Abstract TMP115: Nox-2 and Cerebrovascular Function in Metabolic Syndrome After a Stroke
Bibliographic record
Abstract
Introduction: The aim here is to elucidate the mechanisms involved in post-stroke cerebrovascular impairments in metabolic syndrome (MetS) that pre-dispose obese patients to more severe post-stroke deficits. Methods: 1 hr middle cerebral artery occlusion was performed in 17 week old lean (LZR) and obese Zucker (OZR: MetS model) rats. At 24 hr or 15 days post-stroke, the ipsilateral middle cerebral artery (MCA) was cannulated in an ex-vivo microvessel preparation to examine MCA reactivity. Cerebrovascular microvessel density (MVD) was examined 15 days post-stroke via IHC. To examine a potential role of Nox2 and oxidative stress, a specific inhibitor of Nox2 oxidase Nox2-dstat (i.p 10mg/kg) was given during the stroke procedure in OZR. Results: In LZR, MCA reactivity was impaired vs. non-stroke control at 24hr post-stroke and remained stable at 15 days post-stroke. In LZR, NO bioavailability was reduced at 24hrs vs. controls, which remained stable at 15 days. In OZR, the MCA impairment was greater at 24 hr vs. LZR, and worsened significantly at 15 days post stroke. NO bioavailability for OZR at 24 hr was similar to LZR stroke, but by 15 days had fallen. MVD was reduced 15 days post-stroke, with a larger loss in OZR vs. LZR. Stroke mortality and infarct size were higher for OZR. Nox2 inhibition restored MCA reactivity, improved MVD and NO levels, and limited stroke infarct size in OZR post-stroke. Discussion: Our data suggest that the MetS increases stroke severity and drives a progressive decline in cerebrovascular dysfunction following ischemic stroke. Inhibiting Nox2 production improved stroke outcome in MetS.
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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) | 0.003 | 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".