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Record W2128852790 · doi:10.1196/annals.1332.004

<i>BACE1</i> Gene Expression and Protein Degradation

2004· article· en· W2128852790 on OpenAlexaff
Weihui Zhou, Hong Qing, Yigang Tong, Weihong Song

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2004
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBACE1-ASAmyloid precursor proteinBiochemistry of Alzheimer's diseaseProteasomeAmyloid precursor protein secretaseP3 peptideAlpha secretaseUbiquitinAmyloid betaChemistryProtein degradationAmyloid (mycology)Protein precursorCell biologyMolecular biologyGeneBiochemistryBiologyAlzheimer's diseasePeptideMedicineDiseaseTransgeneInternal medicine

Abstract

fetched live from OpenAlex

Deposition of amyloid beta protein in the brain is the major pathological feature of Alzheimer's disease. Amyloid beta protein is generated from beta-amyloid precursor protein by beta-secretase and gamma-secretase. Proteolytic processing of amyloid precursor protein at the beta site by BACE1 is essential to generate amyloid beta protein. BACE1, the major beta-secretase involved in cleaving amyloid precursor protein, has been identified as a type 1 membrane-associated aspartyl protease. In this study, we found that BACE1 gene expression is controlled by a TATA-less promoter. BACE1 gene expression is tightly regulated at the transcriptional level and the transcription factor Sp1 plays an important role in regulation of BACE1 to process amyloid precursor protein generating amyloid beta protein. Furthermore, we found that BACE1 protein is ubiquitinated, and the degradation of BACE1 proteins and amyloid precursor protein processing are regulated by the ubiquitin-proteasome pathway.

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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.108
GPT teacher head0.371
Teacher spread0.263 · 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

Citations11
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of the New York Academy of Sciences→Same topicAlzheimer's disease research and treatments→French-language works237,207→