STAT3 is an essential cellular transcription factor that activates a cascade of survival and proliferation signaling program in cells upon cytokine and growth factor stimulus. STAT3 forms a converging point for many upstream activated signaling pathways required for maintaining normal and oncogenic condition. As an active transcription factor, it controls transcription of downstream genes involved in various steps of cancer progression like cell proliferation, migration, immune evasion and angiogenesis. It is known to be constitutively active in many cancers with approximately 40% of breast cancer cases positive for activated STAT3. Apart from the wellstudied pY705 activation (canonical pathway), STAT3 is reported to undergo alternative post-translational modifications like pS727 and K685Ac (non-canonical pathway) that are now appearing to be responsible for triggering activated STAT3 in many cancers including breast cancer. Hence, correct designation and targeting ability of these post-translational modifications (PTM) of STAT3 signaling in any particular cancer may hold the key in treating patients with STAT3 overexpression.
Wireless sensor networks (WSN) are emerging in various fields like disaster management, battle field surveillance and border security surveillance. A large number of sensors in these applications are unattended and work autonomously. Clustering is a key technique to improve the network lifetime, reduce the energy consumption and increase the scalability of the sensor network. In this paper, we study the impact of heterogeneity of the nodes to the performance of WSN. This paper surveys the different clustering algorithm for heterogeneous WSN.
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