| Project/Area Number |
11672226
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Environmental pharmacy
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| Research Institution | Osaka University |
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Principal Investigator |
TANI Katsuji Graduate School of Pharmaceutical Sciences, Osaka University Lecturer, 薬学研究科, 講師 (50217113)
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| Co-Investigator(Kenkyū-buntansha) |
NASU Masao Graduate School of Pharmaceutical Sciences, Osaka University Professor, 薬学研究科, 教授 (90218040)
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| Project Period (FY) |
1999 – 2000
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| Project Status |
Completed (Fiscal Year 2000)
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| Budget Amount *help |
¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2000: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Keywords | image analyzing system / detection of bacterial cells / automation / fluorecent staining / rapidity / enumeration / convenience / low cost / 多重染色法 / 蛍光抗体法 / 蛍光in situハイブリダイゼーション / 活性染色法 / 特定細菌 / FITC / CTC / cy5 |
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| Research Abstract |
In order to prevent epidemics of infectious diseases and to maintain microbiological safety in pharmaceutical and food industry, we developed a system to detect microbes easily and rapidly. We optimized a direct count method with fluorescent staining, a fluorescent antibody method and a fluorescent in situ hybridization method to detect specific bacteria under fluorescent microscopy For the detection of physiologically active bacteria, double staining by CTC and DAPI were used.
This system was applied to specific detection of Escherichia coli O157 with physiological activity. Staining O157 first by CTC and have it reacted with anti O157 antibody labeled with FITC next allowed specific detection of physiologically active O157. E.coli with O157 antigen were also specifically detected by double staining with Cy3 labeled gene probe and with anti O157 antibody labeled with FITC.In order to apply the system routinely in the practical scenes, automation is essential. We developed software to analyze images acquired by a cooled CCD camera. Bacterial cells were automatically discriminated from other particles by image analysis with smoothing, secondary differential filing and edge detection. Bacterial number, morphological character, and fluorescent intensity of individual cells were obtained at the same time using this system. A user interface to enable the software to function as a comprehensive system easily used in everyday analysis was established.
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