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Fast, easy, and reproducible fingerprint methods for endotoxin characterization in nanocellulose and alginate-based hydrogel scaffolds

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posted on 2024-09-16, 09:05 authored by Jan Zuber, Paula Lopes Cascabulho, Sara Gemini Piperni, Ronaldo José Farias Corrêa do Amaral, Carla Vogt, Vincent Carre, Jasmine Hertzog, Eero Kontturi, Anna TrubetskayaAnna Trubetskaya

Nanocellulose- and alginate-based hydrogels have been suggested as potential wound-healing materials, but their utilization is limited by the Food and Drug Administration (FDA) requirements regarding endotoxin levels. Cytotoxicity and the presence of endotoxin were assessed after gel sterilization using an autoclave and UV treatment. A new fingerprinting method was developed to characterize the compounds detected in cellulose nanocrystal (CNC)- and cellulose-nanofiber (CNF)-based hydrogels using both positive- and negative-ion mode electrospray ionization Fourier transform ion cyclotron resonance mass spectroscopy (ESI FT-ICR MS). These biobased hydrogels were used as scaffolds for the cultivation and growth of human dermal fibroblasts to test their biocompatibility. A resazurin-based assay was preferred over all other biocompatibility methodologies since it allowed for the evaluation of viability over time in the same sample without causing cell lysis. The CNF dispersion of 6 EU mL−1 was slightly above the limits, and it did not affect the cell viability, whereas CNC hydrogels induced a reduction of metabolic activity by the fibroblasts. The chemical structure of the detected endotoxins did not contain phosphates, but it encompassed hydrophobic sulfonate groups, requiring the development of new high-pressure sterilization methods for the use of cellulose hydrogels in medicine.

History

Publication

Biomacromolecules, 2024

Publisher

American Chemical Society

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Other Funding information

Dr. A.T. acknowledges Nansenfondet Oslo, Norway, for the financial support (project 1051). Dr. R.J.F.C.A. acknowledges FAPERJ - Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (260003/007043/2022), CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (001), and CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico - Brazil for the financial support. This work was partially supported by the MassLor research infrastructure at the University of Lorraine

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  • School of Engineering

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