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• W2557182431 abstract "My PhD Thesis work, developed in Veneto Nanotech Laboratories (Nanofab in Marghera, LaNN in Padova and ECSIN in Rovigo), was aimed at the exploitation of the Surface Plasmon Resonance (SPR) phenomenon for the set-up of biosensing platforms for clinical and environmental applications.In particular, two types of SPR-based platforms were set-up and optimised: the first one was an oligonucleotide-based platform for the detection of Cystic Fibrosis (CF) causing mutations while the second one was an antibody-based platform for the detection of Legionella pneumophila whole cells.Both sensors are based on the same detection strategy, exploiting the advantages of using a highly sensitive Grating Coupled - Surface Plasmon Resonance (GC-SPR) enhanced spectroscopy method, designed using a conical illumination configuration for label-free molecular detection.Concerning DNA platform for Cystic Fibrosis, a strategy for the detection of some of the most frequent mutations responsible for CF among the Italian population is investigated. For the detection of the CF mutations, gold sinusoidal gratings are used as sensing surfaces, and the specific biodetection is achieved through the usage of allele specific oligonucleotide (ASO) DNA hairpin probes, designed for single nucleotide discrimination. Substrates were used to test unlabeled PCR amplified homozygous wild type (wt) and heterozygous samples (wt/mut) - deriving from clinical samples - for the screened mutations.Hybridisation conditions were optimised to obtain the maximum discrimination ratio (DR) between the homozygous wild type and the heterozygous samples. SPR signals obtained from hybridising wild type and heterozygous samples showed DRs able to identify univocally the correct genotypes, as confirmed by fluorescence microarray experiments run in parallel. Furthermore, SPR genotyping was not impaired in samples containing unrelated DNA, allowing the platform to be used for the parallel discrimination of several alleles also scalable for a high throughput screening setting.Concerning antibody platform for Legionella pneumophila bacteria detection, a strategy for the exploitation of the SPR phenomenon to develop a fully automated platform for fast optical detection of Legionella pneumophila pathogens was investigated. The legal limit of L. pneumophila in a high-risk hospital environment in Italy is 102 CFU/L, and the gold standard for its identification is a time consuming microbiological culture method, that requires up to 7 days.Starting from these considerations a sensitive GC-SPR system was applied to the detection of L. pneumophila to test the detection limit of the developed sensing device in term of detectable bacterium CFU. The detection was accurately set up and precisely optimised firstly through the usage of flat gold functionalised slides to be then translated to sinusoidal gold gratings for label-free GC-SPR detection using ellipsometer, in order to ensure a reproducible and precise identification of bacteria. Through azimuthally-controlled GC-SPR, 10 CFU were detected, while in the case of fluorescence analysis results, a negative readout is obtained if incubating less than 104 CFU. Successful results were obtained when incubating environmental derived samples. This detection platform could be implemented as a prototype in which water and air samples will be sequentially concentrated, injected into a microfluidic system, and delivered to the SPR sensor for analysis.The peculiar Grating Coupled - Surface Plasmon Resonance method applied for this work has therefore revealed to be an accurate and highly sensitive strategy – with multiplexing possibility - for the sensing and detecting of different kind of biomolecules, from DNA fragments to whole bacteria cell." @default.
• W2557182431 created "2016-11-30" @default.
• W2557182431 creator A5006499474 @default.
• W2557182431 date "2016-01-29" @default.
• W2557182431 modified "2023-09-27" @default.
• W2557182431 title "Surface plasmon resonance based platforms for clinical and environmental biosensing applications" @default.
• W2557182431 hasPublicationYear "2016" @default.
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