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Comparative Analysis of Dry and Wet Porometry Methods for Characterization of Regular and Cross-Linked Virus Removal Filter Papers
Pore-size distribution (PSD) is the most critical parameter for size-exclusion virus removal filters. Yet, different dry- and wet-state porometry methods yield different pore-size values. The goal of this work is to conduct comparative analysis of nitrogen gas sorption (NGSP), liquid-liquid and cryo...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359513/ https://www.ncbi.nlm.nih.gov/pubmed/30577520 http://dx.doi.org/10.3390/membranes9010001 |
Sumario: | Pore-size distribution (PSD) is the most critical parameter for size-exclusion virus removal filters. Yet, different dry- and wet-state porometry methods yield different pore-size values. The goal of this work is to conduct comparative analysis of nitrogen gas sorption (NGSP), liquid-liquid and cryoporometry with differential scanning calorimetry (CP-DSC) methods with respect to characterization of regular and cross-linked virus removal filter paper based on cellulose nanofibers, i.e. the mille-feuille filter. The filters were further characterized with atomic force and scanning electron microscopy. Finally, the removal of the worst-case model virus, i.e. minute virus of mice (MVM; 20 nm, nonenveloped parvovirus) was evaluated. The results revealed that there is no difference of the obtained PSDs between the wet methods, i.e. DSC and liquid-liquid porometry (LLP), as well as no difference between the regular and cross-linked filters regardless of method. MVM filtration at different trans membrane pressure (TMP) revealed strong dependence of the virus removal capability on applied pressure. It was further observed that cross-linking filters showed enhanced virus removal, especially at lower TMP. In all, the results of this study highlight the complex nature of virus capture in size-exclusion filters. |
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