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Pediculosis is a frequent public health problem. The pattern and prevalence of Pediculosis is dependent on many socio-demographic and economic factors. It is common in schoolchildren especially primary level; it may affect their learning performance. This study aimed to determine the prevalence of head louse among primary students, in Fayoum and Bagor districts, and explore the predisposing factors of head louse infestation in both public and private schools. The study was a cross-sectional descriptive study, conducted in two governorates: Fayoum and Minofiya governorates which represent upper and lower Egypt respectively during the academic year of 2012-2013. The students were selected from different grades with a total of 10,935 students. The prevalence of head lice in the study group was 16.7 %. The incidence was higher in public schools 20.7 % than private schools 9.04 % and in girls 25.8 % more than boys, especially covered hair girls 6.2 %. There was a socio-demographic influence of louse infestation on residence, presence of water supply, number of house rooms, and number of family member. It is concluded that head lice are a common childhood problem related to poor hygiene and socioeconomic status. There is a need for collaboration effort between family, school, community, and media, to create an environment that establishes healthy behaviors and health promotion.

Background Let-7 microRNAs (miRNAs) may contribute to neurodegeneration, including Alzheimer's disease (AD), but, they were not investigated in Streptozotocin (STZ)-induced AD. Letrozole increases the expression of Let-7 in cell lines, with conflicting evidence regarding its effects on memory. This study examined Let-7 miRNAs in STZ-induced AD, their correlation with memory and hyperphosphorylated Tau (p-Tau) and the effects of Letrozole on them. Methods Seven groups of adult Sprague Dawley rats were used: Negative control, Letrozole, Letrozole Vehicle, STZ (with AD induced by intracerebroventricular injection of STZ in artificial cerebrospinal fluid (aCSF)), CSF Control, STZ + Letrozole (STZ-L), and CSF + Letrozole Vehicle. Alternation percentage in T-maze was used as a measure of working memory. Let-7a, b and e and p-Tau levels in the hippocampus were estimated using quantitative real-time reverse transcription–polymerase chain reaction (qRT–PCR) and enzyme-linked immunosorbent assay (ELISA), respectively. Results Significant decreases in alternation percentage and increase in p-Tau concentration were found in the STZ, Letrozole and STZ-L groups. Expression levels of all studied microRNAs were significantly elevated in the Letrozole and the STZ-L groups, with no difference between the two, suggesting that this elevation might be linked to Letrozole administration. Negative correlations were found between alternation percentage and the levels of all studied microRNAs, while positive ones were found between p-Tau concentration and the levels of studied microRNAs. Conclusions This study shows changes in the expression of Let-7a, b and e miRNAs in association with Letrozole administration, and correlations between the expression of the studied Let-7 miRNAs and both the status of working memory and the hippocampal p-Tau levels. These findings might support the theory suggesting that Letrozole aggravates pre-existing lesions. They also add to the possibility of Let-7’s neurotoxicity.

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The rapid development of Internet has given birth to a new technology called cloud computing. Cloud computing is attractive to business owners as it provides several features, such as no up-front investment, lowering operating cost, highly scalable, reducing business risks and lowering maintenance expenses. However, cloud computing is still in its infancy, as many crucial problems need to be addressed. Energy saving is one of these problems; where efficient power management can help lower the cost of operating a large data center hosting massive computing resources. This paper studies a new proposed model that can reduce the system energy consumption by setting hystereses thresholds of activating and deactivating servers. The model is implemented and simulated using OPNET Modeler and Simulator to evaluate its performance metrics. Simulations have shown the effect of the model on reducing server activation/deactivation rates which consequently reduces the energy consumption. Moreover, simulations proved that the model is a generic model that works for non-Markovian assumptions.