Surface-enhanced Raman spectroscopy (SERS) was employed to detect deoxyribose nucleic acid (DNA) variations associated with the development of nasopharyngeal carcinoma (NPC). Significant SERS spectral differences between the DNA extracted from early NPC, advanced NPC, and normal nasopharyngeal tissue specimens were observed at 678, 729, 788, 1337, 1421, 1506, and 1573 cm−1, which reflects the genetic variations in NPC. Principal component analysis combined with discriminant function analysis for early NPC discrimination yielded a diagnostic accuracy of 86.8%, 92.3%, and 87.9% for early NPC, advanced NPC, and normal nasopharyngeal tissue DNA, respectively. In this exploratory study, we demonstrated the potential of SERS for early detection of NPC based on the DNA molecular study of biopsy tissues.
Secreted proteins, the promising source of biomarkers for early detection and diagnosis of cancer, have received considerable attention. Raman spectroscopy and principal component analysis (PCA) were used to characterize the secreted proteins collected from the cell cultures of human hepatoma cell line HepG2 and normal human liver cell line LO2 in this paper. We found the major difference of secreted proteins Raman spectra between HepG2 and LO2 cells were in the range of 1200cm-1-1800cm-1. Compared with LO2 cells, some significant changes based on secondary structure of secreted proteins in HepG2 cells were observed, including the increase in the relative intensity of the band at 1004cm-1, 1445cm-1, 1674cm-1 and the decrease at 1074cm-1. These variations of Raman bands indicated that the species and conformation of secreted proteins in HepG2 cells changed. The measured Raman spectra of the two groups were separated into two distinct clusters with no overlap and high specificity and sensitivity by PCA. These results show that the combination of Raman spectroscopy and PCA analysis may be a powerful tool for distinguishing the secreted proteins between human hepatoma cells and normal human liver cells, provide a new thought to analyze the secreted proteins from cancer cells and find a novel cancer biomarker.
Gold nanoparticles are delivered into living cells by transient electroporation method to obtain intracellular surface-enhanced Raman spectroscopy (SERS). The subcellular localization of gold nanoparticles is characterized by transmission electron microscopy, and the forming large gold nanoaggregates are mostly found in the cytoplasm. The SERS detection of cells indicates that this kind of gold nanostructures induces a high signal enhancement of cellular chemical compositions, in addition to less cellular toxicity than that of silver nanoparticles. These results demonstrate that rapid incorporation of gold nanoparticles by electroporation into cells has great potential applications in the studies of cell biology and biomedicine.
Despite the introduction of high-technology methods of detection and diagnosis, screening of primary liver cancer (PLC) remains imperfect. To diagnosis PLC earlier, Surface-enhanced Raman spectroscopy (SERS) coupled with cellulose-acetate membrane electrophoresis were introduced to separate human serum albumin and SERS spectra. Three groups (15 normal persons’ samples, 17 hepatitis/cirrhosis samples, 15 cases of PLC) of serum albumin were tested. Silver colloid was used to obtain SERS spectra of human serum albumin. Principal component analysis (PCA) and linear discriminant analysis (LDA) were also employed for statistical analysis. The mean Raman spectra of three groups and the difference spectra of any two suggested that the albumin has changed in liver patients. Compared to normal groups, some Raman peaks have shifted or even disappeared in hepatitis/cirrhosis and PLCs groups. The sensitivity and specificity between PLCs and normal groups is 80% and 93.3%. Among hepatitis/cirrhosis and normal groups, the sensitivity is 88.2% and specificity is also 93.3%. Besides, the sensitivity and specificity between PLCs and hepatitis/cirrhosis groups is 86.7% and 76.5%. All the above data and results indicated that early screening of PLC is potential by SERS in different stages of liver disease before cancer occurs.
The use of normal Raman (NR) spectroscopy and surface enhanced Raman scattering (SERS) spectroscopy to analyze the biochemical information of human serum proteins and hence distinguish between normal and primary hepatic carcinoma (PHC) serum samples was investigated. The serum samples were obtained from patients who were clinically diagnosed with PHC (n=20) and healthy volunteers (n=20). All spectra were collected in the spectral range of 400-1800 cm-1 and analyzed through the multivariate statistical methods of principal component analysis (PCA). The results showed that both NR and SERS combined with PCA had good performance in distinguishing the human serum proteins between PHC patients and healthy volunteers with high sensitivity and specificity of 100%. And we can get more detail information of component and conformation of human serum proteins by considering NR and SERS spectrum. Our results support the concept again that serum protein Raman and SERS spectroscopy combined with PCA analysis both can become noninvasive and rapid diagnostic tools to detect the primary hepatic carcinoma.
KEYWORDS: Raman spectroscopy, Diagnostics, Remote sensing, Statistical analysis, Principal component analysis, Control systems, Analytical research, Medical research, Signal detection, Medicine
Raman spectroscopy is a rapidly non-invasive technique with great potential for biomedical research. The aim of this
study was to evaluate the feasibility of using Raman spectroscopy of human saliva for acute myocardial infarction (AMI)
detection. Raman spectroscopy measurements were performed on two groups of saliva samples: one group from patients
(n=30) with confirmed AMI and the other group from healthy controls (n=31). The diagnostic performance for
differentiating AMI saliva from normal saliva was evaluated by multivariate statistical analysis. The combination of
principal component analysis (PCA) and linear discriminate analysis (LDA) of the measured Raman spectra separated
the spectral features of the two groups into two distinct clusters with little overlaps, rendering the sensitivity of 80.0%
and specificity of 80.6%. The results from this exploratory study demonstrated that Raman spectroscopy of human saliva
can serve as a potentially clinical tool for rapid AMI detection and screening.
Surface-enhanced Raman scattering (SERS) spectroscopy combined with membrane electrophoresis (ME) was firstly employed to detect albumin variation in type II diabetic development. Albumin was first purified from human serum by ME and then mixed with silver nanoparticles to perform SERS spectral analysis. SERS spectra were obtained from blood albumin samples of 20 diabetic patients and 19 healthy volunteers. Subtle but discernible changes in the acquired mean spectra of the two groups were observed. Tentative assignment of albumin SERS bands indicated specific structural changes of albumin molecule with diabetic development. Meanwhile, PCA-LDA diagnostic algorithms were employed to classify the two kinds of albumin SERS spectra, yielding the diagnostic sensitivity of 90% and specificity of 94.7%. The results from this exploratory study demonstrated that the EM-SERS method in combination with multivariate statistical analysis has great potential for the label-free detection of albumin variation for improving type II diabetes screening.
Molecular characterization of semen that can be used to provide an objective diagnosis of semen quality is still lacking. Raman spectroscopy measures vibrational modes of molecules, thus can be utilized to characterize biological fluids. Here, we employed Raman spectroscopy to characterize and compare normal and abnormal semen samples in the fingerprint region (400-1800cm-1). Multivariate analysis methods including principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) were used for spectral analysis to differentiate between normal and abnormal semen samples. Compared with PCA-LDA analysis, PLS-DA improved the diagnostic results, showing a sensitivity of 77% and specificity of 73%. Furthermore, our preliminary quantitative analysis based on PLS algorithm demonstrated that spermatozoa concentration were relatively well predicted (R2=0.825). In conclusion, this study demonstrated that micro-Raman spectroscopy combined with multivariate methods can provide as a new diagnostic technique for semen analysis and differentiation between normal and abnormal semen samples.
Surface-enhanced Raman scattering (SERS) spectra of serum proteins purified from human serum samples were employed to detect colorectal cancer. Acetic acid as a new aggregating agent was introduced to increase the magnitude of the SERS enhancement. High-quality SERS spectra of serum proteins were acquired from 103 cancer patients and 103 healthy volunteers. Tentative assignments of SERS bands reflect that some specific biomolecular contents and protein secondary structures change with colorectal cancer progression. Principal component analysis combined with linear discriminant analysis was used to assess the capability of this approach for identifying colorectal cancer, yielding diagnostic accuracies of 100% (sensitivity: 100%; specificity: 100%) based on albumin SERS spectroscopy and 99.5% (sensitivity: 100%; specificity: 99%) based on globulin SERS spectroscopy, respectively. A partial least squares (PLS) approach was introduced to develop diagnostic models. An albumin PLS model successfully predicted the unidentified subjects with a diagnostic accuracy of 93.5% (sensitivity: 95.6%; specificity: 91.3%) and the globulin PLS model gave a diagnostic accuracy of 93.5% (sensitivity: 91.3%; specificity: 95.6%). These results suggest that serum protein SERS spectroscopy can be a sensitive and clinically powerful means for colorectal cancer detection.
Due to its high sensitivity, flexibility, and “fingerprints” sensing capability, Surface-enhanced Raman Spectroscopy
(SERS) is a very powerful method for characterization of substances. In this paper, two kinds of Radix Astragali with
different quality were firstly extracted through continuous circumfluence extraction method and then mixed with silver
nanoparticles for SERS detection. Most Raman bands obtained in Radix Astragali extraction solution are found at
300-7000cm-1 and 900-1390 cm-1. Although, major peak positions at 470, 556, 949, 1178 and 1286 cm-1 found in these
two kinds of Radix Astragali appear nearly the same, Raman bands of 556 and 1178 cm-1 are different in intensity, thus
may be used as a characteristic marker of Radix Astragali quality. In detail, we can make full use of the different
intensity of two different kinds but the same state at 556 cm-1 to describe the quality standard of Radix Astragali. Our
preliminary results show that SERS combining with continuous circumfluence extraction method may provide a direct,
accurate and rapid detection method of Radix Astragali.
The molecular characterization of ABO blood types, which is clinically significant in blood transfusion, has clinical and
anthropological importance. Polymerase chain reaction sequence-based typing (PCR-SBT) is one of the most commonly
used methods for the analysis of genetic bases of ABO blood types. However, such methods as PCR-SBT are
time-consuming and are high in demand of equipments and manipulative skill. Here we showed that membrane
electrophoresis based SERS method employed for studying the molecular bases of ABO blood types can provide rapidand
easy-operation with high sensitivity and specificity. The plasma proteins were firstly purified by membrane
electrophoresis and then mixed with silver nanoparticles to perform SERS detection. We use this method to classify
different blood types, including blood type A (n=13), blood type B (n=9) and blood type O (n=10). Combination of
principal component analysis (PCA) and liner discriminant analysis (LDA) was then performed on the SERS spectra of
purified albumin, showing good classification results among different blood types. Our experimental outcomes represent
a critical step towards the rapid, convenient and accurate identification of ABO blood types.
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