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Stability studies are essential to ensure that a drug maintains its qualities after leaving the production line until the end of the validity date. This study aimed to identify the alterations related to shelf time in commercial formulations containing dipyrone (metamizole) and to model the shelf time by Raman spectroscopy (830 nm, 350 mW). Spectra of nine commercial medicines containing dipyrone sodium were obtained during the validity period (valid samples) and after the expiration date (overdue samples) with shelf times ranging from 46 to 62 months. The spectra were compared to identify changes due to the dipyrone degradation and develop a model to estimate the shelf time. The Raman analysis of valid and overdue samples showed peaks due to the hydrolysis-oxidation of dipyrone: a blue-shift (N feature in the difference spectrum) of the bands assigned to aromatic and pyrazole rings due to the presence of the metabolite N-methylaminoantipyrine, a decrease in peaks related to the dissociation of − SO3Na due to the hydrolysis/oxidation, and an increase in peaks associated with sodium sulfate/disulfate. A regression model based upon principal component analysis (PCA) showed a strong correlation between shelf time and the PCA variable PC2 (Pearson’s correlation coefficient r = 0.804). The study showed the feasibility of Raman spectroscopy in identifying the degradation of dipyrone sodium to characterize the shelf time and use in the quality control of commercial medicines.

Axonotmesis causes sensorimotor and neurofunctional deficits, and its regeneration can occur slowly or not occur if not treated appropriately. Low-level laser therapy (LLLT) promotes nerve regeneration with the proliferation of myelinating Schwann cells to recover the myelin sheath and the production of glycoproteins for endoneurium reconstruction. This study aimed to evaluate the effects of LLLT on sciatic nerve regeneration after compression injury by means of the sciatic functional index (SFI) and Raman spectroscopy (RS). For this, 64 Wistar rats were divided into two groups according to the length of treatment: 14 days (n = 32) and 21 days (n = 32). These two groups were subdivided into four sub-groups of eight animals each (control 1; control 2; laser 660 nm; laser 808 nm). All animals had surgical exposure to the sciatic nerve, and only control 1 did not suffer nerve damage. To cause the lesion in the sciatic nerve, compression was applied with a Kelly clamp for 6 s. The evaluation of sensory deficit was performed by the painful exteroceptive sensitivity (PES) and neuromotor tests by the SFI. Laser 660 nm and laser 808 nm sub-groups were irradiated daily (100 mW, 40 s, energy density of 133 J/cm

No Brasil, a adulteração de combustíveis para obtenção de lucro é prática comum e motivo de preocupação por partes das autoridades, consumidores e da Agência Nacional de Petróleo, Gás Natural e Biocombustíveis (ANP). O controle de qualidade é tarefa importante para reduzir problemas com mau funcionamento de motores e sonegação de impostos. Este estudo analisou 10 amostras de gasolina tipo C coletadas em diferentes postos de combustíveis, e através da espectroscopia Raman (830 nm de excitação) buscou-se identificar adulterações por adição de etanol anidro acima do permitido ou por mistura de outros solventes orgânicos. As técnicas de análise de componente principal (PCA) e lógica paraconsistente anotada (LPA) foram empregadas para discriminação e classificação das amostras em função da ausência ou presença de adulteração. Os espectros foram obtidos com níveis diferentes de ruídos a fim de avaliar a influência destes na classificação. Os resultados indicaram que 6 das 10 amostras apresentaram adulteração, com presença sugerida de etanol anidro acima do permitido por lei e/ou por mistura de outros solventes orgânicos. Ambas as técnicas mostraram excelentes resultados em termos de classificação correta. A PCA demonstrou maior capacidade de discriminação em diferentes condições experimentais de tempo de coleta e temperatura da câmera CCD que se utiliza no espectrômetro Raman (100% de acerto), pois é capaz de separar o ruído e interferências do sinal. Já a LPA necessita de uma combinação de tempo e temperatura para melhores resultados. A LPA teve desempenho de 100% de acertos nas análises feitas em 2, 1, 0,5 e 0,2 s, onde dos 30 testes feitos (3 por amostra). A PCA acertou 100% dos grupos em todos os tempos de análise (20, 10, 5, 2, 1, 0,5, 0,2 e 0,1 s) em temperaturas de -75, -45 e -20 ºC, enquanto a LPA, nas mesmas condições, resultou em 100% de acerto somente nas análises feitas nos tempos de 2, 1, 0,5, e 0,2 s. A PCA mostrou resultados melhores, pois é capaz de separar o ruído aleatório que ocorre nos espectros Raman e assim consegue extrair com mais eficiência as variáveis de relevância dos espectros.

Raman spectroscopy has been used to discriminate human breast cancer and its different tumor molecular subtypes (luminal A, luminal B, HER2, and triple-negative) from normal tissue in surgical specimens.Breast cancer and normal tissue samples from 31 patients were obtained by surgical resection and submitted for histopathology. Before anatomopathological processing, the samples had been submitted to Raman spectroscopy (830 nm, 25 mW excitation laser parameters). In total, 424 Raman spectra were obtained. Principal component analysis (PCA) was used in an exploratory analysis to unveil the compositional differences between the tumors and normal tissues. Discriminant models were developed to distinguish the different cancer subtypes by means of partial least squares (PLS) regression.PCA vectors showed spectral features referred to the biochemical constitution of breast tissues, such as lipids, proteins, amino acids, and carotenoids, where lipids were decreased and proteins were increased in breast tumors. Despite the small spectral differences between the different subtypes of tumor and normal tissues, the discriminant model based on PLS was able to discriminate the spectra of the breast tumors from normal tissues with an accuracy of 97.3%, between luminal and nonluminal subtypes with an accuracy of 89.9%, between nontriple-negative and triple-negative with an accuracy of 94.7%, and each molecular subtype with an accuracy of 73.0%.PCA could reveal the compositional difference between tumors and normal tissues, and PLS could discriminate the Raman spectra of breast tissues regarding the molecular subtypes of cancer, being a useful tool for cancer diagnosis.

This study employed Raman spectroscopy for the identification of spectral differences in automotive lubricant oils with different SAE specifications. Samples of 18 lubricant oils were obtained from...

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.

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.

This study proposed the diagnosis of COVID-19 by means of Raman spectroscopy. Samples of blood serum from 10 patients positive and 10 patients negative for COVID-19 by RT-PCR RNA and ELISA tests were analyzed. Raman spectra were obtained with a dispersive Raman spectrometer (830 nm, 350 mW) in triplicate, being submitted to exploratory analysis with principal component analysis (PCA) to identify the spectral differences and discriminant analysis with PCA (PCA-DA) and partial least squares (PLS-DA) for classification of the blood serum spectra into Control and COVID-19. The spectra of both groups positive and negative for COVID-19 showed peaks referred to the basal constitution of the serum (mainly albumin). The difference spectra showed decrease in the peaks referred to proteins and amino acids for the group positive. PCA variables showed more detailed spectral differences related to the biochemical alterations due to the COVID-19 such as increase in lipids, nitrogen compounds (urea and amines/amides) and nucleic acids, and decrease of proteins and amino acids (tryptophan) in the COVID-19 group. The discriminant analysis applied to the principal component loadings (PC2, PC4, PC5, and PC6) could classify spectra with 87% sensitivity and 100% specificity compared to 95% sensitivity and 100% specificity indicated in the RT-PCR kit leaflet, demonstrating the possibilities of a rapid, label-free, and costless technique for diagnosing COVID-19 infection. Supplementary Information The online version contains supplementary material available at 10.1007/s10103-021-03488-7.

O trabalho se propõe a avaliar o efeito do ruído de fluorescência (ruído de fóton ou shot noise) na classificação dos espectros de amostras de gasolinas padrão e adulteradas obtidas em postos de combustíveis na região de Santos/SP. Foram obtidas 15 amostras de diferentes postos de abastecimento, sendo 5 amostras padrão e 10 contendo algum tipo de adulteração (maior concentração de etanol ou presença de solvente orgânico). As técnicas de Lógica Paraconsistente Anotada com anotação de dois valores (LPA2v) e a análise de componente principal (PCA) com análise discriminante foram empregadas buscando-se verificar até que ponto a influência de diferentes níveis de ruído de fluorescência impactaria a classificação das amostras. Os resultados demonstraram que o ruído de fluorescência impacta a classificação das amostras, onde menores níveis de ruído (até 100 contagens) foram classificados corretamente pela LPA2v, enquanto que maiores níveis de ruído (200 contagens) promoveram melhor classificação para a técnica PCA.

This work proposed the diagnosis of iron deficiency anemia (IDA) and sickle cell disease (SCD) in human blood caused by iron deficiency and hemoglobin S (HbS), which are among the most common anemias, by means of Raman spectroscopy. Whole blood samples from patients diagnosed with IDA and HbS, as well as from normal subjects (HbA), were obtained and submitted to Raman spectroscopy (830 nm, 150 mW, 400-1800 cm-1 spectral range, 4 cm-1 resolution). Difference spectra of IDA-HbA showed spectral features of hemoglobin with less intensity in the IDA, whereas the difference spectra of SCD-HbA showed spectral features of deoxyhemoglobin increased and of oxyhemoglobin decreased in SCD. An exploratory analysis by principal components analysis (PCA) showed that the peaks referred to oxy- and deoxyhemoglobin markedly differentiated SCD and HbA, as well as the increased amount of hemoglobin features in the SCD group, suggesting increased erythropoiesis. The IDA group showed hemoglobin features with lower intensities as well as peaks referred to the iron bonding to the porphyrin ring with reduced intensities when compared to the HbA. Discriminant analysis based on partial least squares (PLS-DA) and PCA (PCA-DA) showed that the IDA and SCD anemias could be discriminated from the HbA spectra with 95.0% and 93.8% of accuracy, for the PLS and PCA respectively, with sensitivity/specificity of 93.8%/95.7% for the PLS-DA model. The iron depletion and the sickling of erythrocytes could be identified by Raman spectroscopy and a spectral model based on PLS accurately discriminated these IDA and SCD samples from the normal HbA.

This preliminary study proposed the diagnosis of COVID-19 by means of Raman spectroscopy. Samples of blood serum from 10 patients positive and 10 patients negative for COVID-19 by RT-PCR RNA and ELISA tests were analyzed. Raman spectra were obtained with a dispersive Raman spectrometer (830 nm, 350 mW) in triplicate, being submitted to exploratory analysis with principal component analysis (PCA) to identify the spectral differences and discriminant analysis with PCA (PCA-DA) and partial least squares (PLS-DA) for classification of the blood serum spectra into Control and COVID-19. The spectra of both groups positive and negative for COVID-19 showed peaks referred to the basal constitution of the serum (mainly albumin). The difference spectra showed decrease in the peaks referred to proteins and amino acids for the group positive. PCA variables showed more detailed spectral differences related to the biochemical alterations due to the COVID-19 such as increase in lipids, nitrogen compounds (urea and amines/amides) and nucleic acids, and decrease of proteins and amino acids (tryptophan) in the COVID-19 group. The discriminant analysis applied to the principal component loadings (PC 2, PC 4, PC 5 and PC 6) could classify spectra with 87% sensitivity and 100% specificity compared to 95% sensitivity and 100% specificity indicated in the RT-PCR kit leaflet, demonstrating the possibilities of a rapid, label-free and costless technique for diagnosing COVID-19 infection.

Petrogal Brasil S.A., through the project “Sustainable biotechnological alternatives to increase the oil recovery factor of carbonate reservoirs” under the management of Instituto de Petróleo e Gás – ISPG and the National Agency of Petroleum, Natural Gas and Biofuels (ANP) provided financial support and grants to PJLG, PFA, ICFS, and ALBP, IDWS, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico -CNPq provided a grant to LSF, and SP had financial support and grant from the Scottish Funding Council Global Challenges Research Fund. Oil recovery is a challenge and microbial enhanced oil recovery is an option. We theorized that the use of produced water (PW) with photo-stimulation could influence both production and viscosity of Xanthan gum. This study aimed at the evaluation of the effect of photo-stimulation by λ630 ± 1 ηm LED light on the biosynthesis of Xanthan gum produced by Xanthomonas campestris IBSBF 2103 strain reusing PW of the oil industry. We assessed the effect of photo-stimulation by LED light (λ630 nm) on the biosynthesis of Xanthan gum produced by X. campestris in medium containing produced water. Different energy densities applied during the microbial growth phase were tested. The highest production was achieved when using 12 J/cm2 LED light (p

The severe COVID‐19 pandemic requires the development of novel, rapid, accurate, and label‐free techniques that facilitate the detection and discrimination of SARS‐CoV‐2 infected subjects. Raman spectroscopy has been used to diagnose COVID‐19 in serum samples of suspected patients without clinical symptoms of COVID‐19 but presented positive immunoglobulins M and G (IgM and IgG) assays versus Control (negative IgM and IgG). A dispersive Raman spectrometer (830 nm, 350 mW) was employed, and triplicate spectra were obtained. A total of 278 spectra were used from 94 serum samples (54 Control and 40 COVID‐19). The main spectral differences between the positive IgM and IgG versus Control, evaluated by principal component analysis (PCA), were features assigned to proteins including albumin (lower in the group COVID‐19 and in the group IgM/IgG and IgG positive) and features assigned to lipids, phospholipids, and carotenoids (higher the group COVID‐19 and in the group IgM/IgG positive). Features referred to nucleic acids, tryptophan, and immunoglobulins were also seen (higher the group COVID‐19). A discriminant model based on partial least squares regression (PLS‐DA) found sensitivity of 84.0%, specificity of 95.0%, and accuracy of 90.3% for discriminating positive Ig groups versus Control. When considering individual Ig group versus Control, it was found sensitivity of 77.3%, specificity of 97.5%, and accuracy of 88.8%. The higher classification error was found for the IgM group (no success classification). Raman spectroscopy may become a technique of choice for rapid serological evaluation aiming COVID‐19 diagnosis, mainly detecting the presence of IgM/IgG and IgG after COVID‐19 infection., Raman spectroscopy has been used to diagnose COVID‐19 in serum samples of subjects without clinical symptoms of COVID‐19. The main spectral differences between the positive IgM and IgG versus Control were features assigned to proteins, lipids (including phospholipids), immunoglobulins, carotenoids, nucleic acids, and amino acids (tryptophan). Discriminant model applied to the Raman spectra could discriminate positive Ig groups versus Control with an accuracy of 90.3%. Raman spectroscopy may become a technique for rapid serological evaluation aiming diagnosis of COVID‐19 infection.

Lubricating oils are essential in vehicles motors, and there are currently three variations in oil types: mineral, semisynthetic and synthetic. This work aimed to evaluate the degradation of these three types, by heating them in the laboratory between 120 to 150 oC for 48h, and subsequently evaluating their change in the composition through Raman spectroscopy. It was possible to observe compounds in common between the mineral and semi-synthetic oils in the peaks at 1002, 1380 and 1621 cm-1, and between the semi-synthetic and synthetic in the peak at 892 cm-1. In the evaluation of samples after heating, trough principal component analysis (PCA) technique, it was observed a decrease in the intensity of some peaks, suggesting molecular breakdown, as well as an increase in the intensity of other peaks suggesting formation of amorphous carbon. It was found a high correlation through heating time and peak intensity, by adjusting 2nd order polynomial curves, R² ranging from 0.96 to 0.99.

Raman spectroscopy was used to identify biochemical differences in normal brain tissue (cerebellum and meninges) compared to tumors (glioblastoma, medulloblastoma, schwannoma, and meningioma) through biochemical information obtained from the samples. A total of 263 spectra were obtained from fragments of the normal cerebellum (65), normal meninges (69), glioblastoma (28), schwannoma (8), medulloblastoma (19), and meningioma (74), which were collected using the dispersive Raman spectrometer (830 nm, near infrared, output power of 350 mW, 20 s exposure time to obtain the spectra), coupled to a Raman probe. A spectral model based on least squares fitting was developed to estimate the biochemical concentration of 16 biochemical compounds present in brain tissue, among those that most characterized brain tissue spectra, such as linolenic acid, triolein, cholesterol, sphingomyelin, phosphatidylcholine, β-carotene, collagen, phenylalanine, DNA, glucose, and blood. From the biochemical information, the classification of the spectra in the normal and tumor groups was conducted according to the type of brain tumor and corresponding normal tissue. The classification used in discrimination models were (a) the concentrations of the biochemical constituents of the brain, through linear discriminant analysis (LDA), and (b) the tissue spectra, through the discrimination by partial least squares (PLS-DA) regression. The models obtained 93.3% discrimination accuracy through the LDA between the normal and tumor groups of the cerebellum separated according to the concentration of biochemical constituents and 94.1% in the discrimination by PLS-DA using the whole spectrum. The results obtained demonstrated that the Raman technique is a promising tool to differentiate concentrations of biochemical compounds present in brain tissues, both normal and tumor. The concentrations estimated by the biochemical model and all the information contained in the Raman spectra were both able to classify the pathological groups.

Automotive engine lubricating oils are not only intended to reduce friction between parts, but also act on the cooling of motor components and protection of metals against corrosion. To improve its properties and efficiency, additives are added to the base oil for different goals. However, over time of use, external factors modify its properties, such as the engine operating temperature, the frictional force between parts, the mixture of this oil with fuel before burning and with combustion products, causing loss of their efficiency. This work aimed to evaluate, with Raman spectroscopy technique, the temperature-induced changes related to degradation of mineral, semi-synthetic and synthetic automotive lubricating oils. Samples being subject to periodic heating cycle were kept to average temperature of 133 ℃, considering 8 h per day, for six days, until complete 48 h of heating. By analyzing the Raman spectra, it was possible to identify common peaks between the three types of oils and changes caused by heating cycles. Principal components analysis showed that the synthetic oil degraded in less extent than the semi-synthetic one, and this one degraded less than the mineral oil. Spectral models to predict the heating time based on the spectral variations identified using principal components analysis and the regression done using partial least squares, using the heating time as independent variable and the spectral features as dependent variables, was able to predict the heating time for each of oil types with high correlation and prediction error ( r > 0.97 and error

Oil is expected to continue to be one of the most important sources of energy in the world and world's energy matrix for the foreseeable future. However, high demand for energy and the decline of the production of oil fields makes oil recovery a challenge. Most techniques used for the recovery process are expensive, non-sustainable and technically difficult to implement. In this context, microbial enhanced oil recovery (MEOR) represents an attractive alternative. It employs products derived from the metabolism of microorganisms that produce biopolymers. Certain bacteria species (e.g., Xanthomonas campestris) produce polysaccharides (exopolysaccharides – EPS) such as the well-known Xanthan gum (XG). We hypothesized that the use of produced water (PW) water in combination photo-stimulation with laser/LED could influence the production and composition of XG. Raman spectroscopy has been used for qualitative and quantitative evaluation of the biochemical composition of XG biopolymer under light stimulation. X. campestris cultures in either distilled water or dialysis-produced water were studied under the absence or presence of laser irradiation (λ = 660 nm, CW, spot size 0.040 cm2, 40 mW, 444 s, 8.0 J/cm2) or LED (λ = 630 nm ± 2 nm, CW, spot size 0.50 cm2, 140 mW, 500 s, 12 J/cm2). XG produced by these cultures was analyzed by Raman spectroscopy at 1064 nm excitation and subjected to principal component analysis (PCA). Results of the exploratory analysis and ANOVA general linear model (GLM) suggested that the extent of XG and pyruvate (pyruvyl mannose) production was affected differentially in X. campestris when cultured in distilled water plus LED photo-stimulation versus dialysis-produced water plus LED photo-stimulation. XG production increased in the distilled water culture. In contrast, both pyruvate acetyl mannose content went up in the dialysis-water culture. These results open a wide field of opportunities in the use of metal-enriched cultures in combination with photo-biomodulation to direct and optimize bacterial production of compounds (i.e., XG) that may be of great benefit in the implementation of sustainable practices for oil extraction.

Chronic non-infectious diseases are important to research as they are the main causes of death in Brazil and worldwide. One very important chronic non-infectious disease is cardiovascular disease, whose risk factors (diabetes, dyslipidemia, and renal failure) can be detected through assessments of serum biochemical components. The objective of this study was to evaluate the analytical performance of Raman spectroscopy for analysis of lipid profile (total cholesterol, triglycerides, and HDL cholesterol), non-protein nitrogenous compounds (urea and creatinine), and glucose in 242 human serum samples. Models to discriminate and quantify the samples were developed using the predicted concentration by quantitative regression model based on partial least squares (PLS). The analytical error for the "leave-one-out" cross-validation based on the predicted PLS concentration was 10.5 mg/dL for total cholesterol, 21.4 mg/dL for triglyceride, 13.0 mg/dL for HDL cholesterol, 4.9 mg/dL for urea, 0.21 mg/dL for creatinine, and 15.4 mg/dL for glucose. The Kappa coefficient indicate very good agreement for cholesterol (0.83), good for triglyceride (0.77), urea (0.70) and creatinine (0.66), and fair for HDL cholesterol (0.38) and glucose (0.30). The results of the analytical performance demonstrated that Raman spectroscopy can be considered an important methodology to screen the population, especially for serum triglycerides and cholesterol.

This study aimed the diagnosis of non-melanoma skin cancer (basal cell carcinoma - BCC, squamous cell carcinoma - SCC) and actinic keratosis (AK) and normal tissue (NO) by means of Raman spectra collected in vivo and ex vivo as well as determine, through the main Raman features, which biochemical element present in the skin is related to the spectral changes in the lesions compared to normal tissue. A total of 471 Raman spectra in vivo and 227 spectra ex vivo from NO, BCC, SCC and AK tissues were collected using a dispersive Raman spectrometer (830 nm excitation, 30 s exposure time, 200 mW laser power) as well as spectra of basal skin constituents (proteins, lipids, nucleic acids). Student's t-test (p

The aim of this study was to identify biochemical changes in sciatic nerve (SN) after crush injury and low-level laser therapy (LLLT) with 660 nm and 808 nm by Raman spectroscopy (RS) analysis. A number of 32 Wistar rats were used, divided into four groups (control 1, control 2, LASER 660 nm, and LASER 808 nm). All animals underwent surgical procedure of the SN and groups control 2, LASER 660 nm, and LASER 808 nm were submitted to SN crush damage (axonotmesis). The LLLT in the groups LASER 660 nm and LASER 808 nm was applied daily for 21 consecutive days (100 mW, 30 s, 133 J/cm2 fluence). The hind paw was removed and the SN was dissected and positioned on an aluminum support to collect dispersive Raman spectra (830 nm excitation, 30 s accumulation). To estimate the biochemical changes in the SN associated with LLLT, the principal component analysis (PCA) was applied. The Raman spectra of the sciatic nerve fragments showed peaks of the major biochemical components of the nerve, especially sphingolipids, phospholipids, glycoproteins, and collagen. The spectral features identified in some of the principal component loading vectors are referred to the biochemical elements present on the SN and were increased in the groups treated with LLLT, mainly lipids (sphingo and phospholipids) and proteins (collagen)—constituents of the myelin sheath. The RS was effective in identifying the biochemical differences in the SN after the crush injury, and LASER 660 nm was more efficient than the LASER 808 nm in cell proliferation and repair of the injured SN.

Copaiba oleoresin presents several compounds with known biologic activity and physiologic effects, including analgesic and insecticide properties. Among them are the terpenoids (mainly dite...

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.

The use of chemicals is often related to suicide attempts and acute poisoning, which account for a significant number of hospital admissions. The differential diagnosis of patients exposed to poisoning is intricate and varies according to the substance used. The identification of drugs and drug abuse in cases of poisoning often requires time-consuming and complex techniques, such as chromatography. The use of vibrational spectroscopy such as Raman spectroscopy and Fourier transform infrared spectroscopy (FTIR) enables the quick identification of toxic substances using no reagents or markers. This study aims to apply these techniques in the long term to identify and quantify substances found at the locations of suicide attempts, poisonings, and even drug consumption sites, including crack samples containing a cocaine base and adulterants commonly seized in drug busts, such as caffeine, lidocaine, and sodium carbonate. In this study, Raman and FTIR spectra of ternary mixtures of crack with caffeine and sodium carbonate and crack with lidocaine and sodium carbonate were obtained. These spectra were used for building multivariate models based on partial least squares (PLS) for determining the composition of the samples quantitatively. High correlation coefficients (r > 0.98) and small cross-validation prediction errors (

Hypercholesterolemia is associated with deterioration of bone tissue. Trough Raman spectroscopy, the present study aimed to assess the molecular changes in terms of mineral and organic bone-tissue remodeling in low-density lipoprotein receptor gene knockout mice (LDLr-/-) submitted to treadmill aerobic training. In order to evaluate alterations in trabecular bone and cartilage surface, neck and head femoral were assessed into four groups: (CON, n=7), the 1) animals did not perform any physical activity and had hypercholesterolemia (CON, n=7); The trained groups where animals underwent a protocols of low, moderate and high training for 8weeks and 4 times per week on a treadmill with progressive intensities: running speed (8-13m/min) and time of exercise (20-60min). These progressive intensities were needed to adjust the working load for the physical training to 2) 30-49% (LOW, n=7), 3) 50-79% (MOD, n=7), and 4) 80-100% (HIGH, n=7) of the maximum running speed. Each group was examined for molecular changes in both bone phases (mineral and organic) using principal components analysis (PCA). All exercised groups showed a significant increase (p

Higher blood pressure level and poor glycemic control in diabetic patients are considered progression factors that cause faster decline in kidney functions leading to kidney damage. The present study aimed to develop a quantification model of biomarkers creatinine, urea, and glucose by means of selected peaks of these compounds, measured by Raman spectroscopy, and to estimate the concentration of these analytes in the urine of normal subjects (G_N), diabetic patients with hypertension (G_WOL) patients with chronic renal failure doing dialysis (G_D). Raman peak intensities at 680 cm−1 (creatinine), 1004 cm−1 (urea), and 1128 cm−1 (glucose) from normal, diabetic, and hypertensive and doing dialysis patients, obtained with a dispersive 830 nm Raman spectrometer, were estimated through Origin software. Spectra of creatinine, urea, and glucose diluted in water were also obtained, and the same peaks were evaluated. A discrimination model based on Mahalanobis distance was developed. It was possible to determine the concentration of creatinine, urea, and glucose by means of the Raman peaks of the selected biomarkers in the urine of the groups G_N, G_WOL, and G_D (r = 0.9). It was shown that the groups G_WOL and G_D had lower creatinine and urea concentrations than the group G_N (p

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.

This study aimed to assess the repair of complete surgical tibial fractures fixed with internal rigid fixation (IRF) associated or not to the use of mineral trioxide aggregate (MTA) cement and treated or not with laser (λ = 780 nm, infrared) or LED (λ = 850 ± 10 nm, infrared) lights, 142.8 J/cm2 per treatment, by means of Raman spectroscopy. Open surgical tibial fractures were created on 18 rabbits (6 groups of 3 animals per group, ∼8 months old) and fractures were fixed with IRF. Three groups were grafted with MTA. The groups of IRF and IRF + MTA that received laser or LED were irradiated every other day during 15 days. Animals were sacrificed after 30 days, being the tibia surgically removed. Raman spectra were collected via the probe at the defect site in five points, resulting in 15 spectra per group (90 spectra in the dataset). Spectra were collected at the same day to avoid changes in laser power and experimental setup. The ANOVA general linear model showed that the laser irradiation of tibial bone fractures fixed with IRF and grafted with MTA had significant influence in the content of phosphate (peak ∼960 cm-1) and carbonated (peak ∼1,070 cm-1) hydroxyapatites as well as collagen (peak 1,452 cm-1). Also, peaks of calcium carbonate (1,088 cm-1) were found in the groups grafted with MTA. Based on the Raman spectroscopic data collected in this study, MTA has been shown to improve the repair of complete tibial fractures treated with IRF, with an evident increase of collagen matrix synthesis, and development of a scaffold of hydroxyapatite-like calcium carbonate with subsequent deposition of phosphate hydroxyapatite.

s Digital rectal examination (DRE) was the primary means to detect prostate diseases. The DRE has a high variability as it is based manly in the tactile sensitivity and expertise of the examiner. The prostate-specific antigen (PSA) test was initially developed for surveillance of prostate cancer and later it was also used as a diagnosis test. Raman spectroscopy is a powerful analytical technique that can measure the chemical composition of complex biological samples, such as body fluids. Biochemical changes caused by diseases can lead to significant changes in the Raman spectra. This study aimed to identify the differences in the Raman spectra of serum samples with normal and altered PSA values and correlate these differences by using multivariate techniques (principal component analysis - PCA and partial least squares regression – PLS). A total of 321 spectra were collected from 108 subjects. Two hundred and seventy were obtained from 91 non-altered PSA samples and 51 spectra from 17 samples with altered PSA. Each spectrum acquired was standardized to the area under the curve (1-norm). Discriminating and quantitative models employing PCA and PLS were developed. The PCA analyses showed 85.7% predictive power (87.41% sensitivity and 76.47% specificity). The PLS test showed a near-perfect sensitivity (98.51%) and an intermediate specificity (62.75%). The quantitative model through PLS regression showed a good correlation between PSA values and the spectral features (r = 0.605). This preliminary study suggests that Raman spectroscopy could be efficiently used for screening patients with altered PSA as well as for follow-up of the treatment of the prostate cancer by using initially the PLS to identify the possible presence of the prostate cancer and later on use de PCA to confirm the diagnosis.

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) + β-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

Urea and creatinine are commonly used as biomarkers of renal function. Abnormal concentrations of these biomarkers are indicative of pathological processes such as renal failure. This study aimed to develop a model based on Raman spectroscopy to estimate the concentration values of urea and creatinine in human serum. Blood sera from 55 clinically normal subjects and 47 patients with chronic kidney disease undergoing dialysis were collected, and concentrations of urea and creatinine were determined by spectrophotometric methods. A Raman spectrum was obtained with a high-resolution dispersive Raman spectrometer (830 nm). A spectral model was developed based on partial least squares (PLS), where the concentrations of urea and creatinine were correlated with the Raman features. Principal components analysis (PCA) was used to discriminate dialysis patients from normal subjects. The PLS model showed r = 0.97 and r = 0.93 for urea and creatinine, respectively. The root mean square errors of cross-validation (RMSECV) for the model were 17.6 and 1.94 mg/dL, respectively. PCA showed high discrimination between dialysis and normality (95 % accuracy). The Raman technique was able to determine the concentrations with low error and to discriminate dialysis from normal subjects, consistent with a rapid and low-cost test.

Produced water (PW) is a by-product generated throughout oil exploration. Geological formation and geographical location of the reservoir influence its physical, chemical and biological characteristics. Xanthan gum (XG), an exopolysaccharide (EPS) produced by Xanthomonas campestris, has been widely used in enhanced oil recovery (EOR) technology because of its high viscosity, pseudoplastic behavior, stability in function of salinity, temperature and alkaline conditions. The production of XG may be affected by the composition of the PW, where the acetyl and pyruvyl radicals may be present in the mannoses. The aim of this study was to evaluate the composition of XG produced by X. campestris, particularly the amount of Xanthan, acetyl and pyruvyl groups, in culture mediums containing distilled (DW) or produced (PW) water in different concentrations, by means of dispersive Raman spectroscopy (1064 nm). The spectra of XG showed peaks referred to the main constituents of the Xanthan (glucose, mannose and glucuronic acid). Spectral features assigned to pyruvyl were seen in all samples mainly at ~1010 cm−1, with higher intensity when using DW and 25% PW. PCA loadings showed that the peaks assigned to pyruvyl are consistent to presence of sodium pyruvate (~1040/~1050 and ~ 1432 cm−1) and were higher in the samples obtained in 25% PW. ANOVA GLM applied to Raman peaks of interest (~1010 and ~ 1090 cm−1) and to PCA scores (Score 1 to Score 3) showed that both were influenced by the type of water used in the culture medium, where the XG were strongly reduced in the groups PW compared to DW while the pyruvyl content increased proportionally with the concentration of PW. The results suggest that the composition of the water used in the bacteria's culture medium influenced the composition of XG, including the amount of Xanthan and particularly the pyruvyl content, and therefore needs to be considered when using this approach of injecting XG in oil fields as pyruvyl content affects viscosity.

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.

In this work, dispersive Raman spectroscopy has been employed as a rapid and nondestructive technique to detect the metabolites in urine of physical exercise practitioners before and after exercise. For so, urine samples from 14 men were obtained before and immediately after physical activities and submitted to Raman spectroscopy (830 nm excitation, 250 mW laser power, 20 s integration time). The Raman spectra of urine showed peaks related to urea, creatinine and phosphate. These metabolic biomarkers presented peaks with different intensities in the urine 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 subjects using urine samples, allowing nutrition adjustment with the sport’s performance.

This work proposed the diagnosis of iron deficiency anemia (IDA) in human blood caused by iron (Fe) deficiency, which is the most common nutritional deficiency, by means of Raman spectroscopy. Total blood samples from patients diagnosed with IDA, as well as from normal subjects (HbA) were obtained and submitted to Raman spectroscopy (830 nm, 150 mW, 400–1800 cm−1 spectral range, 2 cm−1 resolution) through a Raman probe and an aluminum sample holder. Then, the normalized spectra were submitted to discriminant analysis based on partial least squares (PLS-DA) and principal components analysis (PCA-DA). The comparison between the spectra of HbA and IDA showed very similar spectral features, and an exploratory analysis based on the scores and loadings of PCA showed that the spectral differences appear in the peaks at 971, 1237, 1374 and 1551 cm−1, which can be attributed to hemoglobin molecule. Discriminant analysis using PLS-DA and PCA-DA showed that the IDA spectra could be separated from the HbA spectra with 88.3% and 81.7% of accuracy, for the PLS and PCA respectively. It was concluded that the iron depletion of red blood cells can be identified by the Raman spectroscopy and these depletion could be used to accurately discriminate these IDA samples from the normal HbA.

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.

Acute leukemias are oncohematological diseases that compromise the bone marrow and have a complex diagnostic definition, leading to a high mortality when diagnosed late. This study proposed to determine the spectral differences between whole blood and plasma samples of healthy and leukemic subjects based on Raman spectroscopy (RS), correlating these differences with their resulting biochemical alterations and performing discriminant analysis of the samples (n = 38 whole blood and n = 40 plasma samples). Raman spectra were obtained using a dispersive Raman spectrometer (830-nm wavelength, 280-mW laser power, 30-s exposure time) with a Raman probe. The exploratory analysis based on principal component analysis (PCA) of the blood and plasma sample’s spectra showed loading vectors with peaks related to amino acids, proteins, carbohydrates, lipids, and carotenoids, being the spectral differences related to amino acids and proteins for whole blood samples, and mainly carotenoids for plasma samples. Discriminant models based on partial least squares (PLS) and PCA were developed and classified the spectra as healthy or leukemic, with sensitivity of 91.9% (PLS) and 83.9% (PCA), specificity of 100% (both PLS and PCA), and overall accuracy of 96.5% (PLS) and 93.0% (PCA) for the whole blood spectra. In plasma, the sensitivity was 95.7% (PLS) and 11.6% (PCA), specificity of 98% (PLS) and 100% (PCA), and overall accuracy of 97.1% (PLS) and 64.1% (PCA). The study demonstrated that RS is a technique with potential to be applied in the diagnosis of acute leukemias in whole blood samples.

The repair of bone tissue is complex and can be influenced by several local and systemic factors that can delay the repair. Laser and LED phototherapies have shown positive results in the repair of bone tissue. The aim of this study was to evaluate, through Raman spectroscopy, the influence of laser (λ780 nm) and LED (λ850 nm) phototherapies in the repair of surgical defects in femurs of euthyroid and hypothyroid rats. Thirty Albinus Wistar rats were randomly divided into 6 groups. The animals of the hypothyroid groups were submitted to surgical removal of the thyroid gland. After general anesthesia, a surgical bone defect was created in the femur of each animal and filled with blood clot in all groups. In group I (Euthyroid) the defect was created in euthyroid animals; In Group II (Hypo) the defect was created in hypothyroid animals; In Group III (Euthyroid Laser) the defect was irradiated with Laser; on Group IV (Hypo Laser) the defect was made in a hypothyroid animal and irradiated with Laser; on Group V (Euthyroid LED) the defect was irradiated with LED and on Group VI (Hypo LED) the defect was created in hypothyroid animals and LED irradiated. Irradiation was carried out at every 48-h for 15 days. Specimens were taken and stored in liquid nitrogen. Intensity of peaks of phosphate HA (~960 cm-1), carbonated HA (~1,070 cm-1) and collagen (~1,414 cm-1) were measured by Raman Spectroscopy. The results showed that the health status had significant influence all peaks. Irradiation influenced only the peak of ~1454 cm-1. It is concluded that phototherapies influences bone repair in cases of thyroid diseases.

Current forensic methods for detecting and identifying cocaine and other drugs of abuse are destructive, so evidence cannot be re-analyzed. Raman spectroscopy, based on inelastic light scattering, allows for rapid, inexpensive and nondestructive analysis in forensic science. This review presents the state-of-the-art use of Raman spectroscopy as a confirmatory method for the identification of cocaine and other drugs of abuse in seized samples, including hidden compounds in legal materials such as beverages and clothes, among others, used for trafficking. Quantitative Raman spectroscopy is used to determine the actual drug concentrations in street cocaine and crack rocks and to identify possible adulterants in these samples for forensic toxicology and criminalistics. Finally, recent developments in Raman spectrometers (portable instruments and new excitation wavelengths) and advancements in data analysis offer exciting opportunities for new applications of Raman spectroscopy in the identification and quantification of drugs of abuse, including investigations conducted immediately at the scene of a crime. Copyright © 2016 JohnWiley & Sons, Ltd.