Non‐Invasive Collection and Examination of Human Corneal Epithelial Cells
Bibliographic record
Abstract
PURPOSE: To report the development of a new apparatus for non-invasive collection of human corneal epithelial cells. METHODS: Previous methods of non-invasive, irrigative corneal cell collection resulted in low cell yields limiting potential analysis. A new ocular surface cell collection apparatus (OSCCA) was designed to collect more epithelial cells from direct irrigation of the corneal surface to allow for clinical comparisons. Forty-five samples were obtained (unilateral or bilateral over seven visits) from five human participants. Cell yield, size, phenotype, and corneal staining (prior and post eye wash) were examined. RESULTS: On average 364 ± 230 epithelial cells were collected from the cornea per eye. Epithelial cell sizes ranged from 8.21 to 51.69 μm in diameter, and 67.30 to 2098.85 μm area. The proportion of corneal specific cells collected per sample was 75 ± 14% as determined by positive K3 expression with AE5. On average, 77 ± 0.2% of epithelial cells harvested were nucleated, the remainder were non-nucleated ghost cells. Corneal staining was reduced in the OSCCA-washed vs. contralateral non-washed eyes (p = 0.02). CONCLUSIONS: The OSCCA allows collection of human corneal epithelial cells with significantly higher yields, and greater specificity than previously reported. Reduced corneal staining observed post eye-wash demonstrated the safety of the technique, and its ability to remove cells directly from the corneal surface. The OSCCA could provide an objective non-invasive method of investigating pathological changes, effects of topical therapeutics, and impact of contact lenses and care-solutions of the cells of the ocular surface.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".