Fourier transform infrared spectroscopy coupled with machine learning classification for identification of oxidative damage in freeze-dried heart valves

Abstract Freeze-drying can be used to ensure off-the-shelf availability of decellularized heart valves for cardiovascular surgery. In this study, decellularized porcine aortic heart valves were analyzed by nitroblue tetrazolium (NBT) staining and Fourier transform infrared spectroscopy (FTIR) to ide...

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Autores principales:	Dejia Liu, Sükrü Caliskan, Bita Rashidfarokhi, Harriëtte Oldenhof, Klaus Jung, Harald Sieme, Andres Hilfiker, Willem F. Wolkers
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c8342ed5b18f41329cfb21e52d1a6688
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spelling	oai:doaj.org-article:c8342ed5b18f41329cfb21e52d1a66882021-12-02T15:03:07ZFourier transform infrared spectroscopy coupled with machine learning classification for identification of oxidative damage in freeze-dried heart valves10.1038/s41598-021-91802-22045-2322https://doaj.org/article/c8342ed5b18f41329cfb21e52d1a66882021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-91802-2https://doaj.org/toc/2045-2322Abstract Freeze-drying can be used to ensure off-the-shelf availability of decellularized heart valves for cardiovascular surgery. In this study, decellularized porcine aortic heart valves were analyzed by nitroblue tetrazolium (NBT) staining and Fourier transform infrared spectroscopy (FTIR) to identify oxidative damage during freeze-drying and subsequent storage as well as after treatment with H2O2 and FeCl3. NBT staining revealed that sucrose at a concentration of at least 40% (w/v) is needed to prevent oxidative damage during freeze-drying. Dried specimens that were stored at 4 °C depict little to no oxidative damage during storage for up to 2 months. FTIR analysis shows that fresh control, freeze-dried and stored heart valve specimens cannot be distinguished from one another, whereas H2O2- and FeCl3-treated samples could be distinguished in some tissue section. A feed forward artificial neural network model could accurately classify H2O2 and FeCl3 treated samples. However, fresh control, freeze-dried and stored samples could not be distinguished from one another, which implies that these groups are very similar in terms of their biomolecular fingerprints. Taken together, we conclude that sucrose can minimize oxidative damage caused by freeze-drying, and that subsequent dried storage has little effects on the overall biochemical composition of heart valve scaffolds.Dejia LiuSükrü CaliskanBita RashidfarokhiHarriëtte OldenhofKlaus JungHarald SiemeAndres HilfikerWillem F. WolkersNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Dejia Liu Sükrü Caliskan Bita Rashidfarokhi Harriëtte Oldenhof Klaus Jung Harald Sieme Andres Hilfiker Willem F. Wolkers Fourier transform infrared spectroscopy coupled with machine learning classification for identification of oxidative damage in freeze-dried heart valves
description	Abstract Freeze-drying can be used to ensure off-the-shelf availability of decellularized heart valves for cardiovascular surgery. In this study, decellularized porcine aortic heart valves were analyzed by nitroblue tetrazolium (NBT) staining and Fourier transform infrared spectroscopy (FTIR) to identify oxidative damage during freeze-drying and subsequent storage as well as after treatment with H2O2 and FeCl3. NBT staining revealed that sucrose at a concentration of at least 40% (w/v) is needed to prevent oxidative damage during freeze-drying. Dried specimens that were stored at 4 °C depict little to no oxidative damage during storage for up to 2 months. FTIR analysis shows that fresh control, freeze-dried and stored heart valve specimens cannot be distinguished from one another, whereas H2O2- and FeCl3-treated samples could be distinguished in some tissue section. A feed forward artificial neural network model could accurately classify H2O2 and FeCl3 treated samples. However, fresh control, freeze-dried and stored samples could not be distinguished from one another, which implies that these groups are very similar in terms of their biomolecular fingerprints. Taken together, we conclude that sucrose can minimize oxidative damage caused by freeze-drying, and that subsequent dried storage has little effects on the overall biochemical composition of heart valve scaffolds.
format	article
author	Dejia Liu Sükrü Caliskan Bita Rashidfarokhi Harriëtte Oldenhof Klaus Jung Harald Sieme Andres Hilfiker Willem F. Wolkers
author_facet	Dejia Liu Sükrü Caliskan Bita Rashidfarokhi Harriëtte Oldenhof Klaus Jung Harald Sieme Andres Hilfiker Willem F. Wolkers
author_sort	Dejia Liu
title	Fourier transform infrared spectroscopy coupled with machine learning classification for identification of oxidative damage in freeze-dried heart valves
title_short	Fourier transform infrared spectroscopy coupled with machine learning classification for identification of oxidative damage in freeze-dried heart valves
title_full	Fourier transform infrared spectroscopy coupled with machine learning classification for identification of oxidative damage in freeze-dried heart valves
title_fullStr	Fourier transform infrared spectroscopy coupled with machine learning classification for identification of oxidative damage in freeze-dried heart valves
title_full_unstemmed	Fourier transform infrared spectroscopy coupled with machine learning classification for identification of oxidative damage in freeze-dried heart valves
title_sort	fourier transform infrared spectroscopy coupled with machine learning classification for identification of oxidative damage in freeze-dried heart valves
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/c8342ed5b18f41329cfb21e52d1a6688
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Fourier transform infrared spectroscopy coupled with machine learning classification for identification of oxidative damage in freeze-dried heart valves

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