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Record W2056907950 · doi:10.1126/science.1156037

Phosphorylation by p38 MAPK as an Alternative Pathway for GSK3β Inactivation

2008· article· en· W2056907950 on OpenAlexaff
Tina M. Thornton, Gustavo Pedraza‐Alva, Bin Deng, C. David Wood, Alexander Aronshtam, James L. Clements, Guadalupe Sabio, Roger J. Davis, Dwight E. Matthews, Bradley W. Doble, Mercedes Rincón

Bibliographic record

VenueScience · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicWnt/β-catenin signaling in development and cancer
Canadian institutionsMcMaster University
FundersNational Center for Research ResourcesNational Institute of Allergy and Infectious Diseases
KeywordsGSK-3PhosphorylationProtein kinase BCell biologyMAPK/ERK pathwayp38 mitogen-activated protein kinasesProtein kinase AGSK3BKinaseSubstrate-level phosphorylationChemistryCateninBiologySignal transductionWnt signaling pathway

Abstract

fetched live from OpenAlex

Glycogen synthase kinase 3beta (GSK3beta) is involved in metabolism, neurodegeneration, and cancer. Inhibition of GSK3beta activity is the primary mechanism that regulates this widely expressed active kinase. Although the protein kinase Akt inhibits GSK3beta by phosphorylation at the N terminus, preventing Akt-mediated phosphorylation does not affect the cell-survival pathway activated through the GSK3beta substrate beta-catenin. Here, we show that p38 mitogen-activated protein kinase (MAPK) also inactivates GSK3beta by direct phosphorylation at its C terminus, and this inactivation can lead to an accumulation of beta-catenin. p38 MAPK-mediated phosphorylation of GSK3beta occurs primarily in the brain and thymocytes. Activation of beta-catenin-mediated signaling through GSK3beta inhibition provides a potential mechanism for p38 MAPK-mediated survival in specific tissues.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.271
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), 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

Citations469
Published2008
Admission routes1
Has abstractyes

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