Development and Verification of a Novel Three-Dimensional Aqueous Outflow Model for High-Throughput Drug Screening
Bibliographic record
Abstract
Distal outflow bleb-forming procedures in ophthalmic surgery expose subconjunctival tissue to inflammatory cytokines present in the aqueous humor, resulting in impaired outflow and, consequently, increased intraocular pressure. Clinically, this manifests as an increased risk of surgical failure often necessitating revision. This study (1) introduces a novel high-throughput screening platform for testing potential anti-fibrotic compounds and (2) assesses the clinical viability of modulating the transforming growth factor beta-SMAD2/3 pathway as a key contributor to post-operative outflow reduction, using the signal transduction inhibitor verteporfin. Human Tenon's capsule fibroblasts (HTCFs) were cultured within a 3D collagen matrix in a microfluidic system modelling aqueous humor drainage. The perfusate was augmented with transforming growth factor beta 1 (TGFβ1), and afferent pressure to the tissue-mimetic was continuously monitored to detect treatment-related pressure elevations. Co-treatment with verteporfin was employed to evaluate its capacity to counteract TGFβ1 induced pressure changes. Immunofluorescent studies were conducted on the tissue-mimetic to corroborate the pressure data with cellular changes. Introduction of TGFβ1 induced treatment-related afferent pressure increase in the tissue-mimetic. HTCFs treated with TGFβ1 displayed visibly enlarged cytoskeletons and stress fiber formation, consistent with myofibroblast transformation. Importantly, verteporfin effectively mitigated these changes, reducing both afferent pressure increases and cytoskeletal alterations. In summary, this study models the pathological filtration bleb response to TGFβ1, while demonstrating verteporfin's effectiveness in ameliorating both functional and cellular changes caused by TGFβ1. These demonstrate modulation of the aforementioned pathway as a potential avenue for addressing post-operative changes and reductions in filtration bleb outflow capacity. Furthermore, the establishment of a high-throughput screening platform offers a valuable pre-animal testing tool for investigating potential compounds to facilitate surgical wound healing.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".