Use of Polymyxin as an Endotoxin Blocker in the Prevention of Diffuse Lamellar Keratitis in an Animal Model
Bibliographic record
Abstract
PURPOSE: To determine whether bacterial endotoxin, lipopolysaccharide (LPS), could induce diffuse lamellar keratitis (DLK) in an animal model and whether DLK could be prevented by endotoxin blockers such as polymyxin. METHODS: Laser in situ keratomileusis (LASIK) flaps were created in rabbit eyes. The stromal bed was treated with 20 microg of Burkholderia cepacia LPS or balanced salt solution (BSS). Development of DLK, histological degree of inflammation, and presence of LPS detected by anti-LPS antibody were evaluated after 48 hours. In a second experiment, all eyes received LPS and were randomly assigned to receive either polymyxin in the form of two drops of Polytrim (Allergan, Irvine, Calif) on the stromal bed or two drops of BSS. RESULTS: In the animal model study, LPS was significantly associated with the development of DLK (P<.05, n=30). Infiltration with polymorphonuclear cells and presence of DLK were found in LPS treated eyes but not in controls. In the second experiment, 4 (27%) of 15 eyes that received polymyxin in addition to LPS developed DLK compared to 18 (95%) of 19 eyes that received only LPS (P<.05, n=34). There was a trend towards higher flap displacement in polymyxin treated eyes but this was not significant (P=.07). CONCLUSIONS: Diffuse lamellar keratitis in a rabbit model can be caused by bacterial endotoxin (LPS). Endotoxin blockers, such as polymyxin, are effective in decreasing the incidence of endotoxin-induced DLK in a rabbit 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".