Macroporous mesh of nanoporous gold in electrochemical monitoring of superoxide release from skeletal muscle cells.

Real-time monitoring of metabolically relevant biochemicals released in minuscule amounts is of utmost diagnostic importance. Superoxide anion as a primary member of reactive oxygen species, has physiological and pathological effects that depend on its concentration and release rate. Here we present fabrication and successfully testing of a highly sensitive electrochemical biosensor featuring a three-dimensional macroporous mesh of nanoporous gold tailored to measure the dynamics of extracellular superoxide concentration. Wide and accessible surface of the mesh combined with high porosity of the thin nanoporous gold coating enables capturing the analyte in pico- to nano-molar ranges. The mesh is functionalized with cytochrome-c (cyt-c) and incorporated as a working electrode to measure the release rate of drug-induced superoxides from C2C12 cells through a porous membrane. The device displays a considerably improved superoxide sensitivity of 7.29nAnM-1cm-2 and a low level of detection of 70pM. Such sensitivity is orders of magnitude higher than any similar enzyme-based electrochemical superoxide sensor and is attributed to the facile diffusion of the analyte through the well-spread nanofeatured gold skin. Superoxide generation rates captured from monolayer myoblast cultures containing about 4×104 cells, varied from 1.0 to 9.0nMmin-1 in a quasi-linear fashion as a function of drug concentration. This work provides a platform for the development of highly sensitive molecular electrochemical biosensors.

Artificial neural network modeling of biomarkers to infer characteristics of contaminant exposure in Clarias gariepinus.

This study examined the potential of artificial neural network (ANN) modeling to infer timing, route and dose of contaminant exposure from biomarkers in a freshwater fish. Hepatic glutathione S-transferase (GST) activity and biliary concentrations of BaP, 1-OH BaP, 3-OH BaP and 7,8D BaP were quantified in juvenile Clarias gariepinus injected intramuscularly or intraperitoneally with 10-50 mg/kg benzo[a]pyrene (BaP) 1-3 d earlier. A feedforward multilayer perceptron (MLP) ANN resulted in more accurate prediction of timing, route and exposure dose than a linear neural network or a radial basis function (RBF) ANN. MLP sensitivity analyses revealed contribution of all five biomarkers to predicting route of exposure but no contribution of hepatic GST activity or one of the two hydroxylated BaP metabolites to predicting time of exposure and dose of exposure. We conclude that information content of biomarkers collected from fish can be extended by judicious use of ANNs.

Real-time gas identification by analyzing the transient response of capillary-attached conductive gas sensor.

In this study, the ability of the Capillary-attached conductive gas sensor (CGS) in real-time gas identification was investigated. The structure of the prototype fabricated CGS is presented. Portions were selected from the beginning of the CGS transient response including the first 11 samples to the first 100 samples. Different feature extraction and classification methods were applied on the selected portions. Validation of methods was evaluated to study the ability of an early portion of the CGS transient response in target gas (TG) identification. Experimental results proved that applying extracted features from an early part of the CGS transient response along with a classifier can distinguish short-chain alcohols from each other perfectly. Decreasing time of exposition in the interaction between target gas and sensing element improved the reliability of the sensor. Classification rate was also improved and time of identification was decreased. Moreover, the results indicated the optimum interval of the early transient response of the CGS for selecting portions to achieve the best classification rates.