Anti-Human CASP6 monoclonal antibody

PURPOSE: To investigate the effects of ischemic preconditioning (IPC) on the expression of pro and anti-apoptotic genes in rat endothelial cells undergoing enteric ischemia (I) and reperfusion (R). METHODS: Thirty rats underwent clamping of the superior mesenteric vessels. Sham group (GS) laparotomy only; Ischemia (GI): intestinal ischemia (60 min); Ischemia and Reperfusion (GIR): ischemia (60 min) and reperfusion (120 min); Ischemia and intestinal ischemic preconditioning (GI + IPC) : 5 minutes of ischemia followed by 10 min of reperfusion before sustained ischemia (60 min) ischemia and reperfusion and IPC (GIR + IPC): 5 min ischemia followed by 10 min of reperfusion before sustained ischemia (60min) and reperfusion (120 min). Rat Endothelial Cell Biology (PCR array) to determine the expression of genes related to endothelial cell biology. RESULTS: Gene expression of pro-apoptotic markers (Casp1, Casp6, Cflar, Fas, and Pgl) was down regulated in GI+IPC and in GIR + IPC. In contrast, the expression of anti-apoptotic genes (Bcl2 and Naip2), was up-regulated in GI + IPC and in GIR + IPC. CONCLUSION: Ischemic preconditioning may protect against cell death caused by ischemia and reperfusion.

The structure prediction of loops with flexible stem residues is addressed in this article. While the secondary structure of the stem residues is assumed to be known, the geometry of the protein into which the loop must fit is considered to be unknown in our methodology. As a consequence, the compatibility of the loop with the remainder of the protein is not used as a criterion to reject loop decoys. The loop structure prediction with flexible stems is more difficult than fitting loops into a known protein structure in that a larger conformational. space has to be covered. The main focus of the study is to assess the precision of loop structure prediction if no information on the protein geometry is available. The proposed approach is based on (1) dihedril angle sampling, (2) structure optimization by energy minimization with a physically based energy function, (3) clustering, and (4) a comparison of strategies for the selection of loops identified in (3). Steps (1) and (2) have similarities to previous approaches to loop structure prediction with fixed stems. Step (3) is based on a new iterative approach to clustering that is tailored for the loop structure prediction problem with flexible stems. In this new approach, clustering is not only used to identify conformers that are likely to be close to the native structure, but clustering is also employed to identify far-from-native decoys. By discarding these decoys iteratively, the overall quality of the ensemble and the loop structure prediction is improved. Step (4) provides a comparative study of criteria for loop selection based on energy, colony energy, cluster density, and a hybrid criterion introduced here. The proposed method is tested on a large set of 3215 loops from proteins in the Pdb-Select25 set and to 179 loops from proteins from the Casp6 experiment.