3,590 research outputs found

    Effector Caspases and Leukemia

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    Caspases, a family of aspartate-specific cysteine proteases, play a major role in apoptosis and a variety of physiological and pathological processes. Fourteen mammalian caspases have been identified and can be divided into two groups: inflammatory caspases and apoptotic caspases. Based on the structure and function, the apoptotic caspases are further grouped into initiator/apical caspases (caspase-2, -8, -9, and -10) and effector/executioner caspases (caspase-3, -6, and -7). In this paper, we discuss what we have learned about the role of individual effector caspase in mediating both apoptotic and nonapoptotic events, with special emphasis on leukemia-specific oncoproteins in relation to effector caspases

    Identifying online user reputation in terms of user preference

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    Identifying online user reputation is significant for online social systems. In this paper, taking into account the preference physics of online user collective behaviors, we present an improved group-based rating method for ranking online user reputation based on the user preference (PGR). All the ratings given by each specific user are mapped to the same rating criteria. By grouping users according to their mapped ratings, the online user reputation is calculated based on the corresponding group sizes. Results for MovieLens and Netflix data sets show that the AUC values of the PGR method can reach 0.9842 (0.9493) and 0.9995 (0.9987) for malicious (random) spammers, respectively, outperforming the results generated by the traditional group- based method, which indicates that the online preference plays an important role for measuring user reputation

    Accumulation of Dense Core Vesicles in Hippocampal Synapses Following Chronic Inactivity.

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    The morphology and function of neuronal synapses are regulated by neural activity, as manifested in activity-dependent synapse maturation and various forms of synaptic plasticity. Here we employed cryo-electron tomography (cryo-ET) to visualize synaptic ultrastructure in cultured hippocampal neurons and investigated changes in subcellular features in response to chronic inactivity, a paradigm often used for the induction of homeostatic synaptic plasticity. We observed a more than 2-fold increase in the mean number of dense core vesicles (DCVs) in the presynaptic compartment of excitatory synapses and an almost 20-fold increase in the number of DCVs in the presynaptic compartment of inhibitory synapses after 2 days treatment with the voltage-gated sodium channel blocker tetrodotoxin (TTX). Short-term treatment with TTX and the N-methyl-D-aspartate receptor (NMDAR) antagonist amino-5-phosphonovaleric acid (AP5) caused a 3-fold increase in the number of DCVs within 100 nm of the active zone area in excitatory synapses but had no significant effects on the overall number of DCVs. In contrast, there were very few DCVs in the postsynaptic compartments of both synapse types under all conditions. These results are consistent with a role for presynaptic DCVs in activity-dependent synapse maturation. We speculate that these accumulated DCVs can be released upon reactivation and may contribute to homeostatic metaplasticity

    Load Adaptive PMSM Drive System Based on an Improved ADRC for Manipulator Joint

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    Identifying online user reputation of user–object bipartite networks

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    Identifying online user reputation based on the rating information of the user–object bipartite networks is important for understanding online user collective behaviors. Based on the Bayesian analysis, we present a parameter-free algorithm for ranking online user reputation, where the user reputation is calculated based on the probability that their ratings are consistent with the main part of all user opinions. The experimental results show that the AUC values of the presented algorithm could reach 0.8929 and 0.8483 for the MovieLens and Netflix data sets, respectively, which is better than the results generated by the CR and IARR methods. Furthermore, the experimental results for different user groups indicate that the presented algorithm outperforms the iterative ranking methods in both ranking accuracy and computation complexity. Moreover, the results for the synthetic networks show that the computation complexity of the presented algorithm is a linear function of the network size, which suggests that the presented algorithm is very effective and efficient for the large scale dynamic online systems
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