Unlocking the full power of electrochemical fingerprinting for on-site sensing applications.

Electrochemical sensing for the semi-quantitative detection of biomarkers, drugs, environmental contaminants, food additives, etc. shows promising results in point-of-care diagnostics and on-site monitoring. More specifically, electrochemical fingerprint (EF)-based sensing strategies are considered an inviting approach for the on-site detection of low molecular weight molecules. The fast growth of electrochemical sensors requires defining the concept of direct electrochemical fingerprinting in sensing. The EF can be defined as the unique electrochemical signal or pattern, mostly recorded by voltammetric techniques, specific for a certain molecule that can be used for its quantitative or semi-quantitative identification in a given analytical context with specified circumstances. The performance of EF-based sensors can be enhanced by considering multiple features of the signal (i.e., oxidation or reduction patterns), in combination with statistical data analysis or sample pretreatments or by including electrode surface modifiers to enrich the EF. In this manuscript, some examples of EF-based sensors, strategies to improve their performances, and open challenges are discussed to unlock the full power of electrochemical fingerprinting for on-site sensing applications. Graphical abstract Electrochemical fingerprint-based sensing strategies can be used for the detection of electroactive analytes, such as antibiotics, phenolic compounds, and drugs of abuse. These strategies show selective and sensitive responses and are easily combined with portable devices.

Recording of the fast oscillations in the human electro-oculogram.

The fast oscillations (FO) of the electro-oculogram were recorded in 102 eyes of 51 normal subjects. We evaluated the normal range and variability of FO parameters, i.e. Rf, which is the average ratio in percentage of the average amplitude in the dark period (AD) and the average amplitude in the light period (AL), and df, which is the average difference between AD and AL in microV. The standing potential was recorded continuously during six subsequent cycles, each consisting of a one minute period in the dark and one minute period in the light. The mean +/- standard error for Rf was 112.9 +/- 1.3% and 69.6 +/- 5.3 microV for df. There was no statistically significant difference between both genders or different age groups. Rf and df were calculated using a different number of dark-light cycles. In normal subjects both the Rf and df show no difference when only 4 dark-light cycles are used in calculating these values. Therefore there seems no additional advantage in performing as many as 6 cycles. Using 4 dark-light cycles reduces the duration of the examination (8 vs. 12 min) of the fast oscillations and in particular when examining both fast and slow oscillations successively it might be useful to reduce the time of the examination.