Chemotactic and chemokinetic properties of topical ophthalmic preparations
Bibliographic record
Abstract
PURPOSE: Chronic ocular inflammation can be due to a disease process or to iatrogenic factors that attract inflammatory cells to the anterior chamber. This study was conducted to investigate the effect of commonly used ophthalmic preparations on leukocyte migration. METHODS: A modified multi-well Boyden chamber was used to study the chemotactic and chemokinetic effects of 33 commercial ophthalmic preparations. To determine whether the chemotactic effect was a property of the commercial ophthalmic preparation or other chemicals present in the products, experiments were also done with some common preservatives and excipients. RESULTS: Of the drugs, 14 (42.4%) showed chemokinetic and/or chemotactic activity and 19 (57.6%) had either no effect or decreased neutrophil migration. Of the preservatives and excipients, 5 (62.5%) were found to be chemotactic. Eleven of 14 chemotactic drugs (78.6%) and 8 of 19 non-chemotactic drugs (42.1%) were positive for at least one chemotactic excipient. The correlation between chemotactic ophthalmic preparations and the presence of a chemotactic excipient in their composition was significant (p < 0.05). CONCLUSIONS: Chemotactic activity was commonly found in commercial ophthalmic preparation. Furthermore, the presence of certain chemotactic preservatives and/or excipients was a contributing factor enhancing this property. Avoiding known chemotactic compounds or adjusting the intervals of the treatment may help to eliminate this iatrogenic component of the inflammatory process especially in patients with chronic ocular inflammation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".