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Record W2002616643 · doi:10.1093/gerona/glp179

The Effect of Aging on Human Skeletal Muscle Mitochondrial and Intramyocellular Lipid Ultrastructure

2009· article· en· W2002616643 on OpenAlexafffund
Justin D. Crane, M. C. Devries, Adeel Safdar, Mazen J. Hamadeh, Mark A. Tarnopolsky

Bibliographic record

VenueThe Journals of Gerontology Series A · 2009
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsYork UniversityMcMaster University
FundersCanadian Institutes of Health Research
KeywordsMitochondrionEndocrinologyInternal medicineUltrastructureCitrate synthaseSkeletal muscleCytochrome c oxidaseBiologyLipid metabolismLipid dropletAgeingAnatomyBiochemistryEnzymeMedicine

Abstract

fetched live from OpenAlex

The purpose of this study was to determine whether ultrastructural changes in intramyocellular lipid (IMCL) and mitochondria occur with aging. Muscle samples were analyzed from 24 young and 20 old, equally active, individuals for IMCL and mitochondria quantity and size as well as their association. Old men had larger IMCL droplets than all other groups in the total muscle area. Old individuals showed higher IMCL content in the subsarcolemmal area. Young participants had a greater number of mitochondria compared with old participants in both fiber regions and greater enzyme activities of cytochrome c oxidase and citrate synthase. The fraction of IMCL touching mitochondria was lowest in old women in the total area and in old men in the subsarcolemmal region. In summary, older adults have larger IMCL droplets, fewer mitochondria, and a lower proportion of IMCL in contact with mitochondria. These factors likely contribute to age-related reductions in mitochondrial function and lipid metabolism.

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 score0.461
Threshold uncertainty score0.301

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 head0.017
GPT teacher head0.310
Teacher spread0.293 · 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

Citations259
Published2009
Admission routes2
Has abstractyes

Explore more

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