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Record W2028364874 · doi:10.1016/j.jalz.2010.05.667

P1‐118: Physiological regulation of plasma amyloid‐beta in APP/PS1dE9 mice and mouse lemur primates

2010· article· en· W2028364874 on OpenAlexaff
Maggie Roy, Carole Malgorn, Audrey Kraska, Marion Chaigneau, Philippe Hantraye, Martine Perret, Emmanuel Comoy, Fabienne Aujard, Marc Dhénain

Bibliographic record

VenueAlzheimer s & Dementia · 2010
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsGenetically modified mouseLemurKnockout mouseTransgeneGene knockoutAmyloid betaMouse strainAmyloidosisMolecular biologyInternal medicineChemistryEndocrinologyBiologyGeneMedicineDiseaseBiochemistryNeurosciencePrimate

Abstract

fetched live from OpenAlex

Testing potential drugs against Alzheimer's disease (AD) and understanding the physiopathology of AD require animal models. Biomarkers, such as CSF and plasma amyloid-beta peptide (Abeta), can evaluate the efficacy of these treatments in induced or spontaneous models of AD as well as the evolution of pathology. Understanding physiopathological processes that modulate those biomarkers is however critical. The aim of our study was to assess the effect of factors such as age, sex, genetic background, and the expression of a putative Abeta receptor (the prion protein (PrP)) on plasma Abeta levels in a transgenic (tg) mouse model of amyloidosis and in a primate model of spontaneous cerebral aging: the mouse lemur primate. Plasma Abeta was assessed in double tg APPswe/PS1dE9 mice and in mouse lemur primates. Mice were 4 to 29 months of age and carried three different genetic backgrounds: B6C3F1 (n = 20), C57Bl6 (n = 23) and Swiss (n = 9). Evaluation of PrP effect was performed by crossing APPswe/PS1dE9 mice (B6C3F1/J background) with PrP+/+ and PrP-/-, mice knockout for PrP gene. Mouse lemurs were 1 to 9 years of age (n = 44). Blood samples were collected in EDTA tubes and centrifuged (2000g; 10min, 4°c) in the 15 minutes following the collection. The supernatant was collected in 200μl polypropylene tubes. A cocktail of protease inhibitors (Complete Mini Roche) was added to plasma samples. Plasma Abeta40 and 42 detections were performed using commercial ELISA kits (BioSource). Plasma Abeta was affected by the strain of mice, stressing the importance of choosing the right animal model. However, plasma Abeta was not modulated by age or pathology progression in APPswe/PS1dE9 mice. Next, we studied prion protein (PrP) expression effect on Abeta peptide in APPswe/PS1dE9/PrP mice. We showed that PrP regulated positively plasma Abeta levels in tg mice. Plasma Abeta was not significantly different between young and aged mouse lemurs. Plasmatic Abeta detection in tg mice and mouse lemurs is a simple and very precise tool, and is modulated by genetic background and PrP expression. This tool could follow the effects of potential treatments for 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 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 score0.017

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.027
GPT teacher head0.295
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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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