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Record W2075512365 · doi:10.1002/cbf.1416

p38<sup>MAPK</sup> regulation of transcription factor targets in muscle and heart of the hibernating bat, <i>Myotis lucifugus</i>

2007· article· en· W2075512365 on OpenAlexaff
Sean Eddy, Kenneth B. Storey

Bibliographic record

VenueCell Biochemistry and Function · 2007
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsCarleton University
Fundersnot available
KeywordsMyotis lucifugusCREBHibernation (computing)BiologyTorporSkeletal muscleTranscription factorp38 mitogen-activated protein kinasesMAPK/ERK pathwayInternal medicineEndocrinologyCell biologyPhosphorylationGeneBiochemistryThermoregulationMedicineEcology

Abstract

fetched live from OpenAlex

Mammalian hibernation combines a profound net metabolic rate suppression with the selective up-regulation of key genes whose protein products address specific metabolic needs of the hibernator. The signal transduction pathways and transcription factors involved in regulating hibernation-responsive gene expression are of great interest. The present study suggests an important role for the p38 mitogen-activated protein kinase (p38 MAPK) and selected downstream transcription factors under its control (CREB, ATF-2, Elk-1) in the metabolic response by skeletal muscle during hibernation of little brown bats, Myotis lucifugus. Western blotting was used to quantify both total protein and levels of the phosphorylated, active forms of p38 MAPK, CREB, ATF-2 and Elk-1 in both skeletal muscle and heart of euthermic and hibernating bats. The p38 MAPK pathway was not apparently activated in heart during torpor but skeletal muscle showed strong increases (2.2-11-fold) in the amounts of phosphorylated p38 T180/Y182, CREB S133, ATF-2T69/71 and Elk-1(S383) in the torpid versus aroused state. By contrast both total and phosphorylated levels of Elk-1 in heart were reduced during hibernation to just 30% of the euthermic values. These data implicate p38 MAPK and its transcription factor targets, CREB, ATF-2 and Elk-1 in skeletal muscle maintenance during hibernation.

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 score0.227
Threshold uncertainty score0.296

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 head0.212
Teacher spread0.203 · 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

Citations43
Published2007
Admission routes1
Has abstractyes

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