| Project/Area Number |
13650850
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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 |
生物・生体工学
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| Research Institution | Kyushu Institute of Technology |
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Principal Investigator |
HARUYAMA Tetsuya Kyushu Institute of technology, Department of Biological Functions and Enineering, Professor, 大学院・生命体工学研究科, 教授 (30251656)
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| Project Period (FY) |
2001 – 2002
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| Project Status |
Completed (Fiscal Year 2002)
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| Budget Amount *help |
¥3,800,000 (Direct Cost: ¥3,800,000)
Fiscal Year 2002: ¥1,600,000 (Direct Cost: ¥1,600,000)
Fiscal Year 2001: ¥2,200,000 (Direct Cost: ¥2,200,000)
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| Keywords | BIO CHIP / SINGLE MOLECULAR / MOLECULAR ORIENTATION / PROTEIN CHIP / ELECTROCHEMISTRY / IMMOBILIZED PROTEIN / タンパク質 / 固定化 / 電気化学的 |
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| Research Abstract |
Cells represent the minimum functional and integrating communicable unit of living system. Cultured cells both transduce and transmit a variety of chemical and physical signals, I.e., production of specific substances and proteins, throughout their life cycle within specific tissues and organs. Such cellular responses might be usefully employed as parameters to obtain chemical information for both pharmaceutical and chemical safety, and drug efficacy profiles in vitro as a screening tool. However, such cellular signals are very weak and not easily detected with conventional analytical methods. By using micro-and nanobiotechnology methods integrated on-chip, a higher sensitivity and signal amplification has been developed for cellular biosensing. Micro- and nanotechology is rapidly evolving to open new combinations of methods with improved technical performance, helping to resolve challenging bioanalytical problems including sensitivity, signal resolution and specificity by interfacing these technologies in small volumes in order to confirm specific cellular signals. Integration of cell signals in both rapid time and small space, and importantly, between different cell populations (communication and systems modeling) will permit many more valuable measurements of the dynamic aspects of cell responses to various chosen stimuli and their feedback. This represents the future for cell-based biosensing.
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