Rabbit Anti-Human MIB2 Polyclonal antibody

Tumor necrosis factor (TNF) is an inflammatory cytokine that can signal cell survival or cell death. The mechanisms that switch between these distinct outcomes remain poorly defined. Here, we show that the E3 ubiquitin ligase Mind Bomb-2 (MIB2) regulates TNF-induced cell death by inactivating RIPK1 via inhibitory ubiquitylation. Although depletion of MIB2 has little effect on NF-kappa B activation, it sensitizes cells to RIPK1- and caspase-8-dependent cell death. We find that MIB2 represses the cytotoxic potential of RIPK1 by ubiquitylating lysine residues in the C-terminal portion of RIPK1. Our data suggest that ubiquitin conjugation of RIPK1 interferes with RIPK1 oligomerization and RIPK1-FADD association. Disruption of MIB2-mediated ubiquitylation, either by mutation of MIB2's E3 activity or RIPK1's ubiquitin-acceptor lysines, sensitizes cells to RIPK1-mediated cell death. Together, our findings demonstrate that Mind Bomb E3 ubiquitin ligases can function as additional checkpoint of cytokine-induced cell death, selectively protecting cells from the cytotoxic effects of TNF.

Algorithms for real-time performance management and adaptive fault/anomaly detection in Internet protocol (IP) networks and services have been developed, and a corresponding real-time distributed software platform has been implemented. These algorithms automatically and adaptively detect "soft" faults or anomalies (performance degradations) in IP networks and services, enabling timely correction of network exceptions before failures occur and services are compromised and thereby achieving proactive network and service management. Further these algorithms are implemented as a reliable, fully distributed real-time software platform-the network/service anomaly detector (NSAD)-with the following features. First, it provides a flexible platform on which preconstructed monitoring and detection components can be mixed, matched, and distributed to form a wide range of application-specific NSADs and performance monitors. Second, NSAD and its components can auto-recover in real time, making it a reliable system for persistent monitoring of networks and their services. Third, anomaly detection is performed on raw network observables-for example, performance data such as management information base-2 (MIB2) and remote monitor-1/2 (RMON1/2) variables-and algebraic functions of these observables (objective functions), thereby enabling objective-driven anomaly detection of wide range and high sensitivity. Fourth, controlled testing (with anomalies injected a priori into a test network) demonstrates that NSAD can detect anomalies reliably in IP networks. Thus, NSAD provides a powerful framework/platform for automatic, proactive fault/anomaly defection and performance management in IP networks and services.