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Record W2139018071 · doi:10.1186/alzrt211

The role of APP and BACE1 trafficking in APP processing and amyloid-β generation

2013· review· en· W2139018071 on OpenAlexafffund
Xiaojie Zhang, Weihong Song

Bibliographic record

VenueAlzheimer s Research & Therapy · 2013
Typereview
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsAmyloid precursor proteinSenile plaquesAmyloid precursor protein secretaseAlpha secretaseP3 peptideCell biologyBiochemistry of Alzheimer's diseaseBACE1-ASExtracellularAmyloid (mycology)Cleavage (geology)Alzheimer's diseaseChemistryNeuroscienceBiologyDiseaseMedicinePathology

Abstract

fetched live from OpenAlex

Neuritic plaques in the brain are a major neuropathological hallmark of Alzheimer's disease. They are formed by the deposition and aggregation of extracellular amyloid-β protein (Aβ). Aβ is derived from the sequential cleavage of amyloid-β precursor protein (APP) by β-secretase and γ-secretase. β-Site APP cleaving enzyme 1 (BACE1) functions as the primary, if not sole, β-secretase in vivo and is essential for Aβ production. Regulation of APP processing is a major focus of research into AD pathogenesis. The trafficking systems of APP and its cleavage enzymes are complex. Transporting APP and secretases into the same subcellular organelles facilitates their interaction and favors APP processing. The role of APP and BACE1 trafficking in the amyloidgenic pathway and the underlying mechanisms for Aβ production are discussed in this review. In addition, the distinct mechanisms of amino- and carboxy-terminal Aβ generation are reviewed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.165
GPT teacher head0.433
Teacher spread0.268 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations206
Published2013
Admission routes2
Has abstractyes

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