Characterization of a 3xTg‐AD mouse model of Alzheimer's disease with the senescence accelerated mouse prone 8 (SAMP8) background
Bibliographic record
Abstract
No model fully recapitulates the neuropathology of Alzheimer's disease (AD). Although the triple-transgenic mouse model of AD (3xTg-AD) expresses Aβ plaques and tau-laden neurofibrillary tangles, as well as synaptic and behavioral deficits, it does not display frank neuronal loss. Because old age is the most important risk factor in AD, senescence-related interactions might be lacking to truly establish an AD-like environment. To investigate this hypothesis, we bred the 3xTg-AD mouse with the senescence-accelerated mouse prone 8 (SAMP8), a model of accelerated aging. We generated four groups of heterozygous mice with either the SAMP8 or SAMR1 (senescence-resistant-1) genotype, along with either the 3xTg-AD or non-transgenic (NonTg) genotype. Despite no differences among groups in total latency to escape the Barnes maze, a greater number of errors were noticed before entering the target hole in 19-month-old P8/3xTg-AD mice at day 5, compared to other groups. Postmortem analyses revealed increased cortical levels of phospho-tau (Thr231) in female P8/3xTg-AD mice (+277% vs. R1/3xTg-AD mice), without other tau-related changes. Female P8/3xTg-AD mice exhibited higher cortical soluble Aβ40 and Aβ42 concentrations (Aβ40, +85%; Aβ42, +35% vs. R1/3xTg-AD), whereas insoluble forms remained unchanged. Higher Aβ42 load coincided with increased astroglial activation in female P8/3xTg-AD mice, as measured with glial fibrillary acidic protein (GFAP) (+57% vs. R1/3xTg-AD mice). To probe neuronal degeneration, concentrations of neuronal nuclei (NeuN) were measured, but no differences were detected between groups. Altogether, the SAMP8 genotype had deleterious effects on spatial memory and exerted female-specific aggravation of AD neuropathology without overt neurodegeneration in 3xTg-AD 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".