<p>The Pro-Fibrotic Behavior of Human Tenon’s Capsule Fibroblasts in Medically Treated Glaucoma Patients</p>
Bibliographic record
Abstract
PURPOSE: The aim of this study was to compare human Tenon's capsule fibroblasts (HTCFs) obtained from patients who received medical therapy for glaucoma (glaucomatous patients) and patients not treated for glaucoma (non-glaucomatous patients) in terms of wound healing and fibrosis. PATIENTS AND METHODS: Bioartificial tissues (BATs) were generated using primary HTCF-populated collagen lattices. Pro-fibrotic gene expression within HTCFs was compared between glaucomatous patients and non-glaucomatous patients after BAT culture. The BATs were also assessed regarding fibroblast-myofibroblast transition, collagen remodeling and collagen contraction using alpha-smooth muscle actin immunohistochemistry, picrosirius red staining and collagen contraction assays, respectively. RESULTS: Pro-fibrotic gene expression in BAT-cultured HTCFs derived from glaucomatous patients was significantly increased compared to non-glaucomatous patients. BATs imbued with HTCFs collected from glaucomatous patients exhibited a greater proportion of myofibroblasts as well as increased collagen contraction/remodeling compared to HTCFs isolated from non-glaucomatous patients. CONCLUSION: HTCFs from glaucomatous and non-glaucomatous patients differ in the expression of genes involved in fibrosis, proportion of fibroblasts undergoing transdifferentiation into myofibroblasts, contractile properties and collagen remodeling. These results suggest that for any number of reasons, at a cellular level, patients who received medical therapy for glaucoma have eyes primed for fibrosis.
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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) | 0.001 | 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 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".