Cardiac macrophage migration inhibitory factor inhibits JNK pathway activation and injury during ischemia/reperfusion
Why this work is in the frame
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Bibliographic record
Abstract
Macrophage migration inhibitory factor (MIF) is a proinflammatory cytokine that also modulates physiologic cell signaling pathways. MIF is expressed in cardiomyocytes and limits cardiac injury by enhancing AMPK activity during ischemia. Reperfusion injury is mediated in part by activation of the stress kinase JNK, but whether MIF modulates JNK in this setting is unknown. We examined the role of MIF in regulating JNK activation and cardiac injury during experimental ischemia/reperfusion in mouse hearts. Isolated perfused Mif-/- hearts had greater contractile dysfunction, necrosis, and JNK activation than WT hearts, with increased upstream MAPK kinase 4 phosphorylation, following ischemia/reperfusion. These effects were reversed if recombinant MIF was present during reperfusion, indicating that MIF deficiency during reperfusion exacerbated injury. Activated JNK acts in a proapoptotic manner by regulating BCL2-associated agonist of cell death (BAD) phosphorylation, and this effect was accentuated in Mif-/- hearts after ischemia/reperfusion. Similar detrimental effects of MIF deficiency were observed in vivo following coronary occlusion and reperfusion in Mif-/- mice. Importantly, excess JNK activation also was observed after hypoxia-reoxygenation in human fibroblasts homozygous for the MIF allele with the lowest level of promoter activity. These data indicate that endogenous MIF inhibits JNK pathway activation during reperfusion and protects the heart from injury. These findings have clinical implications for patients with the low-expression MIF allele.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it