MOTS-c attenuates lung ischemia-reperfusion injury via MYH9-Dependent nuclear translocation and transcriptional activation of antioxidant genes
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Bibliographic record
Abstract
Acute respiratory distress syndrome (ARDS) following cardiopulmonary bypass (CPB) is driven by oxidative stress during lung ischemia-reperfusion injury (LIRI). Mitochondrial-derived peptide MOTS-c has emerged as a regulator of mitochondrial-nuclear communication, yet its role in CPB-induced ARDS remains unclear. Here, we identify MOTS-c as a critical mediator of endothelial protection against LIRI through MYH9-dependent nuclear translocation and transcriptional activation of antioxidant genes. In rat LIRI models, endothelial cells exhibited the most significant MOTS-c upregulation, correlating with barrier preservation and reduced oxidative stress. Mechanistically, hypoxia-reoxygenation (HR) triggered reactive oxygen species (ROS)-dependent phosphorylation of MYH9 at Ser1943 via casein kinase II subunit alpha (CK2A), enabling MOTS-c binding to MYH9-γ-Actin complexes for nuclear transport. RNA sequencing (RNA-seq) combined with chromatin immunoprecipitation sequencing (ChIP-seq) revealed direct MOTS-c interaction with promoters of antioxidant genes (e.g., HMOX1, NQO1), which harbor antioxidant response elements (AREs). Clinically, serum MOTS-c increments within 24 h post-CPB (ΔMOTS-c) outperformed traditional biomarkers in predicting ARDS incidence, with multivariate models incorporating ΔMOTS-c achieving superior discriminative power (AUC = 0.885). Exogenous MOTS-c administration in rats attenuated lung injury by reducing oxidative damage, inflammation, and mortality, recapitulating endogenous protective mechanisms. Our findings establish MOTS-c as a dual-function molecule-acting via ROS-CK2A-MYH9 signaling to activate nuclear antioxidant defenses and serving as a prognostic biomarker for CPB-related complications. This study bridges mitochondrial dynamics, nuclear transcriptional regulation, and clinical outcomes, offering novel preventive avenues for IRI-associated pathologies.
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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 | 0.000 | 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) | 0.000 | 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