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We report on a continuous and non-invasive approach in vivo to monitor arterial blood pH based on the laser trapping and Raman detection of single live erythrocytes. A home-built confocal laser tweezers Raman system (LTRS) is applied to trace the live erythrocytes at different pH values of the extracellular environment to record their corresponding Raman changes in vitro and in vivo. The analysis results in vitro show that when the extracellular environment pH changes from 6.5 to 9.0, the Raman intensity ratio (R1603, 1616 = I1603/I1616) of single erythrocytes decrease regularly; what is more, there is a good linear relationship between these two variables, and the linearity is 0.985, which is also verified successfully via in vivo Raman measurements. These results demonstrate that the Raman signal of single live erythrocytes is possible as a marker of the extracellular pH value. This in vivo and quantitative Raman-pH sensor of arterial blood will be an important candidate for monitoring the acid–base status during the treatment of ill patients and in some major surgeries because of its continuous and non-invasive characters. [ABSTRACT FROM AUTHOR]

[Display omitted] • Laser tweezers Raman spectroscopy is a potential method for disease diagnosis. • A novel method is proposed for diagnosis of Alzheimer's disease. • Raman spectra of platelets are studied for diagnosing Alzheimer's disease. • Machine learning improves the accuracy of medical diagnosis by data mining. Alzheimer's disease (AD) is a common nervous system disease to affect mostly elderly people over the age of 65 years. However, the diagnosis of AD is mainly depend on the imaging examination, clinical assessments and neuropsychological tests, which may get error diagnosis results and are not able to detect early AD. Here, a rapid, non-invasive, and high accuracy diagnostic method for AD especially early AD is provided based on the laser tweezers Raman spectroscopy (LTRS) combined with machine learning algorithms. AD platelets from different 3xTg-AD transgenic rats at different stages of disease are captured to collect high signal-to-noise ratio Raman signals without contact by LTRS, which is then combined with partial least squares discriminant analysis (PLS-DA), support vector machine (SVM) and principal component analysis (PCA)-canonical discriminate function (CDA) for classification. The results show that the normal and diseased platelets at 3-, 6- and 12-month AD are successfully distinguished and the accuracy is 91%, 68% and 97% respectively, which demonstrates the suggested method can provide a precise detection for AD diagnosis at early, middle and advanced stages. [ABSTRACT FROM AUTHOR]

Two kinds of enamels, including Chinese cloisonné wares from Fuwang chamber and gourd-shaped painted enamels decorations from the Forbidden City, in the Imperial Palace of China, are investigated by micro-Raman spectroscopy in combination with laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and energy-dispersive X-ray fluorescence (EDXRF) in order to examine and analyze the composition of the glaze layer in each case. In this study the excitation is employed with either a NIR laser (785 nm) or a red laser (632.8 nm) in order to effectively eliminate the interference of background fluorescence and resonance effect. We have identified that the major matrix ingredients of the cloisonné wares are lead-based potash-lime silicate glasses while lead-potash silicate glass matrix is the main constituent for the painted enamels. Eight different colored areas of glaze layer also have been discussed in detail due to the distinct colors including turquoise, deep blue, yellow, white, red, pink, deep green and pale green. Their identification based on Raman data will be useful with regard to rapid and on site analysis and the restoration of the enamel decorations. [ABSTRACT FROM AUTHOR]

Abstract: A novel method using feature selection is proposed to classify Alzheimer''s disease using Raman spectra. The method first find all the significant peak from the preprocessed spectrum as the feature candidates for classification. We select the most discrimination peak as a reference feature and compute the correlation coefficients between the reference and every peaks chosen. Then we discard highly correlated features to reduce the number of possible feature candidates. With the peak value and their ratio of the remaining features, we carry out the preliminary classification experiments and examine top 10% cases to seek the most frequently appearing features. Among them, we choose top 2 features, intensity of 1658cm−1 and ratio of intensity of 757 and 743cm−1. These features correspond to protein bands of Amide I mode and cytochrome c, which are also considered important for the detection of Alzheimer''s disease by other researchers. The classification result using 278 spectra achieved 95.8% classification rates for MLP (multi-layer perceptron) with these two features. It confirms that the features chosen with the proposed method could be effectively used for the diagnosis of Alzheimer''s disease. [Copyright &y& Elsevier]

Abstract: In this paper, we consider a new background elimination method for Raman spectra. The proposed method is based on peak detection, smoothing, and interpolation. Since the background is usually slowly varying with respect to wavelength, we could estimate the background by eliminating significant peaks. For this purpose, we seek the peaks by inspecting the smoothed derivative of a given spectrum. After clipping out the corresponding peak regions, we estimate the background by applying a modified linear interpolation. Then the background is eliminated from the measured Raman spectrum by simple subtraction. The experimental results showed that the proposed method gave satisfactory results for real Raman spectra as well as synthetic data. As the proposed method requires no prior knowledge of spectrum, we expect that the method could be applied to other spectral data as well. [Copyright &y& Elsevier]

Abstract: Five triphenyl phosphonium salts including N-phenylacetamidyl triphenyl phosphonium chloride (1), N-phenylpropanamidyl triphenyl phosphonium chloride (2), ethyl 2-methylacetatyl triphenyl phosphonium chloride (3), ethyl butyryl triphenyl phosphonium chloride (4) and hexadecyl triphenyl phosphonium bromide (5) were synthesized and then were characterized by FT-Raman spectroscopy. Surface-enhanced Raman spectroscopy (SERS) in conjunction with electronic absorption spectroscopy was employed to study their interaction with DNA. The decreasing of Raman intensity at 1000, 1029, 1103 and 1588cm−1 from compound 5 indicated that this compound has affinity for DNA. This was probably because compound 5 inserted into DNA and a new conjugated system was formed. The results of electronic absorption spectra were coincident with those of SERS. On the other hand, compound 5 showed a significant higher inhibitory rate on human cervix cancer cells. The targets of the compounds in the anti-cancer process were discussed. The mechanism of the anti-cancer process of compound 5 might be related to its interaction with DNA. [Copyright &y& Elsevier]

Abstract: A new hybrid algorithm is proposed to eliminate the varying background of spectral signals. The method is based on the use of multi-resolution, which is one of the main advantages provided by wavelet transform. Compared with the analyte signal, the background has a low frequency. The new method firstly split the signals into different frequency components, and then removes the varying low-frequency background. The method is successfully applied to simulated spectral data set and experimental Raman spectral data. The results showed that the wavelet transform technique could handle all kinds of background and low signal-to-background ratio spectra, and required no prior knowledge about the sample composition, no selection of suitable background correction points, and no mathematical assumption of the background distribution. The proposed procedure was illustrated, by processing real spectra, to be an effective and practical tool for background elimination in Raman spectra. In addition, the proposed strategy can be applied to other spectral signals as well. [Copyright &y& Elsevier]