Rheological behavior of commercial artificial tear solutions
Bibliographic record
Abstract
PURPOSE: To measure the rheological behavior of artificial tears to gain insight into the potential role of rheology in predicting the efficacy of artificial tear solutions for the treatment of dry-eye disease (DED). SETTING: Research laboratories of I-MED Pharma, Canada, Rohn and Associates, Inc., New Jersey, and Hydan Technologies, New Jersey. DESIGN: Laboratory investigation. METHODS: Twenty commercially available artificial tear drops were purchased in Canada and the United Kingdom. Rheological measurements of viscosity and normal stress as a function of shear rate were performed at 25°C. RESULTS: For comparison of the rheological behavior, the various artificial tears were sorted into 3 groups: group A, which exhibit significant non-Newtonian shear-thinning behavior; group B, which exhibit moderate non-Newtonian shear-thinning behavior; and group C, which exhibit Newtonian behavior throughout the shear rate range. Results of normal stress difference, N1, as a function of shear rate were concordant with the rheological testing, indicated the viscoelastic nature of the samples in groups A and B, whereas members of group C did not exhibit any elasticity. CONCLUSIONS: The various artificial tear solutions were sorted into groups based on their Newtonian or non-Newtonian behaviors. The results suggest that non-Newtonian solutions should provide better comfort and longer-lasting symptomatic relief for DED. It remains to be confirmed clinically if there is a direct correlation between the rheological behavior of artificial tears and their ability to provide prolonged relief in DED, or if other factors are more important.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".