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研究生:呂慧歆
研究生(外文):Hui-Hsin Lu
論文名稱:表面增強拉曼散射定量生物分子分析
論文名稱(外文):Surface Enhanced Raman Scattering Quantitative Analysis on Biomolecule
指導教授:江惠華江惠華引用關係
指導教授(外文):Huihua Kenny Chiang
學位類別:碩士
校院名稱:國立陽明大學
系所名稱:醫學工程研究所
學門:工程學門
學類:生醫工程學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:中文
論文頁數:86
中文關鍵詞:表面增強拉曼散射奈米金屬粒子肌酸酐
外文關鍵詞:SERSmetal nanoparticlecreatinine
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本論文研究發展表面增強拉曼散射(Surface-enhanced Raman Scattering, SERS)光譜技術對人體體液所含的生化分子-肌酐酸、尿酸進行定性與定量分析。表面增強拉曼活性物質(SERS-active substrates)是使用奈米膠體金粒子(colloidal gold particles)與銀奈米粒子的溶膠凝膠(silver doped sol-gel)。
人體體液的成分含有可用作評估健康情形和疾病診斷的重要資訊。倘若,使用光學技術檢測可以提供許多優點,包括較少的樣本接觸以及同時可提供多種分析物質的訊息。我們採用體液中,為非侵入式且最易取得的尿液,使用SERS的技術,進行成分的定性與定量分析。
實驗結果顯示使用拉曼光譜技術檢測尿液成分物質的濃度具有相當高的線性關係,相關係數(R)為0.99;使用SERS技術可測得混合樣本(urine control)的肌酐酸生理濃度並進行定量分析,其SERS光譜在1400cm-1到1500cm-1強度與濃度的相關係數(R)為0.99。在真實世界的應用,我們收集10個健康成人的尿液,使用部分最小平方(PLS)法分析其SERS光譜進行肌酸酐濃度的預測,方均根誤差為26.1mg/dl,PLS預測濃度與參考濃度的相關係數(R)初步達0.93。由本研究可以得知表面增強拉曼散射技術在作為檢測人體體液的生物分子具有良好的潛力。
In this thesis, we investigated the use of surface-enhanced Raman scattering technique as the tool to quantify some biomolecules in human bodily fluid. SERS-active substrates in our research are colloidal gold and silver-doped sol-gel, which contain metal nanoparticles.
The components of bodily fluid provide the important information of healthy state and disease diagnosis. Urine is easily available and non-invasive to evaluate the health of human body. Compared with regular clinical chemical urinalysis, optical methods have some spectacular features, including less specimen contact, non-destructive specimen and multiple components analysis. We develop SERS-technique to detect the biomolecule of human urine.
In the present initial investigation, the nitrogen compounds in urine can be detected by using normal Raman spectroscopic method. The creatinine and uric acid in urine can be detected by SERS method. For the mixture sample, the correlation coefficient (R) between the creatinine concentration and SERS band intensity was found to 0.99. For human subject analysis, ten normal human urine samples were analyzed by the SERS technique. Partial least square cross-validation (PLSCV) method was utilized to obtain the estimated creatinine concentration in clinically relevant (55.9mg/dl to 208mg/dl) concentration range. The correlation coefficient (R) between reference concentration and PLS predicted concentration was 0.93 and the root-mean square error of cross validation (RMSECV) is 26.1mg/dl.This research demonstrates the feasibility of using SERS for human subject urine creatinine detection, and establishes the SERS platform technique for bodily fluids measurement.
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