Metabolic reprogramming by immune-responsive gene 1 up-regulation improves donor heart preservation and function
Bibliographic record
Abstract
Preservation quality of donor hearts is a key determinant of transplant success. Preservation duration beyond 4 hours is associated with primary graft dysfunction (PGD). Given transport time constraints, geographical limitations exist for donor-recipient matching, leading to donor heart underutilization. Here, we showed that metabolic reprogramming through up-regulation of the enzyme immune response gene 1 (IRG1) and its product itaconate improved heart function after prolonged preservation. Irg1 transcript induction was achieved by adding the histone deacetylase (HDAC) inhibitor valproic acid (VPA) to a histidine-tryptophan-ketoglutarate solution used for donor heart preservation. VPA increased acetylated H3K27 occupancy at the IRG1 enhancer and IRG1 transcript expression in human donor hearts. IRG1 converts aconitate to itaconate, which has both anti-inflammatory and antioxidant properties. Accordingly, our studies showed that Irg1 transcript up-regulation by VPA treatment increased nuclear translocation of nuclear factor erythroid 2–related factor 2 (Nrf2) in mice, which was accompanied by increased antioxidant protein expression [hemeoxygenase 1 (HO1) and superoxide dismutase 1 (SOD1)]. Deletion of Irg1 in mice (Irg1 −/− ) negated the antioxidant and cardioprotective effects of VPA. Consistent with itaconate’s ability to inhibit succinate dehydrogenase, VPA treatment of human hearts increased itaconate availability and reduced succinate accumulation during preservation. VPA similarly increased IRG1 expression in pig donor hearts and improved its function in an ex vivo cardiac perfusion system both at the clinical 4-hour preservation threshold and at 10 hours. These results suggest that augmentation of cardioprotective immune-metabolomic pathways may be a promising therapeutic strategy for improving donor heart function in transplantation.
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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) | 0.002 | 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".