Literature DB >> 26904817

[Red Blood Cells Raman Spectroscopy Comparison of Type Two Diabetes Patients and Rats].

Lei Wang, Gui-dong Liu, Xin Mu, Hong-bin Xiao, Chao Qi, Si-qi Zhang, Guang-kun Jiang, Yue-nan Feng, Jing-qi Bian.   

Abstract

By using confocal Raman spectroscopy, Raman spectra were measured in normal rat red blood cells, normal human red blood cells, STZ induced diabetetic rats red blood cells, Alloxan induced diabetetic rats red blood cells and human type 2 diabetes red blood cells. Then principal component analysis (PCA) with support vector machine (SVM) classifier was used for data analysis, and then the distance between classes was used to judge the degree of close to two kinds of rat model with type 2 diabetes. The results found significant differences in the Raman spectra of red blood cell in diabetic and normal red blood cells. To diabetic red blood cells, the peak in the amide VI C=O deformation vibration band is obvious, and amide V N-H deformation vibration band spectral lines appear deviation. Belong to phospholipid fatty acyl C-C skeleton, the 1 130 cm(-1) spectral line is enhanced and the 1 088 cm(-1) spectral line is abated, which show diabetes red cell membrane permeability increased. Raman spectra of PCA combined with SVM can well separate 5 types of red blood cells. Classifier test results show that the classification accuracy is up to 100%. Through the class distance between the two induced method and human type 2 diabetes, it is found that STZ induced model is more close to human type 2 diabetes. In conclusion, Raman spectroscopy can be used for diagnosis of diabetes and rats STZ induced diabetes method is closer to human type 2 diabetes.

Entities:  

Mesh:

Year:  2015        PMID: 26904817

Source DB:  PubMed          Journal:  Guang Pu Xue Yu Guang Pu Fen Xi        ISSN: 1000-0593            Impact factor:   0.589


  1 in total

1.  Raman characterizations of red blood cells with β-thalassemia using laser tweezers Raman spectroscopy.

Authors:  Wenguang Jia; Ping Chen; Wenqiang Chen; Yongqing Li
Journal:  Medicine (Baltimore)       Date:  2018-09       Impact factor: 1.889

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.