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Record W2007048586 · doi:10.1073/pnas.0305803101

Increased soluble amyloid-β peptide and memory deficits in amyloid model mice overexpressing the low-density lipoprotein receptor-related protein

2004· article· en· W2007048586 on OpenAlexaff
Celina Zerbinatti, David F. Wozniak, John R. Cirrito, Judy Cam, Hiroshi Osaka, Kelly R. Bales, Min Zhuo, Steven M. Paul, David M. Holtzman, Guojun Bu

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2004
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of Toronto
FundersNational Institute of Neurological Disorders and StrokeNational Institute on Aging
KeywordsPeptideP3 peptideIn vivoAmyloid (mycology)Alzheimer's diseasePathogenesisBACE1-ASLipoproteinLDL receptorReceptorAmyloid precursor proteinBiochemistry of Alzheimer's diseaseChemistryEndocrinologyBiologyBiochemistryNeuroscienceInternal medicineMedicineDiseaseCholesterolGenetics

Abstract

fetched live from OpenAlex

Amyloid-beta peptide (Abeta) is central to the pathogenesis of Alzheimer's disease, and the low-density lipoprotein receptor-related protein (LRP) has been shown to alter Abeta metabolism in vitro. Here, we show that overexpression of a functional LRP minireceptor in the brain of PDAPP mice results in age-dependent increase of soluble brain Abeta, with no changes in Abeta plaque burden. Importantly, soluble brain Abeta was found to be primarily in the form of monomers/dimers and to be highly correlated with deficits in spatial learning and memory. These results provide in vivo evidence that LRP may contribute to memory deficits typical of Alzheimer's disease by modulating the pool of small soluble forms of Abeta.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.033
GPT teacher head0.297
Teacher spread0.264 · 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

Citations131
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicAlzheimer's disease research and treatmentsFrench-language works237,207