Plasma Levels of Myocardial MicroRNA-133a Increase by Intraoperative Cytokine Hemoadsorption in the Complex Cardiovascular Operation
Bibliographic record
Abstract
BACKGROUND: Complex cardiovascular procedures may initiate a systemic inflammatory response syndrome (SIRS) with a massive cytokine release, which is involved in postoperative myocardial injury. Intraoperative cytokine hemoadsorption (HA) mitigates the inflammatory response. Micro ribonucleic acids (miRNAs) are emerging as a marker of myocardial injury. METHODS: This study evaluated if intraoperative cytokine reduction by HA modulates SIRS and affects myocardial injury as measured by miRNA-126, 223 and miRNA-1, 133a, respectively. Twenty-eight patients were assigned into HA (n = 15) and control (C) (n = 13) groups. HA was performed by integrating CytoSorb™ into the extracorporeal circuit. RESULTS: MiRNA-133a plasma levels were increased postoperatively in both groups but were much higher in the HA group than in the C group at 3 h (P = 0.037) and 18 h (P = 0.017) after reperfusion. MiRNA-1 and miRNA-223 plasma levels were significantly increased postoperatively, but did not differ between groups. The vascular miRNA-126 was not affected. CONCLUSION: Intraoperative cytokine HA in cardiovascular operations increased the plasma levels of miRNA-133a, suggesting higher myocardial 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".