A Neurobehavioral Analysis of the Prevention of Visual Impairment in the DBA/2J Mouse Model of Glaucoma
Bibliographic record
Abstract
PURPOSE: Timoptic-XE treatment was used to examine the relationship between age-related changes in intraocular pressure (IOP), retinal cell loss, visual ability, and neuronal labeling in the superior colliculus in the DBA/2J mouse model of pigmentary glaucoma. METHODS: Mice were administered Timoptic-XE (0.0%, 0.25%, or 0.50%) daily from 9 weeks to 12 months of age. Visual ability and IOP were evaluated at 3, 6, 9, and 12 months of age. Mice from each group were then given intraocular injections of wheat germ agglutinin conjugated to horseradish peroxidase (WGA-HRP), and estimates of the number of cells in the ganglion cell layer of the retina, WGA-HRP transneural labeling of cells, cell count, and cross-sectional area of Nissl-stained cells in the superior colliculus were obtained. RESULTS: Mice treated with 0.50% and 0.25% Timoptic-XE maintained a high level of performance in behavioral vision tasks, while 12-month-old untreated mice (0.0% Timoptic-XE) exhibited impaired visual performance. Timoptic-XE therapy reduced IOP and cell loss in the ganglion cell layer of the retina and prevented somal shrinkage and the decrease in WGA-HRP transneural labeling in the superior colliculus that occurred in untreated mice at 12 months of age. CONCLUSIONS: This study provides a comprehensive assessment of the efficacy of Timoptic-XE in DBA/2J mice by correlating age-related visual system changes in the retina and brain with changes in IOP and visual ability. These results showed that reducing IOP not only rescued retinal ganglion cell atrophy but also restored visual function and altered patterns of neurodegeneration that occur with blindness.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".