Analysis of serum from type II diabetes mellitus and diabetic complication using surface-enhanced Raman spectra (SERS)

Hong-wen, Han; Yan, Xinhui; Dong, Ruixin; Ban, G.; Li, K.

doi:10.1007/s00340-008-3299-5

Cited by 74 publications

(66 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…SERS spectra of blood plasma are dominated by many vibrational modes of various biomolecules, such as proteins, lipids and nucleic acids, which may change in quantity or conformation associated with neoplastic transformation. To better understand the molecular basis for the observed SERS spectra of human plasma, Table 1 lists tentative assignments for the observed SERS bands, according to data from the literature [33][34][35][36][37][38][39]. For example, the SERS peak at 1338 cm −1 due to the C-H vibration of nucleic acid bases exhibited a higher signal in cancer plasma, indicating an increase in the percentage of the nucleic acid bases content relative to the total SERSactive components in the plasma of gastric cancer patients.…”

Section: Discussionmentioning

confidence: 99%

Study on gastric cancer blood plasma based on surface-enhanced Raman spectroscopy combined with multivariate analysis

Feng

Pan

et al. 2011

Sci. China Life Sci.

View full text Add to dashboard Cite

A surface-enhanced Raman spectroscopy (SERS) method combined with multivariate analysis was developed for non-invasive gastric cancer detection. SERS measurements were performed on two groups of blood plasma samples: one group from 32 gastric patients and the other group from 33 healthy volunteers. Tentative assignments of the Raman bands in the measured SERS spectra suggest interesting cancer-specific biomolecular changes, including an increase in the relative amounts of nucleic acid, collagen, phospholipids and phenylalanine and a decrease in the percentage of amino acids and saccharide in the blood plasma of gastric cancer patients as compared with those of healthy subjects. Principal components analysis (PCA) and linear discriminant analysis (LDA) were employed to develop effective diagnostic algorithms for classification of SERS spectra between normal and cancer plasma with high sensitivity (79.5%) and specificity (91%). A receiver operating characteristic (ROC) curve was employed to assess the accuracy of diagnostic algorithms based on PCA-LDA. The results from this exploratory study demonstrate that SERS plasma analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of gastric cancers.

show abstract

Section: Discussionmentioning

confidence: 99%

Study on gastric cancer blood plasma based on surface-enhanced Raman spectroscopy combined with multivariate analysis

Feng

Pan

et al. 2011

Sci. China Life Sci.

View full text Add to dashboard Cite

show abstract

“…4 For diabetes diagnosis, Han et al 5 used RS to analyze the serum of diabetic patients and Barman et al 6 used it to detect the glycated hemoglobin in hemolysate model formed by twocomponent mixture (Hb and HbA1c). To the best of our knowledge, there is no report on using RS of human hemoglobin -a multicomponent mixture -for diabetes detection.…”

Section: Introductionmentioning

confidence: 99%

Raman Spectroscopy of Human Hemoglobin for Diabetes Detection

Lin

Huang

et al. 2014

J. Innov. Opt. Health Sci.

View full text Add to dashboard Cite

Glycated hemoglobin (HbA1c) has been increasingly accepted as the gold standard for diabetes monitoring. In this study, Raman spectroscopy was tentatively employed for human hemoglobin (Hb) biochemical analysis aimed at developing a simple blood test for diabetes monitoring. Raman spectroscopy measurements were performed on hemoglobin samples of patients (n ¼ 39) with con¯rmed diabetes and healthy volunteers (n ¼ 37). The tentative assignments of the measured Raman bands were performed to compare the di®erence between these two groups. Meanwhile, principal component analysis (PCA) combined with linear discriminant analysis (LDA) were employed to develop e®ective diagnostic algorithms for classi¯cation between normal controls and patients with diabetes. As a result, the spectral features of these two groups demonstrated two distinct clusters with a sensitivity and speci¯city of 92.3% and 73%, respectively. Then the e®ec-tiveness of the diagnostic algorithm based on PCA-LDA technique was con¯rmed by receiver operating characteristic (ROC) curve. The area under the ROC curve was 0.92, indicating a good diagnostic result. In summary, our preliminary results demonstrate that proposing Raman spectroscopy can provide a signi¯cant potential for the noninvasive detection of diabetes.

show abstract

“…17,18 SERS is especially attractive for application in cancer diagnosis and evaluation utilizing human biological samples such as blood, 19 tissues, 20 cells, 21 and serum. 22 As a potential diagnostic media for disease detection, saliva offers main advantages over blood due to the easy and noninvasive sample collection, which eliminates any feelings of pain and discomfort during the process of blood collection. In addition, human saliva contains a rich variety of proteins that may carry several significant biological functions, rendering saliva protein an attractive source of disease biomarkers.…”

mentioning

confidence: 99%

Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors

Feng¹,

Huang²,

Lin³

et al. 2015

IJN

112

View full text Add to dashboard Cite

The capability of saliva protein analysis, based on membrane protein purification and surface-enhanced Raman spectroscopy (SERS), for detecting benign and malignant breast tumors is presented in this paper. A total of 97 SERS spectra from purified saliva proteins were acquired from samples obtained from three groups: 33 healthy subjects; 33 patients with benign breast tumors; and 31 patients with malignant breast tumors. Subtle but discernible changes in the mean SERS spectra of the three groups were observed. Tentative assignments of the saliva protein SERS spectra demonstrated that benign and malignant breast tumors led to several specific biomolecular changes of the saliva proteins. Multiclass partial least squares–discriminant analysis was utilized to analyze and classify the saliva protein SERS spectra from healthy subjects, benign breast tumor patients, and malignant breast tumor patients, yielding diagnostic sensitivities of 75.75%, 72.73%, and 74.19%, as well as specificities of 93.75%, 81.25%, and 86.36%, respectively. The results from this exploratory work demonstrate that saliva protein SERS analysis combined with partial least squares–discriminant analysis diagnostic algorithms has great potential for the noninvasive and label-free detection of breast cancer.

show abstract

Analysis of serum from type II diabetes mellitus and diabetic complication using surface-enhanced Raman spectra (SERS)

Cited by 74 publications

References 20 publications

Study on gastric cancer blood plasma based on surface-enhanced Raman spectroscopy combined with multivariate analysis

Study on gastric cancer blood plasma based on surface-enhanced Raman spectroscopy combined with multivariate analysis

Raman Spectroscopy of Human Hemoglobin for Diabetes Detection

Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors

Contact Info

Product

Resources

About