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Record W2310987806 · doi:10.1093/cercor/bhv332

Intraneuronal Amyloid Beta Accumulation Disrupts Hippocampal CRTC1-Dependent Gene Expression and Cognitive Function in a Rat Model of Alzheimer Disease

2016· article· en· W2310987806 on OpenAlexafffundabout
Edward N. Wilson, Andrew R. Abela, Sonia Do Carmo, S.T.M. Allard, Adam Marks, Lindsay A. Welikovitch, Adriana Ducatenzeiler, Yogita Chudasama, A. Claudio Cuello

Bibliographic record

VenueCerebral Cortex · 2016
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcGill University Health CentreMcGill University
FundersCanadian Institutes of Health Research
KeywordsNeuroscienceHippocampal formationPsychologyCognitionAmyloid betaSynaptic plasticityAlzheimer's diseaseHippocampusBiologyDiseaseMedicineInternal medicineReceptor

Abstract

fetched live from OpenAlex

In Alzheimer disease (AD), the accumulation of amyloid beta (Aβ) begins decades before cognitive symptoms and progresses from intraneuronal material to extracellular plaques. To date, however, the precise mechanism by which the early buildup of Aβ peptides leads to cognitive dysfunction remains unknown. Here, we investigate the impact of the early Aβ accumulation on temporal and frontal lobe dysfunction. We compared the performance of McGill-R-Thy1-APP transgenic AD rats with wild-type littermate controls on a visual discrimination task using a touchscreen operant platform. Subsequently, we conducted studies to establish the biochemical and molecular basis for the behavioral alterations. It was found that the presence of intraneuronal Aβ caused a severe associative learning deficit in the AD rats. This coincided with reduced nuclear translocation and genomic occupancy of the CREB co-activator, CRTC1, and decreased production of synaptic plasticity-associated transcripts Arc, c-fos, Egr1, and Bdnf. Thus, blockade of CRTC1-dependent gene expression in the early, preplaque phase of AD-like pathology provides a molecular basis for the cognitive deficits that figure so prominently in early 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 score0.154
Threshold uncertainty score0.544

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 head0.050
GPT teacher head0.319
Teacher spread0.269 · 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

Citations56
Published2016
Admission routes3
Has abstractyes

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