Left ventricular transcriptome and extracellular vesicle-derived miRNAs in porcine donation after circulatory death (DCD) hearts undergoing prolonged working mode <i>ex situ</i> perfusion
Bibliographic record
Abstract
ABSTRACT Donation after circulatory death (DCD) hearts suffer from warm ischemia-reperfusion injury, which compromises graft quality. We have previously demonstrated that a postconditioning-based cardioprotective treatment (1% Intralipid, 2% (v/v) sevoflurane, 3 nM remifentanil) improved the function and viability of porcine DCD hearts undergoing ex situ heart perfusion (ESHP). However, transcriptional changes in DCD hearts subjected to prolonged working mode ESHP as compared with healthy hearts, and more so transcriptional changes in the presence or absence of cardioprotection, as well as the early reperfusion profile of extracellular vesicle (EV)-derived miRNAs, critical regulators of the transcriptional control, have not been investigated. A total of 5,483 differentially expressed transcripts were identified in left ventricular tissue samples of DCD hearts (N=10) collected after 6 hours of ESHP when compared with healthy hearts not subjected to ESHP (N=8), irrespective of cardioprotection. Downregulation of protein synthesis, metabolic, and DNA repair gene sets was most prominent, while inflammatory and remodeling gene sets were upregulated. Between DCD hearts that were treated with (pDCD_ESHP, N=5) or without (uDCD_ESHP, N=5) cardioprotection, only 43 transcripts were differentially regulated. Specifically, lipid breakdown, beta-oxidation, and DNA repair gene sets were upregulated in pDCD_ESHP, whereas lipid accumulation, inflammation, oxidative stress, and maladaptive remodeling gene sets were upregulated in uDCD_ESHP. Predominantly cardioprotective EV-derived miRNAs were released into the perfusate in pDCD_ESHP, while predominantly cardiac injury-associated miRNAs were released into the perfusate in uDCD_ESHP. Cardioprotection promoted adaptive rather than maladaptive transcriptional changes and enabled the release of potentially beneficial miRNAs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".