Prevention of vision loss protects against age-related impairment in learning and memory performance in DBA/2J mice
Bibliographic record
Abstract
The DBA/2J mouse is a model of pigmentary glaucoma in humans as it shows age-related increases in intraocular pressure (IOP), retinal ganglion cell death and visual impairment. Previously, we showed that visual ability declines from 9 to 12 months of age and visual impairment is correlated with poor learning and memory performance in visuo-spatial tasks but not in tasks that do not depend on visual cues. To test the "sensory impairment" hypothesis of aging, which postulates that sensory impaired individuals are disadvantaged in their performance on psychometric tests as a direct result of difficulties in sensory perception, we treated DBA/2J mice with a conventional glaucoma medication used in humans (Timoptic-XE, 0.00, 0.25, or 0.50%) daily from 9 weeks to 12 months of age to determine whether prevention of vision loss prevented the decline in visuo-spatial learning and memory performance. At all ages tested (3, 6, 9, and 12 months of age), mice treated with Timoptic-XE (0.25 and 0.50%) maintained a high level of performance, while 12 month old control mice (0.00%) exhibited impaired performance in visually-dependent, but not non-visual tasks. These results demonstrate that when sensory function is preserved, cognitive performance is normalized. Thus, as in many aging humans, DBA/2J mice show age-related decrements in performance on visually presented cognitive tests, not because of cognitive impairment but as a direct consequence of poor visual ability. Our results demonstrate that age-related impairment in performance in visuo-spatial tasks in DBA/2J mice can be prevented by the preservation of visual ability.
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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 | 0.001 | 0.000 |
| 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".