Effects of Partial Liver Ischemia Followed by Global Liver Reperfusion on the Remote Tissue Expression of Nitric Oxide Synthase: Lungs and Kidneys

Hepatic ischemia followed by reperfusion (IR) results in mild to severe remote organ injury. Oxidative stress and nitric oxide (NO) seem to be involved in the IR injury. Our aim was to investigate the effects of liver I/R on hepatic function and lipid peroxidation, leukocyte infiltration and NO synthase (NOS) immunostaining in the lung and the kidney. We randomized 24 male Wistar rats into 3 groups: 1) control; 2) 60 minutes of partial (70%) liver 1 and 2 hours of global liver R; and 3) 60 minutes of partial (70%) liver I and 6 hours of global liver R. Groups 2 and 3 showed significant increases in plasma alanine and aspartate aminotransferase levels and in tissue malondialdehyde and myeloperoxidase contents. In the kidney, positive endothelial NOS (eNOS) staining was significantly decreased in group 3 compared with group 1. However, staining for inducible NOS (iNOS) and neuronal NOS (nNOS) did not differ among the groups. In the lung, the staining for eNOS and iNOS did not show significant differences among the groups; no positive nNOS staining was observed in any group. These results suggested that partial liver I followed by global liver R induced liver, kidney, and lung injuries characterized by neutrophil sequestration and increased oxidative stress. In addition, we supposed that the reduced NO formation via eNOS may be implicated in the moderate impairment of renal function, observed by others at 24 hours after liver I/R.

The Great appropriation: Political Possibilities Since 1974

Argued that a new cadre of 'intellectual journalists' (such as Paul Kelly), unlike scholars of Graham Maddox's standing, have usurped critical appraisals of the possibilities of politics. This new anti-democratic liberalism wrongly suggests that political achievements reached when Australia was less rich (such as compulsory industrial arbitration) now need to abandoned, subordinating national well-being to an international policy orthodoxy.

The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.