A Role of Caveolae in Trabecular Meshwork Mechanosensing and Contractile Tone
Bibliographic record
Abstract
Polymorphisms in the CAV1/2 gene loci impart increased risk for primary open-angle glaucoma (POAG). CAV1 encodes caveolin-1 (Cav1), which is required for biosynthesis of plasma membrane invaginations called caveolae. Cav1 knockout mice exhibit elevated intraocular pressure (IOP) and decreased outflow facility, but the mechanistic role of Cav1 in IOP homeostasis is unknown. We hypothesized that caveolae sequester/inhibit RhoA, to regulate trabecular meshwork (TM) mechanosensing and contractile tone. Using phosphorylated myosin light chain (pMLC) as a surrogate indicator for Rho/ROCK activity and contractile tone, we found that pMLC was elevated in Cav1-deficient TM cells compared to control (131 ± 10%, n = 10, p = 0.016). Elevation of pMLC levels following Cav1 knockdown occurred in cells on a soft surface (137 ± 7%, n = 24, p < 0.0001), but not on a hard surface (122 ± 17%, n = 12, p = 0.22). In Cav1-deficient TM cells where pMLC was elevated, Rho activity was also increased (123 ± 7%, n = 6, p = 0.017), suggesting activation of the Rho/ROCK pathway. Cyclic stretch reduced pMLC/MLC levels in TM cells (69 ± 7% n = 9, p = 0.002) and in Cav1-deficient TM cells, although not significantly (77 ± 11% n = 10, p = 0.059). Treatment with the Cav1 scaffolding domain mimetic, cavtratin (1 μM) caused a reduction in pMLC (70 ± 5% n = 7, p = 0.001), as did treatment with the scaffolding domain mutant cavnoxin (1 μM) (82 ± 7% n = 7, p = 0.04). Data suggest that caveolae differentially regulate RhoA signaling, and that caveolae participate in TM mechanotransduction. Cav1 regulation of these key TM functions provide evidence for underlying mechanisms linking polymorphisms in the Cav1/2 gene loci with increased POAG risk.
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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) | 0.002 | 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".