Aging and brain free cholesterol concentration on amyloid‐β peptide accumulation in guinea pigs
Bibliographic record
Abstract
Abstract Alzheimer’s disease is a complex multifactorial neurodegenerative disorder wherein age is a major risk factor. The appropriateness of the Hartley guinea pig (GP), which displays high sequence homologies of its amyloid‐β (Aβ40 and Aβ42) peptides, Mdr1 and APP (amyloid precursor protein) and similarity in lipid handling to humans, was appraised among 9–40 weeks old guinea pigs. Protein expression levels of P‐gp (Abcb1) and Cyp46a1 (24(S)‐hydroxylase) for Aβ40, and Aβ42 efflux and cholesterol metabolism, respectively, were decreased with age, whereas those for Lrp1 (low‐density lipoprotein receptor related protein 1), Rage (receptor for advanced glycation endproducts) for Aβ efflux and influx, respectively, and Abca1 (the ATP binding cassette subfamily A member 1) for cholesterol efflux, were unchanged among the ages examined. There was a strong, negative correlation of the brain Aβ peptide concentrations and Abca1 protein expression levels with free cholesterol. The correlation of Aβ peptide concentrations with Cyp46a1 was, however, not significant, and concentrations of the 24(S)‐hydroxycholesterol metabolite revealed a decreasing trend from 20 weeks old toward 40 weeks old guinea pigs. The composite data suggest a role for free cholesterol on brain Aβ accumulation. The decreases in P‐gp and Lrp1 protein levels should further exacerbate the accumulation of Aβ peptides in guinea pig brain.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".