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Nonlinear complex system modeling has drawn attention from diverse fields and many approaches have been developed. Among those approaches, the advantages of the belief rule base (BRB) expert system have been shown for managing multiple types of information under uncertainty and modeling the nonlinearity present in many theoretical and practical complex systems. However, two challenges still need to be addressed. First, BRB needs to be downsized to conserve modeling and computational effort. For this challenge, a new disjunctive assumption is applied, which can significantly downsize BRB while maintaining its completeness. Second, the structure and parameters of BRB need to be jointly optimized. For this challenge, a new Akaike information criterion (AIC)-based optimization objective is derived to represent both modeling accuracy and modeling complexity. Moreover, a joint bi-level optimization model with an AIC-based objective is constructed for the BRB structure and parameters, and a bi-level optimization algorithm is proposed. Three evolutionary algorithms, namely, the genetic algorithm, particle swarm optimization algorithm, and differential evolutionary algorithm, are tested in a comparative fashion to determine the best fit for the optimization engine. The results of two practical case studies show that the joint optimization approach can identify an optimal configuration for both its structure and parameters, which is referred to as the best decision structure in this paper. [ABSTRACT FROM AUTHOR]

It is vital to assess the lives of newly developed products by using failure data from various testing environments. In the current methods, two steps are generally included. The first step is transforming the failure data under one testing environment into the actual working environment, and the second step is integrating all failure data under the actual working environment into a unified result. However, most available methods cannot use information that includes part failure data and part expert knowledge simultaneously. To resolve the above issue, based on the belief rule base (BRB) and the evidential reasoning (ER) approach, a new BRB-ER-based model is proposed, where the BRB is used to transform the failure data from one testing environment into the actual working environment. The ER approach, which is adopted to aggregate the failure data from different testing environments, is used to assess the life of a product. To conclude, the BRB-ER-based model is applied to represent and integrate asynchronous multisource information. In the proposed model, the initial BRB system is constructed based on experts’ knowledge, which results in uncertainty because of the ambiguous nature of human judgment and calls for training the parameters in the BRB-ER-based model. Therefore, an optimal algorithm that employs the differential evolutionary algorithm is proposed. The proposed model and the optimal algorithm operate in an integrated manner to improve the assessment precision by using both failure data and expert knowledge effectively. A case study in three scenarios and use of the conventional approach is examined to demonstrate the capability and potential applications of the new BRB-ER-based model. [ABSTRACT FROM AUTHOR]

A structure learning approach is proposed using the principal component analysis (PCA) in order to downsize the belief rule base (BRB). First, we select the principal components (PCs) from the attributes, and then identify the attributes with bigger contributions to the PCs using the loading matrix. A numerical case study to evaluate the comprehensive capability for an armored system of systems is analyzed under both single input and multiple inputs scenarios. The efficiency of the proposed approach is validated by the results of the case study: the BRB is significantly downsized and the consistency between the proposed approach and RIMER is preserved. Besides, the robustness of the structure learning approach is further verified. [ABSTRACT FROM AUTHOR]

Due to the complicated clinical features of mitochondrial encephalomyopathy, simplified mitochondrial disease criteria (MDC) have recently been established in Europe. This study evaluated the sensitivity and specificity of this scoring system in Chinese patients. Seventy-eight patients with suspected mitochondrial encephalomyopathy were recruited to be scored by the simplified MDC and were further classified into 'possible' (2-4), 'probable' (5-7), or 'definite' categories (≥8). Significant differences were observed between the total scores in the mitochondrial encephalomyopathy group and the other myopathy group. In the mitochondrial encephalomyopathy group, 73.5% of patients had a score above 8, whereas in the other myopathy group, the 'definite' percentage was only 3.2%, suggesting the proposed MDC scoring system has a high sensitivity for diagnosis of mitochondrial encephalomyopathy in China. Moreover, there were significant differences in the clinical scores and imaging portions of the MDC, suggesting that the simplified MDC may distinguish mitochondrial disorder from other multisystem disorders to aid in early diagnosis prior to a muscle biopsy. [ABSTRACT FROM AUTHOR]

The central neurotensin system has been implicated in reward, memory processes, also in the regulation of anxiety. However, the neural substrates where neurotensin acts to regulate anxiety have not been fully identified. The prelimbic region of medial prefrontal cortex (PrL) holds a key position in the modulation of anxiety-related behaviors and expresses neurotensin 1 receptor (NTS1). This study investigated the effects of activation or blockade of NTS1 in the PrL on anxiety-like behaviors of rats. Our results demonstrated that infusion of a selective NTS1 agonist or neurotensin into the PrL produced anxiogenic-like effects. Administration of a NTS1 antagonist into the PrL did not affect anxiety-like behaviors of normal rats, but attenuated anxiogenic effects induced by restraint stress. Moreover, we employed molecular approaches to downregulate the expression of NTS1 in the PrL, and found that downregulation of NTS1 in the PrL induced anxiolytic effects in restraint stress rats, also confirming the pharmacological results. Together, these findings suggest that NTS1 in the PrL is actively involved in the regulation of anxiety. • Activation of neurotensin 1 receptor (NTS1) in the prelimbic cortex (PrL) induced anxiogenic behaviors. • Antagonism of NTS1 in the PrL blocked the anxiogenic effects of neurotensin. • Blockage of NTS1 in the PrL did not affect anxiety-like behaviors of normal rats. • Blocking NTS1 in the PrL reversed anxiogenic effects induced by restraint stress. • Knockdown of NTS1 in the PrL attenuated anxiogenic responses of restraint stress. [ABSTRACT FROM AUTHOR]

Aims Accumulated evidence indicates that cerebral metabolic features, evaluated by proton magnetic resonance spectroscopy (1H- MRS), are sensitive to early mitochondrion dysfunction associated with mitochondrial encephalomyopathy ( ME). The metabolite ratios of lactate (lac)/Cr, N-acetyl aspartate ( NAA)/creatine (Cr), total choline ( tCho)/Cr, and myoinositol ( mI)/Cr are measured in the infarct-like lesions by 1H- MRS and may reveal metabolic changes associated with ME. However, the application of this molecular imaging technique in the investigation of the pathology of ME subtypes is unknown. Methods In this study, cerebral metabolic features of pathologically diagnosed ME cases, that is, 19 mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes ( MELAS); nine chronic progressive external ophthalmoplegia ( CPEO); and 23 healthy controls, were investigated using 1H- MRS. Receiver operating characteristics ( ROC) analysis was used to evaluate the diagnostic power of the cerebral metabolites. Histochemical evaluation was carried out on muscle tissues derived from biopsy to assess the abnormal mitochondrial proliferation. The association between cerebral metabolic and mitochondrial cytopathy was examined by correlation analysis. Results Patients with MELAS or CPEO exhibited a significantly higher Lac/Cr ratio and a lower NAA/Cr ratio compared with controls. The ROC curve of Lac/Cr ratio indicated prominent discrimination between MELAS or CPEO and healthy control subjects, whereas the NAA/Cr ratio may present diagnostic power in the distinction of MELAS from CPEO. Lower NAA/Cr ratio was associated with higher Lac/Cr in MELAS, but not in CPEO. Furthermore, higher ragged-red fibers ( RRFs) percentages were associated with elevated Lac/Cr and reduced NAA/Cr ratios, notably in MELAS. This association was not noted in the case of mI/Cr ratio. Conclusions Mitochondrial cytopathy (lactic acidosis and RRFs on muscle biopsy) was associated with neuronal viability but not glial proliferation, notably in MELAS. Mitochondrial neuronopathy and neuronal vulnerability are considered significant causes in the pathogenesis of MELAS, particularly with regard to stroke-like episodes. [ABSTRACT FROM AUTHOR]

Aims The purpose of this study was to evaluate the energy metabolism and mitochondrial function in skeletal muscle from patients with Mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes ( MELAS) or chronic progressive external ophthalmoplegia ( CPEO) using phosphorus magnetic resonance spectroscopy (31P- MRS), to determine whether abnormally increasing cytochrome c oxidase ( COX), as detected in muscle biopsy, could be a cause for MELAS. Methods 31P- MRS was performed on the quadriceps femoris muscle of 12 healthy volunteers and 11 patients diagnosed as MELAS or CPEO by muscle biopsy and genetic analysis. All subjects experienced a state of rest, 5-min exercise, and 5-min recovery protocol in a supine position. Results Compared to CPEO, MELAS patients typically exhibited COX-positive ragged-red fibers ( RRFs) as well as strongly SDH-positive blood vessels ( SSVs). However, based on 31P- MRS results, MELAS showed a higher inorganic phosphate (Pi)/phosphocreatine ( PCr) ratio and lower ATP/ PCr ratio during exercise and delayed Pi/ PCr and ATP/ PCr recovery to normal. Conclusions This study suggests that high COX expression contributes to severe skeletal energy failure by 31P- MRS spectroscopy in MELAS. [ABSTRACT FROM AUTHOR]

The belief rule-base (BRB) model is a new intelligent expert system with the characteristics of both expert system and data-driven model. In BRB there are many if-then rules which use belief degrees to express various types of uncertain information, including fuzziness, randomness, and ignorance. As a semi-quantitative modeling tool for complex systems, BRB has the superiorities of dealing both numerical quantitative data and linguistic qualitative knowledge that are derived from heterogeneous sources. Moreover, it is also a white box approach which can provide direct access and transparency to decision makers and stakeholders. Currently, BRB has been widely applied in many fields, such as decision making, reliability evaluation, network security situation awareness, fault diagnosis, and so on. To fully demonstrate the progress of BRB, the original BRB, and some evolution forms are introduced in this article. [ABSTRACT FROM AUTHOR]

It is vital to online assess the safety of a complex dynamic system by taking into account the current state, degradation trend, and historical records together. This paper proposes a new safety assessment model with an online algorithm based on the evidential reasoning (ER) approach. It does not only take into account the relative importance of each safety indicator, but also consider the reliability of each indicator. To obtain the integrated safety level, multiple safety indicators are fused at first and the “history,” “current,” and “future” safety states are then integrated. First, a forecasting model based on the third-order Volterra filter is proposed to predict the safety indicators’ information online. Second, an adaptive weighting model is developed to automatically adjust to various conditions and track the characteristics of the dynamic system, and the reliability of each indicator is considered to diminish the influence of inherent disturbance and/or noise. Finally, a safety assessment aggregation scheme based on the ER approach is presented to fuse the history, current, and future safety indicators to obtain the corresponding safety state, and the safety states are then fused synthetically to obtain a comprehensive safety assessment result of the complex dynamic system. A numerical study is examined to demonstrate the implementation and effectiveness. Moreover, a practical example of the inertial navigation system is studied to show the potential applications of the proposed ER-based safety assessment method. [ABSTRACT FROM AUTHOR]

The belief rule-base (BRB) inference methodology, which uses the evidential reasoning (RIMER) approach, has been widely popular in recent years. As an expert-system methodology using the RIMER approach, BRB is used for storing various types of uncertain knowledge in the form of belief structure. Several structure-learning approaches have been proposed in recent years. However, these approaches are deficient in various aspects, do not have repeatability, hold incomplete data, and are constrained by the associated scale-utility value. Moreover, considering the influence of the number of rules for a BRB system, two scenarios are designed to reveal the relationship between structure feature and fewer/excessive rules. Excessive rules may lead to a BRB that is equipped with an over-complete structure, whereas significantly fewer rules may result in a BRB with an incomplete structure. To solve these problems, we initially proposed to develop an adjusted structure that is leading to the establishment of a complete structure instead of incomplete and over-complete structures. By scenario analysis and experimental verification through parameter learning of BRBs, we summarize several features of two scenarios, which can be used to reveal certain number of key BRB properties. Finally, density and error analyses are introduced to dynamically prune or add rules to construct the complete structure, particularly that of the BRB comprising multiple-antecedent attributes. We verify the effectiveness of the proposed approach by testing its use in a practical case study on oil pipeline-leak detection and demonstrate how the approach can be implemented. [ABSTRACT FROM AUTHOR]

Abstract: KYKZL-1, a newly synthesized compound with COX/5-LOX dual inhibition, was subjected to the inhibitory activity test on Hep G2 growth. We found that KYKZL-1 inhibited the growth of Hep G2 cells via inducing apoptosis. Further studies showed that KYKZL-1 activated caspase-3 through cytochrome c release from mitochondria and down regulation of Bcl-2/Bax ratio and reduced the high level of COX-2 and 5-LOX. As shown in its anti-inflammatory effect, KYKZL-1 also exhibited inhibitory effect on the PGE2 and LTB4 production in Hep G2 cells. Accordingly, exogenous addition of PGE2 or LTB4 reversed the decreases in cell viability. In addition, KYKZL-1 caused cell cycle arrest at the S–G2 checkpoint via the activation of p21CIP1 protein and down-regulation of cyclin A expression. These data indicate that the growth inhibitory effect of KYKZL-1 is associated with inhibition of AA metabolites and caspase-3 pathway and cell cycle arrest. Combined with our previous findings, KYKZL-1 exhibiting COX/5-LOX inhibition may be a promising potential agent not only for inflammation control but also for cancer prevention/therapy with an enhanced gastric safety profile. [Copyright &y& Elsevier]

Abstract: Inflammation is an important contributing mechanism in ischemic brain injury. The current study elucidates a previously unexplored role of Fas ligand (FasL) in post-stroke inflammatory responses that is independent of its well-known effect in triggering apoptosis. Focal cerebral ischemia was induced for 2h by right middle cerebral artery occlusion (MCAO) in FasL mutant (gld) and wild-type mice. FasL mutation profoundly reduced brain damage and improved neurological performance from 6 to 72h after ischemic stroke. The production of inflammatory cytokines in the brain was attenuated in gld mice after ischemia in the absence of dramatic change in inflammatory cell apoptosis. FasL mutation attenuated the recruitment of peripheral inflammatory cells (neutrophil) and inhibited the activation of residential glial cells (microglia and astrocyte). FasL mutation reduced CD8+ T cells and turned the Th1/Th2 balance towards Th2 in the brain and peripheral blood after cerebral ischemia. In contrast to cerebral ischemia, the molecular and cellular inflammatory changes induced by intracerebroventricular injection of lipopolysaccharide (LPS) were also attenuated in gld mice. Moreover, the soluble FasL (sFasL) and phospho-SAPK/JNK were decreased in gld mice, suggesting that the inflammatory role of FasL in experimental stroke might relate to sFasL and the c-Jun N-terminal kinase (JNK) signaling pathway. Taken together, our data suggest a novel role of FasL in the damaging inflammatory responses associated with cerebral ischemia. Neutralization of FasL may be a novel therapeutic strategy to suppress post-stroke inflammation and improve the long-term outcomes of stroke. [Copyright &y& Elsevier]