Chonbuk National University

About: Chonbuk National University is a education organization based out in Jeonju, South Korea. It is known for research contribution in the topics: Apoptosis & Nanofiber. The organization has 14820 authors who have published 28884 publications receiving 554131 citations.

The major target of the endogenously generated reactive oxygen species in response to insulin stimulation is Phosphatase and Tensin homolog and not phosphoinositide-3 kinase (PI-3 kinase) in the PI-3 kinase/Akt pathway

Abstract: Phosphoinositide-3 kinase (PI-3 kinase) and its downstream signaling molecules PDK-1 and Akt were analyzed in SK-N-SH and SK-N-BE(2) human neuroblastoma cell lines. When cells were stimulated with insulin, PI-3 kinase was activated in both cell lines, whereas the translocation of PDK-1 to the membrane fraction and phosphorylated Akt were observed only in SK-N-SH cells. Analyses of the insulin-mediated reactive oxygen species (ROS) generation and Phosphatase and Tensin homolog (PTEN) oxidation indicate that PTEN oxidation occurred in SK-N-SH cells, which can produce ROS, but not in SK-N-BE(2) cells, which cannot increase ROS in response to insulin stimulation. When SK-N-SH cells were pretreated with the NADPH oxidase inhibitor diphenyleneiodonium chloride before insulin stimulation, insulin-mediated translocation of PDK-1 to the membrane fraction and phosphorylation of Akt were remarkably reduced, whereas PI-3 kinase activity was not changed significantly. These results indicate that not only PI-3 kinase activation but also inhibition of PTEN by ROS is needed to increase cellular level of phosphatidylinositol 3,4,5-trisphosphate for recruiting downstream signaling molecules such as PDK-1 and Akt in insulin-mediated signaling. Moreover, the ROS generated by insulin stimulation mainly contributes to the inactivation of PTEN and not to the activation of PI-3 kinase in the PI-3 kinase/Akt pathway.

A cluster-based resampling method for pseudo-relevance feedback

Abstract: Typical pseudo-relevance feedback methods assume the top-retrieved documents are relevant and use these pseudo-relevant documents to expand terms. The initial retrieval set can, however, contain a great deal of noise. In this paper, we present a cluster-based resampling method to select better pseudo-relevant documents based on the relevance model. The main idea is to use document clusters to find dominant documents for the initial retrieval set, and to repeatedly feed the documents to emphasize the core topics of a query. Experimental results on large-scale web TREC collections show significant improvements over the relevance model. For justification of the resampling approach, we examine relevance density of feedback documents. A higher relevance density will result in greater retrieval accuracy, ultimately approaching true relevance feedback. The resampling approach shows higher relevance density than the baseline relevance model on all collections, resulting in better retrieval accuracy in pseudo-relevance feedback. This result indicates that the proposed method is effective for pseudo-relevance feedback.

Technological trends in heavy metals removal from industrial wastewater: A review

Abstract: Rapid industrialization, with economic prosperity set as the prime goal, has always created some secondary intolerable problems such as heavy metal contamination, wastewater that need remediation. Industrial wastewater is the major contributors to contamination of aquatic and terrestrial ecosystems with toxic heavy metals like arsenic, copper, chromium, cadmium, nickel, zinc, lead, and mercury whose hazardous bio-accumulative nature in biotic systems is attributed to their high solubility in the aquatic environments. There has, therefore, always been a need for the removal and/or recovery of these toxic, non-biodegradable, and persistent heavy metals from the industrial wastewater. For several decades, extensive investigations have been performed for easy, efficient, and economic removal of heavy metals with a varying degree of success. Chemical precipitation, adsorption, ion floatation, ion-exchange, coagulation/flocculation and electrochemical methods have been the most readily available conventional methods for the removal of these heavy metals. These methods however have posed some serious shortcomings such as high sludge production needing further treatment, low removal efficiency and high energy requirements. In the present years, newer more efficient, more economic and innovative technologies are being investigated. Recently photocatalysis, electrodialysis, hydrogels, membrane separation technique and introducing newer adsorbents have been developed for better adsorption. Hence in this paper, we have reviewed efforts and technological advances achieved so far in the pursuit of more efficient removal and recovery of heavy metals from industrial wastewaters and have evaluated their efficiency dependence on various parameters such as pH, temperature & initial dosing.