Potential roles of extracellular granzyme B in corneal and conjunctival diseases: A narrative review
Bibliographic record
Abstract
The cornea and conjunctiva are critical structures of the ocular surface that are prone to a range of inflammatory diseases impacting the vision of millions globally. Moreover, due to their complex etiology and pathophysiology, these conditions remain a significant clinical challenge. Granzyme B (GrB), a serine protease traditionally recognized for its intracellular role in targeting tumor or pathogen-infected cells, has been implicated in numerous pathogenic mechanisms observed in inflammatory corneal and conjunctival diseases, such as dysregulated inflammation and tissue remodeling, barrier dysfunction, epithelial-to-mesenchymal transition (EMT), fibrosis, neovascularization, and cell death, through its extracellular activity by cleaving various substrates upon being released into the extracellular space. On the ocular surface, GrB has been found to be upregulated in several inflammatory conditions, including keratolysis, herpes simplex keratitis (HSK), corneal graft rejection, pterygium, Stevens-Johnson syndrome (SJS), and even keratoconus, where it may contribute to chronic inflammation, epithelial barrier dysfunction, dysregulated tissue remodeling, and fibrosis. Although recent research has explored both classic immune-mediated intracellular roles and emerging extracellular roles of GrB across different tissues, organs, and diseases, its role in ocular diseases, particularly in the cornea and conjunctiva, remains understudied. This review aims to consolidate current knowledge on GrB's role in ocular surface diseases and explore its potential contributions to corneal and conjunctival pathologies by integrating findings from both ocular and systemic diseases to explore its molecular mechanisms, cellular sources, and extracellular substrates.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".