Protective role of Nrf2 against ischemia reperfusion injury and cardiac allograft vasculopathy
Bibliographic record
Abstract
Ischemia-reperfusion injury (IRI) and cardiac allograft vasculopathy (CAV) remain unsolved complications post-heart transplant (Tx). The antioxidant transcription factor Nuclear factor erythroid 2-related factor 2 (Nrf2) has been suggested to inhibit reactive oxygen species-mediated NF-κB activation. We hypothesized that Nrf2 inhibits NF-κB activation post-Tx and suppresses IRI and the subsequent development of CAV. IRI and CAV were investigated in murine heterotopic Tx models, respectively. Nrf2 wild-type (WT) and KO mice were used as donors. Sulforaphane was used as an Nrf2 agonist. In saline-treated animals following 24 hours of reperfusion in isogenic grafts, Nrf2-KO showed significantly less SOD1/2 activity compared with WT. Nrf2-KO displayed significantly high total and phosphorylated p65 expressions and percentage of cells with nuclear p65. mRNA levels of NF-κB-mediated proinflammatory genes were also high. Graft dysfunction, apoptosis, and caspase-3 activity were significantly higher in Nrf2-KO. In the allograft studies, graft beating score was significantly weaker in Nrf2-KO compared with WT. Nrf2-KO also demonstrated significantly more coronary luminal narrowing. In WT animals, sulforaphane successfully augmented all the protective effects of Nrf2 with increase of SOD2 activity. Nrf2 inhibits NF-κB activation and protects against IRI via its antioxidant properties and suppresses the subsequent development of CAV.
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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 | 0.000 |
| 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".