No abstract

Parkinson’s disease (PD) is a common neurodegenerative disease that severely affects the quality of life of patients. There is no specific drug for PD up to now. Previous studies have shown that neuroinflammation plays an important role in the pathogenesis of PD. Isoliquiritigenin (ILG) is thought to have a variety of biological activities including anti-inflammatory. However, to date, no studies have reported the role of ILG on neuroinflammation in PD in vivo. This study aimed to investigate the effect of ILG on PD in vivo and its mechanism, and to provide an experimental basis for clinical treatment of PD. Our results showed that ILG at a concentration of 20 mg/kg was effective in reducing the number of rotations in PD mice. In addition, ILG increased the expression of tyrosine hydroxylase and decreased the expression of α-synuclein. The results also showed that ILG reduced the expression of Iba1, IL-1β, IL-6, and TNF-α. Not only that, ILG also upregulated the expression of Nrf2 and NQO-1 in vivo. Our results suggest that ILG significantly attenuates neurological deficits in PD, and the mechanism may be through the activation of the Nrf2/NQO-1 signaling pathway to reduce neuroinflammation. Moreover, our findings provide a new therapeutic strategy for PD.

A model of walking stability analysis of a humanoid robot is given, in which the different environments are considered. By applying the concept of fictitious zero-moment point (FZMP), a method to maintain the walking stability of humanoid robot under external disturbance is presented. The support polygon and the rotation edge in the case of losing balance in single and double foot support phase are determined in computerized form. A new control strategy is proposed to maintain stability in different environments. The measures to keep stable walking are the adjustment of the support polygon, the push or pull support of hand with environment and the movement modification of upper robot body. The relative position between the FZMP and the rotation edge represents the strength and direction of losing the stability. The optimization gait of humanoid robot was determined by using genetic algorithms. The feasibility of the proposed method is demonstrated by the simulation.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most difficult to treat of all malignancies. Multimodality regimens provide only short-term symptomatic improvement with minor impact on survival, underscoring the urgent need for novel therapeutics and treatment strategies for PDAC. We screened out the highly expressed gene LAMC2 in PDAC tissues through the GEO online database, and further demonstrated that it is related to the poor prognosis of PDAC patients. Next, we investigated the effect of LAMC2 in the development and metastasis of PDAC by silencing LAMC2 expression in PDAC cells. The results showed that silencing of LAMC2 inhibited the proliferation, invasion and metastasis, and promoted apoptosis of PDAC cells, silencing of LAMC2 also reversed the epithelial mesenchymal transition (EMT) and suppressed the activation of NF-κB signaling pathway. Our results identify LAMC2 as a pivotal regulator of PDAC malignant progression, and its overexpression is sufficient to confer the characteristically aggressive clinical features of this disease.

Abstract. The variable precision rough set (VPRS) model is an extension of original rough set model. For inconsistent information system, the VPRS model allows a flexible approximation boundary region by a precision variable. This paper is focused on data mining in inconsistent information system using the VPRS model. A method based on VPRS model is proposed to apply to data mining for inconsistent information system. By our method the deterministic and probabilistic classification rules are acquired from the inconsistent information system. An example is given to show that the method of data mining for inconsistent information system is effective.