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.
Background: Perinatal asphyxia is a major cause of neonatal and childhood morbidity and mortality. Electronic foetal monitoring is used routinely to know the condition of the baby during Intrapartum period. Normal trace correlates highly with absence of acidemia at birth. Abnormal trace needs further evaluation. In order to better define the metabolic status of the new born, umbilical lactate levels have been measured. Objectives of this study were to determine the validity of umbilical cord blood lactate levels in predicting the adverse early neonatal outcome in babies with intrapartum foetal distress and to compare the validity of umbilical cord blood lactate and umbilical artery pH in predicting adverse neonatal outcome in babies with intrapartum foetal distress.Methods: 295 pregnant women with abnormal CTG in active labour were subjected for estimation of cord blood lactate and umbilical artery pH immediately after delivery and were compared in predicting adverse neonatal outcome.Results: In the present study specificity of serum lactate (97.7%) and umbilical artery pH (95.97%) was almost similar in babies with Apgar <7 at 1 minute and 5 minutes, but sensitivity of serum lactate (23.14%) and cord ph (31.4%) was less in babies with Apgar score ≤7 at 1 minute. Area under ROC showed serum lactate is more accurate in predicting adverse neonatal outcome compared to umbilical artery pH.Conclusions: Umbilical cord blood lactate is more specific than umbilical artery pH in predicting adverse neonatal outcome. Area under ROC (at 95th percentile) shown serum lactate is more accurate in predicting adverse neonatal outcome compared to umbilical artery pH at birth.
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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