Abstract TMP22: Intravenous Glyburide Treatment is Associated with Reduced Matrix Metalloproteinase-9 in Human Acute Stroke
Bibliographic record
Abstract
Background: Elevated matrix metalloproteinase-9 (MMP-9) following acute ischemic stroke is associated with blood-brain barrier breakdown and hemorrhagic conversion. Prior retrospective evidence suggests that sulfonylurea use may be associated with reduced risk of hemorrhagic conversion. We hypothesized that sulfonylureas may reduce MMP-9 level in stroke patients. Methods: Using serial plasma samples from six subjects in the Glyburide Advantage in Malignant Edema and Stroke Pilot trial (GAMES-Pilot), we evaluated the level of MMP-9 in human subjects presenting with large hemispheric stroke who were treated with intravenous glyburide (RP-1127). MMP-9 was measured in a control cohort with large ischemic stroke who were not treated with glyburide. Commercially available ELISA kits and gel zymography were used to measure MMP-9 at baseline and at approximately 48 hours after stroke. GAMES subjects had additional time points analyzed until approximately 84 hours after stroke. Results: Average MMP-9 level in glyburide-treated stroke patients was 47.2 ± 8.0 ng/mL compared to 143.4 ± 60.35 ng/mL in untreated control subjects (p=0.004). Zymography analysis demonstrated a significant decrease in the pro-enzyme but no change in the active form of MMP-9. There was no difference in the level of the MMP-9 specific inhibitor, TIMP-1. No subjects exhibited parenchymal hemorrhagic conversion on 24 hour head CT scan. Conclusions: Glyburide treatment in human stroke patients with large hemispheric stroke is associated reduced level of MMP-9. Elucidating the underlying mechanism of glyburide’s effect on MMP-9 and the risk of hemorrhagic conversion may highlight future directions of therapy, including in combination with intravenous tissue plasminogen activator (IV t-PA).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".