Understanding Inflammation-associated Ophthalmic Pathologies: A Novel 3D Co-culture Model of Monocyte-myofibroblast Immunomodulation
Bibliographic record
Abstract
Purpose: Inflammation is associated with, and may be causal of, a variety of ophthalmic pathologies. These pathologies are currently difficult to model in vitro because they involve complex interactions between the innate immune system, stromal cells, and other cells that normally maintain ocular tissue homeostasis. Using transscleral drainage channel fibrosis after glaucoma surgery as an example of inflammation-associated ocular fibrosis, we have assessed a simple but novel 3D cell culture system designed to reveal the immunomodulatory impacts of ocular connective tissue cells on monocytes, a major cellular component of the circulating immune system.Methods: Primary human Tenon’s capsule fibroblasts derived from five unrelated patients were activated into myofibroblasts in 3D collagen matrices under isometric tension, with and without exposure to an inflammatory cytokine-enhanced milieu, and co-cultured with an immortalized human monocyte cell line (THP-1 cells). Quantitative PCR analyses were performed on 8 candidate genes to assess the impacts of inflammatory cytokines on the myofibroblasts and the monocytes in mono-cultures and compared to cells in co-culture to clearly distinguish any co-culture-induced impacts on gene expression.Results: Our data indicate that both Tenon’s capsule myofibroblasts in 3D mono-culture and THP-1 monocytes in suspension mono-culture were responsive to inflammatory cytokine stimuli. Co-culture with Tenon’s capsule myofibroblasts significantly modulated the gene expression responses of THP-1 monocytes to inflammatory cytokine stimulation, indicative of an immunomodulatory “feedback” system between these cell types.Conclusion: Our findings provide proof of principle for the use of simple 3D co-culture systems as a means to enhance our understanding of ocular stromal cell interactions with cells of the innate immune system and to provide more informative in vitro models of inflammation-associated ophthalmic pathologies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".