Differential diagnosis between experimental endophthalmitis and uveitis in vitreous with Raman spectroscopy and principal components analysis

Rossi, E; Pinheiro, António Luiz Barbosa; Baltatu, Ovidiu Constantin; Pacheco, Marcos Tadeu Tavares; Silveira, Landulfo

doi:10.1016/j.jphotobiol.2011.12.001

Cited by 10 publications

(2 citation statements)

References 33 publications

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“…Raman spectral features extracted from PCA have been used to reveal the differences in the biochemistry of normal and altered/pathological status of tissues and fluids, thus being able to discriminate histological groups of skin cancer in vitro and in vivo (Silveira et al, 2015) and atherosclerosis in coronary arteries (Silveira et al, 2002), differential diagnosis in uveitis and endophthalmitis (Rossi et al, 2012), and detecting biomarkers for diseases in biological fluids such as serum and urine (Bispo et al, 2013;Saade et al, 2008). The loading vectors may be an important tool to show the differences in the biochemistry when the spectra of pure biochemicals cannot be obtained, and may present the same results in discrimination models using spectra of standard biochemicals (Bodanese et al, 2010).…”

Section: Discussionmentioning

confidence: 99%

Detecting alterations of glucose and lipid components in human serum by near-infrared Raman spectroscopy

et al. 2015

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Introduction: Raman spectroscopy may become a tool for the analysis of glucose and triglycerides in human serum in real time. This study aimed to detect spectral differences in lipid and glucose components of human serum, thus evaluating the feasibility of Raman spectroscopy for diagnostic purposes. Methods: A total of 44 samples of blood serum were collected from volunteers and submitted for clinical blood biochemical analysis. The concentrations of glucose, cholesterol, triglycerides, and low-density and high-density lipoproteins (LDL and HDL) were obtained using standard biochemical assays. Serum samples were placed in Eppendorf tubes (200 µL), kept cooled (5 °C) and analyzed with near-infrared Raman spectroscopy (830 nm, 250 mW, 50 s accumulation). The mean spectra of serum with normal or altered concentrations of each parameter were compared to determine which Raman bands were related to the differences between these two groups.Results: Differences in peak intensities of altered sera compared to normal ones depended on the parameter under analysis: for glucose, peaks were related to glucose; for lipid compounds the main changes occurred in the peaks related to cholesterol, lipids (mainly triolein) and proteins. Principal Components Analysis discriminated altered glucose, cholesterol and triglycerides from the normal serum based on the differences in the concentration of these compounds. Conclusion: Differences in the peak intensities of selected Raman bands could be seen in normal and altered blood serum samples, and may be employed as a means of diagnosis in clinical analysis.

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Section: Discussionmentioning

confidence: 99%

Detecting alterations of glucose and lipid components in human serum by near-infrared Raman spectroscopy

et al. 2015

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“…These interactions produce spectral bands, formed by photons scattered at the frequencies of the molecular vibrations that provide valuable sensitive and specific information of the biochemical composition of the tissue. 20 Recently, sophisticated data analysis techniques based on multivariate analysis have made it possible to exploit the full information content of Raman spectra and to draw conclusions about the chemical structure and composition of very complex systems such as detecting of glucose in serum, whole blood, and human aqueous humor. 3,15,19,21–24 However, some limitations of Raman spectroscopy for biomedical applications have included issues such as weak scattering signals, long spectral acquisition times, fluorescence from biological samples, the instability of the laser intensity, and the photothermal damage to samples.…”

Section: Introductionmentioning

confidence: 99%

Noninvasive Measurement of Glucose in Artificial Plasma with Near-Infrared and Raman Spectroscopy

et al. 2014

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The goal of this research was to develop a method for noninvasive blood glucose assay. Near-infrared (NIR) spectroscopy and Raman spectroscopy, two more promising techniques compared to other methods, were investigated in two kinds of artificial plasma (AP). Calibration models were generated by performing partial least squares (PLS) regression and optimized individually by considering spectral range, spectral pretreatment methods, and number of model factors. The two spectroscopic models were validated for the determination of glucose, and the results show that the two spectroscopic models established are robust, accurate, and repeatable. Compared to Raman spectroscopy, the performance of NIR spectroscopy was much better, with lower root mean square errors of cross-validation (RMSECV) of 0.128 and 0.094 mg/ml, lower root mean square errors of validation (RMSEP) of 0.061 and 0.046 mg/ml, higher correlation coefficients (R) of 99.15% and 99.55%, and higher residual predictive deviations (RPD) of 10.8 and 15.0 for artificial plasma I and II, respectively.

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Optimal Driving Current for Improved Noninvasive Near Infrared Glucose Meter

2021

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Differential diagnosis between experimental endophthalmitis and uveitis in vitreous with Raman spectroscopy and principal components analysis

Cited by 10 publications

References 33 publications

Detecting alterations of glucose and lipid components in human serum by near-infrared Raman spectroscopy

Detecting alterations of glucose and lipid components in human serum by near-infrared Raman spectroscopy

Noninvasive Measurement of Glucose in Artificial Plasma with Near-Infrared and Raman Spectroscopy

Optimal Driving Current for Improved Noninvasive Near Infrared Glucose Meter

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