The Effects of Tween 20 on<i>in vitro</i>Bovine Lenses
Bibliographic record
Abstract
The optical properties of the cultured bovine lens were analyzed after exposure to various concentrations of Tween 20, a nonionic surfactant, to find a nonirritating concentration for commercial products. Bovine lenses were extracted and placed into a culture chamber for 24 hours at 37°C with 4–5% CO2. The lenses were placed into three treatment (1%, n = 10; 10%, n = 9; and 100%, n = 10 Tween 20) and one control group (n = 7) for 15 minutes. For 8 days following treatment, the lens optics were analyzed periodically for back vertex distance (focal length) and back vertex distance variability (sharpness of focus) using a laser-scanning device. For both the control and the 1% Tween 20 condition, no significant change was seen from the beginning of the experiment (p > 0.05). The 10% Tween 20 solution induced significant loss of sharp focus (0.62 ± 0.1 mm SEM) 4 hours after exposure, increasing to BVD = 1.69 ± 0.3 mm SEM by the end of experimentation (p < 0.05). At full strength (100%), Tween 20 began to cause damage after 4 hours (BVD = 0.50 ± 0.06 mm SEM), and this change increased to BVD = 4.46 ± 0.59 mm SEM after 8 days following treatment (p < 0.05). Therefore, a dose-dependant increase in back vertex distance (BVD) variability was detected. This research suggests that using 1% Tween 20 in commercial solutions should not produce ocular irritation, whereas concentrations above 10% will cause significant irritation. As well, the bovine lens assay, paired with the automated lens scanner, provided a sensitive approach to measure mild ocular irritation.
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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 | 0.000 | 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".