Blood Serum Surface-enhanced Raman Spectroscopy Research Articles

Identification and assessment of pulmonary Cryptococcus neoformans infection by blood serum surface-enhanced Raman spectroscopy

Cryptococcus neoformans (C. neoformans) is a causative agent for acute pulmonary infection, which can further develop to lethal meningoencephalitis if untreated. The meningoencephalitis infection can be prevented, if timely treatment on pulmonary cryptococcal infection can be implemented based on its early diagnosis and accurate assessment. In this study, blood serum surface-enhanced Raman spectroscopy (SERS) method was investigated on identification and assessment of pulmonary C. neoformans infection. The serum SERS measurements were collected from the mice infected with C. neoformans and the healthy mice, in which the infected mice were further divided into four subgroups according to the duration of infection. Based on those SRES measurements, biochemical differences were analyzed among those different groups to investigate the potential biomarkers for identifying and assessing the pulmonary C. neoformans infection. Furthermore, partial least square (PLS) analysis followed by linear discriminant analysis (LDA) model was employed to identify pulmonary cryptococcal infection and to assess the degrees of infection with the accuracies of 96.7% and 85.3%, respectively. Therefore, our study has demonstrated the great clinical potential of using serum SERS technique for an accurate identification and assessment of pulmonary cryptococcal infection.

Identifying functioning and nonfunctioning adrenal tumors based on blood serum surface-enhanced Raman spectroscopy.

Adrenal tumors are common tumors in urology and they can be further divided into functioning and nonfunctioning tumors according to whether there is uncommon endocrine function. In clinical practice, the early identification and accurate assessment of adrenal tumors are essential for the guidance of subsequent treatment. However, a nonfunctioning adrenal tumor often lacks obvious clinical symptoms, making it difficult to be timely and precisely diagnosed by conventional examinations. Therefore, a rapid and accurate method for identifying the functioning and nonfunctioning adrenal tumors is urgently required to achieve precise treatment of adrenal tumors. In this study, surface-enhanced Raman spectroscopy was investigated as a diagnostic tool to identify the blood serum samples from healthy volunteers as well as the patients with functioning and nonfunctioning adrenal tumors. Based on the SERS peak analysis, abnormal glycolysis, DNA/RNA, and amino acid metabolites were found to be potential biomarkers for identifying patients with adrenal tumors, while metabolites related to disordered protein catabolism and excessive hormone secretion were expected to further differentiate functioning adrenal tumors from nonfunctioning adrenal tumors. In addition, principal component analysis followed by support vector machine (PCA-SVM) was further applied on those serum SERS measurements, and the classification accuracies of 96.8% and 84.5% were achieved for differentiating healthy group versus adrenal tumor group and functioning adrenal tumor group versus nonfunctioning adrenal tumor group, respectively. The results have demonstrated the prodigious potential of precise adrenal tumor diagnosis by using the blood serum surface-enhanced Raman spectroscopy technique.

Identifying benign and malignant thyroid nodules based on blood serum surface-enhanced Raman spectroscopy

The aim of this study is to evaluate the feasibility of using blood serum surface-enhanced Raman spectroscopy (SERS) to identify benign and malignant thyroid nodules. Blood serum samples collected from three different groups including healthy volunteers (n = 22), patients with benign nodules (n = 19) and malignant nodules (n = 22) were measured by SERS. The spectral analysis results demonstrate that biomolecules in serum, such as amino acids, adenine and nucleic acid bases, change differently due to the different progression of nodules. By further combining with partial least square analysis and linear discriminant analysis (PLS-LDA) method, diagnostic accuracies of 93.65% and 82.93%, sensitivities of 92.68% and 81.82% and specificities of 95.45% and 84.21% can be achieved for differentiating healthy versus thyroid nodular groups and benign versus malignant groups, respectively. The above results have suggested that the blood serum SERS technique is helpful for precise diagnosis and timely treatment for patients with thyroid nodules.

Label-free serum detection of Trichinella spiralis using surface-enhanced Raman spectroscopy combined with multivariate analysis

Based on blood serum surface-enhanced Raman spectroscopy (SERS) analysis, this paper proposed a simple and unlabeled non-invasive serum detection for T. spiralis infection. Serum samples were collected and analyzed from 40 rats at 0 days post infection (dpi) (normal rats), 19 uninfected rats, and 16 rats infected with T. spiralis at 28 dpi, using SERS measurements. Multivariate statistical techniques, such as linear discriminant analysis (LDA) and principal components analysis (PCA), were used to analyze and identify the obtained blood serum SERS spectra. The diagnosis algorithms, based on PCA-LDA, achieved a diagnostic sensitivity of 87.5%, a specificity of 94.7%, and an accuracy of 91.4% for separating the samples infected with T. spiralis from the control samples. This exploratory study demonstrated that colloidal Ag NPs-based SERS serum analysis technique combined with PCA-LDA has a great potential in improving the detection of T. spiralis infection and onsite screening.

Identifying non-muscle-invasive and muscle-invasive bladder cancer based on blood serum surface-enhanced Raman spectroscopy.

The assessment of the muscle invasion of bladder cancer typically plays a crucial role in therapeutic decision-making and has significant impacts on the recurrence rate and survival rate. Although histopathology is sufficiently accurate and usually served as the gold standard for bladder cancer diagnosis, it is invasive, time-consuming, and requires intensive sample preparation by a well-trained pathologist to achieve an optimal diagnosis. Therefore, a fast and noninvasive method to accurately identify non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) is in demand. In this study, the SERS technique combined with the PLS-LDA method based on a small amount of blood serum samples is employed to distinguish healthy volunteers, NMIBC, and MIBC patients. According to the results, the overall diagnostic accuracy is 93.3%. The diagnostic accuracies are 97.8% and 93.2% for healthy versus bladder cancer groups and NMIBC versus MIBC groups, respectively. Therefore, the proposed method has demonstrated excellent performance on accurately identifying muscle invasion of bladder cancer, which can assist timely diagnosis and proper treatment for bladder cancer patients.

Diagnostic potential of polarized surface enhanced Raman spectroscopy technology for colorectal cancer detection.

The purpose of this study was to develop a more powerful blood analysis method based on polarized surface enhanced Raman spectroscopy (SERS) technology for non-invasive and sensitive colorectal cancer (CRC) detection. The efficiency of different polarized scattering signals (non-polarization, parallel polarization and perpendicular polarization) on blood serum SERS was explored for the first time. Results demonstrated that polarized SERS was more sensitive to explore distinctive spectral differences between cancer and normal groups. And higher diagnostic accuracy of 91.6% could be achieved using polarized SERS integrated with PCA-LDA for classification of the two serum groups in comparison to conventional SERS technology. This exploratory study demonstrated that the nanobiosensor based on polarized SERS technique in conjunction with PCA-LDA provided a novel strategy for blood SERS analysis, and had the potential as a clinical complement for CRC screening.