Spatiotemporal metabolic mapping of ex-situ preserved hearts subjected to dialysis by integration of bio-SPME sampling with non-targeted metabolipidomic profiling
Bibliographic record
Abstract
Normothermic ex situ heart perfusion (ESHP) has emerged as a valid modality for advanced cardiac allograft preservation and conditioning prior to transplantation though myocardial function declines gradually during ESHP thus limiting its potential for expanding the donor pool. Recently, the utilization of dialysis has been shown to preserve myocardial and coronary vasomotor function. Herein, we sought to determine the changes in myocardial metabolism that could support this improvement. Male Yorkshire porcine hearts were subjected to ESHP for 8 h with or without dialysis. Alterations in metabolism were studied with an innovative in vivo solid-phase microextraction (SPME) technology coupled with global metabolite profiling at 15 min, 1.5, 4, and 8 h of perfusion. Bio-SPME sampling was performed by inserting SPME fibres coated with a PAN-based extraction phase containing mixed-mode (C8+benzenesulfonic acid) functionalities into the myocardium to a depth of their entire 8 mm coating or immersing them in the perfusate, followed by a 20-min extraction period for the analytes of interest. Dialyzed hearts demonstrated improved bioenergetics as evidenced by accelerated purine metabolism and less pronounced accumulation of intermediates of fatty acid β/ω-oxidation. Metabolic waste accumulation such as pro-inflammatory lipid mediators (e.g., leukotrienes) was mitigated thereby supporting the process of resolution of inflammation through excretion of specialized pro-resolving mediators (resolvins D1/D2, E2, protecin D1). Through implementing the unique analytical pipeline we demonstrated that the addition of dialysis may preserve cardiac metabolism allowing for prolonged ESHP. This strategy has the potential to facilitate high-risk donor organs’ reconditioning prior to transplantation. • In vivo SPME-LC/MS may facilitate non-invasive monitoring of cardiac allografts. • Implementation of SPME enabled spatiotemporal metabolic mapping of heart grafts. • Significant alterations in cardiac metabolism during ex vivo perfusion were found. • Dialysis during heart perfusion prevented detrimental metabolism remodeling. • SPME-LC-HR/MS revealed beneficial impact of dialysis for ex situ preserved grafts.
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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".