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Tesi etd-01282020-123111


Thesis type
Tesi di dottorato di ricerca
Author
KIRCHHAIN, ARNO
email address
arno.kirchhain@dcci.unipi.it, a.kirchhain@studenti.unipi.it, arno.kirchhain@web.de
URN
etd-01282020-123111
Title
Development of novel sensors for quantitative analysis of wound tissue
Settore scientifico disciplinare
CHIM/01
Corso di studi
SCIENZE CHIMICHE E DEI MATERIALI
Supervisors
tutor Prof. Di Francesco, Fabio
Parole chiave
  • Matrix metalloproteinases
  • Biosensors
  • Molecular probes
  • Electrochemical sensors
Data inizio appello
26/02/2020;
Consultabilità
Parziale
Data di rilascio
26/02/2023
Riassunto analitico
A main obstacle in the treatment of chronic wounds is the lack of reliable tools for the evaluation of the wound bed status. For this reason, new and reliable sensor technologies would represent a major breakthrough in the management of wounds, as they would make an intelligent choice of the best medical treatment possible. Matrix metalloproteinases (MMPs) are a group of zinc containing enzymes that catalyse the hydrolysis of damaged tissue, but also attack healthy tissue if over expressed.
Consequently, it is desirable to investigate a possible methodology for their detection and monitoring. In this thesis, we designed and synthesized molecular probes for MMPs and studied methods to bind them to electrode surfaces to fabricate sensors. For this purpose, different transducing mechanisms can be exploited, but I decided to use electrochemical impedance spectroscopy (EIS) to monitor the binding interaction of the enzyme to the probe due to the limited complexity of the readout electronics, the availability on the market of portable instruments and the high sensitivity of this method, which is needed to detect the low concentrations of MMPs. With enzyme inhibitors as design blueprint, the overall project involved the design and synthesis of the probes, the assessment of the binding affinity, the functionalization of suitable electrodes for the fabrication of the sensor and the sensor tests with model solutions.
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