Enhancement of Outflow Facility in the Murine Eye by Targeting Selected Tight-Junctions of Schlemm’s Canal Endothelia
Bibliographic record
Abstract
The juxtacanalicular connective tissue of the trabecular meshwork together with inner wall endothelium of Schlemm's canal (SC) provide the bulk of resistance to aqueous outflow from the anterior chamber. Endothelial cells lining SC elaborate tight junctions (TJs), down-regulation of which may widen paracellular spaces between cells, allowing greater fluid outflow. We observed significant increase in paracellular permeability following siRNA-mediated suppression of TJ transcripts, claudin-11, zonula-occludens-1 (ZO-1) and tricellulin in human SC endothelial monolayers. In mice claudin-11 was not detected, but intracameral injection of siRNAs targeting ZO-1 and tricellulin increased outflow facility significantly. Structural qualitative and quantitative analysis of SC inner wall by transmission electron microscopy revealed significantly more open clefts between endothelial cells treated with targeting, as opposed to non-targeting siRNA. These data substantiate the concept that the continuity of SC endothelium is an important determinant of outflow resistance, and suggest that SC endothelial TJs represent a specific target for enhancement of aqueous movement through the conventional outflow system.
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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 | 0.001 | 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".