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Record W2090537649 · doi:10.1159/000213742

IMPLICATIONS OF INCREASED INTERCELLULAR VARIABILITY OF LIPOFUSCIN CONTENT WITH AGE IN DENTATE GYRUS GRANULE CELLS IN THE MOUSE

2009· article· en· W2090537649 on OpenAlexaff
W.A.L. Moore, Gwen O. Ivy

Bibliographic record

VenueGerontology · 2009
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversity of TorontoOntario Brain Institute
Fundersnot available
KeywordsLipofuscinDentate gyrusIntracellularGranule (geology)BiologyPopulationEndocrinologySenescenceInternal medicineMetabolismCell biologyHippocampusMedicineBiochemistry

Abstract

fetched live from OpenAlex

The purpose of this study was to further characterize lipofuscin (LF) accumulation with aging in brain cells, with a specific focus on the amount of intercellular variability of lipofuscin content within an apparently a homogenous population of dentate gyrus granule cells in the hippocampus of mice, as a function of age and caloric restriction (CR). Three age groups of CR and control mice including groups at maximum lifespan were studied. This study demonstrated that the intercellular variability of lipofuscin content was significantly greater in older mice and was significantly less in mice calorically restricted. Increased variability of metabolic function among cells with age, as measured by increased intercellular variability of lipofuscin content, may represent a definitive mechanism underlying the overall decreased efficiency of tissue and organ functioning that occurs with age. That this is so, is supported by the fact that CR, which has been shown to maintain the "youthful" state of many physiological functions, has been shown in this study to maintain the "youthful" state of low intercellular variability of lipofuscin content within a population of cells. LF accumulation may be a marker for the intrusion of entropy into cell 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.396

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 head0.046
GPT teacher head0.294
Teacher spread0.247 · 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 designObservational
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

Citations7
Published2009
Admission routes1
Has abstractyes

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