• The Journal of the Korean bone and joint tumor society
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• v.4 no.1
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• pp.13-21
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• 1998

Taxol, the extract from the Taxus brevifolia which is a Pacific yew tree has aroused the interest of the tumor investigators since the 1960s. As well, it is shown to have broad antitumor activity in preclinical experimental models. Its action mechanism is an anti-microtubule effect by duplication of tubulin. The most impressive antitumor activity of taxol has been observed in advanced ovarian cancer and metastatic breast cancer. The purpose of this study was to determine how taxol acts on malignant bone tumor cell lines, to compare its cytotoxic effect with those of other chemotherapeutic agents, and to ascertain the its combination effect with adriamycin. Cell lines used in this study were G-292(osteosarcoma, human), SaOS-2(osteosarcoma, primary, human), and HT-1080(fibrosarcoma, human). Methotrexate, adriamycin, cisplatinum, ifosfamide and taxol were used as testing chemotherapeutic agents and their maximum test concentration were $500{\mu}g/ml$, $200{\mu}g/ml$, $500{\mu}g/ml$, $1000{\mu}g/ml$, and $600{\mu}g/ml$, respectively. The media for cell culture was RPMI-1640 with 10% fetal bovine serum and gentamycin. The results were as follows. The $IC_{50}$ of methotrexate, ifosfamide, cisplatinum, adriamycin and Taxol in G-292 were $2.3{\times}10^{-1}{\mu}g/ml$, $8.0{\times}10^0{\mu}g/ml$, $3.5{\times}10^0{\mu}g/ml$, $9.8{\times}10^{-1}{\mu}g/ml$, $2.7{\times}10^{-2}{\mu}g/ml$ respectively, in SaOS-2 $3.5{\times}10^{-1}{\mu}g/ml$, $1.5{\times}10^1{\mu}g/ml$, $2.8{\times}10^0{\mu}g/ml$, $9.9{\times}10^{-2}{\mu}g/ml$, $1.0{\times}10^{-2}{\mu}g/ml$, respectively, in HT-1080 $4.2{\times}10^{-2}{\mu}g/ml$, $5.4{\times}10^1{\mu}g/ml$, $3.8{\times}10^0{\mu}g/ml$, $5.5{\times}10^{-3}{\mu}g/ml$, $1.1{\times}10^{-3}{\mu}g/ml$, respectively. In conclusion, taxol had very potent cytotoxic effect on the malignant bone tumor cell lines with adriamycin, and was more potent than methotrexate, cisplatinum and ifosfamide. There were synergistic antitumor effects on G-292 and SaOS-2 cell lines in combination test of taxol and adriamycin. From the above results, it would be estimated that taxol could be a new antitumor drug for the malignant bone tumors, providing measures against the side effects and followed by the clinical tests.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.19-33
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• 2013

In this research, a proposed Dynamic Virtual Ontology using Tags (DyVOT) supports dynamic search of resources depending on user's requirements using tags from social web driven resources. It is general that the tags are defined by annotations of a series of described words by social users who usually tags social information resources such as web-page, images, u-tube, videos, etc. Therefore, tags are characterized and mirrored by information resources. Therefore, it is possible for tags as meta-data to match into some resources. Consequently, we can extract semantic relationships between tags owing to the dependency of relationships between tags as representatives of resources. However, to do this, there is limitation because there are allophonic synonym and homonym among tags that are usually marked by a series of words. Thus, research related to folksonomies using tags have been applied to classification of words by semantic-based allophonic synonym. In addition, some research are focusing on clustering and/or classification of resources by semantic-based relationships among tags. In spite of, there also is limitation of these research because these are focusing on semantic-based hyper/hypo relationships or clustering among tags without consideration of conceptual associative relationships between classified or clustered groups. It makes difficulty to effective searching resources depending on user requirements. In this research, the proposed DyVOT uses tags and constructs ontologyfor effective search. We assumed that tags are extracted from user requirements, which are used to construct multi sub-ontology as combinations of tags that are composed of a part of the tags or all. In addition, the proposed DyVOT constructs ontology which is based on hierarchical and associative relationships among tags for effective search of a solution. The ontology is composed of static- and dynamic-ontology. The static-ontology defines semantic-based hierarchical hyper/hypo relationships among tags as in (http://semanticcloud.sandra-siegel.de/) with a tree structure. From the static-ontology, the DyVOT extracts multi sub-ontology using multi sub-tag which are constructed by parts of tags. Finally, sub-ontology are constructed by hierarchy paths which contain the sub-tag. To create dynamic-ontology by the proposed DyVOT, it is necessary to define associative relationships among multi sub-ontology that are extracted from hierarchical relationships of static-ontology. The associative relationship is defined by shared resources between tags which are linked by multi sub-ontology. The association is measured by the degree of shared resources that are allocated into the tags of sub-ontology. If the value of association is larger than threshold value, then associative relationship among tags is newly created. The associative relationships are used to merge and construct new hierarchy the multi sub-ontology. To construct dynamic-ontology, it is essential to defined new class which is linked by two more sub-ontology, which is generated by merged tags which are highly associative by proving using shared resources. Thereby, the class is applied to generate new hierarchy with extracted multi sub-ontology to create a dynamic-ontology. The new class is settle down on the ontology. So, the newly created class needs to be belong to the dynamic-ontology. So, the class used to new hyper/hypo hierarchy relationship between the class and tags which are linked to multi sub-ontology. At last, DyVOT is developed by newly defined associative relationships which are extracted from hierarchical relationships among tags. Resources are matched into the DyVOT which narrows down search boundary and shrinks the search paths. Finally, we can create the DyVOT using the newly defined associative relationships. While static data catalog (Dean and Ghemawat, 2004; 2008) statically searches resources depending on user requirements, the proposed DyVOT dynamically searches resources using multi sub-ontology by parallel processing. In this light, the DyVOT supports improvement of correctness and agility of search and decreasing of search effort by reduction of search path.