Age-related changes in social behaviours in the 5xFAD mouse model of Alzheimer’s disease
Bibliographic record
Abstract
Abstract In addition to memory impairments, patients with Alzheimer’s disease (AD) exhibit a number of behavioural and psychological symptoms that can affect social interactions over the course of the disease. While altered social interactions have been demonstrated in a number of mouse models of AD, many models only recapitulate the initial stages of the disease, and these behavioural changes have yet to be examined over the course of disease progression. By performing a longitudinal study using the 5xFAD mouse model, we have demonstrated that transgenic females exhibit progressive alterations in social investigation compared to wild-type controls. Transgenic females exhibited an age-related reduction in interest for social odours, as well as reduced investigative behaviours towards novel conspecifics in a novel environment. However, transgenic mice exhibited no obvious olfactory deficits, nor any changes in scent-marking behaviour compared to wild-type controls, indicating that changes in investigative behaviour were due to motivation to engage with a social stimulus. This evidence suggests that transgenic 5xFAD females exhibit increased social anxiety in novel environments compared to wildtype controls. Overall, transgenic 5xFAD female mice mimic some features of social withdrawal observed in human AD patients suggesting this strain may be suitable for modelling aspects of the social dysfunction observed in human patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".