Melanin content of cultured human melanocytes and UV-induced cytotoxicity

Cultured melanocytes originating from persons with different skin phototypes were utilized for measurement of endonuclease sensitive sites induced by UVB and the determination of cell survival after UVA or UVB irradiation. During culture, the melanocytes largely maintained their phenotypic characteristics according to their original skin phototype. Total melanin concentrations were 4.9 times higher in the darker skin phototype (IV-VI) melanocytes when compared to the cells from lighter skin phototypes (I-III). Also phaeomelanin contents were higher (2.5 times) in the skin phototype (IV-VI) melanocytes which implies that the cells from light skin types contain less melanin, but a relatively high proportion of phaeomelanin. After UVB irradiation a stronger induction of endonuclease sensitive sites was found for melanocytes with a lower level of total melanin and a high content of pheomelanin. By measuring the clone forming ability in different melanocyte cultures after UVB irradiation, significant better survival was found in case of the cells with the higher melanin content. Despite the large variations in melanin content, no significant difference in survival after UVA irradiation could be demonstrated in this way. Our results suggest a protective effect of melanin for UVB and indicate the importance of the measurements of melanin content and composition when different parameters of UV-induced damage are studied in melanin producing cells.     

Diffuse Reflectance Spectroscopy as a Tool to Measure the Absorption Coefficient in Skin: South African Skin Phototypes

In any laser skin treatment, the optical properties (absorption and scattering coefficients) are important parameters. The melanin content of skin influences the absorption of light in the skin. The spread in the values of the absorption coefficients for the South African skin phototypes are not known. A diffuse reflectance probe consisting of a ring of six light delivery fibers and a central collecting fiber was used to measure the diffused reflected light from the arms of 30 volunteers with skin phototypes I–V (on the Fitzpatrick scale). The absorption coefficient was calculated from these measurements. This real‐time in vivo technique was used to determine the absorption coefficient of sun‐exposed and ‐protected areas on the arm. The range of typical absorption coefficients for the South African skin phototypes is reported. The values for the darker South African skin types were much higher than was previously reported for darker skin phototypes. In the analysis, the contributions of the eumelanin and pheomelanin were separated, which resulted in improved curve fitting for volunteers of southern Asian ethnicity without compromising the other groups.     

Relationship between Skin Color and Sun Exposure History: A Statistical Classification Approach

In this study our aim was to determine the biophysical values of constitutive skin color in Caucasians and to define the correlation between skin color and phototype assessed according to the Fitzpatrick method. Constitutive skin color was measured on the buttock, with a Minolta CR-200 colorimeter, in a population of 557 consecutive subjects belonging to phototype categories I, II, III and IV. The colorimeter expresses the results in five different color systems. We used the “Yxy” and L*a*b* systems, which are the most widespread in dermatology. Statistical analysis of the data showed that the “Yxy” system is even more discriminant than the L*a*b* system when the Fitzpatrick classification scheme is adopted as the reference and shows a poor ability to correctly classify the intermediate phototypes (II and III). On the contrary the “Yxy” system performs well in distinguishing phototypes I and IV. To establish whether this low discriminating capacity for phototypes II and III is related to a low discriminating capacity of the method suggested by Fitzpatrick or by our procedure, an objective technique (minimal erythemal dose) should be used to evaluate the percentage errors of classification of both the Fitzpatrick method and instrumental measurement of skin color. The results of such a study are extremely important because the evaluation of skin color is objective, simple and has potential applications in dermatology and cosmetology.     

ULTRAVIOLET ERYTHEMA SENSITIVITY IN ANAMNESTIC (I-IV) and PHOTOTESTED (1–4) CAUCASIAN SKIN PHOTOTYPES: THE NEED FOR A NEW CLASSIFICATION SYSTEM

Abstract— The anamnestic skin phototypes (ASP) I-IV^1,2 of 21 Caucasian volunteers were compared with their phototested skin phototypes (PSP) using solar simulating, broadband UV radiation. The Commission Internationale de' éclairage (CIE)-weighted (i.e. erythemally effective) minimal erythema doses (MED) for solar simulating radiation varied from 20 mJ/cm² (PSP type 1) to 57 mJ/cm² (PSP type 4). In only 11 of 21 volunteers did the ASP (I-IV) and PSP (1–4) classifications coincide, and the MED values of the volunteers within the different ASP groups (I-IV) overlapped considerably. To compare the reactivity to erythematogenic radiation of different wavelengths, narrowband monochromator irradiations were performed at 298 nm, 310 nm and 330 nm. The CIE-weighted MED values at these wavelengths (20–80 mJ/cm²) corresponded well with those obtained in the broadband testing. Our results indicate that, with classification by interrogation, Caucasian skin can reliably be classified into only two subtypes, corresponding to Fitzpatrick phototypes I–III and phototype IV, respectively. A classification into four sensitivity types can be achieved by phototesting, only. We propose that the concept of ASP should be used with caution. The concept of PSP 1–4 should be favored.     

Relationship between vitamin D status and skin phototype in general adult population

A link between bone mineral density and skin color has been reported recently, and pigmentation has been shown to affect cutaneous vitamin D production. In the present study, we investigated the relationship between phototype, global self-assessed sun exposure, geographical location and vitamin D serum levels in 1191 French adults. When the factors were analyzed separately, individuals with lower phototypes as well as those with lower sun exposure showed significantly lower levels of vitamin D than those with darker phototypes or those with higher sun exposure. However, when factors were analyzed as a whole, the vitamin D status was no longer linked with the phototype, but with sun exposure and geographical location. Since phototypes and global self-assessments of sun exposure were positively linked, our data suggest that lower vitamin D levels in fair-skinned individuals are due to their sun exposure behavior.     

Constraining shape smoothness in multivariate curve resolution–alternating least squares

The resolution of complex multicomponent hyperspectral images with multivariate curve resolution–alternating least squares is mainly performed by using a limited number of constraints on the pure constituent distribution maps, such as non‐negativity or local constraints. This work proposes a constraint that works with the spatial information of the whole image and has been given the name shape smoothness constraint. Contrary to local constraints, shape smoothness constraint imposes a global character on the distribution map pattern. It uses two‐dimensional P‐splines to enforce smoothness of the global spatial features of the distribution maps generated within the alternating least squares procedure. This allows revealing main pattern(s) in the spatial data leaving high‐frequency signals, corresponding to fine‐scale structures in the image. This approach has been successfully applied on several simulated examples where imposing shape smoothness resulted in the recovery of the correct pattern for the image objects, which in turn provided more accurate distribution maps and spectral profiles. It was also shown that when information about the smoothness of the pattern(s) of the image constituents holds, the constraint can be a flexible and robust alternative for the resolution of real hyperspectral imaging data. Copyright © 2015 John Wiley & Sons, Ltd.     

Urocanic Acid Concentration and Photoisomerization in Caucasian Skin Phototypes

Abstract— To investigate the relationship between erythemal sensitivity of the skin to U V radiation and epidermal urocanic acid (UCA) concentration, 45 healthy volunteers of anamnestic skin phototypes (ASP) I-IV were studied. In 16 of the subjects, we analyzed UCA photoisomerization after graded UVB exposures. The median and mean total UCA concentration in unirradiated skin was 22.4 and 35.3 nmol/cm², and no statistically significant difference in total UCA concentrations was detectable either between ASP I through II and III through IV or between the phototested skin type (PSP) groups 1 through 2 and 3 through 4. The relative amount of the cis -isomer varied between 3 and 35%, with median and mean values of 7 and 12%, respectively. No statistically significant difference in absolute or relative cis -UCA concentrations was detectable between ASP I through II and III through IV, but a significantly lower absolute ( P < 0.009) and relative ( P < 0.002) cis -UCA concentration in unirradiated skin was recorded in PSP groups 1 through 2, compared to types 3 through 4. In all tested subjects, an erythemally weighted dose of 1 mj/cm²sufficed to cause trans - to cis -UCA isomerization. When comparing photosensitive (skin phototype I) and phototolerant (phototypes III and IV) individuals, who were irradiated with a reference 5 mJ/cm²UV dose or with fractions of 0.1-1.0 of their individual minimal erythema dose values, no skin phototype-dependent difference in ability to photoisomerize was discernible.     

Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis

The use of near infrared (NIR) hyperspectral imaging and hyperspectral image analysis for distinguishing between hard, intermediate and soft maize kernels from inbred lines was evaluated. NIR hyperspectral images of two sets (12 and 24 kernels) of whole maize kernels were acquired using a Spectral Dimensions MatrixNIR camera with a spectral range of 960-1662 nm and a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm. Exploratory principal component analysis (PCA) was used on absorbance images to remove background, bad pixels and shading. On the cleaned images, PCA could be used effectively to find histological classes including glassy (hard) and floury (soft) endosperm. PCA illustrated a distinct difference between glassy and floury endosperm along principal component (PC) three on the MatrixNIR and PC two on the sisuChema with two distinguishable clusters. Subsequently partial least squares discriminant analysis (PLS-DA) was applied to build a classification model. The PLS-DA model from the MatrixNIR image (12 kernels) resulted in root mean square error of prediction (RMSEP) value of 0.18. This was repeated on the MatrixNIR image of the 24 kernels which resulted in RMSEP of 0.18. The sisuChema image yielded RMSEP value of 0.29. The reproducible results obtained with the different data sets indicate that the method proposed in this paper has a real potential for future classification uses.     

Prediction of some quality attributes of lamb meat using near-infrared hyperspectral imaging and multivariate analysis

The goal of this study was to explore the potential of near-infrared (NIR) hyperspectral imaging in combination with multivariate analysis for the prediction of some quality attributes of lamb meat. In this study, samples from three different muscles (semitendinosus (ST), semimembranosus (SM), longissimus dorsi (LD)) originated from Texel, Suffolk, Scottish Blackface and Charollais breeds were collected and used for image acquisition and quality measurements. Hyperspectral images were acquired using a pushbroom NIR hyperspectral imaging system in the spectral range of 900–1700 nm. A partial least-squares (PLS) regression, as a multivariate calibration method, was used to correlate the NIR reflectance spectra with quality values of the tested muscles. The models performed well for predicting pH, colour and drip loss with the coefficient of determination (R²) of 0.65, 0.91 and 0.77, respectively. Image processing algorithm was also developed to transfer the predictive model in every pixel to generate prediction maps that visualize the spatial distribution of quality parameter in the imaged lamb samples. In addition, textural analysis based on gray level co-occurrence matrix (GLCM) was also conducted to determine the correlation between textural features and drip loss. The results clearly indicated that NIR hyperspectral imaging technique has the potential as a fast and non-invasive method for predicting quality attributes of lamb meat.     

Optical properties of human melanocytic nevi in vivo

We present an in vivo study of the optical properties of melanin present in melanocytic nevi of human subjects with Fitzpatrick skin type III (Caucasian descent) using optical spectroscopy. We show that the melanin absorption spectrum exhibits an exponential dependence on wavelength with a decay constant which follows a normal distribution characteristic of a random biological variable. Moreover, we demonstrate lack of correlation among melanin optical properties, melanin concentration and skin light scattering properties, which indicates that the true optical absorption of melanin can be measured free from confounding scattering effects. We also show that the average melanin absorption spectrum in vivo is in very good agreement with a previously reported oxygen photoconsumption action spectrum of melanin. Finally, we provide an overview of the emerging picture of the melanin absorption properties in vivo among various skin types and also among various skin lesions such as melanocytic nevi and melanoma.     

Hyperspectral NIR imaging for calibration and prediction: a comparison between image and spectrometer data for studying organic and biological samples

A hyperspectral image in the near infrared contains thousands of position-referenced spectra. After imaging reference materials of known composition it is possible to build Partial Least Squares (PLS) regression models for predicting unknown compositions from new images or spectra. In this paper a comparison is made between spectra from a hyperspectral image and spectra from two spectrometers: a scanning grating instrument with rotating sample holders and an FT-NIR instrument utilizing a fiber-optic probe. The raw spectra and the quality of the PLS calibration models and predictions are compared. Two sample datasets consist of a set of 13 designed artificial mixtures of pure constituents and a selection of 13 sampled cheeses. The prediction error from the hyperspectral image spectra is between that of the two spectrometers. For a typical food sample, the average bias [and replicate standard deviation] was -0.6% [0.5%] for protein and -0.2% [1.3%] for fat. Comparable values for the best spectrometer were -0.2% bias for protein and -0.5% for fat. Some of the advantages of working with hyperspectral images are highlighted: the simultaneous exploration of representations of both spectral and spatial data, and the analysis of concentration profiles and concentration maps all contribute to better characterization of organic and biological materials.     

Nir-chemical imaging study of acetylsalicylic acid in commercial tablets

Near Infrared Chemical Imaging (NIR-CI) is demonstrating an increasing interest in pharmaceutical research since it meets the challenging analytical needs of pharmaceutical quality and may serve as a versatile adjunct to conventional NIR spectroscopy in many fields.The direct analysis of samples by using hyperspectral imaging techniques, which provide a NIR spectrum in each pixel of the image, generates a big amount of information from one sample. Focusing the interest in pharmaceutical research, several chemometric algorithms are demonstrating their usefulness extracting the relevant information (i.e. quantitative determination of the component in one sample) in tablets with only one sample and without damaging it.In this work, a quantitative method to analyze different commercial Acetylsalicylic acid tablets is proposed by using Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) method to the hyperspectral image and without any previous calibration model. For this purpose, a large concentration range of active pharmaceutical ingredient (ASA, Acetylsalicylic acid in this work), between 82% and 12%, was covered depending on the manufacturer. MCR-ALS allowed obtaining a concentration maps for acetylsalicylic acid and therefore, consequent analysis of the ASA distribution in the tablet was developed by using the histograms of the distribution of concentration.Results certified the good distribution of ASA despite the different origins of the tablets. Moreover, the obtained values of concentration showed a very good concordance with the nominal value of ASA. As a matter of fact, the quality of the results demonstrated the useful of encompassing NIR-CI techniques with MCR-ALS and, consequently, the well development on the production of Acetylsalicylic acid tablets.     

基于高光谱技术的培养基上细菌菌落分类方法研究

利用高光谱技术对培养基上细菌(大肠杆菌、李斯特菌和金黄色葡萄球菌)菌落进行快速识别和分类。采集琼脂培养基上细菌菌落的高光谱反射图像(390~1040 nm),在对波段差图像进行大津阈值分割的基础上自动提取细菌菌落光谱,并建立细菌分类检测的全波长和简化偏最小二乘判别( PLS-DA)模型。全波长模型对预测集样本的分类准确率和置信预测分类准确率分别为100%和95.9%。此外,利用竞争性自适应重加权算法( CARS)、遗传算法( GA)和最小角回归算法( LARS-Lasso)进行波长优选并建立对应简化模型。其中,CARS简化模型在精度、稳定性及分类准确率方面均优于GA和LARS-Lasso简化模型,其对预测集样本的分类准确率和置信预测分类准确率分别达到了100%和98.0%。研究表明,高光谱是一种细菌菌落高精度、快速、无损识别检测的有效方法。简化模型中优选的波长可以为开发低成本检测仪器提供理论依据。     

The importance of the depth distribution of melanin in skin for DNA protection and other photobiological processes

Melanin pigments are important regulators for the evolution of essential functions of human skin. The concentration of melanin, as well as its depth distribution, is strongly affected by ultraviolet radiation. In un-tanned skin, melanin pigments are found only in the basal layer of the epidermis, while in tanned skin it is distributed throughout the epidermis. So far, mainly the amount of melanin, and not its distribution, has been considered in view of skin photobiology. With an advanced radiative transfer model we investigate, for the first time, how the depth distribution of melanin influences the amount of ultraviolet radiation that reaches living cells in the epidermis, and thus can damage the DNA in the cells. The simulations are performed for average pigmented skins (type III-IV). A surprisingly large factor, up to 12, is found between the ultraviolet protection of skin with melanin distributed throughout the epidermis, and skin with melanin only in the basal layer of the epidermis. We also show that the synthesis of previtamin D3, in skin, can vary with more than 100% if the depth distribution of melanin is changed, while the degradation of folate in dermal blood is almost un-affected by variations in the melanin depth distribution.     

Rapid detection of Escherichia coli contamination in packaged fresh spinach using hyperspectral imaging

A rapid method based on hyperspectral imaging for detection of Escherichia coli contamination in fresh vegetable was developed. E. coli K12 was inoculated into spinach with different initial concentrations. Samples were analyzed using a colony count and a hyperspectroscopic technique. A hyperspectral camera of 400-1000 nm, with a spectral resolution of 5 nm was employed to acquire hyperspectral images of packaged spinach. Reflectance spectra were obtained from various positions on the sample surface and pretreated using Sawitzky-Golay. Chemometrics including principal component analysis (PCA) and artificial neural network (ANN) were then used to analyze the pre-processed data. The PCA was implemented to remove redundant information of the hyperspectral data. The ANN was trained using Bayesian regularization and was capable of correlating hyperspectral data with number of E. coli. Once trained, the ANN was also used to construct a prediction map of all pixel spectra of an image to display the number of E. coli in the sample. The prediction map allowed a rapid and easy interpretation of the hyperspectral data. The results suggested that incorporation of hyperspectral imaging with chemometrics provided a rapid and innovative approach for the detection of E. coli contamination in packaged fresh spinach.     

基于拉曼光谱成像的食品中化学添加剂的无损检测

基于拉曼光谱成像技术对小麦粉中过氧化苯甲酰和L-抗坏血酸进行快速、 无损、 原位检测, 并对2种添加剂的空间分布进行了可视化研究. 采用实验室自行搭建的线扫描式拉曼光谱成像系统, 激发光源波长为785 nm, 有效光谱范围为0~2885.7 cm^-1. 分别在小麦粉中添加含量为0.1%~30%的过氧化苯甲酰和L-抗坏血酸, 对制备的样品进行拉曼光谱扫描, 选取感兴趣区域的光谱信号进行平均, 得到平均光谱代表该样品的拉曼信息. 分别选取过氧化苯甲酰和L-抗坏血酸的2个特征峰, 与该物质在小麦粉中的含量建立线性关系, 其决定系数R²分别为0.9828 和0.9912. 采集的特征波段拉曼图像经过自适应迭代重加权惩罚最小二乘(airPLS)方法扣除荧光背景后, 选取合适的特征峰强度作为阈值, 对校正拉曼图像进行二值化分析, 得到添加物的空间分布可视化图像. 该方法与点检测拉曼技术相比, 具有检测结果准确且检测时间较短的优势, 且可以实现不均匀样品中多种物质的同时检测与分布可视化.     

Rapid prediction of moisture content of dehydrated prawns using online hyperspectral imaging system

Because the shape of prawn is not round, spectroscopy instruments cannot measure the spectra of the whole prawn without containing background information. In this study, an online hyperspectral imaging system in the spectral region of 380–1100 nm was developed to determine the moisture content of prawns at different dehydrated levels. Hyperspectral images of prawns were acquired at different dehydration periods. The spectra of prawns then were extracted from hyperspectral images based on ‘Manual Prawn Mask’ and ‘Automatic Prawn Mask’, respectively. Spectral data were analyzed using partial least squares regression (PLSR) and least-squares support vector machines (LS-SVM) to establish the calibration models, respectively. Successive projections algorithm (SPA) was first applied for the optimal wavelength selection in the hyperspectral image analysis. Out of 482 wavelengths, only twelve wavelengths (428, 445, 544, 569, 629, 672, 697, 760, 827, 917, 958, and 999 nm) were selected by SPA as the optimum wavelengths for moisture prediction. Based on these optimum wavelengths, a multiple linear regression (MLR) calibration model was established and used to obtain the moisture distribution of each prawn. The overall results of this study revealed the potentiality of hyperspectral imaging as an objective and non-destructive method to obtain the content and distribution of moisture of prawns whose shapes are not round.     

基于高光谱成像结合分光光度技术的喷墨打印墨水种类鉴别方法

在法庭科学实践中,往往需要通过对文件中字迹墨水的成分分析来精确地判定检材和样本文件的同一性。利用高光谱成像和分光光度技术结合化学计量法,提出了一种对喷墨打印墨水分类的方法。采集14台不同品牌、型号的四色喷墨打印墨水高光谱数据和色度值。计算出平均色度值后进行PCA降维处理和K-Means聚类分析,将样品初步分类。之后应用LightGBM模型、XGBoost模型和SVM模型共三种分类模型,以1:4的比例确定测试集和训练集,对聚类分析结果中每一类别的样品进行逐一鉴别。结果表明,LightGBM和XGBoost对四色样品的分类精度都能达到95%以上,SVM的分类精度为100%。提出的方法能够做到无损、准确、快速地将不同品牌乃至型号的喷墨打印墨水进行区分。     

Methodology for fiber-optic Raman mapping and FTIR imaging of metastases in mouse brains

The objectives of this study were to optimize the preparation of pristine brain tissue to obtain reference information, to optimize the conditions for introducing a fiber-optic probe to acquire Raman maps, and to transfer previous results obtained from human brain tumors to an animal model. Brain metastases of malignant melanomas were induced by injecting tumor cells into the carotid artery of mice. The procedure mimicked hematogenous tumor spread in one brain hemisphere while the other hemisphere remained tumor free. Three series of sections were prepared consecutively from whole mouse brains: dried, thin sections for FTIR imaging, hematoxylin and eosin-stained thin sections for histopathological assessment, and pristine, 2-mm thick sections for Raman mapping. FTIR images were recorded using a spectrometer with a multi-channel detector. Raman maps were collected serially using a spectrometer coupled to a fiber-optic probe. The FTIR images and the Raman maps were segmented by cluster analysis. The color-coded cluster memberships coincided well with the morphology of mouse brains in stained tissue sections. More details in less time were resolved in FTIR images with a nominal resolution of 25 microm than in Raman maps collected with a laser focus 60 microm in diameter. The spectral contributions of melanin in tumor cells were resonance enhanced in Raman spectra on excitation at 785 nm which enabled their sensitive detection in Raman maps. Possible reasons why metastatic cells of malignant melanomas were not identified in FTIR images are discussed.