Localization of candidate stem and progenitor cell markers within the human cornea, limbus, and bulbar conjunctiva in vivo and in cell culture
Bibliographic record
Abstract
Corneal diseases are some of the most prevalent causes of blindness worldwide. While the most common treatment for corneal blindness is the transplantation of cadaver corneas, expanded limbal stem cells are finding recent application. Unknown, however, is the identity of the actual repopulating stem cell fraction utilized in both treatments and the critical factors governing successful engraftment and repopulation. In order to localize potential stem cell populations in vivo, we have immunohistochemically mapped a battery of candidate stem and progenitor cell markers including c-Kit and other growth factor receptors, nuclear markers including DeltaNp63, as well as adhesion factors across the cornea and distal sclera. Cell populations that differentially and specifically stained for some of these markers include the basal and superficial limbal/conjunctival epithelium and scattered cells within the substantia propria of the bulbar conjunctiva. We have also determined that the culture of differentiated cornea epithelial cells as dissociated and explant cultures induces the expression of several markers previously characterized as candidate limbal stem cell markers. This study provides a foundation to explore candidate corneal stem cell populations. As well, we show that expression of traditional stem cell markers may not be reliable indicator of stem cell content during limbal stem cell expansion in vitro and could contribute to the variable success rates of corneal stem cell transplantation.
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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 | 0.000 | 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 | 0.001 |
| 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".