The pathogenesis of multiple organ dysfunction syndrome (MODS) in septic shock is complicated and not fully understood. Some studies show that an overproduction of nitric oxide (NO) leads to the refractory hypotension and multiple organ failure, while other studies suggest that free radicals, e.g. superoxide (O2−), contribute to the detrimental effect on vascular responsiveness and tissue/organ damage. Thus, this study was performed on the Wistar rat by using cecal ligation and puncture (CLP) to induce septic shock‐associated MODS. We evaluated the effect of an antioxidant melatonin in CLP‐induced septic rats and demonstrated that melatonin (3 mg/kg, i.v. at 3, 6, 12 hr after CLP) significantly (a) attenuated hyporeactivity to norepinephrine and delayed hypotension, (b) reduced plasma index of hepatic and renal dysfunction, (c) diminished plasma NO and interleukin‐1β (IL‐1β) concentrations as well as aortic O2− levels, (d) reduced marked infiltration of polymorphonuclear neutrophils (PMNs) in the lung and liver tissues, and (e) promoted the survival rate at 18 hr to twofold compared with the CLP alone group. The current study underlined the inhibition of plasma NO and IL‐1β as well as aortic O2− production and the reduction of PMN infiltration may lead to the amelioration of MODS, which may contribute to the beneficial effect of antioxidants (e.g. melatonin in this study) in conscious rats with peritonitis‐induced lethality. Thus, the antioxidant could be a novel agent for the treatment of septic animals or patients in the early stage.

There is good evidence that endotoxemia, sepsis, and septic shock are associated with the generation and release of reactive oxygen species (ROS) such as superoxide anion (O2), indicating that oxygen-derived free radicals play an important role in the pathogenesis of sepsis/shock. Studies on the application of free oxygen radical scavengers to limit the damage to tissues and organs have been recently attempted. A stable piperidine nitroxide of low molecular weight (Tempol) can permeate biological membranes and scavenge O2 in vitro and in vivo. Thus, we investigated effects of Tempol on the circulatory failure and multiple organ injuries caused by a clinically relevant polymicrobial sepsis model in the rat-cecal ligation and puncture (CLP). CLP not only successfully induced circulatory failure but also substantially increased plasma concentrations of glutamate-oxalate-transferase and glutamate-pyruvate-transferase (indicators of liver injury), creatinine and blood urea nitrogen (indicators of kidney injury), and decreased base excess in arterial blood in the late stage, indicating the development of multiple organ injury in this study. These were also confirmed by a histologic examination showing that the CLP-induced sepsis accompanied increase of polymorphonuclear neutrophil (PMN) infiltration in the lung and sequestration in the liver. Our results demonstrated that Tempol not only ameliorated the deterioration of hemodynamic changes and renal and liver injuries but also attenuated PMN infiltration in the lung and sequestration in the liver (histology). In addition, Tempol improved the survival in CLP-induced septic rats. Moreover, Tempol reduced the plasma NO. and interleukin-1beta and organ O2 levels in CLP-treated rats. In conclusion, Tempol prevented circulatory failure and attenuated organ dysfunction/injury as well as decreased the mortality rate in CLP-treated animals. These beneficial effects of Tempol may be attributed to inhibition of ROS formation (e.g., NO. and O2), suggesting antioxidant (e.g., Tempol) is a potential therapeutic agent in the treatment of intraperitoneal septic shock.

This study proposes an intelligent optimization system based on the Taguchi method, back-propagation neural network (BPNN), multilayer perceptron (MLP) and modified PSO-GA to find optimal process parameters in plastic injection molding (PIM). Firstly, the Taguchi method is used to determine the initial combination of parameter settings by calculating the signal-to-noise (S/N) ratios from the experimental data. Significant factors are determined using analysis of variance (ANOVA). The S/N ratio predictors (BPNNS/N) and quality predictors (BPNNQ) are constructed using BPNN with the experimental data. In addition, a modified PSO-GA algorithm in conjunction with MLP is used to find initial weights of BPNN and to reduce the training time of BPNN. In the first stage optimization, the S/N ratio predictors are coupled with GA to reduce the variations of the manufacturing process. In the second stage optimization, The combination of S/N ratio predictors and quality predictors with modified PSO-GA is empoyed to search for the optimal parameters. Finally, three confirmation experiments are performed to assess the effectiveness of these approaches. The experimental results show that the proposed system can create the best performance, and optimal process parameter settings which not only enhance the stability in the whole injection molding process but also effectively improve the PIM product quality. Furthermore, experiences of the novel hybrid optimization system can be transferred into the intelligent PIM machines for the coming up internet of things (IoT) and big data environment.