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Record W2149167204 · doi:10.1093/gerona/59.2.b108

Fiber Atrophy and Hypertrophy in Skeletal Muscles of Late Middle-Aged Fischer 344 x Brown Norway F1-Hybrid Rats

2004· article· en· W2149167204 on OpenAlexafffund
Russell T. Hepple, Kristina Ross, A. B. Rempfer

Bibliographic record

VenueThe Journals of Gerontology Series A · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchUniversity of Calgary
KeywordsDenervationSoleus muscleMuscle hypertrophyAtrophyInternal medicineEndocrinologySarcopeniaGastrocnemius muscleCytochrome c oxidaseSkeletal muscleFiberAnatomyBiologyChemistryMedicineMitochondrionBiochemistry

Abstract

fetched live from OpenAlex

We examined young adult and late middle-aged male rats to test the hypothesis that gastrocnemius (a locomotor muscle) demonstrates reduced fiber size with aging, whereas soleus (a postural muscle) demonstrates atrophy of some fibers and compensatory hypertrophy in other fibers. Although body mass was greater in late middle-aged animals, mass was reduced in gastrocnemius but not soleus muscle. In another group of animals, physical activity was reduced by 34% in late middle-aged animals. Whereas mean fiber size was lower in gastrocnemius of late middle-aged animals, it was not different in soleus. Histograms revealed atrophied fibers (</=1000 micro m(2)) in soleus and gastrocnemius and hypertrophied fibers (>/=8000 micro m(2)) in soleus with aging. Atrophied fibers often demonstrated no subsarcolemmal mitochondrial staining, suggesting denervation, whereas hypertrophied fibers often demonstrated cytochrome oxidase deficiency, suggesting mitochondrial dysfunction. These results underscore the divergent influences (e.g., physical inactivity, denervation, mitochondrial dysfunction) affecting fiber size with 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 score0.374
Threshold uncertainty score0.516

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 head0.021
GPT teacher head0.249
Teacher spread0.228 · 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

Citations51
Published2004
Admission routes2
Has abstractyes

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