Urine disinfection and in situ pathogen killing using a Microbial Fuel Cell cascade system

© 2017 Ieropoulos et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Microbial Fuel Cells (MFCs) are emerging as an effective means of treating different types of waste including urine and wastewater. However, the fate of pathogens in an MFC-based system remains unknown, and in this study we investigated the effect of introducing the enteric pathogen Salmonella enterica serovar enteritidis in an MFC cascade system. The MFCs continuously fed with urine showed high disinfecting potential. As part of two independent trials, during which the bioluminescent S. enteritidis strain was introduced into the MFC cascade, the number of viable counts and the level of bioluminescence were reduced by up to 4.43-0.04 and 4.21-0.01 log-fold, respectively. The killing efficacy observed for the MFCs operating under closed-circuit conditions, were higher by 1.69 and 1.72 log-fold reduction than for the open circuit MFCs, in both independent trials. The results indicated that the bactericidal properties of a well performing anode were dependent on power performance and the oxidation-reduction potential recorded for the MFCs. This is the first time that the fate of pathogenic bacteria has been investigated in continuously operating MFC systems

Separation of spatially localized cortical activities in the EEG: model-based analysis and optimization

The mapping of brain sources into the scalp electroencephalogram (EEG) depends on volume conduction properties of the head and on an electrode montage involving a reference. In this article, the source mapping (SM) is formalized mathematically in the form of an observation function (OF) matrix. The OF-matrix is used to analyze and optimize the SM for a generation model for the desynchronized spontaneous EEG. The optimization leads to a novel reference that minimizes the impact in the EEG of the sources located distant from the electrodes. Thereby, this reference separates spatially localized cortical activities in the EEG. For this reason, it is called the localized reference (LR). The LR is compared with the Hjorth Laplacian reference (HR), which is commonly used for recordings of localized cortical activities. The comparison is made in terms of the relative power contribution of the sources into EEG channels. For the model, the LR is found to have up to 15-20% better performance than the HR, and thus the LR is considered a good alternative to the HR when a head model is available. The HR is, however, a fair approximation of the LR and thus is close to optimum for practical intents and purposes