Physiologically regulated transgenic ABCA1 does not reduce amyloid burden or amyloid‐beta peptide levels in vivo
Bibliographic record
Abstract
J Lipid Res. 2007 Apr;48(4):914-23. Epub 2007 Jan 18. Physiologically regulated transgenic ABCA1 does not reduce amyloid burden or amyloid-beta peptide levels in vivo. Hirsch-Reinshagen V, Chan JY, Wilkinson A, Tanaka T, Fan J, Ou G, Maia LF, Singaraja RR, Hayden MR, Wellington CL. Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, Canada. Abstract ABCA1-deficient mice have low levels of poorly lipidated apolipoprotein E (apoE) and exhibit increased amyloid load. To test whether excess ABCA1 protects from amyloid deposition, we crossed APP/PS1 mice to ABCA1 bacterial artificial chromosome (BAC) transgenic mice. Compared with wild-type animals, the ABCA1 BAC led to a 50% increase in cortical ABCA1 protein and a 15% increase in apoE abundance, demonstrating that this BAC supports modest ABCA1 overexpression in brain. However, this was observed only in animals that do not deposit amyloid. Comparison of ABCA1/APP/PS1 mice with APP/PS1 controls revealed no differences in levels of brain ABCA1 protein, amyloid, Abeta, or apoE, despite clear retention of ABCA1 overexpression in the livers of these animals. To further investigate ABCA1 expression in the amyloid-containing brain, we then compared ABCA1 mRNA and protein levels in young and aged cortex and cerebellum of APP/PS1 and ABCA1/APP/PS1 animals. Compared with APP/PS1 controls, aged ABCA1/APP/PS1 mice exhibited increased ABCA1 mRNA, but not protein, selectively in cortex. Additionally, ABCA1 mRNA levels were not increased before amyloid deposition but were induced only in the presence of extensive Abeta and amyloid levels. These data suggest that an induction of ABCA1 expression may be associated with late-stage Alzheimer's neuropathology. PMID: 17235115 [PubMed - indexed for MEDLINE]
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
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".