摘要
利用拉曼光镊并结合多元统计分析方法无损地对活体糖尿病(DM)小鼠中的白细胞(WBC)进行了研究,分别检测了糖尿病和正常小鼠活体中的白细胞拉曼光谱,利用主成分分析(PCA)建立拉曼光谱诊断多元统计算法模型。结果表明,患糖尿病小鼠和正常小鼠白细胞拉曼光谱差别明显,且实验存在较好的重现性。利用PCA统计分析方法得到诊断特异性和灵敏度达到了98%。在活体糖尿病小鼠白细胞中出现较高的蛋白质的特征峰1302cm-1,表明活体糖尿病白细胞中的蛋白质浓度比正常状态高。糖尿病小鼠内的白细胞与正常相比,DNA磷酸骨架基团强度和蛋白质酰胺强度升高,表明DNA双螺旋结构、蛋白质主链和氢键体系发生变化,二级构象改变。
Raman spectra of normal white blood cell （WBC） and diabetes mellitus （DM） WBC in vivo are studied by laser tweezers combined with multivariate statistic analysis method. Raman spectrum and multivariate statistic model is founded by the principal components analysis （PCA）. The result of Raman spectrum suggests that DM WBC and normal WBC could be differentiated with PCA. Diagnostic specificity and sensitivity are nearly 98%. The protein vibration bands at 1302 cm-1 in DM WBC mouse in vivo show that the concentration of protein in DM WBC is higher than normal WBC. The Raman intensities at O-P-O of DNA and amide bands of DM cell are significantly higher than normal cell, which shows that the changes in the comformation of O-P-O and the backbone and hydrogen bonds of protein, as well as the second comformation of protein.
出处
《激光与光电子学进展》
CSCD
北大核心
2012年第6期174-179,共6页
Laser & Optoelectronics Progress
基金
国家自然科学基金(60868002、31060128)
广西自然科学基金(桂科回0731013,2011GXNSFA018143)
广西研究生创新项目基金(201106020702M40)资助课题
关键词
光谱学
拉曼光谱
糖尿病
白细胞
主成分分析
活体
spectroscopy
Raman spectrum
diabetes mellitus
white blood cell
principal component analysis
in vivo
