Objective: To identify potential biomarkers during ex vivo lung perfusion (EVLP) using metabolomics approach. Summary Background Data: EVLP increases the number of usable donor lungs for lung transplantation (LTx) by physiologic assessment of explanted marginal lungs. The underlying paradigm of EVLP is the normothermic perfusion of cadaveric lungs previously flushed and stored in hypothermic preservation fluid, which allows the resumption of active cellular metabolism and respiratory function. Metabolomics of EVLP perfusate may identify metabolic profiles of donor lungs associated with early LTx outcomes. Methods: EVLP perfusate taken at 1and 4 hperfusion were collected from 50 clinical EVLP cases, and submitted to untargeted metabolic profiling with mass spectrometry. The findings were correlated with early LTx outcomes. Results: Following EVLP, 7 cases were declined for LTx. In the remaining transplanted cases, 9 cases developed primary graft dysfunction (PGD) 3. For the metabolic profile at EVLP-1h, a logistic regression model based on palmitoyl-sphingomyelin, 5-aminovalerate, and decanoylcarnitine yielded a receiver operating characteristic (ROC) curve with an area under the curve (AUC) of 0.987 in differentiating PGD 3 from Non-PGD 3 outcomes. For the metabolic profile at EVLP-4h, a logistic regression model based on N2-methylguanosine, 5-aminovalerate, oleamide, and decanoylcarnitine yielded a ROC curve with AUC 0.985 in differentiating PGD 3 from non-PGD 3 outcomes. Conclusions: Metabolomics of EVLP perfusate revealed a small panel of metabolites highly correlated with early LTx outcomes, and may be potential biomarkers that can improve selection of marginal lungs on EVLP. Further validation studies are needed to confirm these findings.
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Αλέξανδρος Γ. Σφακιανάκης Medicine by Alexandros G. Sfakianakis,Anapafseos 5 Agios Nikolaos 72100 Crete Greece,00302841026182,0030693260717...
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heory of COVID-19 pathogenesis Publication date: November 2020Source: Medical Hypotheses, Volume 144Author(s): Yuichiro J. Suzuki ScienceD...
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