Front Cover: Differentiating smokers and nonsmokers based on Raman spectroscopy of oral fluid and advanced statistics for forensic applications (J. Biophotonics 3/2020)

Raman spectroscopy was employed as a nondestructive technique for the analysis of dry traces of oral fluid to differentiate between smoker and nonsmoker donors with the aid of advanced statistical tools. A genetic algorithm (GA) was used to determine eight spectral regions that contribute the most to the differentiation of smokers and nonsmokers. Thereafter, a classification model was developed based on the artificial neural network (ANN) that showed 100% accuracy after external validation. (Image ©: Dr. Aliaksandra Sikirzhytskaya). Further details can be found in the article by Entesar Al‐Hetlani, Lenka Halamkova, Mohamed O. Amin, and Igor K. Lednev ( e201960123 ).

     

Raman spectroscopy‐based detection of RNA viruses in saliva: A preliminary report

Several non‐invasive Raman spectroscopy‐based assays have been reported for rapid and sensitive detection of pathogens. We developed a novel statistical model for the detection of RNA viruses in saliva, based on an unbiased selection of a set of 65 Raman spectral features that mostly attribute to the RNA moieties, with a prediction accuracy of 91.6% (92.5% sensitivity and 88.8% specificity). Furthermore, to minimize variability and automate the downstream analysis of the Raman spectra, we developed a GUI‐based analytical tool “RNA Virus Detector (RVD).” This conceptual framework to detect RNA viruses in saliva could form the basis for field application of Raman Spectroscopy in managing viral outbreaks, such as the ongoing COVID‐19 pandemic. ( http://www.actrec.gov.in/pi-webpages/AmitDutt/RVD/RVD.html ).     

Effect of hemolysis on Fourier transform infrared and Raman spectra of blood plasma

Hemolysis is a very common phenomenon and is referred as the release of intracellular components from red blood cells to the extracellular fluid. Hemolyzed samples are often rejected in clinics due to the interference of hemoglobin and intracellular components in laboratory measurements. Plasma and serum based vibrational spectroscopy studies are extensively applied to generate spectral biomarkers for various diseases. However, no studies have reported the effect of hemolysis in blood based vibrational spectroscopy studies. This study was undertaken to evaluate the effect of hemolysis on infrared and Raman spectra of blood plasma. In this study, prostate cancer plasma samples (n = 30) were divided into three groups (nonhemolyzed, mildly hemolyzed, and moderately hemolyzed) based on the degree of hemolysis and FTIR and Raman spectra were recorded using high throughput (HT)‐FTIR and HT‐Raman spectroscopy. Discrimination was observed between the infrared and Raman spectra of nonhemolyzed and hemolyzed plasma samples using principal component analysis. A classical least square fitting analysis showed differences in the weighting of pure components in nonhemolyzed and hemolyzed plasma samples. Therefore, it is worth to consider the changes in spectral features due to hemolysis when comparing the results within and between experiments.     

Therapeutic prognosis of prostate cancer using surface-enhanced Raman scattering of patient urine and multivariate statistical analysis

Surface-enhanced Raman scattering (SERS) is highly sensitive and label-free analytical technique based on Raman spectroscopy aided by field-multiplying plasmonic nanostructures. We report the use of SERS measurements of patient urine in conjunction with biostatistical algorithms to assess the treatment response of prostate cancer (PCa) in 12 recurrent (Re) and 63 nonrecurrent (NRe) patient cohorts. Multiple Raman spectra are collected from each urine sample using monodisperse silver nanoparticles (AgNPs) for Raman signal enhancement. Genetic algorithms-partial least squares-linear discriminant analysis (GA-PLS-LDA) was employed to analyze the Raman spectra. Comprehensive GA-PLS-LDA analyses of these Raman spectral features (p = 3.50 × 10⁻¹⁶ ) yield an accuracy of 86.6%, sensitivity of 86.0%, and specificity 87.1% in differentiating the Re and NRe cohorts. Our study suggests that SERS combined with multivariate GA-PLS-LDA algorithm can potentially be used to detect and monitor the risk of PCa relapse and to aid with decision-making for optimal intermediate secondary therapy to recurred patients.     

Raman microspectroscopic study for the detection of oral field cancerisation using brush biopsy samples

Field cancerisation (FC) is potentially an underlying cause of poor treatment outcomes of oral squamous cell carcinoma (OSCC). To explore the phenomenon using Raman microspectroscopy, brush biopsies from the buccal mucosa, tongue, gingiva and alveolus of healthy donors (n = 40) and from potentially malignant lesions (PML) of Dysplasia Clinic patients (n = 40) were examined. Contralateral normal samples (n = 38) were also collected from the patients. Raman spectra were acquired from the nucleus and cytoplasm of each cell, and subjected to partial least squares‐discriminant analysis (PLS‐DA). High discriminatory accuracy for donor and PML samples was achieved for both cytopalmic and nuclear data sets. Notably, contralateral normal (patient) samples were also accurately discriminated from donor samples and contralateral normal samples from patients with multiple lesions showed a similar spectral profile to PML samples, strongly indicating a FC effect. These findings support the potential of Raman microspectroscopy as a screening tool for PML using oral exfoliated cells.     

Sub millimetre flexible fibre probe for background and fluorescence free Raman spectroscopy

Using the shifted-excitation Raman difference spectroscopy technique and an optical fibre featuring a negative curvature excitation core and a coaxial ring of high numerical aperture collection cores, we have developed a portable, background and fluorescence free, endoscopic Raman probe. The probe consists of a single fibre with a diameter of less than 0.25 mm packaged in a sub-millimetre tubing, making it compatible with standard bronchoscopes. The Raman excitation light in the fibre is guided in air and therefore interacts little with silica, enabling an almost background free transmission of the excitation light. In addition, we used the shifted-excitation Raman difference spectroscopy technique and a tunable 785 nm laser to separate the fluorescence and the Raman spectrum from highly fluorescent samples, demonstrating the suitability of the probe for biomedical applications. Using this probe we also acquired fluorescence free human lung tissue data.     

Raman spectroscopy of blood and urine liquid biopsies for ovarian cancer diagnosis: identification of chemotherapy effects

Blood plasma and serum Raman spectroscopy for ovarian cancer diagnosis has been applied in pilot studies, with promising results. Herein, a comparative analysis of these biofluids, with a novel assessment of urine, was conducted by Raman spectroscopy application in a large patient cohort. Spectra were obtained through samples measurements from 116 ovarian cancer patients and 307 controls. Principal component analysis identified significant spectral differences between cancers without previous treatment (n = 71) and following neo-adjuvant chemotherapy (NACT), (n = 45). Application of five classification algorithms achieved up to 73% sensitivity for plasma, high specificities and accuracies for both blood biofluids, and lower performance for urine. A drop in sensitivities for the NACT group in plasma and serum, with an opposite trend in urine, suggest that Raman spectroscopy could identify chemotherapy-related changes. This study confirms that biofluids' Raman spectroscopy can contribute in ovarian cancer's diagnostic work-up and demonstrates its potential in monitoring treatment response.     

Fast denoising and lossless spectrum extraction in stimulated Raman scattering microscopy

Stimulated Raman scattering (SRS) microscopy is a nonlinear optical imaging method for visualizing chemical content based on molecular vibrational bonds. However, the imaging speed and sensitivity are currently limited by the noise of the light beam probing the Raman process. In this paper, we present a fast non-average denoising and high-precision Raman shift extraction method, based on a self-reinforcing signal-to-noise ratio (SNR) enhancement algorithm, for SRS spectroscopy and microscopy. We compare the results of this method with the filtering methods and the reported experimental methods to demonstrate its high efficiency and high precision in spectral denoising, Raman peak extraction and image quality improvement. We demonstrate a maximum SNR enhancement of 10.3 dB in fixed tissue imaging and 11.9 dB in vivo imaging. This method reduces the cost and complexity of the SRS system and allows for high-quality SRS imaging without use of special laser, complicated system design and Raman tags.     

A graphical user interface (NWUSA) for Raman spectral processing,analysis and feature recognition

It is a practical necessity for non-professional users to interpret biologically derived Raman spectral information for obtaining accurate and reliable analytical results. An integrated Raman spectral analysis software (NWUSA) was developed for spectral processing, analysis, and feature recognition. It provides a user-friendly graphical interface to perform the following preprocessing tasks: spectral range selection, cosmic ray removal, polynomial fitting based background subtraction, Savitzky–Golay smoothing, area-under-curve normalization, mean-centered procedure, as well as multivariate analysis algorithms including principal component analysis (PCA), linear discriminant analysis, partial least squares-discriminant analysis, support vector machine (SVM), and PCA-SVM. A spectral dataset obtained from two different samples was utilized to evaluate the performance of the developed software, which demonstrated that the analysis software can quickly and accurately achieve functional requirements in spectral data processing and feature recognition. Besides, the open-source software can not only be customized with more novel functional modules to suit the specific needs, but also benefit many Raman based investigations, especially for clinical usages.     

Biophotonic technologies for assessment of breast tumor surgical margins—A review

Breast conserving surgery (BCS) offering similar surgical outcomes as mastectomy while retaining breast cosmesis is becoming increasingly popular for the management of early stage breast cancers. However, its association with reoperation rates of 20% to 40% following incomplete tumor removal warrants the need for a fast and accurate intraoperative surgical margin assessment tool that offers cellular, structural and molecular information of the whole specimen surface to a clinically relevant depth. Biophotonic technologies are evolving to qualify as such an intraoperative tool for clinical assessment of breast cancer surgical margins at the microscopic and macroscopic scale. Herein, we review the current research in the application of biophotonic technologies such as photoacoustic imaging, Raman spectroscopy, multimodal multiphoton imaging, diffuse optical imaging and fluorescence imaging using medically approved dyes for breast cancer detection and/or tumor subtype differentiation toward intraoperative assessment of surgical margins in BCS specimens, and possible challenges in their route to clinical translation.     

Plasma copper and lipid peroxidation in cigarette smokers

Plasma levels of copper and lipid peroxidation were evaluated in 14 smokers as compared to 14 nonsmokers. Plasma copper concentrations were higher in smokers than in nonsmokers (122.5 ± 19.15 vs. 101.5 ± 16.2 μg/dl, P < .01). Plasma lipoperoxidation, evaluated as fluorescent damage products of lipid peroxidation (FDPL), also was higher in smokers than in nonsmokers (20.35 ± 2.6 vs. 17.1 ± 2.95 units of relative fluorescence/ml, P < .01). A significant and positive correlation between the number of cigarettes smoked, expressed as pack years, and the levels of either FDPL (r = .61, P < .025) or copper (r = .55, P < .05) was found. Moreover, a significant and positive relationship between copper and FDPL values was observed in smokers (r = .64; P < .025), but not in nonsmokers. These data indicate that cigarette smoke-related plasma oxidant load may be partly due to enhanced levels of the prooxidant metal copper, potentially suggesting the supplementation of specific antioxidants (e.g., zinc) to counteract cigarette smoke-induced oxidative stress in smokers.     

Oxidation of glutathione and cysteine in human plasma associated with smoking

Cigarette smoking contributes to the development or progression of numerous chronic and age-related disease processes, but detailed mechanisms remain elusive. In the present study, we examined the redox states of the GSH/GSSG and Cys/CySS couples in plasma of smokers and nonsmokers between the ages of 44 and 85 years (n = 78 nonsmokers, n = 43 smokers). The Cys/CySS redox in smokers (−64 ± 16 mV) was more oxidized than nonsmokers (− 76 ± 11 mV; p < .001), with decreased Cys in smokers (9 ± 5 μM) compared to nonsmokers (13 ± 6 μM; p < .001). The GSH/GSSG redox was also more oxidized in smokers (−128 ± 18 mV) than in nonsmokers (−137 ± 17 mV; p = .01) and GSH was lower in smokers (1.8 ± 1.3 μM) than in nonsmokers (2.4 ± 1.0; p < .005). Although the oxidation of GSH/GSSG can be explained by the role of GSH in detoxification of reactive species in smoke, the more extensive oxidation of the Cys pool shows that smoking has additional effects on sulfur amino acid metabolism. Cys availability and Cys/CySS redox are known to affect cell proliferation, immune function, and expression of death receptor systems for apoptosis, suggesting that oxidation of Cys/CySS redox or other perturbations of cysteine metabolism may have a key role in chronic diseases associated with cigarette smoking.     

Raman spectroscopy of human skin for kidney failure detection

The object of this paper is in vivo study of skin spectral-characteristics in patients with kidney failure by conventional Raman spectroscopy in near infrared region. The experimental dataset was subjected to discriminant analysis with the projection on latent structures (PLS-DA). Application of Raman spectroscopy to investigate the forearm skin in 85 adult patients with kidney failure (90 spectra) and 40 healthy adult volunteers (80 spectra) has yielded the accuracy of 0.96, sensitivity of 0.94 and specificity of 0.99 in terms of identifying the target subjects with kidney failure. The autofluorescence analysis in the near infrared region identified the patients with kidney failure among healthy volunteers of the same age group with specificity, sensitivity, and accuracy of 0.91, 0.84, and 0.88, respectively. When classifying subjects by the presence of kidney failure using the PLS-DA method, the most informative Raman spectral bands are 1315 to 1330, 1450 to 1460, 1700 to 1800 cm⁻¹. In general, the performed study demonstrates that for in vivo skin analysis, the conventional Raman spectroscopy can provide the basis for cost-effective and accurate detection of kidney failure and associated metabolic changes in the skin.     

Vitamin E kinetics in smokers and nonsmokers.

Does cigarette smoking increase vitamin E utilization in vivo? A trial was carried out in 6 smokers and 5 nonsmokers of comparable ages and serum lipids. Subjects consumed 75 mg each d(3)-RRR and d(6)-all rac-alpha-tocopheryl acetates (natural and synthetic vitamin E, respectively) daily for 7 d with a standardized breakfast. Fasting blood samples were drawn on days -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 9, 14, 21 (negative days indicate supplementation). In both groups, plasma d(3)-alpha-tocopherol concentrations were approximately double of d(6)-alpha-tocopherol. At day 0, the %d(3) alpha-tocopherols (d(3)-alpha-tocopherol/total-alpha-tocopherol x 100) were similar in both smokers and nonsmokers. Subsequently, there was a trend toward a faster exponential disappearance of the plasma %d(3) alpha-tocopherol in smokers compared with nonsmokers (0.30 +/- 0.04 compared with 0.24 +/- 0.05, p =.0565). The calculated %d(3) half-lives were 55.6 +/- 7.4 h in smokers and 72.1 +/- 17.3 h in nonsmokers (p =.0630). By day 21, the %d(3) in smokers had decreased to 1.4% +/- 0.3% while it was 2.2% +/- 0.7% (p =.0418) in the nonsmokers. These data suggest that smoking increases plasma vitamin E disappearance, but further studies are needed to confirm this finding and to assess its cause.     

Classification of pathogenic bacteria by Raman spectroscopy combined with variational auto-encoder and deep learning

Rapid and early identification of pathogens is critical to guide antibiotic therapy. Raman spectroscopy as a noninvasive diagnostic technique provides rapid and accurate detection of pathogens. Raman spectrum of single cells serves as the “fingerprint” of the cell, revealing its metabolic characteristics. Rapid identification of pathogens can be achieved by combining Raman spectroscopy and deep learning. Traditional classification techniques frequently require lots of data for training, which is time costing to collect Raman spectra. For trace samples and strains that are difficult to culture, it is difficult to provide an accurate classification model. In order to reduce the number of samples collected and improve the accuracy of the classification model, a new pathogen detection method integrating Raman spectroscopy, variational auto-encoder (VAE), and long short-term memory network (LSTM) is proposed in this paper. We collect the Raman signals of pathogens and input them to VAE for training. VAE will generate a large number of Raman spectral data that cannot be distinguished from the real spectrum, and the signal-to-noise ratio is higher than that of the real spectrum. These spectra are input into the LSTM together with the real spectrum for training, and a good classification model is obtained. The results of the experiments reveal that this method not only improves the average accuracy of pathogen classification to 96.9% but also reduces the number of Raman spectra collected from 1000 to 200. With this technology, the number of Raman spectra collected can be greatly reduced, so that strains that are difficult to culture or trace can be rapidly identified.     

Autoantibody against oxidized low-density lipoproteins may be enhanced by cigarette smoking

A total of 59 healthy male subjects (32 smokers and 27 nonsmokers) who had no reported systemic disease and did not take alcohol and vitamin supplementation were included. The levels of autoantibody to oxidized low-density lipoproteins (ox-LDL) in smokers and age-matched nonsmokers were compared. The plasma levels of antioxidants that can affect the formation of ox-LDL were also measured, and correlation analyses between anti ox-LDL IgG and plasma antioxidants, controlling for age and body mass index (BMI), were performed. Plasma alpha-tocopherol and uric acid concentrations of nonsmokers (2.78+/-1.09 microg/mg total lipid and 6.96+/-1.69 mg/dl, respectively) were significantly higher than those of smokers (1.68+/-0.48 microg/mg total lipid and 6.15+/-1.14 mg/dl, respectively) (P<0.05). Although plasma ascorbate and retinol levels were not significantly different between smokers and nonsmokers, smokers older than 45 years old had significantly lower plasma ascorbate levels (0.32+/-0.17 mg/dl) than age-matched nonsmokers (0. 53+/-0.14 mg/dl) (P=0.036). Higher level of plasma anti ox-LDL IgG was noted in the group of smokers compared with nonsmokers (515+/-409 mU/ml vs. 407+/-268 mU/ml, respectively) under the statistic method of Chi-Square test (P=0.049). A significant negative correlation was found between plasma anti ox-LDL IgG and alpha-tocopherol in the combined population as well as in the smoker group (r=-0.26, p=0.047; r=-0.48, p=0.006; respectively). However, there was no correlation between plasma anti ox-LDL IgG and the levels of other antioxidants. These results suggest that reduced concentrations of alpha-tocopherol are associated with cigarette smoking. The significantly negative correlation between plasma anti ox-LDL IgG and alpha-tocopherol in the entire study population as well as in the smoker group suggests that plasma alpha-tocopherol may be partially effective if not totally at protecting LDL from oxidative damage caused by cigarette smoking and dietary supplementation with alpha-tocopherol may provide a protective effect against LDL oxidation, especially in smokers.     

Tri-mode optical biopsy probe with fluorescence endomicroscopy,Raman spectroscopy,and time-resolved fluorescence spectroscopy

We present an endoscopic probe that combines three distinct optical fibre technologies including: A high-resolution imaging fibre for optical endomicroscopy, a multimode fibre for time-resolved fluorescence spectroscopy, and a hollow-core fibre with multimode signal collection cores for Raman spectroscopy. The three fibers are all enclosed within a 1.2 mm diameter clinical grade catheter with a 1.4 mm end cap. To demonstrate the probe's flexibility we provide data acquired with it in loops of radii down to 2 cm. We then use the probe in an anatomically accurate model of adult human airways, showing that it can be navigated to any part of the distal lung using a commercial bronchoscope. Finally, we present data acquired from fresh ex vivo human lung tissue. Our experiments show that this minimally invasive probe can deliver real-time optical biopsies from within the distal lung - simultaneously acquiring co-located high-resolution endomicroscopy and biochemical spectra.     

Blood plasma resonance Raman spectroscopy combined with multivariate analysis for esophageal cancer detection

We herein report a novel, reliable and inexpensive method for detecting esophageal cancer using blood plasma resonance Raman spectroscopy combined with multivariate analysis methods. The blood plasma samples were divided into late stage cancer group (n = 164), early stage cancer group (n = 35) and normal group (n = 135) based on clinical pathological diagnosis. Using a specially designed quartz capillary tube as sample holder, we obtained higher quality resonance Raman spectra of blood plasma than existing method. The study demonstrated that the carotenoids levels in blood plasma were reduced in esophageal cancer patients. The area under the receiver operating characteristic curve (and 95% confidence interval) calculated by wavenumber selection and principal component analysis combined with linear discriminant analysis (PC-LDA) algorithm were 0.894 (0.858-0.929), 0.901 (0.841-0.960) and 0.871 (0.799-0.942) for differentiating late cancer from normal, late cancer from early cancer, and early cancer from normal respectively. The contribution from the two carotenoids wavenumber regions of 1155 and 1515 cm⁻¹ were more than 84.2%. The results show that the plasma carotenoids could be a potential biomarker for screening esophageal cancer using resonance Raman spectroscopy combined with wavenumber selection and PC-LDA algorithms.      

Exploration research on the fusion of multimodal spectrum technology to improve performance of rapid diagnosis scheme for thyroid dysfunction

The spectral fusion by Raman spectroscopy and Fourier infrared spectroscopy combined with pattern recognition algorithms is utilized to diagnose thyroid dysfunction serum, and finds the spectral segment with the highest sensitivity to further advance diagnosis speed. Compared with the single infrared spectroscopy or Raman spectroscopy, the proposal can improve the detection accuracy, and can obtain more spectral features, indicating greater differences between thyroid dysfunction and normal serum samples. For discriminating different samples, principal component analysis (PCA) was first used for feature extraction to reduce the dimension of high‐dimension spectral data and spectral fusion. Then, support vector machine (SVM), back propagation neural network, extreme learning machine and learning vector quantization algorithms were employed to establish the discriminant diagnostic models. The accuracy of spectral fusion of the best analytical model PCA‐SVM, single Raman spectral accuracy and single infrared spectral accuracy is 83.48%, 78.26% and 80%, respectively. The accuracy of spectral fusion is higher than the accuracy of single spectrum in five classifiers. And the diagnostic accuracy of spectral fusion in the range of 2000 to 2500 cm^?1 is 81.74%, which greatly improves the sample measure speed and data analysis speed than analysis of full spectra. The results from our study demonstrate that the serum spectral fusion technique combined with multivariate statistical methods have great potential for the screening of thyroid dysfunction.     

Compartmental analyses of plasma n-3 essential fatty acids among male and female smokers and nonsmokers

The effects of cigarette smoking on n-3 essential FA metabolism were studied in male and female subjects by fitting the concentration-time curves of the d(5)-labeled plasma fatty acids (FAs) originating from a dose of d(5)-18:3n-3 to a compartmental model of n-3 FA metabolism. For 3 weeks, female (smokers, n = 5; nonsmokers, n = 5) and male (smokers, n = 5; nonsmokers, n = 5) subjects subsisted on a beef-based diet. Beginning in the third week, subjects received a dose of d(5)-18:3n-3 ethyl ester (1 g). Plasma FAs were analyzed using gas chromatography (GC) and GC-mass spectrometry, and the kinetic rate parameters were determined from the concentration-time curves for d(5)-18:3n-3, d(5)-20:5n-3, d(5)-22:5n-3, and d(5)-22:6n-3. Women smokers had a 2-fold greater percent of dose in plasma (5.8% vs. 2.9%; P < 0.01) and a higher fractional rate constant coefficient for formation of d(5)-22:6n-3 from d(5)-22:5n-3 (0.03 h(-1) vs. 0.01 h(-1); P < 0.01), compared with nonsmokers. Male smokers had elevated total plasma n-3 FAs, more-rapid turnover of 18:3n-3 (13.3 mg/day(-1) vs. 4.3 mg/day(-1); P < 0.001), a disappearance rate of d(5)-20:5n-3 that was both delayed and slower (0.001 h(-1) vs. 0.012 h(-1); P < 0.05), and a percentage of d(5)-20:5n-3 directed into formation of d(5)-22:5n-3 (99% vs. 61%; P < 0.03) that was greater compared with nonsmokers. Smoking increased the bioavailability of n-3 FAs from plasma, accelerated the fractional synthetic rates, and heightened the percent formation of some long-chain n-3 PUFAs in men and women.