Age‐ and sex‐dependent differences in cognitive decline in rat models of Alzheimer’s disease
Bibliographic record
Abstract
Abstract Background Memory loss has been a central focus of Alzheimer’s disease (AD) research but executive dysfunction may be one of the earliest indicators of AD (Baudic et al., 2006). Executive function refers to a group of cognitive processes that are required for goal directed behaviours, such as working memory and cognitive flexibility. Amyloid‐β (Aβ) plaques and neurofibrillary tangles are considered the pathological hallmarks of AD, but evidence suggests that these are not the earliest pathologies to appear in the AD brain (Sperling et al., 2011). This highlights the importance of assessing both the prodromal and more advanced phases of AD in preclinical modelling. This study aimed to characterize age‐ and sex‐related changes in executive function, learning, and memory across normal aging in rats as well as in two aging transgenic rat strains of AD: TgAPP21 (Aβ plaque‐negative) and TgAPP/PS1 (Aβ plaque‐positive). Method Male and female wildtype Fischer 344, TgAPP21, and TgAPP/PS1 rats were used in this study. The TgAPP21 rat overexpresses the mutant human amyloid precursor protein but does not spontaneously develop Aβ plaques, serving as an important model of prodromal AD. The TgAPP/PS1 rat overexpresses mutant human forms of both the amyloid precursor protein and Presenilin‐1 and does develop age‐dependent Aβ plaques. These strains allowed us to assess cognition under three conditions (i) normal aging, (ii) increased Aβ without plaque deposition, and (iii) age‐dependent Aβ plaque deposition. At 3, 9, or 15 months of age the rats were tested for spatial learning and memory, working memory, and cognitive flexibility using the Morris water maze, the 8‐arm radial water maze, and a T‐maze set‐shifting task. Result Age‐dependent cognitive decline was observed across all genotypes but was exacerbated in both transgenic models. Effects of age, sex, and genotype varied across the cognitive tasks, emphasizing the importance of assessing multiple cognitive domains. Conclusion These findings expand our understanding of the roles of sex, age and Aβ plaque‐positive/negative environments in cognitive decline in preclinical rat strains of AD. Overall, this work supports further investigation into the pathologies driving these cognitive changes and potential biomarkers for earlier detection.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| 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) | 0.003 | 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".