Abstract WMP77: Ischemic Preconditioning Improves Long-Term Outcomes and Preserves Blood-Brain Barrier After Ischemic Stroke via Oxidative Signaling and Nrf2 Activation
Bibliographic record
Abstract
Introduction: Ischemic preconditioning (IPC) protects the brain against subsequent ischemic injuries. However, its protective mechanisms and long-term impact on stroke outcomes are unknown. IPC requires mild oxidative stress and may activate nuclear factor (erythroid-derived 2)-like 2 (Nrf2). Endogenous lipid electrophiles serve as robust Nrf2 activators. This study tests long-term effects of IPC and explores the mechanisms of IPC-mediated ischemic tolerance, focusing on lipid electrophiles and Nrf2 pathway. Methods: Wildtype (WT) and Nrf2 knockout (KO) mice were subjected to 60-min middle cerebral artery occlusion (MCAO) 3 d after IPC (12-min MCAO). Tissue loss, blood-brain barrier (BBB) damage, and neurobehavioral outcomes were assessed up to 35 d post stroke. The molecular mechanisms were explored by primary endothelial cell (EC) cultures with plasmid transfection and molecular biological approaches. Results: IPC reduced sensorimotor and cognitive deficits and tissue loss up to 35 d post stroke in WT mice, while Nrf2 KO abolished IPC-mediated protection. IPC led to mild oxidative stress, lipid electrophile generation and Nrf2 pathway activation. Prominent Nrf2 activation was seen in ECs and a selected group of astrocytes in tight association with microvessels, both of which are BBB components. As expected, IPC reduced BBB leakage 48 h post stroke and increased expressions of junctional proteins Claudin-5 and VE-Cadherin. Moreover, Nrf2 directly regulated Claudin-5 and VE-Cadherin promoter activities. Finally, a novel mechanism for electrophiles to activate Nrf2 was identified-through direct inhibition of glycogen synthase kinase 3β (GSK3β) activity via GSK3β-C199 residue. Conclusions: IPC preserves the BBB and provides long-term neuroprotection against stroke. Mechanistically, mild oxidative stress in IPC generates a pool of electrophiles, which then activates Nrf2 pathway through direct inhibition GSK3β-dependent Nrf2 degradation.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".