Mesenchymal stromal cells from human Wharton’s jelly modulate the intraocular immune response in a glucocorticoid hypertension model: an exploratory analysis
Bibliographic record
Abstract
INTRODUCTION: Glaucoma is a neurodegenerative disease characterized by the loss of retinal ganglion cells. Recent research suggests immunological changes such as cytokine imbalance may affect its pathophysiology. This implies that immunomodulation, like that of mesenchymal cells, could be a potential therapeutic avenue for this disease. However, the effects of intravitreal injections of human Wharton's jelly-derived mesenchymal stromal cells (hWJ-MSCs) on intraocular immune response have not been assessed in ocular hypertension (OH) models. METHODS: We explored this by measuring cytokine levels and expression of other markers, such as glial fibrillary acidic protein (GFAP) and T cells, in 15 randomly divided New Zealand rabbits: G1: OH, G2: hWJ-MSCs, and G3: OH+hWJ-MSCs. We analyzed the aqueous humor (IL-6, IL-8, and TNF-α) and vitreous humor (IFN-γ, IL-10, and TGF-β) using ELISA and flow cytometry (cell populations), as well as TCD3+, TCD3+/TCD4+, and TCD3+/TCD8+ lymphocytes, and GFAP in the retina and optic nerve through immunohistochemistry. RESULTS: We found a decrease in TNF-α, IL-6, IFN-γ, IL-10, and IL-8 in G3 compared to G1 and an increase in TGF-β in both G2 and G3. TCD3+ retinal infiltration in all groups was primarily TCD8+ rather than TCD4+ cells, and strong GFAP expression was observed in both the retina and optic nerves in all groups. CONCLUSION: Our results suggest that cellular and humoral immune responses may play a role in glaucomatous optic neuropathy and that intravitreal hWJ-MSCs can induce an immunosuppressive environment by inhibiting proinflammatory cytokines and enhancing regulatory cytokines.
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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 | 0.001 |
| 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".