• Journal of Ginseng Research
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• v.47 no.3
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• pp.408-419
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• 2023

Background: Ginsenoside compound K (CK), the main active metabolite in Panax ginseng, has shown good safety and bioavailability in clinical trials and exerts neuroprotective effects in cerebral ischemic stroke. However, its potential role in the prevention of cerebral ischemia/reperfusion (I/R) injury remains unclear. Our study aimed to investigate the molecular mechanism of ginsenoside CK against cerebral I/R injury. Methods: We used a combination of in vitro and in vivo models, including oxygen and glucose deprivation/reperfusion induced PC12 cell model and middle cerebral artery occlusion/reperfusion induced rat model, to mimic I/R injury. Intracellular oxygen consumption and extracellular acidification rate were analyzed by Seahorse multifunctional energy metabolism system; ATP production was detected by luciferase method. The number and size of mitochondria were analyzed by transmission electron microscopy and MitoTracker probe combined with confocal laser microscopy. The potential mechanisms of ginsenoside CK on mitochondrial dynamics and bioenergy were evaluated by RNA interference, pharmacological antagonism combined with co-immunoprecipitation analysis and phenotypic analysis. Results: Ginsenoside CK pretreatment could attenuate mitochondrial translocation of DRP1, mitophagy, mitochondrial apoptosis, and neuronal bioenergy imbalance against cerebral I/R injury in both in vitro and in vivo models. Our data also confirmed that ginsenoside CK administration could reduce the binding affinity of Mul1 and Mfn2 to inhibit the ubiquitination and degradation of Mfn2, thereby elevating the protein level of Mfn2 in cerebral I/R injury. Conclusion: These data provide evidence that ginsenoside CK may be a promising therapeutic agent against cerebral I/R injury via Mul1/Mfn2 mediated mitochondrial dynamics and bioenergy.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.529-535
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• 2015

Biological networks have been handled with the static concept. However, life phenomena in cells occur depending on the cellular state and the external environment, and only a few proteins and their interactions are selectively activated. Therefore, we should adopt the dynamic network concept that the structure of a biological network varies along the flow of time. This concept is effective to analyze the progressive transition of the disease. In this paper, we applied the proposed method to Alzheimer's disease to analyze the structural and functional characteristics of the disease network. Using gene expression data and protein-protein interaction data, we constructed the sub-networks in accordance with the progress of disease (normal, early, middle and late). Based on this, we analyzed structural properties of the network. Furthermore, we found module structures in the network to analyze the functional properties of the sub-networks using the gene ontology analysis (GO). As a result, it was shown that the functional characteristics of the dynamics network is well compatible with the stage of the disease which shows that it can be used to describe important biological events of the disease. Via the proposed approach, it is possible to observe the molecular network change involved in the disease progression which is not generally investigated, and to understand the pathogenesis and progression mechanism of the disease at a molecular level.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.3
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• pp.137-145
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• 2014

We present a design sensitivity analysis(DSA) method for multiscale problems based on bridging scale decomposition. In this paper, we utilize a bridging scale method for the coupled system analysis. Since the analysis of full MD systems requires huge amount of computational costs, a coupled system of MD-level and continuum-level simulation is usually preferred. The information exchange between the MD and continuum levels is taken place at the MD-continuum boundary. In the bridging scale method, a generalized Langevin equation(GLE) is introduced for the reduced MD system and the GLE force using a time history kernel is applied at the boundary atoms in the MD system. Therefore, we can separately analyze the MD and continuum level simulations, which can accelerate the computing process. Once the simulation of coupled problems is successful, the need for the DSA is naturally arising for the optimization of macro-scale design, where the macro scale performance of the system is maximized considering the micro scale effects. The finite difference sensitivity is impractical for the gradient based optimization of large scale problems due to the restriction of computing costs but the analytical sensitivity for the coupled system is always accurate. In this study, we derive the analytical design sensitivity to verify the accuracy and applicability to the design optimization of the coupled system.

• Bulletin of the Korean Chemical Society
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• v.7 no.5
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• pp.367-371
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• 1986

Dynamic and equilibrium properties of n-alkane chains immersed in solvent molecules have been investigated by a molecular dynamics method. The n-alkane chain is assumed to be a chain of elements (CH$_2$) interconnected by bonds having a fixed bond length and bond angle, but each bond of the chain is allowed to execute hindered internal rotation. We studied the effect of the number of the chain elements (N$_c$ = 10, 15 and 20) on the equilibrium properties of the system, e.g., the pair correlation functions between a chain element and solvent molecules, g$_{cs}$(r), and between the chain elements, g$_{cc}$(r), and the configurational properties such as the mean-square end-to-end distance < R$^2$ >, the mean-square radius of gyration < S$^2$ >, and the eigenvalues of the moment-of-inertia tensor < S$_i^2$ > / < S$^2$ > (i = 1, 2 and 3). We also studied the dynamic properties of the system, e.g., the autocorrelation function C(A;t) where A = R$^2$(t), = S$^2$(t), or = ${\vec{V}}(t)({\vec{V}}$ = velocity of the center of mass), and the diffusion coefficient D. The g$_{cs}$(r)'s are almost equal irrespective of the change of Nc while g$_{cc}$(r) becomes larger as N$_c$ increases; The MD computed configurational properties < R$^2$2 > and < S$^2$ > were found to be a little different from the values calculated from the statistical equations of < R$^2$ > and < S$^2$ >, it may be due to the fact that our model for the MD simulations includes a long-range volume effect. From the < S$_i^2$ > / < S$^2$ >, it is found that the chain molecule has a nearly spherical shape irrespective of the variation of N$_c$. For the dynamic properties we found that the C(R$^2$;t) and C(S$^2$;t) of lower N$_c$ decay faster than those of higher N$_c$, while the C($\vec V$;t) of the center of mass in the chain is weakly dependent on the N$_c$. The center of mass diffusion coefficient D$_c$ decreases as N$_c$ increases while the end point diffusion coefficient D$_e$ is nearly equal irrespective of the change of N$_c$.