• Biomolecules & Therapeutics
• /
• v.31 no.3
• /
• pp.253-263
• /
• 2023

The biogenesis and biological roles of extracellular vesicles (EVs) in the progression of liver diseases have attracted considerable attention in recent years. EVs are membrane-bound nanosized vesicles found in different types of body fluids and contain various bioactive materials, including proteins, lipids, nucleic acids, and mitochondrial DNA. Based on their origin and biogenesis, EVs can be classified as apoptotic bodies, microvesicles, and exosomes. Among these, exosomes are the smallest EVs (30-150 nm in diameter), which play a significant role in cell-to-cell communication and epigenetic regulation. Moreover, exosomal content analysis can reveal the functional state of the parental cell. Therefore, exosomes can be applied to various purposes, including disease diagnosis and treatment, drug delivery, cell-free vaccines, and regenerative medicine. However, exosome-related research faces two major limitations: isolation of exosomes with high yield and purity and distinction of exosomes from other EVs (especially microvesicles). No standardized exosome isolation method has been established to date; however, various exosome isolation strategies have been proposed to investigate their biological roles. Exosome-mediated intercellular communications are known to be involved in alcoholic liver disease and nonalcoholic fatty liver disease development. Damaged hepatocytes or nonparenchymal cells release large numbers of exosomes that promote the progression of inflammation and fibrogenesis through interactions with neighboring cells. Exosomes are expected to provide insight on the progression of liver disease. Here, we review the biogenesis of exosomes, exosome isolation techniques, and biological roles of exosomes in alcoholic liver disease and nonalcoholic fatty liver disease.

• Proceedings of the Korean Radioactive Waste Society Conference
• /
• 2005.06a
• /
• pp.231-238
• /
• 2005

On the basis of flow resistance theory the conceptual model and related mathematical descriptions is proposed for resistance modeling of groundwater flow in CPM(continuum Porous medium), DFN(discrete fracture network) and fractured-porous medium. The proposed model is developed on the basis of finite volume method assuming steady-state, constant density groundwater flow. The basic approach of the method is to evaluate inter-block flow resistance values for a staggered grid arrangement, i.e. fluxes are stored at cell walls and scalars at cell centers. The balance of forces, i.e. the Darcy law, is utilized for each control volume centered around the point where the velocity component is stored. The transmissivity (or permeability) at the interface is assumed to be the harmonic average of neighboring blocks. Flow resistance theory was utilized to relate the fluxes between the grid blocks with residual pressures. The flow within porous medium is described by three dimensional equations and that within an individual fracture is described by a two dimensional equivalent of the flow equations for a porous medium. Newly proposed models would contribute to develop flow simulation techniques with various matrix characteristics.

• The KIPS Transactions:PartC
• /
• v.9C no.3
• /
• pp.385-398
• /
• 2002

To accommodate the increasing number of mobile terminals in the limited radio spectrum, wireless systems have been designed as micro/picocellular architectures for a higher capacity. This reduced coverage area of a cell has caused a higher rate of hand-off events, and the hand-off technology for efficient process becomes a necessity to provide a stable service. Population-based Bandwidth Reservation(PBR) Scheme is proposed to provide prioritized handling for hand-off calls by dynamically adjusting the amount of reserved bandwidth of a cell according to the amount of cellular traffic in its neighboring cells. We analyze the performance of the PBR scheme according to the changes of a fractional parameter, f, which is the ratio of request reservation to the total amount of bandwidth units required for hand-off calls that will occur for the next period. The vague of this parameter, f should be determined based on QoS(Quality of Service) requirement. To meet the requirement the value of Parameter(f) must be able to be adjusted dynamically according to the changing traffic conditions. The best value of f can be determined by a function of the average speed of mobile stations, average call duration, cell size, and so on. This paper considers the average call duration and the cell size according to the speed of mobile stations. Although some difference exists as per speed, in the range of 0.4 $\leq$ f $\leq$ 0.6, Blocking Probability, Dropping Probability and Utilization show the best values.