Abstract This entry aims at illustrating both the need for new approaches to biomaterials discovery and the significant potential inherent in the joint use of combinatorial and modeling strategies. In particular, this entry regards the application of combinatorial approaches for depositing carbon-based thin films and the investigation of cell adhesion and proliferation as a function of the substrate properties. The traditional materials design proceeds with the synthesis of a new product and its characterization to identify the best candidate for a given application. Generally, in this approach only a small number of materials are synthesized and explored to identify a target polymer with optimum properties. Differently, the combinatorial approach produces large sets of surfaces with different chemical moieties in just one experiment, by changing deposition parameters. In high-throughput combinatorial methods the selection of the synthesized polymers is based on a parallel testing of their properties. The complexity of the living matter and how it interacts with biosubstrates generates some degree of difficulties. Nevertheless, the combinatorial approach may be used to test how different surface functionalities influence cell adhesion and proliferation. Generally such tests will display tendencies in the cell behavior which can be correlated to deposition process parameters. If model relationships between surface chemical, thermodynamical, and physical properties and synthesis condition are available, then it would be possible to associate cell adhesion/proliferation with material properties allowing refinement of the synthetic targets. This will allow significant accelerations in the development of improved medical implants, tissue regeneration scaffolds, and gene/drug delivery systems.

Combinatorial plasma deposition of C-based films to test cell adhesion

Minati, Luca;Antonini, Valeria;Pederzolli, Cecilia;Dalla Serra, Mauro;Speranza, Giorgio
2017

Abstract

Abstract This entry aims at illustrating both the need for new approaches to biomaterials discovery and the significant potential inherent in the joint use of combinatorial and modeling strategies. In particular, this entry regards the application of combinatorial approaches for depositing carbon-based thin films and the investigation of cell adhesion and proliferation as a function of the substrate properties. The traditional materials design proceeds with the synthesis of a new product and its characterization to identify the best candidate for a given application. Generally, in this approach only a small number of materials are synthesized and explored to identify a target polymer with optimum properties. Differently, the combinatorial approach produces large sets of surfaces with different chemical moieties in just one experiment, by changing deposition parameters. In high-throughput combinatorial methods the selection of the synthesized polymers is based on a parallel testing of their properties. The complexity of the living matter and how it interacts with biosubstrates generates some degree of difficulties. Nevertheless, the combinatorial approach may be used to test how different surface functionalities influence cell adhesion and proliferation. Generally such tests will display tendencies in the cell behavior which can be correlated to deposition process parameters. If model relationships between surface chemical, thermodynamical, and physical properties and synthesis condition are available, then it would be possible to associate cell adhesion/proliferation with material properties allowing refinement of the synthetic targets. This will allow significant accelerations in the development of improved medical implants, tissue regeneration scaffolds, and gene/drug delivery systems.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11582/309717
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
social impact