ATP-binding Cassette Transporter A1 Mediates the Beneficial Effects of the Liver X Receptor Agonist GW3965 on Object Recognition Memory and Amyloid Burden in Amyloid Precursor Protein/Presenilin 1 Mice*
Bibliographic record
Abstract
The cholesterol transporter ATP-binding cassette transporter A1 (ABCA1) moves lipids onto apolipoproteins including apolipoprotein E (apoE), which is the major cholesterol carrier in the brain and an established genetic risk factor for late-onset Alzheimer disease (AD). In amyloid mouse models of AD, ABCA1 deficiency exacerbates amyloidogenesis, whereas ABCA1 overexpression ameliorates amyloid load, suggesting a role for ABCA1 in Aβ metabolism. Agonists of liver X receptors (LXR), including GW3965, induce transcription of several genes including ABCA1 and apoE, and reduce Aβ levels and improve cognition in AD mice. However, the specific role of ABCA1 in mediating beneficial responses to LXR agonists in AD mice is unknown. We evaluated behavioral and neuropathogical outcomes in GW3965-treated female APP/PS1 mice with and without ABCA1. Treatment of APP/PS1 mice with GW3965 increased ABCA1 and apoE protein levels. ABCA1 was required to observe significantly elevated apoE levels in brain tissue and cerebrospinal fluid upon therapeutic (33 mg/kg/day) GW3965 treatment. At 33 mg/kg/day, GW3965 was also associated with a trend toward redistribution of Aβ to the carbonate-soluble pool independent of ABCA1. APP/PS1 mice treated with either 2.5 or 33 mg/kg/day of GW3965 showed a clear trend toward reduced amyloid burden in hippocampus and whole brain, whereas APP/PS1-treated mice lacking ABCA1 failed to display reduced amyloid load in the whole brain and showed trends toward increased hippocampal amyloid. Treatment of APP/PS1 mice with either dose of GW3965 completely restored novel object recognition memory to wild-type levels, which required ABCA1. These results suggest that ABCA1 contributes to several beneficial effects of the LXR agonist GW3965 in APP/PS1 mice.
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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 | 0.001 |
| 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 | 0.002 |
| 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".