| Literature DB >> 23741732 |
Giorgia Sciutto1, Lucio Litti, Cristiana Lofrumento, Silvia Prati, Marilena Ricci, Marina Gobbo, Aldo Roda, Emilio Castellucci, Moreno Meneghetti, Rocco Mazzeo.
Abstract
In the field of analytical chemistry, many scientific efforts have been devoted to develop experimental procedures for the characterization of organic substances present in heterogeneous artwork samples, due to their challenging identification. In particular, performances of immunochemical techniques have been recently investigated, optimizing ad hoc systems for the identification of proteins. Among all the different immunochemical approaches, the use of metal nanoparticles - for surface enhanced Raman scattering (SERS) detection - remains one of the most powerful methods that has still not been explored enough for the analysis of artistic artefacts. For this reason, the present research work was aimed at proposing a new optimized and highly efficient indirect immunoassay for the detection of ovalbumin. In particular, the study proposed a new SERRS probe composed of gold nanoparticles (AuNPs) functionalised with Nile Blue A and produced with an excellent green and cheap alternative approach to the traditional chemical nanoparticles synthesis: the laser ablation synthesis in solution (LASiS). This procedure allows us to obtain stable nanoparticles which can be easily functionalized without any ligand exchange reaction or extensive purification procedures. Moreover, the present research work also focused on the development of a comprehensive analytical approach, based on the combination of potentialities of immunochemical methods and Raman analysis, for the simultaneous identification of the target protein and the different organic and inorganic substances present in the paint matrix. An advanced mapping detection system was proposed to achieve the exact spatial location of all the components through the creation of false colour chemical maps.Entities:
Year: 2013 PMID: 23741732 DOI: 10.1039/c3an00057e
Source DB: PubMed Journal: Analyst ISSN: 0003-2654 Impact factor: 4.616