标题：Fourier transform infrared spectroscopy coupled with machine learning classification for identification of oxidative damage in freeze-dried heart valves
摘要：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 H
2O
2 and FeCl
3. 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 H
2O
2- and FeCl
3-treated samples could be distinguished in some tissue section. A feed forward artificial neural network model could accurately classify H
2O
2 and FeCl
3 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.
