Abnormal whisker movements in the <scp>3xTg‐AD</scp> mouse model of Alzheimer's disease
Bibliographic record
Abstract
Alzheimer's disease is the most frequent form of dementia in elderly people. The triple transgenic (3xTg-AD) mouse model of Alzheimer's Disease is important in biomedical research as these mice develop both neuropathological and behavioural phenotypes. However, their behavioural phenotype is variable, with findings depending on the specific task, as well as the age and sex of the mice. Whisker movements show motor, sensory and cognitive deficits in mouse models of neurodegenerative disease. Therefore, we examined whisker movements in 3, 12.5 and 17-month-old female 3xTg-AD mice and their B6129S/F2 wildtype controls. Mice were filmed using a high-speed video camera (500 fps) in an open arena during a novel object exploration task. Genotype and age differences were found in mice exploring the arena prior to object contact. Prior to whisker contact, the 3-month-old 3xTg-AD mice had smaller whisker angles compared with the wildtype controls, suggesting an early motor phenotype in these mice. Pre-contact mean angular position at 3 months and whisking amplitude at 17 months of age differed between the 3xTg-AD and wildtype mice. During object contact 3xTg-AD mice did not reduce whisker spread as frequently as the wildtype mice at 12.5 and 17 months, which may suggest sensory or attentional deficits. We show that whisker movements are a powerful behavioural measurement tool for capturing behavioural deficits in mouse models that show complex phenotypes, such as the 3xTg-AD mouse model.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".