Identification of a Retinal Aldosterone System and the Protective Effects of Mineralocorticoid Receptor Antagonism on Retinal Vascular Pathology
Bibliographic record
Abstract
Blockade of the renin-angiotensin-aldosterone system (RAAS) is being evaluated as a treatment for diabetic retinopathy; however, whether the mineralocorticoid receptor (MR) and aldosterone influence retinal vascular pathology is unknown. We examined the effect of MR antagonism on pathological angiogenesis in rats with oxygen-induced retinopathy (OIR). To determine the mechanisms by which the MR and aldosterone may influence retinal angiogenesis; inflammation and glucose-6-phosphate dehydrogenase (G6PD) were evaluated in OIR and cultured bovine retinal endothelial cells (BRECs) and bovine retinal pericytes (BRPs). In OIR, MR antagonism (spironolactone) was antiangiogenic. Aldosterone may mediate the pathogenic actions of MR in the retina, with 11beta-hydroxysteroid dehydrogenase type 2 mRNA being detected and with aldosterone stimulating proliferation and tubulogenesis in BRECs and exacerbating angiogenesis in OIR, which was attenuated with spironolactone. The MR and aldosterone modulated retinal inflammation, with leukostasis and monocyte chemoattractant protein-1 mRNA and protein in OIR being reduced by spironolactone and increased by aldosterone. A reduction in G6PD may be an early response to aldosterone. In BRECs, BRPs, and early OIR, aldosterone reduced G6PD mRNA, and in late OIR, aldosterone increased mRNA for the NAD(P)H oxidase subunit Nox4. A functional retinal MR-aldosterone system was evident with MR expression, translocation of nuclear MR, and aldosterone synthase expression, which was modulated by RAAS blockade. We make the first report that MR and aldosterone influence retinal vasculopathy, which may involve inflammatory and G6PD mechanisms. MR antagonism may be relevant when developing treatments for retinopathies that target the RAAS.
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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".