Abstract TP559: Sulforaphane Confers Neuroprotection Against Neuronal Loss, White Matter Injury and BBB Damage Following Experimental Vascular Cognitive Impairment
Bibliographic record
Abstract
Sulforaphane reduces brain injury following experimental vascular cognitive impairment by activating Nrf2 pathway Aims: Vascular cognitive impairment (VCI) is a type of dementia, and its major pathophysiological process is chronic ischemia, leading to the blood-brain barrier (BBB) disintegration, neuronal death, and white matter injury. The aim of current study is to test whether sulforaphane (Sfn), a natural activator of nuclear factor erythroid 2-related factor 2 (Nrf2), protects the brain against chronic ischemic injury and improve cognitive function after experiment VCI. Results: VCI was induced in rats by permanent occlusion of both common carotid arteries, which caused remarkable cognitive impairment, accompanied by neuronal death in the cortex and hippocampal CA1, demyelination in the corpus callosum and hippocampal fimbria, and accumulation of myelin debris in the corpus callosum. Sfn alleviated the cognitive impairment and reduced these accompanying pathophysiological changes. Sfn neuroprotection was associated with enhanced Nrf2 activation. In vitro, Sfn reduced neuronal and endothelial death, maintained the integrity of the BBB after oxygen-glucose deprivation; and Nrf2 knockdown with shRNA significantly reduced the protection of Sfn. Furthermore, Nrf2 knockdown in endothelial cells decreased the level of claudin-5, a tight junction protein; and luciferase assay suggested that claudin-5 might be a downstream target of Nrf2. Innovation: This is the first study demonstrates the neuroprotective effects of Sfn against neuronal loss, white matter injury, and BBB damage after VCI. Furthermore, it discovers the accumulated myelin debris in WM and that Nrf2 may control the expression of claudin-5. Conclusion: Our results suggest that Sfn provides comprehensive protection to the brain and may be a promising agent targeting cognitive impairment.
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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) | 0.001 | 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) | 0.003 | 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".