Immunity and Stress Responses Are Induced During Ex Situ Heart Perfusion
Bibliographic record
Abstract
BACKGROUND: Ex situ heart perfusion (ESHP) preserves the donated heart in a perfused, beating condition preventing cold storage-related ischemia and provides a platform to evaluate myocardial viability during preservation. However, myocardial function declines gradually during ESHP. Extracorporeal circulation systems are associated with the induction of systemic inflammatory and stress responses. Our aim was to evaluate the incidence of inflammation and induction of endoplasmic reticulum stress responses during an extended period of ESHP. METHODS: Cardiac function, myocardial tissue injury, markers of inflammation, oxidative stress, and endoplasmic reticulum stress were assessed in healthy pig hearts, perfused for 12 hours either in nonworking mode (non-WM=7) or working mode (WM, n=6). RESULTS: =0.022). Myocardial markers of endoplasmic reticulum stress were expressed higher in ESHP hearts compared with in vivo samples. The proinflammatory cytokines and oxidized low-density lipoprotein significantly increased in the perfusate throughout the perfusion in both perfusion groups. The left ventricular expression of the cytokines and malondialdehyde was induced in non-WM, whereas it was not different between WM and in vivo. CONCLUSIONS: Myocardial function declines during ESHP regardless of perfusion mode. However, ESHP in WM may lead to superior preservation of myocardial function and viability. Both inflammation and endoplasmic reticulum stress responses are significantly induced during ESHP and may contribute to the myocardial functional decline, representing a potential therapeutic target to improve the clinical donor heart preservation.
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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".