Corneal Stromal Mesenchymal Stem Cells for Corneal Stroma Reconstruction
Bibliographic record
Abstract
Abstract Purpose To date, corneal epithelial reconstruction has been very successful. However, in a number of cases of injury or disease, the stromal layer is affected. Our goal is to develop biomaterials that will enable the regeneration of the corneal stroma. In this study, we compare endogenous vs exogenous stem cell courses for corneal stromal regeneration. Methods We have previously developed collagen‐based corneal stromal extracellular matrix substitutes based on EDC crosslinked collagen, and have shown that they promote ingrowth of stromal cells from the host cornea (Merrett et al. 2009; Fagerholm et al. 2010). For cases where stromal progenitors are depleted, we developed a non‐toxic collagen‐based hydrogel system where a macromolecular photoinitiator (Dex‐BBA)was used to form the hydrogel around cells. The feasibility of Dex‐BBA as a photoinitiator to initiate the gelation of aminoethylmethacylate‐modified collagen (Coll‐AEMA) was examined with or without the presence of stroma cells. Results The Dex‐BBA crosslinked hydrogels were weaker than the EDC crosslinked constructs. However, they were fairly robust and no apparent toxicity of the hydrogel system to mesenchymal stroma (or stem) cells (MSCs)were observed during the culture of 7 days, which indicated that Dex‐BBA based macrophotoinitiator and our collagen‐based hydrogel system may have potential in corneal stromal regeneration applications. Conclusion We show that corneal stromal regeneration can be achieved by endogenous stimulation of existing corneal progenitor cells. Where the host cells may be depleted, our results show that hydrogel encapsulated stem cells may be used in the future. Commercial interest
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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) | 0.000 | 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) | 0.003 | 0.001 |
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".