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Record W2075268437 · doi:10.1016/j.jalz.2010.08.218

P4‐159: Lrp9, a New Player in Alzheimer's Disease

2010· article· en· W2075268437 on OpenAlexaff
Julie C. Brodeur, Christine Lavoie

Bibliographic record

VenueAlzheimer s & Dementia · 2010
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsEndosomeRetromerAmyloid precursor proteinCell biologyAlpha secretaseGolgi apparatusAmyloid precursor protein secretasePresenilinBiologyReceptorTransport proteinEndocytosisChemistryAlzheimer's diseaseBiochemistryIntracellularMedicineDisease

Abstract

fetched live from OpenAlex

Amyloid-β peptide (Aβ) production and accumulation in the brain is a central event in the pathogenesis of Alzheimer's disease (AD). Aβ is derived from the amyloid precursor proteins (APP) by sequential proteolysis by enzymes called secretases. These enzymes are localized in different compartments in the cells and the transport of APP to these specific compartments leads to its cleavage by the secretases. Therefore understanding how APP is moved around is central to developing therapies for AD treatment. Various members of the LDLR family (LRP1, SorLA) have been found to interact with APP and to regulate its trafficking and processing. We recently characterized a new member of the LDLR family called LRP9 which cycles between the trans-Golgi Network (TGN) and endosomes. LRP9 C-tail is unique since it contains two DXXLL motifs (that bind clathrin adaptors GGAs) that are crucial for LRP9 trafficking since their mutation (DXXAA) caused a redistribution of LRP9 to the endosomes and plasma membrane. LRP9 homology to the sorting receptor SorLA that shuttles APP between the TGN and endosomes leads us to hypothesize that LRP9 is a functional APP receptor involved in APP trafficking and processing. Studies were performed in CHO cells stably expressing APP alone or together with LRP9 wild-type or DXXAA mutant. The distribution of APP and LRP9 was analyzed using confocal microscopy. Interactions were tested by immunoprecipitation. APP level, half-life and maturation were studied by western blots and 35S-methionine pulse-chase assays. Confocal microscopy studies showed that LRP9 colocalizes with APP at the TGN. Expression of LRP9-DXXAA mutant led to a redistribution of APP from the TGN to early endosomes. Immunoprecipitation studies indicated an interaction of APP with both the cytoplasmic and luminal domain of LRP9. Furthermore, overexpression of LRP9 wild-type decreased the cellular levels of APP as well as its maturation. To assess the functional importance of LRP9 on APP, we are presently analyzing the generation of APP processing products. Our data show that LRP9 binds to APP and modulates its intracellular distribution as well as its maturation, strengthening the potential role of LRP9 as a novel APP sorting receptor.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

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 integrity0.0010.001
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 head0.032
GPT teacher head0.318
Teacher spread0.285 · 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
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

Citations0
Published2010
Admission routes1
Has abstractyes

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