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Record W2162571565 · doi:10.1139/o03-056

Differential expression of Akt, PPARγ, and PGC-1 during hibernation in bats

2003· article· en· W2162571565 on OpenAlexafffundvenue
Sean Eddy, Kenneth B. Storey

Bibliographic record

VenueBiochemistry and Cell Biology · 2003
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsTorporProtein kinase BBrown adipose tissueInternal medicineEndocrinologyBiologyWhite adipose tissueMyotis lucifugusHibernation (computing)Adipose tissuePeroxisome proliferator-activated receptorCatabolismPhosphorylationReceptorCell biologyMetabolismBiochemistryThermoregulationMedicine

Abstract

fetched live from OpenAlex

The effects of hibernation on the expression of Akt (protein kinase B), the peroxisome proliferator-activated receptor gamma isoform (PPARgamma), and the PPARgamma coactivator PGC-1 were assessed in seven tissues of the little brown bat, Myotis lucifugus. Western blotting revealed that the levels of active phosphorylated Akt were strongly reduced in brain, kidney, liver, and white adipose during torpor as compared with aroused animals and that total Akt protein was also reduced in white adipose during torpor. By contrast, both total and phospho-Akt were elevated in brown adipose tissue, the thermogenic organ. PPARgamma and PGC-1 levels showed parallel changes in all organs. Both were strongly suppressed in brain, but levels increased significantly in all other organs during hibernation (except for PGC-1 in heart). Reduced Akt activity is consistent with a probable reduced insulin response during torpor that facilitates the mobilization of lipid reserves for fuel supply and is further supported by increased gene expression of enzymes and proteins involved in lipid catabolism under the stimulation of enhanced PPARgamma and PGC-1 levels.

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 score0.004
Threshold uncertainty score0.224

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 head0.008
GPT teacher head0.238
Teacher spread0.230 · 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

Citations76
Published2003
Admission routes3
Has abstractyes

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