Mechanisms underlying corticosterone mediated inhibition of angiogenesis
Bibliographic record
Abstract
Angiogenesis involves cell proliferation, invasion and migration of endothelial cells. Corticosterone (CORT), elevated in diabetes and metabolic syndrome, is known to be angiostatic, but it's mechanisms of action are unknown. Previously, we found that CORT inhibits matrix metalloproteinase (MMP)‐2 production and activity. We treated rat microvascular endothelial cells with 600 nM CORT for 48 hrs and found a significant decrease in full length MMP‐2 promoter activity using a luciferase reporter assay. This effect was localized to a region between ‐1560 and ‐1386 bp. However, pretreatment of cells with 10 μM RU 486 (glucocorticoid receptor (GR) antagonist) for 2 hrs did not block the CORT mediated inhibition of MMP‐2 production or activation. To observe the effect of CORT on endothelial cell sprouting, we cultured cell spheroids in type‐1 collagen and treated them with CORT for 48 hrs. At 24 hrs CORT treated cells displayed numerous sprouts, similar to controls, but at 48 hrs, sprouts had destabilized and regressed in response to CORT. Our data suggest that the mechanism of CORT‐dependent inhibition of MMP‐2 production may be due to reduced transcription, but that this may not be GR‐mediated. In future studies, we will identify intracellular signals affected by CORT treatment that may contribute to sprout repression. Funding by NSERC & HSFO. Grant Funding Source NSERC
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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 | 0.000 | 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) | 0.002 | 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".