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Isoforms of protein kinase C (PKC) have been shown to modulate some cellular responses such as pathological secretion and generation of inflammatory mediators during acute pancreatitis (AP). We propose that PKC also participates in premature zymogen activation within the pancreatic acinar cell, a key event in the initiation of AP. This hypothesis was examined in in vivo and cellular models of caerulein-induced AP using PKC activators and inhibitors. Phorbol ester, 12-O-tetradecanoylphorbol-13-acetate (TPA, 200 nM), a known activator of PKC, enhanced zymogen activation at both 0.1 nM and 100 nM caerulein concentrations which mimic physiological and supraphysiological effects of the hormone cholecystokinin, respectively, in preparations of pancreatic acinar cells. Isoform-specific PKC inhibitors for PKC-[delta] and PKC-[epsilon] reduced supraphysiological caerulein-induced zymogen activation. Using a cell-free reconstitution system, we showed that inhibition of PKC-[delta] and -[epsilon], reduced zymogen activation in both zymogen granule-enriched and microsomal fractions. In dispersed acinar cells, 100 nM caerulein stimulation caused PKC-[delta] and -[epsilon] isoform translocation to microsomal membranes using cell fractionation and immunoblot analysis. PKC translocation was confirmed with in vivo studies and immunofluorescence microscopy in pancreatic tissues from rats treated with or without 100 nM caerulein. PKC-[epsilon] redistributed from an apical to a supranuclear region following caerulein administration. The signal for PKC-[epsilon] overlapped with granule membrane protein, GRAMP-92, an endosomal/lysosomal marker, in a supranuclear region where zymogen activation takes place. These results indicate that PKC-[delta] and -[epsilon] isoforms translocate to specific acinar cell compartments and modulate zymogen activation. translocation; PKC activator phorbol ester; PKC inhibitor

The pancreatic acinar cell has several phenotypic responses to cAMP agonists. At physiological concentrations of the muscarinic agonist carbachol (1 [micro]M) or the CCK analog caerulein (100 pM), ligands that increase cytosolic [Ca.sup.2+], cAMP acts synergistically to enhance secretion. Supraphysiological concentrations of carbachol (1 mM) or caerulein (100 nM) suppress secretion and cause intracellular zymogen activation; cAMP enhances both zymogen activation and reverses the suppression of secretion. In addition to stimulating cAMP-dependent protein kinase (PKA), recent studies using cAMP analogs that lack a PKA response have shown that cAMP can also act through the cAMP-binding protein, Epac (exchange protein directly activated by cyclic AMP). The roles of PKA and Epac in cAMP responses were examined in isolated pancreatic acini. The activation of both cAMP-dependent pathways or the selective activation of Epac was found to enhance amylase secretion induced by physiological and supraphysiological concentrations of the muscarinic agonist carbachol. Similarly, activation of both PKA or the specific activation of Epac enhanced carbachol-induced activation of trypsinogen and chymotrypsinogen. Disorganization of the apical actin cytoskeleton has been linked to the decreased secretion observed with supraphysiological concentrations of carbachol and caerulein. Although stimulation of PKA and Epac or Epac alone could largely overcome the decreased secretion observed with either supraphysiological carbachol or caerulein, stimulation of cAMP pathways did not reduce the disorganization of the apical cytoskeleton. These studies demonstrate that PKA and Epac pathways are coupled to both secretion and zymogen activation in the pancreatic acinar cell. actin; zymogen; secretion; trypsin; chymotrypsin doi:10.1152/ajpgi.00478.2005.

Clustering Algorithms are nowadays really important tools in microarray data analysis. The different clustering algorithm generally used in biological science does not take into consideration the underlying probability distribution of the data. In this sense, they are heuristic in nature. In this work we proposed a clustering algorithm based on EM Algorithm. It gives 28% less misclassification than the K-means algorithm (which is mostly use in Bio science). We have also shown on a real data set that this algorithm can be efficiently used for detecting the genes which are responsible for a particular disease. [ABSTRACT FROM AUTHOR]