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A review on biomaterials for 3D conductive scaffolds for stimulating and monitoring cellular activities

Articolo
Data di Pubblicazione:
2019
Abstract:
During the last years, scientific research in biotechnology has been reporting a considerable boost forward due to many advances marked in different technological areas. Researchers working in the field of regenerative medicine, mechanobiology and pharmacology have been constantly looking for non-invasive methods able to track tissue development, monitor biological processes and check effectiveness in treatments. The possibility to control cell cultures and quantify their products represents indeed one of the most promising and exciting hurdles. In this perspective, the use of conductive materials able to map cell activity in a three-dimensional environment represents the most interesting approach. The greatest potential of this strategy relies on the possibility to correlate measurable changes in electrical parameters with specific cell cycle events, without affecting their maturation process and considering a physiological-like setting. Up to now, several conductive materials has been identified and validated as possible solutions in scaffold development, but still few works have stressed the possibility to use conductive scaffolds for non-invasive electrical cell monitoring. In this picture, the main objective of this review was to define the state-of-the-art concerning conductive biomaterials to provide researchers with practical guidelines for developing specific applications addressing cell growth and differentiation monitoring. Therefore, a comprehensive review of all the available conductive biomaterials (polymers, carbon-based, and metals) was given in terms of their main electric characteristics and range of applications
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
Cell culture monitoring; Conductive scaffolds; Impedance-based monitoring; Non-invasive monitoring; Materials Science (all); Instrumentation; Engineering (all); Process Chemistry and Technology; Computer Science Applications1707 Computer Vision and Pattern Recognition; Fluid Flow and Transfer Processes
Elenco autori:
Khan, Muhammad Ahmed; Cantù, Edoardo; Tonello, Sarah; Serpelloni, Mauro; Lopomo, Nicola Francesco; Sardini, Emilio
Autori di Ateneo:
SARDINI Emilio
SERPELLONI Mauro
Sensori e Strumentazione Elettronica
TONELLO SARAH
Link alla scheda completa:
https://iris.unibs.it/handle/11379/520940
Pubblicato in:
APPLIED SCIENCES
Journal
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