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Genetic and pharmacological demonstration of a role for cyclic AMP‐dependent protein kinase‐mediated suppression of protein phosphatases in gating the expression of late LTP

2002· article· en· W2169904556 on OpenAlexafffund
Newton H. Woo, Ted Abel, Peter Nguyen

Bibliographic record

VenueEuropean Journal of Neuroscience · 2002
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of Alberta
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Mental HealthNational Institute on AgingUniversity of Alberta
KeywordsLong-term potentiationProtein kinase APhosphataseForskolinLTP inductionOkadaic acidAdenylyl cyclaseCell biologyChemistryProtein phosphatase 1Activator (genetics)KinaseBiologyBiochemistryPhosphorylationSignal transductionReceptor

Abstract

fetched live from OpenAlex

Protein kinases and phosphatases play antagonistic roles in regulating hippocampal long-term potentiation (LTP), with kinase inhibition and phosphatase activation both impairing LTP. The late phase of LTP (L-LTP) requires activation of cAMP-dependent protein kinase (PKA) for its full expression. One way in which PKA may critically modulate L-LTP is by relieving an inhibitory constraint imposed by protein phosphatases. Using mutant PKA mice [R(AB) transgenic mice] that have genetically reduced hippocampal PKA activity, we show that deficient L-LTP in area CA1 of mutant hippocampal slices is rescued by acute application of two inhibitors of protein phosphatase-1 and protein phosphatase-2A (PP1/2A) (okadaic acid and calyculin A). Furthermore, synaptic facilitation induced by forskolin, an adenylyl cyclase activator, was impaired in R(AB) transgenics and was also rescued by a PP1/2A inhibitor in mutant slices. Inhibition of PP1/2A did not affect early LTP (E-LTP) or basal synaptic transmission in mutant and wildtype slices. Our data show that genetic inhibition of PKA impairs L-LTP by reducing PKA-mediated suppression of PP1/2A.

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)0.003
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 score0.015
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.073
GPT teacher head0.322
Teacher spread0.249 · 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

Citations52
Published2002
Admission routes2
Has abstractyes

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