Overexpression of ABCA1 reduces amyloid deposition in the PDAPP mouse model of Alzheimer disease
Bibliographic record
Abstract
APOE genotype is a major genetic risk factor for late-onset Alzheimer disease (AD). ABCA1, a member of the ATP-binding cassette family of active transporters, lipidates apoE in the CNS. Abca1(-/-) mice have decreased lipid associated with apoE and increased amyloid deposition in several AD mouse models. We hypothesized that mice overexpressing ABCA1 in the brain would have increased lipidation of apoE-containing lipoproteins and decreased amyloid deposition. To address these hypotheses, we created PrP-mAbca1 Tg mice that overexpress mouse Abca1 throughout the brain under the control of the mouse prion promoter. We bred the PrP-mAbca1 mice to the PDAPP AD mouse model, a transgenic line overexpressing a mutant human amyloid precursor protein. PDAPP/Abca1 Tg mice developed a phenotype remarkably similar to that seen in PDAPP/Apoe(-/-) mice: there was significantly less amyloid beta-peptide (Abeta) deposition, a redistribution of Abeta to the hilus of the dentate gyrus in the hippocampus, and an almost complete absence of thioflavine S-positive amyloid plaques. Analyses of CSF from PrP-mAbca1 Tg mice and media conditioned by PrP-mAbca1 Tg primary astrocytes demonstrated increased lipidation of apoE-containing particles. These data support the conclusions that increased ABCA1-mediated lipidation of apoE in the CNS can reduce amyloid burden and that increasing ABCA1 function may have a therapeutic effect on AD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".