Discrimination of leukemias and non-leukemic cancers in blood serum samples of children and adolescents using a Raman spectral model.

This study aimed to identify the differences presented in the Raman spectrum of blood serum from normal subjects compared to leukemic and non-leukemic subjects and the differences between the leukemics and non-leukemics, correlating the spectral differences with the biomolecules. Serum samples from children and adolescents were subjected to Raman spectroscopy (830 nm, laser power 350 mW; n = 566 spectra, being 72 controls, 269 leukemics, and 225 non-leukemics). Exploratory analysis based on principal component analysis (PCA) of the serum sample's spectra was performed. Classification models based on partial least squares discriminant analysis (PLS-DA) were developed to classify the spectra into normal, leukemic, and non-leukemic, as well as to discriminate spectra of leukemic from non-leukemic. The exploratory analysis showed principal components with peaks related to amino acids, proteins, lipids, and carotenoids. The spectral differences between normal, leukemic, and non-leukemic showed features assigned to proteins (serum features), amino acids, and carotenoids. The PLS-DA model classified the spectra of the normal group versus leukemic and non-leukemic groups with accuracy of 66%, sensitivity of 99%, and specificity of 57%. The PLS-DA discriminated the spectra of the leukemic and non-leukemic groups with accuracy of 67%, sensitivity of 72%, and specificity of 60%. The study showed that Raman spectroscopy is a technique that may be used for the biochemical differentiation of leukemias and other types of cancer in serum samples of children and adolescents. Nevertheless, building an extensive data library of Raman spectra from serum samples of controls, leukemics, and non-leukemics of different age groups is necessary to understand the findings better.

Paraconsistent Annotated Logic Algorithms Applied in Management and Control of Communication Network Routes.

This paper presents a computational method based on non-classical logic dedicated to routing management and information stream control in communication networks. Paraconsistent logic (PL) was used to create an algorithmic structure whose main property is to accept contradiction. Moreover, a computational structure, the denominated paraconsistent data analyzer (PDAPAL2v), was constructed to perform routing management in communication networks. Direct comparisons of PDAPAL2v with a classical logic system that simulates routing conditions were made in the laboratory. In the conventional system, the paraconsistent algorithms were considered as binary logic gates, and in the tests, the same adjustment limits of PDAPAL2v were applied. Using a database with controlled insertion of noise, we obtained an efficacy of 97% in the detection of deteriorated packets with PDAPAL2v and 72% with the conventional simulation system. Functional tests were carried out, showing that PDAPAL2v is able to assess the conditions and degradation of links and perform the analysis and correlation of various inputs and variables, even if the signals have contradictory values. From practical tests in the laboratory, the proposed method represents a new way of managing and controlling communication network routes with good performance.

Biochemical characterization of pathogenic bacterial species using Raman spectroscopy and discrimination model based on selected spectral features.

This study aimed to evaluate the differences in the Raman spectra of nine clinical species of bacteria isolated from infections (three Gram-positive and six Gram-negative species), correlating the spectra with the chemical composition of each species and to develop a classification model through discriminant analysis to categorize each bacterial strain using the peaks with the most significant differences. Bacteria were cultured in Mueller Hinton agar and a sample of biomass was harvested and placed in an aluminum sample holder. A total of 475 spectra from 115 different strains were obtained through a dispersive Raman spectrometer (830 nm) with exposure time of 50 s. The intensities of the peaks were evaluated by one-way analysis of variance (ANOVA) and the peaks with significant differences were related to the differences in the biochemical composition of the strains. Discriminant analysis based on quadratic distance applied to the peaks with the most significant differences and partial least squares applied to the whole spectrum showed 89.5% and 90.1% of global accuracy, respectively, for classification of the spectra in all the groups. Raman spectroscopy could be a promising technique to identify spectral differences related to the biochemical content of pathogenic microorganisms and to provide a faster diagnosis of infectious diseases.

Detecting creatine excreted in the urine of swimming athletes by means of Raman spectroscopy.

High-level sport requires analysis of athletes' metabolic conditions in order to improve the training. Raman spectroscopy can be used to assess urinary composition advantageously when compared to conventional methods of urinalysis. In this work, Raman spectroscopy has been employed to detect creatine in urine of professional swimmers before and after training compared to sedentaries. It has been collected urine samples from five swimmers before and immediately after 150 min of swimming and submitted to Raman spectroscopy (830 nm excitation, 350 mW laser power, 20 s integration time) and compared to the urine from a control group (14 sedentary subjects). The Raman spectra of urine from four swimmers after training showed peaks related to creatine at 829, 915, 1049, and 1397 cm-1, besides peaks referred to urea, creatinine, ketone bodies, and phosphate. A spectral model estimated the concentration of creatine to be from 0.26 to 0.72 g/dL in the urine of these athletes. The presence of this metabolic biomarker in the urine of some swimmers suggests a metabolic profile influenced by the diet, supplementation, individual metabolism, and the self-response to the training. Raman spectroscopy allows a rapid and reliable detection of creatine excreted in the urine of swimming athletes, which may be used to adjust the nutrition/supplementation of each individual as well as the individual response and energy consumption depending on the type and duration of the training.

Normal-subtracted preprocessing of Raman spectra aiming to discriminate skin actinic keratosis and neoplasias from benign lesions and normal skin tissues.

The differences in the biochemistry of normal and cancerous tissue could be better exploited by Raman spectroscopy when the spectral information from normal tissue is subtracted from the abnormal tissues. In this study, we evaluated the use of the normal-subtracted spectra to evidence the biochemical differences in the pre-cancerous and cancerous skin tissues compared with normal skin, and to discriminate the groups with altered tissues with respect to the normal sites. Raman spectra from skin tissues [normal (Normal), benign (dermatitis-BEN), basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and actinic keratosis (KER)] were obtained in vivo (Silveira et al., 2015, doi: https://doi.org/10.1002/lsm.22318) and used to develop the spectral model. The mean spectrum of the normal sites (circumjacent to each lesion) from each subject was calculated and subtracted from each individual spectrum of that particular subject independently of the group (Normal, BEN, BCC, SCC, KERAT). The mean spectra of each altered group and the mean spectra of the differences were firstly evaluated in terms of biochemical contribution or differentiation comparing the normal site. Then, the normal-subtracted spectra were submitted to discriminant models based on partial least squares and principal components regression (PLS-DA and PCR-DA), and the discrimination were compared with the model using non-subtracted spectra. Results showed that the peaks of nucleic acids, lipids (triolein) and proteins (elastin and collagens I, III, and IV) were significantly different in the lesions, higher for the pre- and neoplastic lesions compared with normal and benign. The PLS-DA showed that the groups could be discriminated with 90.3% accuracy when the mean-subtracted spectra were used, contrasting with 75.1% accuracy when the non-subtracted spectra were used. Also, when discriminating non-neoplastic tissue (Normal + BEN) from pre- and neoplastic sites (BCC + SCC + KERAT), the accuracy increases to 92.5% for the normal-subtracted compared with 85.3% for the non-subtracted. The subtraction of the mean normal spectrum from the subject obtained circumjacent to each lesion could significantly increase the diagnostic capability of the Raman-based discrimination algorithm.

Detecting active ingredients of insect repellents and sunscreens topically in skin by Raman spectroscopy.

We present the use of Raman spectroscopy for determination of functional characteristics of insect repellents and sunscreens by identifying the active ingredients of these products applied topically to the skin. Commercial formulations of insect repellents and sunscreens (SPF 15 and 30) were obtained, and Raman spectra were obtained from the formulations and from volunteers' skins with topical applications of such products compared to controls. The results indicated that, for insect repellents, the peaks at 527 and 1003 cm - 1 were markers of the presence of the active ingredient diethyl toluamide in the skin, while for sunscreens, the peaks at 1177, 1288, and 1611 cm - 1, associated to octinoxate, benzophenone-3, and avobenzone, were markers of the presence of solar filters in the skin. The results suggested reliability in the use of Raman spectroscopy to identify the active ingredients of insect repellents and sunscreens topically applied on the skin; the applied methodology can be used to determine the functional characteristics of topical products with similar characteristics.

Detecting urine metabolites related to training performance in swimming athletes by means of Raman spectroscopy and principal component analysis.

Raman spectroscopy (RS) is a vibrational technique that is suitable for performing biochemical analyses in human tissues and fluids. This work has investigated the identification of biochemical markers due to physical performance in the urine of swimming athletes. This was achieved by means of the Raman features that were found before and after the swimming training compared to the sedentary control subjects. These particular biochemical marker identifications refer to and infer the physiological status of individuals. The urine samples (single stream) were collected before and after the training (velocity, middle distance and distance) of professional swimmers, as well as from sedentary subjects (control). The urine samples were submitted to RS (830 nm excitation, 350 mW, 400-1800 cm-1 spectral range, 4 cm-1 resolution) and the spectra after the training were compared to the spectra before training, and subsequently, to the control subjects. The principal component analysis (PCA) was employed in order to identify the biochemicals that were responsible for the spectral differences. The Raman features of the urine samples after training showed peaks that were related to common urine metabolites, such as urea and creatinine. PCA analysis also revealed Raman features that were attributed to other metabolites, such as creatine, ketone bodies, phosphate and nitrogenous compounds in the swimmers after training. RS was a rapid and reliable technique for the evaluation of urine metabolites that were related to the physical performance of high-level swimmers, which then allowed for an accurate assessment and a control of their physiological efficiencies.

Raman spectroscopy applied to identify metabolites in urine of physically active subjects.

Raman spectroscopy is a rapid and non-destructive technique suitable for biological fluids analysis. In this work, dispersive Raman spectroscopy has been employed as a rapid and nondestructive technique to detect the metabolites in urine of physically active subjects before and after vigorous 30min pedaling or running compared to sedentary subjects. For so, urine samples from 9 subjects were obtained before and immediately after physical activities and submitted to Raman spectroscopy (830nm excitation, 250mW laser power, 20s integration time) and compared to urine from 5 sedentary subjects. The Raman spectra of urine from sedentary showed peaks related to urea, creatinine, ketone bodies, phosphate and other nitrogenous compounds. These metabolic biomarkers presented peaks with different intensities in the urine of physically active individuals after exercises compared to before, measured by the intensity of selected peaks the Raman spectra, which means different concentrations after training. These peaks presented different intensity values for each subject before physical activity, also behaving differently compared to the post-training: some subjects presented increase while others decrease the intensity. Raman spectroscopy may allow the development of a rapid and non-destructive test for metabolic evaluation of the physical training in active and trained subjects using urine samples, allowing nutrition adjustment with the sport's performance.

Quantifying glucose and lipid components in human serum by Raman spectroscopy and multivariate statistics.

Raman spectroscopy has been employed in the quantitative analysis of biochemical components in human serum. This study aimed to develop a spectral model to estimate the concentration of glucose and lipid fractions in human serum, thus evaluating the feasibility of Raman spectroscopy technique for diagnostic purposes. A total of 44 samples of blood serum were collected from volunteers submitted to routine blood biochemical assay analysis. The biochemical concentrations of glucose, triglycerides, cholesterol, and high-density and low-density lipoproteins (HDL and LDL) were obtained by colorimetric method. Serum samples (200 µL) were submitted to Raman spectroscopy (830 nm, 250 mW, 50-s accumulation). The spectra of sera present peaks related to the main constituents, particularly proteins and lipids. A quantitative model based on partial least squares (PLS) regression has been developed to estimate the concentration of these compounds, taking the biochemical concentrations assayed by the colorimetric method as sample's actual concentrations. The PLS model based on leave-one-out cross-validation approach estimated the concentration of triglycerides and cholesterol with r = 0.98 and 0.96, and root mean square error of 35.4 and 15.9 mg/dL, respectively. For the other biochemicals, the r was ranging from 0.75 to 0.86. These results evidenced the possibility of performing biochemical assay in blood serum samples by Raman spectroscopy and PLS regression and may be employed as a means of diagnosis in routine clinical analysis.

Biochemical changes on the repair of surgical bone defects grafted with biphasic synthetic micro-granular HA + ß-tricalcium phosphate induced by laser and LED phototherapies and assessed by Raman spectroscopy.

This work aimed the assessment of biochemical changes induced by laser or LED irradiation during mineralization of a bone defect in an animal model using a spectral model based on Raman spectroscopy. Six groups were studied: clot, laser (λ = 780 nm; 70 mW), LED (λ = 850 ± 10 nm; 150 mW), biomaterial (biphasic synthetic micro-granular hydroxyapatite (HA) + ß-tricalcium phosphate), biomaterial + laser, and biomaterial + LED. When indicated, defects were further irradiated at a 48-h interval during 2 weeks (20 J/cm2 per session). At the 15th and 30th days, femurs were dissected and spectra of the defects were collected. Raman spectra were submitted to a model to estimate the relative amount of collagen, phosphate HA, and carbonate HA by using the spectra of pure collagen and biomaterials composed of phosphate and carbonate HA, respectively. The use of the biomaterial associated to phototherapy did not change the collagen formation at both 15 and 30 days. The amount of carbonate HA was not different in all groups at the 15th day. However, at the 30th day, there was a significant difference (ANOVA, p = 0.01), with lower carbonate HA for the group biomaterial + LED compared to biomaterial (p < 0.05). The phosphate HA was higher in the groups that received biomaterial grafts at the 15th day compared to clot (significant for the biomaterial; p < 0.01). At the 30th day, the phosphate HA was higher for the group biomaterial + laser, while this was lower for all the other groups. These results indicated that the use of laser phototherapy improved the repair of bone defects grafted with the biomaterial by increasing the deposition of phosphate HA.

Paraconsistent analysis network applied in the treatment of Raman spectroscopy data to support medical diagnosis of skin cancer.

Paraconsistent logic (PL) is a type of non-classical logic that accepts contradiction as a fundamental concept and has produced valuable results in the analysis of uncertainties. In this work, algorithms based on a type of PL-paraconsistent annotated logic of two values (PAL2v)-are interconnected into a network of paraconsistent analysis (PANnet). PANnet was applied to a dataset comprising 146 Raman spectra of skin tissue biopsy fragments of which 30 spectra were determined to represent normal skin tissue (N), 96 were determined to represent tissue with basal cell carcinoma, and 19 were determined to be tissue with melanoma (MEL). In this database, paraconsistent analysis was able to correctly discriminate 136 out of a total of 145 fragments, obtaining a 93.793 % correct diagnostic accuracy. The application of PAL2v in the analysis of Raman spectroscopy signals produces better discrimination of cells than conventional statistical processes and presents a good graphical overview through its associated lattice structure. The technique of PAL2v-based data processing can be fundamental in the development of a computational tool dedicated to support the diagnosis of skin cancer using Raman spectroscopy.

Discriminating neoplastic and normal brain tissues in vitro through Raman spectroscopy: a principal components analysis classification model.

BACKGROUND AND OBJECTIVE: Because of their aggressiveness, brain tumors can lead to death within a short time after diagnosis. Optical techniques such as Raman spectroscopy may be a technique of choice for in situ tumor diagnosis, with potential use in determining tumor margins during surgery because of its ability to identify biochemical changes between normal and tumor brain tissues quickly and without tissue destruction. METHODS: In this work, fragments of brain tumor (glioblastoma, medulloblastoma, and meningioma) and normal tissues (cerebellum and meninges) were obtained from excisional intracranial surgery and from autopsies, respectively. Raman spectra (dispersive spectrometer, 830 nm 350 mW, 50 sec accumulation, total 172 spectra) were obtained in vitro on these fragments. It has been developed as a model to discriminate between the spectra of normal tissue and tumors based on the scores of principal component analysis (PCA) and Euclidean distance. RESULTS: ANOVA indicated that the scores of PC2 and PC3 show differences between normal and tumor groups (p<0.05) which could be employed in a discrimination model. PC2 was able to discriminate glioblastoma from the other tumors and from normal tissues, showing featured peaks of lipids/phospholipids and cholesterol. PC3 discriminated medulloblastoma and meningioma from normal tissues, with the most intense spectral features of proteins. PC3 also discriminated normal tissues (meninges and cerebellum) by the presence of cholesterol peaks. Results indicated a sensitivity and specificity of 97.4% and 100%, respectively, for this in vitro diagnosis of brain tumor. CONCLUSIONS: The PCA/Euclidean distance model was effective in differentiating tumor from normal spectra, regardless of the type of tissue (meninges or cerebellum).

Classification model based on Raman spectra of selected morphological and biochemical tissue constituents for identification of atherosclerosis in human coronary arteries.

This study presents the results of Raman spectroscopy applied to the classification of arterial tissue based on a simplified model using basal morphological and biochemical information extracted from the Raman spectra of arteries. The Raman spectrograph uses an 830-nm diode laser, imaging spectrograph, and a CCD camera. A total of 111 Raman spectra from arterial fragments were used to develop the model, and those spectra were compared to the spectra of collagen, fat cells, smooth muscle cells, calcification, and cholesterol in a linear fit model. Non-atherosclerotic (NA), fatty and fibrous-fatty atherosclerotic plaques (A) and calcified (C) arteries exhibited different spectral signatures related to different morphological structures presented in each tissue type. Discriminant analysis based on Mahalanobis distance was employed to classify the tissue type with respect to the relative intensity of each compound. This model was subsequently tested prospectively in a set of 55 spectra. The simplified diagnostic model showed that cholesterol, collagen, and adipocytes were the tissue constituents that gave the best classification capability and that those changes were correlated to histopathology. The simplified model, using spectra obtained from a few tissue morphological and biochemical constituents, showed feasibility by using a small amount of variables, easily extracted from gross samples.

Effects of different swimming exercise intensities on bone tissue composition in mice: a Raman spectroscopy study.

OBJECTIVE: Raman spectroscopy was employed to evaluate the effect of different swimming intensities on femoral bone composition in an animal model. BACKGROUND DATA: Intense swimming exercise may affect bone mineralization, and Raman technique has been shown to be effective in evaluating tissue composition (phosphate minerals and carbonate apatites - bands at 960 and 1170 cm(-1), as well as collagen matrix - amide I band at 1660 cm(-1)). MATERIALS AND METHODS: Eighteen female Swiss Webster mice were separated into three groups (n = 6 per group) of sedentary (SED), and swimming with an intensity of 40% (PT-40) and 80% (PT-80) of the maximum load, with 6 weeks of training. Near-infrared Raman spectra (830 nm wavelength and 80 mW laser power) were obtained with a dispersive Raman spectrometer using a CCD camera and imaging spectrograph with 30-s integration time. Spectra were collected in the medial and lateral diaphysis of the femur and principal components analysis (PCA) was employed to extract features of the Raman bands of bone and to perform quantitative analysis. RESULTS: PC1 vector resembles Raman spectra and carries information about apatite minerals and some contribution from organic matrix. A statistically significant difference was found in the PC1 scores (ANOVA, p < 0.05), indicating lower mineral concentrations in the femur in both the PT-40 and PT-80 groups compared to the SED group. These results corroborated with the radiographic assessment of bone density. CONCLUSION: Raman technique associated with PCA statistics showed that intense swimming exercise may affect bone mineralization and remodeling in a mouse model of training.

Differentiating normal and basal cell carcinoma human skin tissues in vitro using dispersive Raman spectroscopy: a comparison between principal components analysis and simplified biochemical models.

OBJECTIVE: Raman spectroscopy has been used to detect spectral differences between normal and basocellular cell carcinoma (BCC) skin tissues that are related to biochemical alterations between tissues. BACKGROUND DATA: Raman spectroscopy is an analytic tool that could detect biochemical alterations in tissues, and its use would lead to real-time and less-invasive cancer diagnosis. METHODS: Raman spectra from human tissue fragments (normal and BCC) were obtained in a dispersive, near-infrared Raman spectrometer (laser parameters: 830 nm, 80 mW) with a CCD detector. Spectral changes between normal and BCC were analyzed with a principal components analysis (PCA) algorithm and a simplified biochemical model based on the relative amount of collagen and cell fat extracted from tissue Raman spectra. RESULTS: Main spectral differences between these samples were in the region of 800 to 1,000 per centimeter and 1,200 to 1,300 per centimeter, corresponding to vibrational bands from lipids and proteins (C-C bonds and amide III, respectively). The diagnostic algorithm based on PCA and Mahalanobis distance applied to the scores of principal components vectors PC1 and PC2 could identify tissue with sensitivity and specificity of 89% and 93%, respectively, for the training group and 96% and 92% for the prospective group. The simplified biochemical model for collagen amount had sensitivity and specificity of 95% and 83% for the training group and 87% and 92% for the prospective group. CONCLUSIONS: Raman spectroscopy could differentiate between normal and BCC tissues in both the PCA and biochemical models, showing higher sensitivity and specificity for the PCA model, although the simplified biochemical model is easier to implement.

Force, reaction time, and precision of Kung Fu strikes.

The goal was to compare values of force, precision, and reaction time of several martial arts punches and palm strikes performed by advanced and intermediate Kung Fu practitioners, both men and women. 13 Kung Fu practitioners, 10 men and three women, participated. Only the men, three advanced and seven intermediate, were considered for comparisons between levels. Reaction time values were obtained using two high speed cameras that recorded each strike at 2500 Hz. Force of impact was measured by a load cell. For comparisons of groups, force data were normalized by participant's body mass and height. Precision of the strikes was determined by a high speed pressure sensor. The results show that palm strikes were stronger than punches. Women in the study presented, on average, lower values of reaction time and force but higher values of precision than men. Advanced participants presented higher forces than intermediate participants. Significant negative correlations between the values of force and precision and the values of force and reaction time were also found.

ProRaman: a program to classify Raman spectra.

The program ProRaman, developed for the Matlab platform, provides an interactive and flexible graphic interface to develop efficient algorithms to classify Raman spectra into two or three different classes. A set of preprocessing algorithms to decrease the variable dimensionality and to extract the main features which improve the correct classification ratio was implemented. The implemented classification algorithms were based on the Mahalanobis distance and neural network. To verify the functionality of the developed program, 72 spectra from human artery samples, 36 of which had been histopathologically diagnosed as non-diseased and 36 as having an atherosclerotic lesion, were processed using a combination of different preprocessing and classification techniques. The best result was accomplished when the variables were selected from the Raman spectrum shift range from 1200 to 1700 cm(-1), then preprocessed using wavelets for compression and principal component analysis for feature extraction and, finally, classified by a multilayer perceptron with one hidden layer with eight neurons.

Cytotoxicity of octal-bromide zinc phthalocyanine after photodynamic therapy with different light sources.

OBJECTIVE: The objective of this study was to investigate the cytotoxicity of octal-bromide zinc phthalocyanine (ZnPcBr8) at different concentrations (0.25, 0.5, and 1 microM) after irradiating HEp-2 cell cultures with two different light sources: a diode semiconductor laser (660 nm, 30 mW) or an LED (640 nm, 70 mW). In order to obtain comparative results, the irradiation parameters of both light sources were adjusted so that the amount of energy density delivered would be the same (4.5 J/cm2). BACKGROUND DATA: Numerous photosensitizers and light sources used in the treatment of human disease have been studied. Based on these studies, a comparative evaluation of two light sources used in photodynamic therapy (PDT) with ZnPcBr8 was proposed. MATERIALS AND METHODS: HEp-2 cells were incubated with ZnPcBr8 at different concentrations (0.25, 0.5, or 1 microM) for 1 h, irradiated with the diode semiconductor laser (660 nm at 30 mW for 300 sec; 4.5 J/cm2) or the LED laser (640 nm at 70 mW for 128 sec; 4.5 J/cm2), and then incubated in MEM medium for 1 or 24 h. The cells were analyzed using the MTT and trypan blue dye exclusion tests. RESULTS: The results demonstrated that the concentration of 1 microM of ZnPcBr8 was the most effective after PDT administered by both light sources. According to the MTT results, HEp-2-cell viability decreased by 97.96% 1 h after, and by 99.87% 24 h after irradiation with the diode semiconductor laser, and decreased by 94.03% 1 h after, and by 99.21% 24 h after irradiation with the LED. The results obtained using the trypan blue dye exclusion test confirmed the photodynamic efficacy of ZnPcBr8 employed with both light sources. With regard to HEp-2-cell viability, the following results were observed: a decrease of 98.73% 1 h after, and of 99.49% 24 h after irradiation with the diode semiconductor laser; and a decrease of 98.76% 1 h after, and of 99.23% 24 h after irradiation with the LED. CONCLUSIONS: According to our results with the irradiation parameters studied here, both the LED and diode semiconductor laser can be used for PDT in vitro, since both light sources had excellent photodynamic efficacy.

Fluorescence and reflectance spectroscopy for identification of atherosclerosis in human carotid arteries using principal components analysis.

OBJECTIVES: The aim of this work was to verify the differentiation between normal and pathological human carotid artery tissues by using fluorescence and reflectance spectroscopy in the 400- to 700-nm range and the spectral characterization by means of principal components analysis. BACKGROUND DATA: Atherosclerosis is the most common and serious pathology of the cardiovascular system. Principal components represent the main spectral characteristics that occur within the spectral data and could be used for tissue classification. MATERIALS AND METHODS: Sixty postmortem carotid artery fragments (26 non-atherosclerotic and 34 atherosclerotic with non-calcified plaques) were studied. The excitation radiation consisted of a 488-nm argon laser. Two 600-microm core optical fibers were used, one for excitation and one to collect the fluorescence radiation from the samples. The reflectance system was composed of a halogen lamp coupled to an excitation fiber positioned in one of the ports of an integrating sphere that delivered 5 mW to the sample. The photo-reflectance signal was coupled to a (1/4)-m spectrograph via an optical fiber. Euclidean distance was then used to classify each principal component score into one of two classes, normal and atherosclerotic tissue, for both fluorescence and reflectance. RESULTS: The principal components analysis allowed classification of the samples with 81% sensitivity and 88% specificity for fluorescence, and 81% sensitivity and 91% specificity for reflectance. CONCLUSIONS: Our results showed that principal components analysis could be applied to differentiate between normal and atherosclerotic tissue with high sensitivity and specificity.

Efeito da irradiação LED sobre a microinfiltração auricular em camundongo / Effect of LED irradiation on microcirculation of auricular mouse

A microcirculação pode ser considerada uma unidade funcional do sistema circulatório, sendo constituída pelos menores vasos distais. A radiação eletromagnética pode influenciar essa unidade agindo sobre esfíncteres pré-capilares. Essa influência pode gerar alterações na pressão hidrostática capilar, contribuindo na reabsorção de exsudato inflamatório e eliminando acúmulos de catabólitos intermediários. O efeito da radiação eletromagnética coerente na região do visível (vermelho) tem sido estudado principalmente no processo inflamatório, tendo sido encontrado aumento da permeabilidade capilar e vasodilatação. Contudo, poucos trabalhos foram realizados com o emprego de radiação eletromagnética não-coerente (LED) na região do visível. Dessa forma, o objetivo deste estudo foi observar o efeito do LED (640 :!: 20 nm, 100 m W, 1,77 cm2) sobre a microcirculação auricular em camundongos. Para tal, foram utilizados oito animais divididos em dois grupos (grupo placebo e grupo 3 J/cm2). A superfície auricular externa dos animais foi monitorada (durante 15 minutos) sob microscopia óptica (100x) e analisada com o auxílio do programa ImageJ. Observou-se uma diferença significativa no diâmetro dos vasos nos primeiros minutos após a irradiação, comprovando a existência de um efeito vasodilatador da radiação eletromagnética não-coerente, na região do vermelho, com os parâmetros testados. Esse resultado pode ser otimizado empregando-se maior fluência.

Microcirculation, considered a functional unit of the circulatory system, is composed of many smaller distal vessels. The electromagnetic radiation can influence this unit acting on the precapillary sphincters. This influence might generate alterations on the capillary hydrostatic pressure, contributing to the reabsortion of the inflammatory exudation and eliminating intermediate catabolite accumulation. The effect of coherent electromagnetic radiation on the visible region (red) has been studied mainly in the inflammatory process, and an increase in the capillary permeability and vasodilation was found. However few studies have been conducted on the use of noncoherent electromagnetic radiation (LED) in the visible region. Therefore, the aim of this study was to observe the effect of the LED (640:!: 20 nm, 100 mW, 1.77 cm2) on the auricular circulation of mice. To this end 8 animals were separated into 2 groups (placebo group and 3 J/cm2 group). The external auricular surface was monitored (15 minutes) under light microscopy (100X) and analysed with the help of IMAGEJ program. A significant difference was observed in the vessel diameter in the first minutes after the irradiation, proving the existence of a vasodilator effect of non coherent electromagnetic radiation in the red region of the tested parameters. This result can be optimized with the use of greater fluence.