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Salt‐inducible kinase 1 links p300 phosphorylation to CREB regulated gluconeogenesis post burn

2012· article· en· W3173561500 on OpenAlexaff
Natasha C. Brooks, Alexandra H. Smith, Yaeko Hiyama, Celeste C. Finnerty, David N. Herndon, Darren Boehning, Marc G. Jeschke

Bibliographic record

VenueThe FASEB Journal · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNF-κB Signaling Pathways
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
FundersNational Institutes of HealthShriners Hospitals for Children
KeywordsCREBGluconeogenesisCatecholaminePropranololEndocrinologyInternal medicineActivator (genetics)KinaseChemistryBiologyReceptorMedicineTranscription factorGeneBiochemistryMetabolism

Abstract

fetched live from OpenAlex

Severe burn injury results in sustained catecholamine release and increased cyclic AMP (cAMP) levels. cAMP‐induced inhibition of salt‐inducible kinase 1 (SIK1) has been shown to promote recruitment of the transcriptional co‐activator p300 to cAMP response element binding protein (CREB), resulting in gluconeogenesis. Gluconeogenesis is increased and maintained post‐burn injury yet the molecular mechanism is unknown. We hypothesize that catecholamine‐induced inhibition of SIK1 resulting in increased p300 transcriptional activity sustains gluconeogenesis. The 60% total body surface area burn model on rats was employed as a model system. The catecholamine surge during burn injury led to the inhibition of SIK1, increased blood glucose levels, and increased p300 mediated transcription of CREB‐regulated gluconeogenic genes. Restoration of SIK1 activity by administration of propranolol, a non‐selective β1/2 adrenergic receptor antagonist, resulted in inhibition of p300‐ mediated transcription and decreased blood glucose levels. We conclude that catecholamine release after severe burn injury leads to inhibition of SIK1, resulting in sustained gluconeogenesis. This work was supported by grants from Shriners Hospitals for Children and (SHG 8660 and 6840) the National Institute of Health (RO1‐ GM087285‐0182)

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)0.001
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 score0.006
Threshold uncertainty score0.607

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.016
GPT teacher head0.245
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

Citations0
Published2012
Admission routes1
Has abstractyes

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