Sex Differences in Healthspan Predict Lifespan in the 3xTg-AD Mouse Model of Alzheimer’s Disease
Bibliographic record
Abstract
Mouse models of Alzheimer's disease (AD) exhibit marked differences in life expectancy depending on their genotype and sex. The assessment of frailty could provide a measure of healthspan to facilitate comparisons between different AD models. We used a validated mouse frailty index (FI) assessment tool to explore genotype and sex differences in lifespan and healthspan of 3xTg-AD mice and their B6129F2 wild-type (WT) controls. This tool is based on an approach commonly used in people and quantifies frailty by counting the accumulation of age-related health deficits. The number of deficits in an individual divided by the total number measured yields an FI score theoretically between 0 and 1, with higher scores denoting more frailty. Male 3xTg-AD mice aged 300-600 days had higher FI scores (Mean FI = 0.21 ± 0.03) than either male WT (Mean FI = 0.15 ± 0.01) or female 3xTg-AD mice (Mean FI = 0.10 ± 0.01), and the elevated frailty scores were accompanied by parallel increases in mortality. Frailty increased exponentially with age, and higher rates of deficit accumulation elevated mortality risk in all groups of mice. When mice were stratified by FI score, frailty predicted mortality, at least in females. Therefore, the mouse clinical FI provides a valuable tool for evaluating healthspan in mouse models of AD with different lifespans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".