Molecular and biological characterization of Lettuce mosaic virus (LMV) isolates reveals a distinct and widespread type of resistance-breaking isolate: LMV-Most

Lettuce mosaic virus (LMV) causes an economically important seedborne and aphid-transmitted disease of lettuce and ornamental crops worldwide. The genetic diversity among 73 LMV isolates was examined based on a 216-nucleotide sequence at the variable region encoding the NIb-coat protein junction, Three clusters of LMV isolates were distinguished: LMV-Yar, LMV-Greck, and LMV-RoW. In the latter cluster, two subgroups of isolates, LMV-Common and LMV-Most, accounted for a large proportion of the LMV isolates analyzed. These two subgroups included the seedborne isolates, consistent with this property contributing a selective advantage and resulting in widespread distribution. In addition to being seedborne, LMV-Most isolates overcome the two resistance genes commonly used in lettuce, mol(1) and mol(2), and thus represent a potential threat to lettuce cultivation. The complete sequence of an LMV-Most isolate (LMV-AF199) was determined, allowing a better definition of the genetic relationships among LMV-Most, LMV-Common, and an additional isolate of the LMV-RoW cluster.

Canine distemper virus infection in a lesser grison (Galictis cuja): first report and virus phylogeny

Doenças infecciosas em animais selvagens têm aumentado devido às alterações em seu habitat e ao maior contato com animais domésticos. A cinomose já foi descrita em diversas espécies de carnívoros selvagens, representando uma ameaça à conservação da vida selvagem. Nesse estudo é descrito o primeiro caso de infecção pelo vírus da cinomose em um furão (Galictis cuja). Um indivíduo de vida livre, sem sinais clínicos aparentes, apresentou morte súbita após um dia em cativeiro. Foi realizado o diagnóstico molecular para detecção do vírus da cinomose canina, sendo o resultado positivo. A filogenia do vírus indicou que cães domésticos foram a provável fonte de infecção.

Malware distributed collection and pre-classification system using honeypot technology

Malware has become a major threat in the last years due to the ease of spread through the Internet. Malware detection has become difficult with the use of compression, polymorphic methods and techniques to detect and disable security software. Those and other obfuscation techniques pose a problem for detection and classification schemes that analyze malware behavior. In this paper we propose a distributed architecture to improve malware collection using different honeypot technologies to increase the variety of malware collected. We also present a daemon tool developed to grab malware distributed through spam and a pre-classification technique that uses antivirus technology to separate malware in generic classes. © 2009 SPIE.