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Human neurocysticercosis (NCC) is a worldwide neglected disease caused by Taenia solium metacestode and responsible for various complications and neurological disorders. This study aimed to evaluate the use of specific immunoglobulin Y (IgY) produced by laying hens immunized with a hydrophobic fraction of Taenia crassiceps metacestodes (hFTc) in NCC diagnosis. Egg yolk IgY antibodies were fractionated, purified and characterized. Enzyme-linked immunosorbent assay (ELISA) was carried out to evaluate the production kinetics and avidity maturation of anti-hFTc IgY antibodies throughout the IgY obtention process. Antigen recognition tests were carried out by Western blotting and immunofluorescence antibody test using purified and specific anti-hFTc IgY antibodies for detection of parasitic antigens of T. crassiceps and T. solium metacestodes. Sandwich ELISA was performed to detect circulating immune complexes formed by IgG and parasitic antigens in human sera. The results showed high diagnostic values (93.2% sensitivity and 94.3% specificity) for immune complexes detection in human sera with confirmed NCC. In conclusion, specific IgY antibodies produced from immunized hens with hFTc antigens were efficient to detect T. solium immune complexes in human sera, being an innovative and potential tool for NCC immunodiagnosis.

Voltage sags and power interruptions are important power quality problems that affect sensitive customers, mainly because they cause annual massive economical losses to the industrial sector as a result of unexpected production process disruptions. In this sense, to propose corrective and preventive measures and improve the power quality of distribution systems, stochastic methodologies have been proposed in the literature to estimate annual voltage sags and power interruptions. However, these methodologies generally use typical cumulative distribution functions of voltage sag duration (PSgD), which can not reflect the real estate of the network under study. To solve this constraint, this paper proposes a novel methodology to estimate a proper PSgD considering the information of the distribution network (i.e., topology and coordination schemes of the protection system) and the stochastic behaviors of short-circuits that can affect the distribution system. Moreover, the proposed methodology allows estimating permanent failure rates and average repair time considering known or expected values of reliability indicators. The results show that the proposed methodology is capable to adapt from an initial PSgD curve to another one with fidelity to achieve real values of expected annual power interruptions.

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