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Background: Skin cancer continues to be the most common cancer in the Caucasian population. Over the past two decades, researchers around the world started assessing the possibility of diagnosing tissue pathologies by using optical systems. In this study, we aimed to use in vivo optical coherence tomography (OCT) technology to describe the morphologic features of normal and pathologic skin conditions., Materials and Methods: In this study, 72 patients with suspected skin pre-cancer/cancer were recruited. The lesions were subjected to in vivo OCT scanning using compact size probe. The main scanned areas were the centre of the lesion, periphery of the lesion and control reading at least 2cm from the lesion periphery but within the same dermatomal distribution. Following assessment, each lesion was surgically excised. All acquired OCT images were correlated with the corresponding histopathology images to ensure an accurate diagnosis and appropriate co-localisation of abnormal lesion on both OCT image and pathology slide. This was achieved in every resected lesion., Results: Histopathological analysis revealed that of the 96 macroscopically suspicious scanned lesions 26 were actinic keratosis (AK), 51 were basal cell carcinoma (BCC) and 19 were cutaneous squamous cell carcinoma (SCC). Different layers of healthy skin can be distinguished with clear demarcation between the epidermis and papillary dermis. An increase in epidermal thickness was observed in OCT images in AK that appeared relatively hyperintense. Cutaneous SCC was characterized by hypoechoic signal free spaces within the dermis and damaged of dermal-epidermal junction. BCCs were visualized as hypoechoic structures but showed a mixed echogenicity. Solid nodular BCC appeared as single or multiple areas with no clear arrangement surrounding low-reflectivity lobular structures surrounded. Cystic structures were identifiable by signal-free areas adjacent to healthy skin. Sensitivity and specificity for in vivo OCT in diagnosing these lesions were impressive, based on this small sample size., Conclusions: OCT have shown that there are qualitative differences in OCT image features of skin with varying degrees of pathology, and between normal and pathological skin. This study indicates that in vivo OCT shows a good promise as a useful optical diagnostic technique in diagnosing skin pathologies., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Fourier Transform-Infrared (FT-IR) absorption spectroscopy has been used to investigate pathophysiological changes caused by sepsis. Sepsis has been defined as a potentially fatal organic dysfunction caused by a dysregulated host response to infection and can lead a patient to risk of death. This study used samples consisting of the blood plasma of mice which were induced to sepsis state, compared to a healthy group using FT-IR associated with attenuated total reflectance (ATR) spectroscopy. For statistical analysis, principal components analysis (PCA) and linear discriminant analysis (LDA) were applied, independently, to the second derivative spectra of both the fingerprint (900-1800 cm -1 ) and the high wavenumber (2800-3100 cm -1 ) regions. The technique efficiently differentiated the blood plasma of the two groups, sepsis and healthy mice, the analysis indicating that fatty acids and lipids in the blood samples could be an important biomarker of sepsis., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Skin erythema may present due to many causes. One of the common causes is prolonged exposure to sun rays. Other than sun exposure, skin erythema is an accompanying sign of dermatological diseases such as acne, psoriasis, melasma, post inflammatory hyperpigmentation, fever, as well as exposure to specific electromagnetic wave bands., Methods: Quantifying skin erythema in patients enables the dermatologist to assess the patient's skin health. Therefore, quantitative assessment of skin erythema was the target of several studies. The clinical standard for erythema evaluation is visual assessment. However, the former standard has some imperfections. For instance, it is subjective, and unqualified for precise color information exchange. To overcome these shortcomings, the past three decades witnessed various methodologies that aimed to achieve erythema objective assessment, such as diffuse reflectance spectroscopy (DRS), and both optical and non-optical systems., Discussion: This review article reports on the studies published in the past three decades where the performance, the mathematical tactics for computation, and the capabilities of erythema assessment techniques for cutaneous diseases are discussed. In particular, the achievements and limitations of the current techniques in erythema assessment are presented., Conclusion: The profits and development trends of optical and non-optical methods are displayed to provide the researcher with awareness into the present technological advances and its potential for dermatological diseases research., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The aim of this in vitro study was to evaluate the preventive effect of different materials on dental erosion lesions by speckle coherent light scattering analysis. Forty bovine teeth were divided in the following groups (n = 10): 1) DURA- Preventive Treatment with Fluoride Varnish (Duraphat, Colgate-Palmolive); 2) ELX- Preventive treatment with Elmex® Erosion Protection Toothpaste (GABA International AG, Therwil, Switzerland); 3) MP- Preventive treatment with MI Paste® (GC America); and 4) REG- Preventive Treatment with Regenerate Enamel Science™ (Unilever). For all groups, each sample was divided into 3 areas: non-treatment (control); preventive treatment + erosive challenge; non-treatment + erosive challenge. The erosive challenge was carried out using Sprite® Zero soft drink (pH 2.58). After the erosive challenge, the samples were evaluated by speckle coherent light scattering method in the eroded area compared to the sound area. The results showed that there was a statistically significant difference between eroded area with and without preventive treatment, however, there was no statistically significant difference among the different preventive materials tested., Competing Interests: Declaration of Competing Interest The authors declare that there was no financial or commercial conflicts of interest in any of the products employed in this investigation., (Copyright © 2020 Elsevier B.V. All rights reserved.)

We present the effectiveness of Raman spectroscopy (RS) in combination with machine learning for screening and analysis of blood sera collected from tuberculosis patients. Blood samples of 60 patients have confirmed active pulmonary tuberculosis and 14 samples of healthy age matched control were used in the current study. Spectra from entire sera samples were acquired using 785 nm laser Raman system. Support Vector Machine (SVM) together with Principal Component Analysis (PCA) has been used for highlighting variations spectral intensities between healthy and pathological samples. SVM model using Gaussian radial basis is able to discriminate between healthy and diseased patients based on the differences in the concentration of essential biomolecules such as lactate, β-carotene, and amide-I. Diagnostic accuracy of 92%, with precision, specificity and sensitivity of 95%, 98% and 81%, respectively, were achieved considering PC3 and PC4. Automatic analysis of the variations in the concentration of these molecules together with chemometrics can effectively be utilized for an early screening of tuberculosis through minimum invasion., (Copyright © 2018. Published by Elsevier B.V.)

This study presents the analysis of hepatitis B virus (HBV) infection in human blood serum using Raman spectroscopy combined with pattern recognition technique. In total, 119 confirmed samples of HBV infected sera, collected from Pakistan Atomic Energy Commission (PAEC) general hospital have been used for the current analysis. The differences between normal and HBV infected samples have been evaluated using support vector machine (SVM) algorithm. SVM model with two different kernels i.e. polynomial function and Gaussian radial basis function (RBF) have been investigated for the classification of normal blood sera from HBV infected sera based on Raman spectral features. Furthermore, the performance of the model with each kernel function has also been analyzed with two different implementations of optimization problem i.e. Quadratic programming and least square. 5-fold cross validation method has been used for the evaluation of the model. In the current study, best classification performance has been achieved for polynomial kernel of order-2. A diagnostic accuracy of about 98% with the precision of 97%, sensitivity of 100% and specificity of 95% has been achieved under these conditions., (Copyright © 2018. Published by Elsevier B.V.)

Background: In this study is presented the correlation between laser speckle images and enamel hardness loss., Methods: In order to shift the enamel hardness, a dental demineralization model was applied to 32 samples of vestibular bovine teeth. After they were cleaned, cut and polished, the samples were divided into 4 groups and immersed in 30ml of a cola-based soft drink for 10, 20, 30 and 40min twice a day for 7 consecutive days with half the surface protected by two layers of nail polish. Each sample was analyzed by Knoop hardness and laser speckle imaging., Results: Pearson's correlation analysis demonstrated that the laser speckle image technique presents a strong correlation with the hardness loss of the enamel (r=0.7085, p<0.0001). This finding is corroborated by Blend & Altman analysis, in which the data presented a constant behavior throughout the whole interval. For both analyses, more than 95% of the data is within the confidence interval, as expected., Conclusion: This work demonstrates, for the first time to our knowledge, an empirical model for correlating laser speckle images with the loss of tooth enamel hardness., (Copyright © 2016. Published by Elsevier B.V.)