Autophagy deficiency exacerbated hypoxia-reoxygenation induced inflammation and cell death via a mitochondrial DNA/STING/IRF3 pathway
Bibliographic record
Abstract
AIMS: Autophagy is an important cellular process for maintaining physiological homeostasis and is known to protect against cardiovascular diseases including ischemia reperfusion (I/R) injury. The underlying mechanisms behind its protection require further characterization. MATERIALS AND METHODS: Atg7 knock out (AKO) mice were generated and subjected to I/R injury, complemented by Atg7 KO in a H9c2 cardiomyoblast cellular model ± hypoxia-reoxygenation. Subsequently, in both models, inflammation and cell death were studied. KEY FINDINGS: We confirmed that Atg7 KO led to autophagy, including mitophagy, deficiency. Upon H/R, Atg7 KO cells exhibited increased cell death compared to WT cells. Notably, we found that autophagy deficiency increased stress-induced mitochondrial fission, release of mitochondrial DNA, and sterile inflammation, namely activation of a STING/IRF3 axis leading to elevated interferon-α. Following I/R injury, AKO mice showed elevated cell death which correlated with a gene expression profile indicative of decreased anti-inflammatory responses. SIGNIFICANCE: Autophagy deficiency in the cardiomyocyte setting results in detrimental effects during I/R injury in mice or H/R injury in cells, mediated in part via mtDNA/IRF3/STING pathway. As such, modulation of this pathway may yield novel and promising therapeutics to treat or prevent I/R injury.
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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".