Electrochemical aptasensor for human osteopontin detection using a DNA aptamer selected by SELEX.

A DNA aptamer with affinity and specificity for human osteopontin (OPN), a potential breast cancer biomarker, was selected using the SELEX process, considering its homology rate and the stability of its secondary structures. This aptamer exhibited a satisfactory affinity towards OPN, showing dissociation constants lower than 2.5 nM.

Voltammetric aptasensors for protein disease biomarkers detection: A review.

An electrochemical aptasensor is a compact analytical device where the bioreceptor (aptamer) is coupled to a transducer surface to convert a biological interaction into a measurable signal (current) that can be easily processed, recorded and displayed. Since the discovery of the Systematic Evolution of Ligands by Enrichment (SELEX) methodology, the selection of aptamers and their application as bioreceptors has become a promising tool in the design of electrochemical aptasensors. Aptamers present several advantages that highlight their usefulness as bioreceptors such as chemical stability, cost effectiveness and ease of modification towards detection and immobilization at different transducer surfaces.

Development of an electrochemical RNA-aptasensor to detect human osteopontin.

Electrochemical aptasensors may be used to detect protein biomarkers related to tumor activity. Osteopontin (OPN), a protein present in several body fluids, has been suggested as a potential biomarker since its overexpression seems to be associated with breast cancer progression and metastasis. In this work, a simple and label-free voltammetric aptasensor for the detection of OPN, using an RNA aptamer previously reported to have affinity for human OPN as the molecular recognition element, and the ferro/ferricyanide solution as a redox probe, was developed.

An electronic tongue for gliadins semi-quantitative detection in foodstuffs.

An all-solid-state potentiometric electronic tongue with 36 polymeric membranes has been used for the first time to detect gliadins, which are primarily responsible for gluten intolerance in people suffering from celiac disease. A linear discriminant model, based on the signals of 11 polymeric membranes, selected from the 36 above using a stepwise procedure, was used to semi-quantitatively classify samples of a "Gluten-free" foodstuff (baby milked flour), previously contaminated with known amounts of gliadins (<10, 20-50 or >50mg/kg), as "Gluten-free", "Low-Gluten content" or "Gluten-containing". For this food matrix, the device had sensitivity towards gliadins of 1-2mg/kg and overall sensitivity and specificity of 77% and 78%, respectively.