Chemoattraction of Inflammatory Cells by Various Intraocular Lens Materials
Bibliographic record
Abstract
PURPOSE: To compare the chemotactic activity induced by polymethyl methacrylate (PMMA), acrylic, and silicone intraocular lens (IOL) materials, regardless of the surgical and host factors. METHODS: The chemotactic effect of five different IOLs was studied using a modified multi-well Boyden chamber. Two different non-coated PMMA IOLs, a heparin-coated PMMA IOL, an acrylic IOL, and a silicone IOL were assessed. Each mean migration distance of the IOLs was compared with the others using Student's t test. RESULTS: All IOLs induced some amount of leukocyte chemotaxis. There was no statistically significant difference between the chemotactic activity of PMMA IOLs. However, chemotactic activity was significantly higher in acrylic (p<0.05) and silicone (p<0.05) IOLs compared to one of the PMMA lenses. CONCLUSIONS: This limited study has proven that chemotaxis assay is a useful tool to assess the biocompatibility of IOLs. The IOL material itself might attract inflammatory cells to its surface in the absence of surgical and host factors. As PMMA IOLs do not cause an increase in inflammatory reaction, they may be considered safe to use. Further improvement in chemical composition and surface characteristics of IOLs should reduce the inflammatory reaction and increase the biocompatibility and safety of IOLs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".