11 research outputs found

    VTA CRF neurons mediate the aversive effects of nicotine withdrawal and promote intake escalation

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    Dopaminergic neurons in the ventral tegmental area (VTA) are well known for mediating the positive reinforcing effects of drugs of abuse. Here we identify in rodents and humans a population of VTA dopaminergic neurons expressing corticotropin-releasing factor (CRF). We provide further evidence in rodents that chronic nicotine exposure upregulates Crh mRNA (encoding CRF) in dopaminergic neurons of the posterior VTA, activates local CRF1 receptors and blocks nicotine-induced activation of transient GABAergic input to dopaminergic neurons. Local downregulation of Crh mRNA and specific pharmacological blockade of CRF1 receptors in the VTA reversed the effect of nicotine on GABAergic input to dopaminergic neurons, prevented the aversive effects of nicotine withdrawal and limited the escalation of nicotine intake. These results link the brain reward and stress systems in the same brain region to signaling of the negative motivational effects of nicotine withdrawal

    Botnet detection techniques: review, future trends, and issues

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    NoIn recent years, the Internet has enabled access to widespread remote services in the distributed computing environment; however, integrity of data transmission in the distributed computing platform is hindered by a number of security issues. For instance, the botnet phenomenon is a prominent threat to Internet security, including the threat of malicious codes. The botnet phenomenon supports a wide range of criminal activities, including distributed denial of service (DDoS) attacks, click fraud, phishing, malware distribution, spam emails, and building machines for illegitimate exchange of information/materials. Therefore, it is imperative to design and develop a robust mechanism for improving the botnet detection, analysis, and removal process. Currently, botnet detection techniques have been reviewed in different ways; however, such studies are limited in scope and lack discussions on the latest botnet detection techniques. This paper presents a comprehensive review of the latest state-of-the-art techniques for botnet detection and figures out the trends of previous and current research. It provides a thematic taxonomy for the classification of botnet detection techniques and highlights the implications and critical aspects by qualitatively analyzing such techniques. Related to our comprehensive review, we highlight future directions for improving the schemes that broadly span the entire botnet detection research field and identify the persistent and prominent research challenges that remain open.University of Malaya, Malaysia (No. FP034-2012A
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