Impact of age, hypercholesterolemia, and the vitamin D receptor on brain endogenous β‐amyloid peptide accumulation in mice
Bibliographic record
Abstract
Abstract Age, hypercholesterolemia, and vitamin D deficiency are risk factors that increase the brain accumulation of pathogenic β‐amyloid peptides (40 and 42), precursors leading to Alzheimer's disease (AD) in humans. The relative changes accompanying aging, high cholesterol, and/or treatment of calcitriol, active vitamin D receptor (VDR) ligand, under normal physiology are unknown. We examined these relative changes in C57BL/6 mice of ages 2, 4–8, and more than 10 months old, which were fed a normal or high fat / high cholesterol diet and treated with calcitriol, active ligand of the vitamin D receptor (0 or 2.5 μg/kg ×4, intraperitoneally, every other day to elicit cholesterol lowering in liver). Aβ40 but not Aβ42 accumulation in brain and lower P‐glycoprotein (P‐gp) and neprilysin protein expressions for Aβ efflux and degradation, respectively, were found to be associated with aging. But there was no trend for BACE1 (β‐secretase 1, a cholesterol‐sensitive enzyme) toward Aβ synthesis with age. In response to calcitriol treatment, P‐gp was elevated, mitigating partially the age‐related changes. Although age‐dependent decreasing trends in mRNA expression levels existed for Cyp46a1, the brain cholesterol processing enzyme, whose inhibition increases BACE1 and ApoE to facilitate microglia Aβ degradation, mRNA changes for other cholesterol transporters: Acat1 and Abca1, and brain cholesterol levels remained unchanged. There was no observable change in the mRNA expression of amyloid precursor protein (APP) and the influx (RAGE) and efflux (LRP1) transporters with respect to age, diet, or calcitriol treatment. Overall, aging poses as a risk factor contributing to Aβ accumulation in brain, and VDR‐mediated P‐gp activation partially alleviates the outcome.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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".