Rianna, Carmela (2015) Dynamic topographic patterns to control cell adhesion and mechanics. [Tesi di dottorato]


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Item Type: Tesi di dottorato
Resource language: English
Title: Dynamic topographic patterns to control cell adhesion and mechanics
Rianna, Carmelac.rianna@hotmail.it
Date: 31 March 2015
Number of Pages: 128
Institution: Università degli Studi di Napoli Federico II
Department: Ingegneria Industriale
Scuola di dottorato: Ingegneria industriale
Dottorato: Ingegneria dei materiali e delle strutture
Ciclo di dottorato: 27
Coordinatore del Corso di dottorato:
Mensitieri, Giuseppegiuseppe.mensitie@unina.it
Netti, Paolo AntonioUNSPECIFIED
Ventre, MaurizioUNSPECIFIED
Cavalli, SilviaUNSPECIFIED
Date: 31 March 2015
Number of Pages: 128
Keywords: azopolymers; SRGs; topographic patterns; cell mechanics; cell culture
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-IND/22 - Scienza e tecnologia dei materiali
Date Deposited: 12 Apr 2015 00:32
Last Modified: 29 Apr 2016 01:00
URI: http://www.fedoa.unina.it/id/eprint/10159
DOI: 10.6092/UNINA/FEDOA/10159

Collection description

The research described in this thesis aimed to introduce a new class of cell−instructive materials, designed to study cell response to dynamic topographic signals. Understanding cellular reaction to the external environment is a central aspect in tissue engineering and biomedical science. A growing number of works is emphasizing the high sensitivity that cells display towards the chemical and physical features of the substrate to which they are connected. In particular, substrates of defined topography have emerged as powerful tools in the investigation of the mechanisms involved in cell−material interaction. The limitation of many of the proposed substrates is their static form, which does not allow to induce a programmed change during cell culture. This physical stasis has limited the potential of topographic substrates to control cells in culture. For this reason a study on dynamic and reversible platforms was conducted, aiming to investigate cell behavior in a more biomimetic way and to overcome the limit of static systems.


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