• 대한예방한의학회지
• /
• 제16권2호
• /
• pp.113-124
• /
• 2012

The oxidative modification of low density lipoprotein(LDL) has been implicated in the development of atherosclerosis. Oxidized LDL(oxLDL) is captured into macrophage and stimulates to form macrophage foam cell. And it can induce an inflammation and smooth muscle proliferation in atherosclerotic plaque. Objective : In this study, we aimed to investigate the effect of Bupleuri radix(SH) on the foam cell formation, a critical initiation stage of atherosclerosis. Methods : To achieve the goal, we examined the effect of SH on LDL oxidation, nitric oxide production in RAW264.7, and the effect of SH on cupuric sulfate-induced cytotoxicity, LDH release, and macrophage activity. Results : SH inhibited the formation of oxidized LDL from native LDL in RAW264.7 cell culture, and decreased the release of LDH from cupric sulfate-stimulated RAW264.7 cell. In other experiments, SH activated RAW264.7 cell, and prolonged the survival time, and inhibited foam cell formation induced by oxLDL in Raw 264.7 cells. Conclusion : These results showed that SH might prevent atherosclerosis by controlling the early stages of foam cell formation.

• 산업경영시스템학회지
• /
• 제27권3호
• /
• pp.106-112
• /
• 2004

This paper presents a new heuristic algorithm for the machine cell(MC) formation problem. MC formation problem is represented as an unbalanced k-way network partition and the proposed algorithm uses four stage-approach to solve the problem. Four stages are natural sub-network formation, determination of intial vertexes for each sub-network, determination of initial partition, and improvement of initial partition. Results of experiments show that the suggested algorithm provides near optimal solutions within very short computational time.

• Preventive Nutrition and Food Science
• /
• 제19권4호
• /
• pp.299-306
• /
• 2014

Hesperetin has been shown to possess a potential anti-angiogenic effect, including vascular formation by endothelial cells. However, the mechanisms underlying the potential anti-angiogenic activity of hesperetin are not fully understood. In the present study, we evaluated whether hesperetin has anti-angiogenic effects in human umbilical vascular endothelial cells (HUVECs). HUVECs were treated with 50 ng/mL vascular endothelial growth factor (VEGF) to induce proliferation as well as vascular formation, followed by treatment with several doses of hesperetin (25, 50, and $100{\mu}M$) for 24 h. Cell proliferation and vascular formation were analyzed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide and tube formation assay, respectively. In addition, cell signaling related to cell proliferation and vascular formation was analyzed by western blot. Furthermore, a mouse aorta ring assay was performed to confirm the effect of hesperetin on vascular formation. Hesperetin treatment did not cause differences in HUVECs proliferation. However, hesperetin significantly inhibited VEGF-induced cell migration and tube formation of HUVECs (P<0.05). Moreover, hesperetin suppressed the expression of ERK, p38 MAPK, and PI3K/AKT in the VEGF-induced HUVECs. In an ex vivo model, hesperetin also suppressed microvessel sprouting of mouse aortic rings. Taken together, the findings suggest that hesperetin inhibited vascular formation by endothelial cells via the inhibition of the PI3K/AKT, ERK and p38 MAPK signaling.

• 산업경영시스템학회지
• /
• 제23권61호
• /
• pp.41-50
• /
• 2000

Cell formation(CF) Is to group parts with similar geometry, function, material and process into part families, and the corresponding machines into machine cells. Cell formation solutions often contain exceptional elements(EEs). Also, the following objective functions - minimizing the total costs of dealing with exceptional elements and maximizing total similarity coefficients between parts - have been used in CF modeling. Thus, multiobjective programming approach can be developed to model cell formation problems with two conflicting objective functions. This paper presents an effective cell formation method with fuzzy multiobjective nonlinear mixed-integer programming simultaneously to form machine cells and to minimize the cost of eliminating EEs.

• Journal of Mechanical Science and Technology
• /
• 제18권12호
• /
• pp.2137-2147
• /
• 2004

The recycling cell formation problem means that disposal products are classified into recycling part families using group technology in their end-of-life phase. Disposal products have the uncertainties of product status by usage influences during product use phase, and recycling cells are formed design, process and usage attributes. In order to deal with the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem for disposal products. Fuzzy C-mean algorithm and a heuristic approach based on fuzzy ART neural network is suggested. Especially, the modified Fuzzy ART neural network is shown that it has a good clustering results and gives an extension for systematically generating alternative solutions in the recycling cell formation problem. Disposal refrigerators are shown as examples.

• 산업경영시스템학회지
• /
• 제26권4호
• /
• pp.31-41
• /
• 2003

This paper deals with a cell formation problem for a set of m-machines and n-processing parts. Generally, a cell formation problem is known as NP-completeness. Hence the cell formation problem with multiple objectives is more difficult than single objective problem. The paper considers multiple objectives; minimize number of intercell movements, minimize intracell workload variation and minimize intercell workload variation. We propose a multiple objective genetic algorithms(MOGA) resolving the mentioned three objectives. The MOGA procedure adopted Pareto optimal solution for selection method for next generation and the concept of Euclidean distance from the ideal and negative ideal solution for fitness test of a individual. As we consider several weights, decision maker will be reflected his consideration by adjusting high weights for important objective. A numerical example is given for a comparative analysis with the results of other research.

• 산업경영시스템학회지
• /
• 제36권1호
• /
• pp.24-35
• /
• 2013

A cell formation approach based on cluster analysis is developed for the configuration of manufacturing cells. Cell formation, which is to group machines and parts into machine cells and the associated part families, is implemented to add the flexibility and efficiency to manufacturing systems. In order to develop an efficient clustering procedure, this paper proposes a cluster analysis-based approach developed by incorporating and modifying two cluster analysis methods, a hierarchical clustering and a non-hierarchical clustering method. The objective of the proposed approach is to minimize intercellular movements and maximize the machine utilization within clusters. The proposed approach is tested on the cell formation problems and is compared with other well-known methodologies available in the literature. The result shows that the proposed approach is efficient enough to yield a good quality solution no matter what the difficulty of data sets is, ill or well-structured.

• Molecules and Cells
• /
• 제27권4호
• /
• pp.491-492
• /
• 2009

We present the result of our research on the tumorigenic ability of single cell clones isolated from an aggressive murine breast cancer cell line in a matched allografting mouse model. Tumor formation is basically dependent on the cell numbers injected per location. We argue that in vivo tumor formation from single cell clones, isolated in vitro from cancer cell lines, may not provide conclusive evidence to disprove the cancer stem cell (CSC) theory without additional data.

• 대한안전경영과학회지
• /
• 제6권2호
• /
• pp.187-197
• /
• 2004

The recycling cell formation problem means that disposal products are classified into recycling product families using group technology in their end-of-life phase. Disposal products have the uncertainties of product condition usage influences. Recycling cells are formed considering design, process and usage attributes. In this paper, a new approach for the design of cellular recycling system is proposed, which deals with the recycling cell formation and assignment of identical products concurrently. Fuzzy ART neural networks are applied to describe the condition of disposal product with the membership functions and to make recycling cell formation. The approach leads to cluster materials, components, and subassemblies for reuse or recycling and can evaluate the value at each cell of disposal products. Disposal refrigerators are shown as an example.

• 경영과학
• /
• 제16권1호
• /
• pp.157-171
• /
• 1999

In a increasingly competitive marketplace, the manufacturing companies have no choice but looking for ways to improve productivity to sustain their competitiveness and survive in the industry. Recently cellular manufacturing has been under discussion as an option to be easily implemented without burdensome capital investment. The objective of cellular manufacturing is to realize many aspects of efficiencies associated with mass production in the less repetitive job-shop production systems. The very first step for cellular manufacturing is to group the sets of parts having similar processing requirements into part families, and the equipment needed to process a particular part family into machine cells. The underlying problem to determine the part and machine assignments to each manufacturing cell is called the cell formation. The purpose of this study is to develop a clustering algorithm based on the neural network approach which overcomes the drawbacks of ART1 algorithm for cell formation problems. In this paper, a generalized learning vector quantization(GLVQ) algorithm was devised in order to transform a 0/1 part-machine assignment matrix into the matrix with diagonal blocks in such a way to increase clustering performance. Furthermore, an assignment problem model and a rearrangement procedure has been embedded to increase efficiency. The performance of the proposed algorithm has been evaluated using data sets adopted by prior studies on cell formation. The proposed algorithm dominates almost all the cell formation reported so far, based on the grouping index($\alpha$ = 0.2). Among 27 cell formation problems investigated, the result by the proposed algorithm was superior in 11, equal 15, and inferior only in 1.