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Record W2154164205 · doi:10.1084/jem.20081588

Valproic acid inhibits Aβ production, neuritic plaque formation, and behavioral deficits in Alzheimer's disease mouse models

2008· article· en· W2154164205 on OpenAlexafffund
Hong Qing, Guiqiong He, Philip T. T. Ly, Christopher J. Fox, Matthias Staufenbiel, Fang Cai, Zhuohua Zhang, Shengcai Wei, Xiulian Sun, Chia-Hsiung Chen, Weihui Zhou, Ke Wang, Weihong Song

Bibliographic record

VenueThe Journal of Experimental Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchChina Scholarship CouncilMichael Smith Health Research BC
KeywordsSenile plaquesValproic AcidAlzheimer's diseaseGenetically modified mouseIn vivoAmyloid precursor proteinPathogenesisEpilepsyNeuroscienceAmyloid (mycology)PharmacologyTransgeneMedicineBiologyDiseasePathologyBiochemistry

Abstract

fetched live from OpenAlex

Neuritic plaques in the brains are one of the pathological hallmarks of Alzheimer's disease (AD). Amyloid beta-protein (Abeta), the central component of neuritic plaques, is derived from beta-amyloid precursor protein (APP) after beta- and gamma-secretase cleavage. The molecular mechanism underlying the pathogenesis of AD is not yet well defined, and there has been no effective treatment for AD. Valproic acid (VPA) is one of the most widely used anticonvulsant and mood-stabilizing agents for treating epilepsy and bipolar disorder. We found that VPA decreased Abeta production by inhibiting GSK-3beta-mediated gamma-secretase cleavage of APP both in vitro and in vivo. VPA treatment significantly reduced neuritic plaque formation and improved memory deficits in transgenic AD model mice. We also found that early application of VPA was important for alleviating memory deficits of AD model mice. Our study suggests that VPA may be beneficial in the prevention and treatment of AD.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.079
GPT teacher head0.346
Teacher spread0.267 · 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

Citations365
Published2008
Admission routes2
Has abstractyes

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