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Record W2092859042 · doi:10.1096/fj.05-4195fje

Amyloid‐β induces disulfide bonding and aggregation of GAPDH in Alzheimer's disease

2005· article· en· W2092859042 on OpenAlexfundno aff
Robert C. Cumming, David Schubert

Bibliographic record

VenueThe FASEB Journal · 2005
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNational Institutes of HealthAssociation France Alzheimer
KeywordsGlyceraldehyde 3-phosphate dehydrogenaseChemistryCytoplasmBiochemistryAmyloid (mycology)Cell biologyEnzymeBiologyDehydrogenase

Abstract

fetched live from OpenAlex

GAPDH is a redox-sensitive glycolytic enzyme that also promotes apoptosis when translocated to the nucleus and associates with aggregate-prone proteins involved in neurodegenerative disorders. Recent evidence indicates that polymorphic variation within GAPDH genes is associated with an elevated risk of developing Alzheimer's disease (AD). We previously demonstrated that GAPDH readily undergoes disulfide bonding following oxidant exposure, although the consequence of disulfide bonding on GAPDH activity or function is unknown. Here we show that increased GAPDH disulfide bonding is observed in detergent-insoluble extracts from AD patient and transgenic AD mouse brain tissue compared with age-matched controls. Exposure of primary rat cortical neurons to the pro-oxidant amyloid beta peptide promotes nuclear accumulation of a disulfide-linked form of GAPDH, which becomes detergent-insoluble. Disulfide bonding leads to a reduction in GAPDH enzymatic activity and correlates with the appearance of punctate aggregate-like GAPDH staining within the cytoplasm of both oxidant-treated HT22 cells and amyloid beta-treated primary cortical neurons. Our findings suggest that disulfide bonding of GAPDH and subsequent protein aggregate formation may have relevance to the pathophysiology 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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.263

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 head0.035
GPT teacher head0.316
Teacher spread0.280 · 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 designObservational
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

Citations144
Published2005
Admission routes1
Has abstractyes

Explore more

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