The mRNA levels of the selected genes were quantified by means of a semi-quantitative RT-PCR. The actual BCKDH and total BCKDH activities were assayed spectrophotometrically prior to and following incubation with lambda phosphatase, respectively. For 14 days, simvastatin (80 mg/kg b wt/day) or the vehicle (0.3% methylcellulose) were administrated orally by gavage to the treated and control groups, respectively. The present study was aimed at investigating the in vivo effect of simvastatin on liver BCKDH activity, as well as E1, E2 and BDP and BDK mRNA levels in rats fed with either a standard (23% protein) or a low protein (8% protein) diet. Effect of statins on liver BCKDH activity has not been studied yet. It has been previously shown that lipid lowering drugs, fibrates upregulate liver BCKDH activity and stimulate BCAAs catabolism, especially under the condition of dietary protein deprivation. Feeding rats a low-protein diet decreases BCKDH activity. Liver BCKDH activity state alters in response to different nutritional factors. Current catalytic activity of BCKDH, described as BCKDH activity state, and thus also BCAAs catabolic rate depend directly on the portion of BCKDH occurring in its active dephosphorylated form. BCKDH activity is regulated mainly by a reversible dephosphorylation (activation)/phosphorylation (inactivation) cycle catalyzed by a specific phosphatase (BDP) and kinase (BDK). The rate-limiting step in branched-chain amino acids (BCAAs) disposal is catalyzed by the mitochondrial branched-chain α-ketoacid dehydrogenase complex (BCKDH). The ability of α7 nicotinic receptor (α7nAchR) antagonist methyllycaconitine (5 mg kg −1) to counteract the beneficial action provided by buspirone on I/R-induced neutrophil infiltration suggests that the anti-inflammatory effect produced by 5-HT 1A receptor antagonism could be partly ascribed to the indirect activation of α7nAch receptors. Our results confirmed the significant role played by 5-HT 2A receptors not only in the late but also in the early I/R-induced microcirculatory dysfunction and showed that blockade of 5-HT 1A receptors protected against the intestinal leukocyte recruitment, plasma extravasation and reactive oxygen species formation triggered by SMA occlusion and reflow. Second, the effects produced by intravenous administration of 5-HT 1A ligands (partial agonist buspirone 10 mg kg −1, antagonist WAY100135 0.5–5 mg kg −1), 5-HT 2A antagonist sarpogrelate (10 mg kg −1), 5-HT 3 antagonist alosetron (0.1 mg kg −1), 5-HT 4 antagonist GR125487 (5 mg kg −1) and 5-HT re-uptake inhibitor fluoxetine (10 mg kg −1) on I/R-induced inflammatory response were investigated in I/R mice and compared to those obtained in sham-operated animals (S). To this end, we first observed that ischemic preconditioning before I/R injury (IPC + I/R) reverted the increase in 5-HT tissue content and in inflammatory parameters induced by I/R in mice. Starting from these premises, the aim of our present work was to investigate the role played by endogenous 5-HT in the same experimental model where 45 min SMA clamping was followed by 5 h reflow. Recently, we proved the involvement of 5-HT 2A receptors in the intestinal dysmotility and leukocyte recruitment induced by 45 min occlusion of the superior mesenteric artery (SMA) followed by 24 h reperfusion in mice. Experimentally, either protective or detrimental roles have been attributed to 5-HT in the functional and morphological injury caused by mesenteric I/R. ![]() Intestinal ischemia and reperfusion (I/R) is a potentially life-threatening disease, ensuing from various clinical conditions. The results show that the new algorithm generates very compact neural architectures with state-of-the-art generalization capabilities. The problem of overfitting is also analyzed, and a new built-in method to avoid its effects is devised and successfully applied within an active learning paradigm that filter noisy examples. Both sets were used to analyze the size of the constructed architectures and the generalization ability obtained and to compare the results with those from other standard and well known classification algorithms. ![]() The new algorithm is tested on two different sets of benchmark problems: a Boolean function set used in logic circuit design and a well studied set of real world problems. Competition makes it possible that even after new units have been added to the network, existing neurons still can learn if the incoming information is similar to their stored knowledge, and this constitutes a major difference with existing constructing algorithms. The neuron learning is governed by the thermal perceptron rule that ensures stability of the acquired knowledge while the architecture grows and while the neurons compete for new incoming information. C-Mantec is a novel neural network constructive algorithm that combines competition between neurons with a stable modified perceptron learning rule.
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