A bayesian statistical model to alleviate greediness in wireless mesh networks

Wireless mesh Networks (WMNs) are a prominent paradigm of wireless communication that have been widely used in many applications. The growing popularity of such networks opened the door to a profusion of attacks that may target their core functioning leading to a harmful impact on their performance. Hence, the need of robust and fast detection of those attacks became a major prerequisite in order to guarantee an efficient and fair share of network resources among nodes. One of the well known devastating attacks is MAC layer misbehavior which may lead to severe collapse of network performance. In this study, we focus on such misbehavior and in particular on the adaptive greedy behavior of a node in wireless mesh network environment. In such environment, wireless nodes compete to gain access to the medium in order to communicate with a mesh router (MR). In this case, a greedy node may violate the MAC protocol rules to earn extra bandwidth share upon its neighbors. To evade from detection, the cheater node may use more than one technique and switch dynamically between each of them. To counter such misuse, we propose to extend our previous solution, dubbed FLSAC, through the use of a Bayesian statistical model. This new scheme is implemented in conjunction with FLSAC at the mesh router/gateway to monitor the behavior of the attached wireless mesh clients and detect any deviation from the proper protocol rules. The simulation results reveal that this new solution outperforms both of DOMINO and FLSAC in terms of detection rate and accuracy. ©2010 IEEE

Hepatoprotective effects of Spirulina maxima in patients with non-alcoholic fatty liver disease: a case series

<p>Abstract</p> <p>Introduction</p> <p>Non-alcoholic fatty liver diseases range from simple steatosis to non-alcoholic steatohepatitis. The "two hits" hypothesis is widely accepted for its pathogenesis: the first hit is an increased fat flux to the liver, which predisposes our patient to a second hit where increasing free fatty acid oxidation into the mitochondria leads to oxidative stress, lipoperoxidation and a chain reaction with increased ROS. Clinical indications include abdominal cramps, meteorism and fatigue. Most patients, however, are asymptomatic, and diagnosis is based on aminotransferase elevation and ultrasonography (or "brilliant liver"). Spirulina maxima has been experimentally proven to possess <it>in vivo </it>and <it>in vitro </it>hepatoprotective properties by maintaining the liver lipid profile. This case report evaluates the hepatoprotective effects of orally supplied Spirulina maxima.</p> <p>Case presentation</p> <p>Three Hispanic Mexican patients (a 43-year-old man, a 77-year-old man and a 44-year-old woman) underwent ultrasonography and were treated with 4.5 g/day of Spirulina maxima for three months. Their blood samples before and after the treatment determined triacylglycerols, total cholesterol, high-density lipoprotein cholesterol, alanine aminotransferase and low-density lipoprotein cholesterol levels. The results were assessed using ultrasound.</p> <p>Conclusion</p> <p>Treatment had therapeutic effects as evidenced by ultrasonography and the aminotransferase data. Hypolipidemic effects were also shown. We conclude that Spirulina maxima may be considered an alternative treatment for patients with non-alcoholic fatty liver diseases and dyslipidemic disorder.</p

Toxicogenomic Analysis Suggests Chemical-Induced Sexual Dimorphism in the Expression of Metabolic Genes in Zebrafish Liver

10.1371/journal.pone.0051971PLoS ONE712

Silencing hepatic MCJ attenuates non-alcoholic fatty liver disease (NAFLD) by increasing mitochondrial fatty acid oxidation

Nonalcoholic fatty liver disease (NAFLD) is considered the next major health epidemic with an estimated 25% worldwide prevalence. No drugs have yet been approved and NAFLD remains a major unmet need. Here, we identify MCJ (Methylation-Controlled J protein) as a target for non-alcoholic steatohepatitis (NASH), an advanced phase of NAFLD. MCJ is an endogenous negative regulator of the respiratory chain Complex I that acts to restrain mitochondrial respiration. We show that therapeutic targeting of MCJ in the liver with nanoparticle- and GalNAc-formulated siRNA efficiently reduces liver lipid accumulation and fibrosis in multiple NASH mouse models. Decreasing MCJ expression enhances the capacity of hepatocytes to mediate beta -oxidation of fatty acids and minimizes lipid accumulation, which results in reduced hepatocyte damage and fibrosis. Moreover, MCJ levels in the liver of NAFLD patients are elevated relative to healthy subjects. Thus, inhibition of MCJ emerges as an alternative approach to treat NAFLD. Non-alcoholic fatty liver (NAFLD) disease causes degeneration of the liver, affects about 25% of people globally, and has no approved treatment. Here, the authors show that the therapeutic siRNA-driven silencing of MCJ in the liver is an effective and safe treatment for NAFLD in multiple mouse models.We thank Douglas Taatjes and Nicole Bouffard for help with confocal microscopy analysis (Microscopy Imaging Center) at the University of Vermont. We also thank the University of Vermont Medical Center's Department of Pathology and Laboratory Medicine Histology and Clinical Laboratories for assistance with liver section staining and AST/ALT measurement, respectively. This work was supported by NIH STTR R41DK112429 (M.R.), NIH PO GM103496 (M.R.), Mitotherapeutix LLC (M.R., K.F, and M.L.M.-C.), MINECO/Feder SAF2015-65327-R and RTI2018-096494-B-100 (J.A.), MINECO/Feder SAF2017-87301-R (M.L.M-C.), BIOEF (M.L.M.-C.), EITB Maratoia BIO15/CA/014 (M.L.M-C), BBVA (M.L.M.-C.), La Caixa Foundation (M.L.M.-C.), Basque Country Health Department 2013111114 (M.L.M-C), MINECO/Feder SAF2015-64352-R (P.A.) and MINECO-Feder RTI2018-095134-B-100 (P.A.). ISCIII-Feder PI17/00535 (C.G.-M.), ISCIII-Feder CP14/00181, and PI16/00823 (A.G-R.), and Francisco Cobos Foundation (A.G.-R.). CIC bioGUNE is the recipient of a Severo Ochoa Excellence Accreditation (SEV-2016-0644) by the Ministry of Science, Innovation and Universities

Denial of service (DoS) attacks detection in MANETs using Bayesian classifiers

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