Current Landscape and Future Prospects of Corneal Regenerative Medicine
Bibliographic record
Abstract
Corneal disorders are among the leading causes of visual impairment worldwide, with corneal transplantation historically serving as the cornerstone of surgical treatment. However, the global shortage of donor tissue, risk of immune rejection, and variable long-term graft survival underscore the urgent need for alternative approaches, particularly in the setting of ocular surface diseases such as inflammation or dry eye that can compromise graft survival. Regenerative medicine has emerged as a transformative paradigm, offering strategies to restore corneal architecture and function through cell-based therapies, tissue engineering, and gene modulation. These strategies are promising, addressing structural repair and modulating wound-healing responses. In the corneal epithelium, cultivated limbal epithelial transplantation, simple limbal epithelial transplantation, and cultivated oral mucosal epithelial transplantation have expanded therapeutic options for limbal stem cell deficiency, with clinical trials demonstrating long-term ocular surface stability. Regulatory approval of commercial products, such as Holoclar and Nepic, confirms the potential of standardized regenerative products. Stromal regeneration with stromal and mesenchymal stem cells has shown promise in preclinical and early phase clinical trials, with intrastromal stem cell injection improving corneal transparency and biomechanics and potentially stabilizing progressive disorders such as keratoconus. For endothelial dysfunction, intracameral injection of cultured corneal endothelial cells supplemented with Rho-associated protein kinase (ROCK) inhibitors has yielded sustained corneal clarity and visual restoration at 5-10 years, marking a paradigm shift from transplantation to minimally invasive, donor-independent therapies. Tissue engineering innovations, including matrices, hydrogels, and three-dimensional bioprinting, are advancing toward translation, while gene therapy approaches using viral vectors and Clustered Regularly Interspaced Short Palindromic Repeats -Cas9 are being explored to modulate angiogenesis, fibrosis, and inherited dystrophies. Overall, regenerative medicine is reshaping corneal therapeutics, offering effective alternatives to conventional transplantation with reduced donor dependence and improved safety. Future work must focus on long-term safety, cost-effectiveness, and equitable global access to realize its full clinical potential.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".