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A Storage-Dependent Platinum Functionalization with a Commercial Pre-Polymer Useful for Hydrogen Peroxide and Ascorbic Acid Detection.

Patrizia Monti | Quirico Migheli | Andrea R Bartiromo | Antonio Pauciulo | Rocco Gliubizzi | Salvatore Marceddu | Pier A Serra | Giovanna Delogu
Sensors (Basel, Switzerland) | 2019

A preliminary assessment of properties of the commercial product Chemiplus 2DS HB (BI-QEM Specialties SpA) is proposed. Cyclic voltammetry of this oligomer containing sulfate/sulfone groups shows a single oxidative peak at +0.866 V vs. Ag/AgCl, and its passivating process on Pt electrode suggests the formation of a non-conductive layer. Electrode modification was achieved by exploiting the constant potential amperometry setting potential at +0.900 V vs. Ag/AgCl. A substantial change in the oxidative currents from electroactive species H2O2 and ascorbic acid (AA) were observed on Pt/Chemiplus 2DS HB sensors compared to unmodified Pt. Furthermore, the influence of different storage conditions on modified sensors was examined. A storage solution containing AA concentration from 0.1 until 10 mM maintained effective AA rejection of Pt/Chemiplus 2DS HB after 7 days from construction; H2O2 oxidation capability was also retained. Sulfone and sulfonate groups of Chemiplus 2DS HB are likely responsible for the dimensionality of the film and the electrostatic interaction leading to a self-blocking/self-rejection of AA. The way Pt/Chemiplus can reveal the AA presence depends on the maintaining of AA rejection, and this peculiarity can distinguish it from other sensors or biosensors.

Pubmed ID: 31141953

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PRISM (tool)

RRID:SCR_005375

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.

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