BUB-1 targets PP2A:B56 to regulate chromosome congression during meiosis I in C. elegans oocytes

Protein Phosphatase 2A (PP2A) is a heterotrimer composed of scaffolding (A), catalytic (C), and regulatory (B) subunits. PP2A complexes with B56 subunits are targeted by Shugoshin and BUBR1 to protect centromeric cohesion and stabilise kinetochore-microtubule attachments in yeast and mouse meiosis. In Caenorhabditis elegans, the closest BUBR1 orthologue lacks the B56-interaction domain and Shugoshin is not required for meiotic segregation. Therefore, the role of PP2A in C. elegans female meiosis is unknown. We report that PP2A is essential for meiotic spindle assembly and chromosome dynamics during C. elegans female meiosis. BUB-1 is the main chromosome-targeting factor for B56 subunits during prometaphase I. BUB-1 recruits PP2A:B56 to the chromosomes via a newly identified LxxIxE motif in a phosphorylation-dependent manner, and this recruitment is important for proper chromosome congression. Our results highlight a novel mechanism for B56 recruitment, essential for recruiting a pool of PP2A involved in chromosome congression during meiosis I

Cytomegalovirus induces abnormal chondrogenesis and osteogenesis during embryonic mandibular development

<p>Abstract</p> <p>Background</p> <p>Human clinical studies and mouse models clearly demonstrate that cytomegalovirus (CMV) disrupts normal organ and tissue development. Although CMV is one of the most common causes of major birth defects in humans, little is presently known about the mechanism(s) underlying CMV-induced congenital malformations. Our prior studies have demonstrated that CMV infection of first branchial arch derivatives (salivary glands and teeth) induced severely abnormal phenotypes and that CMV has a particular tropism for neural crest-derived mesenchyme (NCM). Since early embryos are barely susceptible to CMV infection, and the extant evidence suggests that the differentiation program needs to be well underway for embryonic tissues to be susceptible to viral infection and viral-induced pathology, the aim of this study was to determine if first branchial arch NCM cells are susceptible to mCMV infection prior to differentiation of NCM derivatives.</p> <p>Results</p> <p>E11 mouse mandibular processes (MANs) were infected with mouse CMV (mCMV) for up to 16 days <it>in vitr</it>o. mCMV infection of undifferentiated embryonic mouse MANs induced micrognathia consequent to decreased Meckel's cartilage chondrogenesis and mandibular osteogenesis. Specifically, mCMV infection resulted in aberrant stromal cellularity, a smaller, misshapen Meckel's cartilage, and mandibular bone and condylar dysmorphogenesis. Analysis of viral distribution indicates that mCMV primarily infects NCM cells and derivatives. Initial localization studies indicate that mCMV infection changed the cell-specific expression of FN, NF-κB2, RelA, RelB, and Shh and Smad7 proteins.</p> <p>Conclusion</p> <p>Our results indicate that mCMV dysregulation of key signaling pathways in primarily NCM cells and their derivatives severely disrupts mandibular morphogenesis and skeletogenesis. The pathogenesis appears to be centered around the canonical and noncanonical NF-κB pathways, and there is unusual juxtaposition of abnormal stromal cells and surrounding matrix. Moreover, since it is critically important that signaling molecules are expressed in appropriate cell populations during development, the aberrant localization of components of relevant signaling pathways may reveal the pathogenic mechanism underlying mandibular malformations.</p

Collective classification for packed executable identification

Malware is any software designed to harm computers. Com-mercial anti-virus are based on signature scanning, which is a technique effective only when the malicious executa-bles have been previously analysed and identified. Malware writers employ several techniques in order to hide their ac-tual behaviour. Executable packing consists in encrypting or hiding the real payload of the executable. Generic unpack-ing techniques do not depend on the packer used, as they execute the binary within an isolated environment (namely ‘sandbox’) to gather the real code of the packed executable. However, this approach is slow and, therefore, a filter step is required to determine when an executable has been packed. To this end, supervised machine learning approaches trained with static features from the executables have been pro-posed. Notwithstanding, supervised learning methods need the identification and labelling of a high number of packed and not packed executables. In this paper, we propose a new method for packed executable detection that adopts a collec-tive learning approach to reduce the labelling requirements of completely supervised approaches. We performed an em-pirical validation demonstrating that the system maintains a high accuracy rate while the labelling efforts are lower than when using supervised learning

A Supervised Classification Approach for Detecting Packets Originated in a HTTP-based Botnet

The possibilities that the management of a vast amount of computers and/or networks offer is attracting an increasing number of malware writers. In this document, the authors propose a methodology thought to detect malicious botnet traffic, based on the analysis of the packets that flow within the network. This objective is achieved by means of the extraction of the static characteristics of packets, which are lately analysed using supervised machine learning techniques focused on traffic labelling so as to proactively face the huge volume of information nowadays filters work with