity

2006· article· en· W2151136828 on OpenAlexafffund
David Baker, Andrew C. Betik, Daniel J. Krause, Russell T. Hepple

Bibliographic record

VenueThe Journals of Gerontology Series A · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsMitochondrial DNATerm (time)Oxidative damageSkeletal muscleOxidative phosphorylationBiologyOxidative stressEndocrinologyGeneticsPhysicsBiochemistryGene

Abstract

fetched live from OpenAlex

We investigated if calorie restriction (CR) preserved skeletal muscle oxidative capacity with aging after accounting for life span extension by CR, and determined if mitochondrial content, mitochondrial DNA integrity, and peroxisome proliferator-activated receptor gamma coactivator-1alpha (PGC-1alpha) were involved. Ad libitum-fed (AL) and CR animals representing young adult, late middle age, and senescence were studied. Whereas citrate synthase and complex IV activities were lower in plantaris and gastrocnemius muscle of young adult CR animals, in contrast to the 15%-40% decline in senescent AL animals, there was no decline with aging in CR animals. There was no decline in citrate synthase protein in gastrocnemius with aging in either group, suggesting that CR preserves oxidative capacity with aging by protecting mitochondrial function rather than content. This protection was independent of mitochondrial DNA damage between groups. However, there was a slower decline in PGC-1alpha gene expression with aging in CR versus AL animals, suggesting a better maintenance of mitochondrial biogenesis with aging in CR animals.

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 score0.675
Threshold uncertainty score0.984

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 head0.019
GPT teacher head0.268
Teacher spread0.249 · 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

Citations87
Published2006
Admission routes2
Has abstractyes

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