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- 저자 : Dentz, Marco (검색결과 2 건)
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Von Dentz Maiza,Gambato Gabriela,Ferrari Andreza,Fontana Roselei Claudete,Rodrigues Eliseu,Salvador Mirian,Camassola Marli,Jahn Matheus Parmegiani 경희대학교 융합한의과학연구소 2021 Oriental Pharmacy and Experimental Medicine Vol.21 No.3
One of the consequences of diabetes mellitus is deregulation in lipid metabolism, resulting in an increase in triglyceride and cholesterol levels in the blood. This study evaluated the effect of the Pycnoporus sanguineus hydroalcoholic extract on lipid metabolism in streptozotocin-induced diabetic rats. Rats received P. sanguineus extract for 4 weeks in the drinking water at a dose of 10 mg/Kg/day. Lipid profile, glucose and hepatic damage in normal and streptozotocin-induced diabetic rats were evaluated. Also, the chemical composition of P. sanguineus extract, cytotoxicity and HMG-CoA reductase activity in vitro were evaluated. The treatment significantly reduced triglyceride levels in the group of diabetic rats treated with the extract (DBT Pyc) compared to the group receiving water without extract (DBT H2O). For total cholesterol, reductions in the DBT Pyc group were also observed in relation to the DBT H2O group. The HMG-CoA reductase activity was not affected by P. sanguineus extract. Our findings demonstrated significant anti-hyperlipidaemic activity of P. sanguinues extract in diabetic rats. These results highlight the therapeutic potential of the P. sanguineus extract, which provides a new possibility for development of drugs to control hyperlipidaemia and provides impetus for further studies.
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Kang, Peter K.,Dentz, Marco,Le Borgne, Tanguy,Lee, Seunghak,Juanes, Ruben C.M.L. Publications 2017 ADVANCES IN WATER RESOURCES Vol.106 No.-
<P><B>Abstract</B></P> <P>We investigate tracer transport on random discrete fracture networks that are characterized by the statistics of the fracture geometry and hydraulic conductivity. While it is well known that tracer transport through fractured media can be anomalous and particle injection modes can have major impact on dispersion, the incorporation of injection modes into effective transport modeling has remained an open issue. The fundamental reason behind this challenge is that—even if the Eulerian fluid velocity is steady—the Lagrangian velocity distribution experienced by tracer particles evolves with time from its initial distribution, which is dictated by the injection mode, to a stationary velocity distribution. We quantify this evolution by a Markov model for particle velocities that are equidistantly sampled along trajectories. This stochastic approach allows for the systematic incorporation of the initial velocity distribution and quantifies the interplay between velocity distribution and spatial and temporal correlation. The proposed spatial Markov model is characterized by the initial velocity distribution, which is determined by the particle injection mode, the stationary Lagrangian velocity distribution, which is derived from the Eulerian velocity distribution, and the spatial velocity correlation length, which is related to the characteristic fracture length. This effective model leads to a time-domain random walk for the evolution of particle positions and velocities, whose joint distribution follows a Boltzmann equation. Finally, we demonstrate that the proposed model can successfully predict anomalous transport through discrete fracture networks with different levels of heterogeneity and arbitrary tracer injection modes.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Injection modes have major impact on anomalous transport in DFNs. </LI> <LI> Evolution of the Lagrangian velocity distribution is governed by injection modes. </LI> <LI> Spatial velocity Markov model for variable injection modes. </LI> <LI> Equivalence between spatial Markov model and Boltzmann equation. </LI> </UL> </P>
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