Abstract
The development of reliable tissue engineering methods using decellularized cadaveric or donor lungs could potentially provide a new source of lung tissue. The vast majority of current lung decellularization protocols are detergent based and incompletely removed residual detergents may have a deleterious impact on subsequent scaffold recellularization. Detergent removal and quality control measures that rigorously and reliably confirm removal, ideally utilizing nondestructive methods, are thus critical for generating optimal acellular scaffolds suitable for potential clinical translation. Using a modified and optimized version of a methylene blue-based detergent assay, we developed a straightforward, noninvasive method for easily and reliably detecting two of the most commonly utilized anionic detergents, sodium deoxycholate (SDC) and sodium dodecyl sulfate (SDS), in lung decellularization effluents. In parallel studies, we sought to determine the threshold of detergent concentration that was cytotoxic using four different representative human cell types utilized in the study of lung recellularization: human bronchial epithelial cells, human pulmonary vascular endothelial cells (CBF12), human lung fibroblasts, and human mesenchymal stem cells. Notably, different cells have varying thresholds for either SDC or SDS-based detergent-induced cytotoxicity. These studies demonstrate the importance of reliably removing residual detergents and argue that multiple cell lines should be tested in cytocompatibility-based assessments of acellular scaffolds. The detergent detection assay presented here is a useful nondestructive tool for assessing detergent removal in potential decellularization schemes or for use as a potential endpoint in future clinical schemes, generating acellular lungs using anionic detergent-based decellularization protocols.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 1937-3384 |
Sprache: | Englisch |
Dokumenten ID: | 45133 |
Datum der Veröffentlichung auf Open Access LMU: | 27. Apr. 2018, 08:08 |
Letzte Änderungen: | 04. Nov. 2020, 13:21 |