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.

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.

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.

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 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.

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.

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.

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.

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.

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.

Comparison of force, power, and striking efficiency for a Kung Fu strike performed by novice and experienced practitioners: preliminary analysis.

This paper presents a comparison of force, power, and efficiency values calculated from Kung Fu Yau-Man palm strikes, when performed by 7 experienced and 6 novice men. They performed 5 palm strikes to a freestanding basketball, recorded by high-speed camera at 1000 Hz. Nonparametric comparisons and correlations showed experienced practitioners presented larger values of mean muscle force, mean impact force, mean muscle power, mean impact power, and mean striking efficiency, as is noted in evidence obtained for other martial arts. Also, an interesting result was that for experienced Kung Fu practitioners, muscle power was linearly correlated with impact power (p = .98) but not for the novice practitioners (p = .46).

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.

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.

Effects of treatment for manipulation of teeth and Er:YAG laser irradiation on dentin: a Raman spectroscopy analysis.

OBJECTIVE: The main purpose of this study was to evaluate the utility of Raman spectroscopy analysis as a research tool to study the effects of Er:YAG laser etching on dentin mineral and organic components. A secondary aim was to study the effects of the decontamination process and the storage procedure on dentin components. BACKGROUND DATA: There are no spectroscopy reports relating the effects of Er:YAG laser irradiation as an alternative to acid etching and the manipulation process on the dentin structure. METHODS: Twelve non-carious human third molars were divided in two main groups: stored in thymol solution (group A, n = 6) or autoclaved (group B, n = 6). The specimens were either etched with 37% phosphoric acid (control subgroup) or irradiated with Er:YAG laser. Irradiated samples were divided into the following subgroups: I, II, and III (80 mJ, 3 Hz, 30 sec; 120 mJ, 3 Hz, 30 sec; and 180 mJ, 3 Hz, 30 sec, respectively). Samples were analyzed by Raman spectroscopy. RESULTS: The mineral and organic dentin contents were more affected in autoclaved teeth than in the specimens stored in thymol. Peak area reduction in group A specimens treated with phosphoric acid and pulse energy of 80 mJ were the most conservative surface treatments regarding changes in the peak area of organic and inorganic dentin components. CONCLUSION: The autoclaving process and pulse energies of 120 and 180 mJ produced greater reduction of organic and inorganic contents in dentin, associated with greater reduction in the areas of 968, 1077, 1460, and 1670 cm(1) Raman peaks.

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.

Molecular analysis of Er:YAG laser irradiation on dentin.

The aim of this study was to evaluate by dispersive Raman spectroscopy the mineral and organic components of human dentin before and after laser irradiation and acid etching. The occlusal enamel of six non-carious human third molars was removed providing 6 dentin discs, which were divided in four quadrants each of them receiving a different surface treatment: etching with a 37% phosphoric acid gel (control); irradiation by Er:YAG laser (KaVo Key Laser II) with 80 mJ, 3 Hz, 30 s (group I); 120 mJ, 3 Hz, 30 s (group II); and 180 mJ, 3 Hz, 30 s (group III). The Raman spectra of normal (untreated) and treated dentin were analyzed and the mineral and the organic component were evaluated. Results were submitted to statistical analysis by ANOVA and Tukey's test at 5% significance level. The minerals and organic content were less affected in the control group and group I (p>0.05). Group II presented more reduction in mineral content (p<0.01) whereas in group III the inorganic (p<0.05) and organic (p<0.01) content were more affected. Dispersive Raman spectroscopy provided valid information of dentin chemical constituents with non-chemical sampling preparation.

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.

Low power laser radiation at 685 nm stimulates stem-cell proliferation rate in Dugesia tigrina during regeneration.

Today's scientific interest in tissue engineering for organ transplantations and regeneration from stem cells, allied with recent observations on biostimulation of tissues and cells by laser radiation, stands as a strong motivation for the present work, in which we examine the effects of the low power laser radiation onto planarians under regenerative process. To investigate those effects, a number of 60 amputated worms were divided in three study groups: a control group and two other groups submitted to daily 1 and 3 min long laser treatment sections at approximately 910 W/m2 power density. A 685 nm diode laser with 35 mW optical power was used. Samples were sent to histological analysis at the 4th, the 7th and the 15th days after amputation. A remarkable increase in stem cells counts for the fourth day of regeneration was observed when the regenerating worms was stimulated by the laser radiation. Our findings encourage further research works on the influence of optical radiation onto stem cells and tissue regeneration.

Laser light is capable of inducing proliferation of carcinoma cells in culture: a spectroscopic in vitro study.

OBJECTIVE: The objective of this work was to evaluate the influence of time, treatment, and wavelength, through the assessment of the cellular viability with MTT, on the proliferation of H.Ep.2 cells subjected to laser irradiation or not (lambda685 and lambda830 nm) with the same energy density (4 J/cm2). BACKGROUND DATA: Although malignant lesions have been studied for some time, there is not yet a definitive cure. Mortality could be reduced if lesions were diagnosed on initial phases of development. MATERIALS AND METHODS: H.Ep.2 cells were cultured in flasks and maintained in DMEN medium (10% FBS, 1% L-glutamine, and 1% antibiotic solution). For irradiation, cells were kept in 24 wells of the 96-well plaques containing DMEM medium (5% FBS, 1% L-glutamine, and 1% antibiotic solution), irradiated with lasers at lambda685- and lambda830-nm wavelength, and stained at 0, 6, 12, 24, and 48 h after irradiation. RESULTS: There was significant differences when the three groups were compared (p = 0.0087). There was significant difference for both irradiated groups, lambda685 nm (p = 0.0202) and lambda830 nm (p = 0.0324). Time of irradiation significantly influenced only the lambda685-nm group (p = 0.04). The wavelength had a significant influence (p = 0.013). CONCLUSION: Time, treatment, and wavelength significantly influenced the proliferation process of H.Ep.2 cells.

Analysis of the picosecond magneto-optical phenomena in scattering media of biological interest.

The behaviour of a magneto-optically active biological-like medium under picosecond optical excitation is analysed. The new technique is based on the fact that photons trapped in multiple scattering events inside the magneto-optical medium leave the medium with larger induced rotation angles, as they travel longer distances. Two- and three-dimensional displacements of the photons in the medium are separately analysed. The dependence of this effect on the applied magnetic field strength, the value of the magneto-optical constant of the medium and the standard deviation of the statistical distribution of the photons scattered inside the turbid medium are studied. The best values for the magnetic field and optical parameters of the biological medium are proposed for the experimental observation of the picosecond magneto-optical phenomena in scattering media of biological origin. We also make some prospective studies to evaluate the potential application of the magneto-optical effect as a tool for optical tissue biopsy. Values for the optimum magnetic field intensities and for the expected experimental sensitivity in diverse conditions are reported.