Laser flaremetric evaluation of experimentally induced blood-aqueous barrier disruption in cats
Bibliographic record
Abstract
OBJECTIVES: To determine whether aqueous humor flare, measured by use of laser flaremetry, was proportional to aqueous humor protein concentration and to use laser flaremetry to evaluate disruption of the blood-aqueous barrier (BAB) in cats. ANIMALS: 30 healthy adult cats. PROCEDURE: Laser flaremetry values for all eyes were compared with aqueous humor protein concentrations determined by use of a Coomassie blue microprotein assay. Laser flaremetry was then performed on both eyes before (0 hours) and 4, 8, and 26 hours after initiation of topical application of 2% pilocarpine (q 8 h) to 1 eye of 9 cats or paracentesis of the anterior chamber of 1 eye of 8 cats. Intraocular pressure and pupil size were also determined. Aqueous humor protein concentration was extrapolated from flare values by use of linear regression. RESULTS: There was a linear relationship between flare values and aqueous humor protein concentrations. Topical application of 2% pilocarpine and paracentesis of the anterior chamber caused a breakdown of the BAB that was detected by use of laser flaremetry. The highest mean flare readings after application of pilocarpine or paracentesis were 24.4 and 132.8 pc/ms, respectively, which corresponded to aqueous humor protein concentrations of 85.5 and 434.9 mg/dl, respectively. CONCLUSIONS AND CLINICAL RELEVANCE: Paracentesis of the anterior chamber resulted in a more severe breakdown of the BAB in cats than topical application of 2% pilocarpine. Laser flaremetry may be a useful clinical method to detect increases in aqueous flare and, hence, disruptions of the BAB in cats.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| 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".