ATR-FTIR spectroscopy imaging of bone repair in mandibular laser-osteotomy.

The aim of this study was to verify the effectiveness of attenuated total reflectance-fourier transform infrared (ATR-FTIR) spectroscopy in the characterization of bone repair in mandibular osteotomy using erbium, chromium-doped yttrium, scandium, gallium and garnet (Er,Cr:YSGG) laser and multilaminate drill on each side. Two mandible bone fragments were removed from 30 rabbits, and the process of bone repair was studied immediately, 3, 7, 15, 21, and 28 days after the surgery. The histological analysis allowed detecting differences in the early stages of tissue repair after bone cutting performed with the Er,Cr:YSGG laser or multilaminate drill. The ATR-FTIR spectroscopy technique was sensitive to changes in the organic content of bone tissue repair process.

Characterization of industrial TNT in ammunition shells: An in-depth study of artificial aging effects using Fourier-Transform infrared spectroscopy and gas chromatography-mass spectrometry.

In this study, we comprehensively investigated the degradation of industrial trinitrotoluene (TNT), focusing on the effects of aging and direct contact with steel surfaces, mirroring real-world usage conditions. While practical knowledge exists regarding this degradation, the existing literature lacks in-depth insights into the underlying processes. To address this gap, we conducted experiments using small steel samples, representative of military ammunition casings, which were coated with TNT and subjected to 30 days of heating at 75 °C under vacuum conditions. A subset of these samples was coated with a protective red alkyd paint. After the aging process, the TNT was carefully removed from the metal surfaces and subjected to a comprehensive analysis encompassing scanning electron microscopy, Fourier-transform infrared spectroscopy, and gas chromatography-mass spectrometry. Our results reveal a remarkable preservation of the chemical integrity of industrial TNT, even in the presence of thermal stress and direct steel contact. Although superficial changes were observed in the TNT's appearance, all analytical data consistently demonstrated the maintenance of its chemical composition. Notably, the sole change in composition was attributed to the presence of degradation products associated with the alkyd paint coating, rather than intrinsic TNT degradation. These findings underscore the negligible impact of degradation processes on TNT in scenarios involving the solid-phase thermal stress of TNT in direct contact with metal, significantly enhancing our understanding of TNT safety when packaged within steel artifacts-a common context in military ammunition.

Biodegradation of Polystyrene by Galleria mellonella: Identification of Potential Enzymes Involved in the Degradative Pathway.

Galleria mellonella is a lepidopteran whose larval stage has shown the ability to degrade polystyrene (PS), one of the most recalcitrant plastics to biodegradation. In the present study, we fed G. mellonella larvae with PS for 54 days and determined candidate enzymes for its degradation. We first confirmed the biodegradation of PS by Fourier transform infrared spectroscopy- Attenuated total reflectance (FTIR-ATR) and then identified candidate enzymes in the larval gut by proteomic analysis using liquid chromatography with tandem mass spectrometry (LC-MS/MS). Two of these proteins have structural similarities to the styrene-degrading enzymes described so far. In addition, potential hydrolases, isomerases, dehydrogenases, and oxidases were identified that show little similarity to the bacterial enzymes that degrade styrene. However, their response to a diet based solely on polystyrene makes them interesting candidates as a potential new group of polystyrene-metabolizing enzymes in eukaryotes.

Detection of Sialic Acid to Differentiate Cervical Cancer Cell Lines Using a Sambucus nigra Lectin Biosensor.

Pap smear screening is a widespread technique used to detect premalignant lesions of cervical cancer (CC); however, it lacks sensitivity, leading to identifying biomarkers that improve early diagnosis sensitivity. A characteristic of cancer is the aberrant sialylation that involves the abnormal expression of α2,6 sialic acid, a specific carbohydrate linked to glycoproteins and glycolipids on the cell surface, which has been reported in premalignant CC lesions. This work aimed to develop a method to differentiate CC cell lines and primary fibroblasts using a novel lectin-based biosensor to detect α2,6 sialic acid based on attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and chemometric. The biosensor was developed by conjugating gold nanoparticles (AuNPs) with 5 µg of Sambucus nigra (SNA) lectin as the biorecognition element. Sialic acid detection was associated with the signal amplification in the 1500-1350 cm-1 region observed by the surface-enhanced infrared absorption spectroscopy (SEIRA) effect from ATR-FTIR results. This region was further analyzed for the clustering of samples by applying principal component analysis (PCA) and confidence ellipses at a 95% interval. This work demonstrates the feasibility of employing SNA biosensors to discriminate between tumoral and non-tumoral cells, that have the potential for the early detection of premalignant lesions of CC.

Fast screening using attenuated total reflectance- fourier transform infrared (ATR-FTIR) spectroscopy of patients based on D-dimer threshold value.

Attenuated Total Reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy is an emerging technology in the medical field. Blood D-dimer was initially studied as a marker of the activation of coagulation and fibrinolysis. It is mainly used as a potential diagnosis screening test for pulmonary embolism or deep vein thrombosis but was recently associated with COVID-19 severity. This study aimed to evaluate the use of ATR-FTIR spectroscopy with machine learning to classify plasma D-dimer concentrations. The plasma ATR-FTIR spectra from 100 patients were studied through principal component analysis (PCA) and two supervised approaches: genetic algorithm with linear discriminant analysis (GA-LDA) and partial least squares with linear discriminant (PLS-DA). The spectra were truncated to the fingerprint region (1800-1000 cm-1). The GA-LDA method effectively classified patients according to D-dimer cutoff (≤0.5 µg/mL and >0.5 µg/mL) with 87.5 % specificity and 100 % sensitivity on the training set, and 85.7 % specificity, and 95.6 % sensitivity on the test set. Thus, we demonstrate that ATR-FTIR spectroscopy might be an important additional tool for classifying patients according to D-dimer values. ATR-FTIR spectral analyses associated with clinical evidence can contribute to a faster and more accurate medical diagnosis, reduce patient morbidity, and save resources and demand for professionals.

Generation of PVP Membranes Using Extracts/Phenolic Fraction of Dysphania ambrosioides, Opuntia ficus-indica, and Tradescantia pallida.

In the present work, electrospun membranes of polyvinylpyrrolidone (PVP) nanofibers were manufactured using extracts and phenolic fractions of Dysphania ambrosioides (epazote), Opuntia ficus-indica (nopal), and Tradescantia pallida (chicken grass). The characterization of the membranes was carried out by scanning electron microscopy and Fourier transform infrared spectroscopy. The membranes synthesized through the use of the extracts generally showed a slight decrease in the diameter of the fibers but an increase in the size of the pores due to the presence of nanoparticles (rosaries) on the surface of the fibers, while the membranes synthesized using the phenolic fraction demonstrated an inversely proportional relationship between the compounds of this family with the diameter of the fibers and the size of the pore, allowing to elucidate part of the polymerization mechanisms of PVP nanofibers, in addition to proposing a reaction mechanism in the interaction between PVP and phenolic compounds for surface functionalization. Likewise, we demonstrate that the generation of reaction seeds through functionalization allows the addition of other compounds to the fibers in the membranes synthesized using the complete extract.

Isolation and Characterization of Protein Fractions for Valorization of Sacha Inchi Oil Press-Cake.

The growing interest in plant-based food protein sources has provided opportunities for the valorization of agri-food by-products, driving the food industry towards more sustainable development. In this study, three extraction procedures (varying the pH value (7.0 and 11.0) and the addition of salt (0 and 5%)) were investigated to obtain seven different protein fractions (SIPF) from Sacha Inchi oil press-cake (SIPC), which were characterized in terms of their protein content, electrophoretic profile, secondary structure, and techno-functional properties. Extractions at pH 11.0 without salt addition produced the highest values of protein content, extraction yield, protein recovery, and protein concentration increase (84.0%, 24.7%, 36.5%, and 1.5-fold, respectively). Under these extraction conditions, the electrophoretic analysis indicated that most of the SIPC proteins were extracted. SIPF displayed an excellent oil absorption capacity (4.3-9.0 w/w), and interesting foam activity (36.4-133.3%). The solubility and emulsifying activity of the albumin fractions were significantly higher than those of the other fractions (~87 vs. <15.8%, and 280-370 vs. <140 m2/g, respectively). Correlation analysis showed that the secondary structure of the SIPF significantly influences their techno-functional properties. These results indicate that SIPC is a by-product of great potential for protein extraction processes, and as a valorization strategy for technical cycle solutions for the Sacha Inchi productive chain in the circular economy context.

Salivary ATR-FTIR Spectroscopy Coupled with Support Vector Machine Classification for Screening of Type 2 Diabetes Mellitus.

The blood diagnosis of diabetes mellitus (DM) is highly accurate; however, it is an invasive, high-cost, and painful procedure. In this context, the combination of ATR-FTIR spectroscopy and machine learning techniques in other biological samples has been used as an alternative tool to develop a non-invasive, fast, inexpensive, and label-free diagnostic or screening platform for several diseases, including DM. In this study, we used the ATR-FTIR tool associated with linear discriminant analysis (LDA) and a support vector machine (SVM) classifier in order to identify changes in salivary components to be used as alternative biomarkers for the diagnosis of type 2 DM. The band area values of 2962 cm-1, 1641 cm-1, and 1073 cm-1 were higher in type 2 diabetic patients than in non-diabetic subjects. The best classification of salivary infrared spectra was by SVM, showing a sensitivity of 93.3% (42/45), specificity of 74% (17/23), and accuracy of 87% between non-diabetic subjects and uncontrolled type 2 DM patients. The SHAP features of infrared spectra indicate the main salivary vibrational modes of lipids and proteins that are responsible for discriminating DM patients. In summary, these data highlight the potential of ATR-FTIR platforms coupled with machine learning as a reagent-free, non-invasive, and highly sensitive tool for screening and monitoring diabetic patients.

Salivary Detection of Zika Virus Infection Using ATR-FTIR Spectroscopy Coupled with Machine Learning Algorithms and Univariate Analysis: A Proof-of-Concept Animal Study.

Zika virus (ZIKV) diagnosis is currently performed through an invasive, painful, and costly procedure using molecular biology. Consequently, the search for a non-invasive, more cost-effective, reagent-free, and sustainable method for ZIKV diagnosis is of great relevance. It is critical to prepare a global strategy for the next ZIKV outbreak given its devastating consequences, particularly in pregnant women. Attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy has been used to discriminate systemic diseases using saliva; however, the salivary diagnostic application in viral diseases is unknown. To test this hypothesis, we intradermally challenged interferon-gamma gene knockout C57/BL6 mice with ZIKV (50 µL,105 FFU, n = 7) or vehicle (50 µL, n = 8). Saliva samples were collected on day three (due to the peak of viremia) and the spleen was also harvested. Changes in the salivary spectral profile were analyzed by Student's t test (p < 0.05), multivariate analysis, and the diagnostic capacity by ROC curve. ZIKV infection was confirmed by real-time PCR of the spleen sample. The infrared spectroscopy coupled with univariate analysis suggested the vibrational mode at 1547 cm-1 as a potential candidate to discriminate ZIKV and control salivary samples. Three PCs explained 93.2% of the cumulative variance in PCA analysis and the spectrochemical analysis with LDA achieved an accuracy of 93.3%, with a specificity of 87.5% and sensitivity of 100%. The LDA-SVM analysis showed 100% discrimination between both classes. Our results suggest that ATR-FTIR applied to saliva might have high accuracy in ZIKV diagnosis with potential as a non-invasive and cost-effective diagnostic tool.

Hybrid materials based on chitosan functionalized with green synthesized copper nanoparticles: Physico-chemical and antimicrobial analysis.

Recently, the development of materials with antimicrobial properties has become a challenge under scrutiny. The incorporation of copper nanoparticles (NpCu) into a chitosan matrix appears to represent a viable strategy to contain the particles and prevent their oxidation. Regarding the physical properties, the nanocomposite films (CHCu) showed a decrease in the elongation at break (5 %) and an increase in the tensile strength of 10 % concerning chitosan films (control). They also showed solubility values lower than 5 % while the swelling diminished by 50 %, on average. The dynamical mechanical analysis (DMA) of nanocomposites revealed two thermal events located at 113° and 178 °C, which matched the glass transitions of the CH-enriched phase and nanoparticles-enriched phase, respectively. In addition, the thermogravimetric analysis (TGA) detected a greater stability of the nanocomposites. Chitosan films and the NpCu-loaded nanocomposites demonstrated excellent antibacterial capacity against Gram-negative and Gram-positive bacteria, proved through diffusion disc, zeta potential, and ATR-FTIR techniques. Additionally, the penetration of individual NpCu particles into bacterial cells and the leakage of cell content were verified by TEM. The mechanism of the antibacterial activity of the nanocomposites involved the interaction of chitosan with the bacterial outer membrane or cell wall and the diffusion of the NpCu through the cells. These materials could be applied in diverse fields of biology, medicine, or food packaging.

Microanalytical Characterization of an Innovative Modern Mural Painting Technique by SEM-EDS, NMR and Micro-ATR-FTIR among Others.

During the 20th century, modern painters experimented with different mediums and painting techniques, one of them was Rafael Coronel in his mural painting, Paisaje Abstracto (Abstract landscape). The painting was created with a peculiar pouring technique and an unknown binding medium; ageing produced fractures and severe conservation problems. Therefore, the characterization of the painting medium became an urgent matter in order to understand the current condition of the painting and to develop a proper treatment. The aim of this research was to characterize the chemical composition and painting technique of Paisaje Abstracto. To approach this goal two microsamples were taken and analyzed by optical microscopy (OM), scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS), nuclear magnetic resonance (NMR) spectroscopy, attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR), micro attenuated total reflection Fourier transform infrared spectroscopy (micro-ATR-FTIR) and gas chromatography/mass spectrometry (GC/MS). The analysis allowed for the identification of cadmium sulfide (CdS) and titanium dioxide (TiO2) as inorganic pigments; aluminosilicate fillers; poly(methyl methacrylate) (pMMA) as a binder; MMA monomer, red organic pigment PR181; benzoyl peroxide, dibutyl phthalate and 1-octadecanol as organic additives. This study presents an innovative painting technique with pMMA, a medium not commonly used by artists, which was probably polymerized onto the painting support.

Potential Role of Fourier Transform Infrared Spectroscopy as a Screening Approach for Breast Cancer.

Breast cancer is a heterogeneous disease, and its spread involves a succession of clinical and pathological stages. Screening is predominantly based on mammography, which has critical limitations related to the effectiveness and production of false-positive or false-negative results, generating discomfort and low adherence. In this context, infrared with attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy emerges as a non-destructive sample tool, which is non-invasive, label-free, has a low operating-cost, and requires only a small amount of sample, including liquid plasma samples. We sought to evaluate the clinical applicability of ATR FT-IR in breast cancer screening. ATR FT-IR spectroscopy through its highest potential spectral biomarker could distinguish, by liquid plasma biopsy, breast cancer patients and healthy controls, obtaining a sensitivity of 97%, specificity of 93%, a receiver operating characteristic ROC curve of 97%, and a prediction accuracy of 94%. The main variance between the groups was mainly in the band 1511 cm-1 of the control group, 1502 and 1515 cm-1 of the cancer group, which are the peaks of the bands referring to proteins and amide II. ATR FT-IR spectroscopy has demonstrated to be a promising tool for breast cancer screening, given its time efficiency, cost of approach, and its high ability to distinguish between the liquid plasma samples of breast cancer patients and healthy controls.

Detection of People Positive to COVID-19 through ATR-FTIR Spectra Analysis of Saliva using Machine Learning / Detección de Personas Positivas a COVID-19 mediante el Análisis de Espectros ATR-FTIR de Muestras de Saliva empleando Machine Learning

ABSTRACT COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. This virus's spread is mainly through droplets released from the nose or mouth of an infected person. Although vaccines have been developed that effectively reduce the effects that this viral infection causes, the most effective method to contain the virus's spread is numerous tests to detect and isolate possible carriers. However, the response time, combined with the cost of actual tests, makes this option impractical. Herein, we compare some machine learning methodologies to propose a reliable strategy to detect people positive to COVID-19, analyzing saliva spectra obtained by Fourier transform infrared (FTIR) spectroscopy. After analyzing 1275 spectra, with 7 strategies commonly used in machine learning, we concluded that a multivariate linear regression model (MLMR) turns out to be the best option to identify possible infected persons. According to our results, the displacement observed in the region of the amide I of the spectrum, is fundamental and reliable to establish a border from the change in slope that causes this displacement that allows us to characterize the carriers of the virus. Being more agile and cheaper than reverse transcriptase polymerase chain reaction (RT-PCR), it could be reliably applied as a preliminary strategy to RT-PCR.

RESUMEN La COVID-19 es una enfermedad infecciosa ocasionada por el virus SARS-CoV-2. La propagación de este virus se produce principalmente a través de gotitas liberadas por la nariz o la boca de una persona infectada. Aunque se han desarrollado vacunas que permiten reducir efectivamente los efectos que esta infección viral provoca, el método más eficaz para contener la propagación del virus son las numerosas pruebas para detectar y aislar los posibles portadores. Sin embargo, el tiempo de respuesta, combinado con el costo de las pruebas reales, hace que esta opción sea poco práctica. Aquí, comparamos algunas metodologías de machine learning para proponer una estrategia confiable para detectar personas positivas a COVID-19 analizando espectros de saliva obtenidos por espectroscopia infrarroja transformada de Fourier (FTIR). Tras analizar 1275 espectros, con 7 estrategias comúnmente empleadas en el área de machine learning, concluimos que un modelo de regresión lineal multivariante (MLMR) resulta ser la mejor opción para identificar posibles infectados. De acuerdo con nuestros resultados, el desplazamiento observado en la región de la amida I del espectro, resulta fundamental y confiable para establecer una frontera a partir del cambio de pendiente que este provoca. Al ser más ágil y económica que la reacción en cadena de la polimerasa con transcriptasa inversa (RT-PCR), podría aplicarse confiablemente como estrategia preliminar a RT-PCR.

Food grade titanium dioxide accumulation leads to cellular alterations in colon cells after removal of a 24-hour exposure.

Titanium dioxide food grade (E171) is one of the most used food additives containing nanoparticles. Recently, the European Food Safety Authority indicated that E171 could no longer be considered safe as a food additive due to the possibility of it being genotoxic and there is evidence that E171 administration exacerbates colon tumor formation in murine models. However, less is known about the effects of E171 accumulation once the exposure stopped, then we hypothesized that toxic effects could be detected even after E171 removal. Therefore, we investigated the effects of E171 exposure after being removed from colon cell cultures. Human colon cancer cell line (HCT116) was exposed to 0, 1, 10 and 50 µg/cm2 of E171. Our results showed that in the absence of cytotoxicity, E171 was accumulated in the cells after 24 of exposure, increasing granularity and reactive oxygen species, inducing alterations in the molecular pattern of nucleic acids and lipids, and causing nuclei enlargement, DNA damage and tubulin depolymerization. After the removal of E171, colon cells were cultured for 48 h more hours to analyze the ability to restore the previously detected alterations. As we hypothesized, the removal of E171 was unable to revert the alterations found after 24 h of exposure in colon cells. In conclusion, exposure to E171 causes alterations that cannot be reverted after 48 h if E171 is removed from colon cells.

Free, but not microplastic-free, drinking water from outdoor refill kiosks: A challenge and a wake-up call for urban management.

Free refill drinking water kiosks are an essential sustainable water supply system for people in metropolitan areas worldwide. Despite their importance in urban settings, the impact of microplastic contamination remains elusive. Here, we investigated the occurrence and characteristics of microplastics in drinking-water samples collected from 22 self-distributed refill kiosks located in 14 multiuse urban parks spread across nine municipalities in Mexico City (Mexico). The results showed that microplastics were detected in all the samples, with an overall mean concentration of 74.18 ± 48.76 microplastics L-1. The abundance of microplastics was significantly different between sampled kiosks, ranging from 23 ± 11.31 to 202 ± 28.39 microplastics L-1. There were more fibrous microplastics (88%) than fragments (9%) and films (3%), with the majority (56%) being <200 µm in length. They were predominantly transparent (85%), with only a few being colored (15%; blue, red, green, and brown). Attenuated Total Reflection-Fourier-transform infrared spectroscopy further revealed microplastics of various polymer types, including polyvinyl alcohol, high-density polyethylene, polypropylene, polyvinyl acetate, ethylene vinyl alcohol, acrylic, alkyd resin, and viscose. Based on our findings, drinking water from urban refill kiosks exposes children more than adults to microplastics. Furthermore, the steps that should be taken at urban refill kiosks to prevent microplastic pollution while offering recreational services to people have been highlighted. Therefore, this first study serves as a wake-up call to urban water management to improve the safety of water from emerging pollutants like microplastics in the infrastructure of refill kiosks.

Discrimination of white automotive paint samples using ATR-FTIR and PLS-DA for forensic purposes.

The consequences of a hit-and-run car crash are significant and may include serious injuries to the victims, health system overload and even victim's death. The vehicle and driver identification are often challenging for local law enforcement. The aim of this study was to develop a methodology to discriminate between automotive paint samples according to the make of the vehicle and its color shade. 143 white samples (collected at traffic accident scenes) were analyzed in situ by Fourier transform infrared spectroscopy with attenuated total reflectance (ATR-FTIR) and coupled microscopy. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed for data analysis. The samples were split into three groups: calibration set, validation set and external test set. The figures of merit were calculated to assess the quality of the model. Sensitivity, specificity, and efficiency rates were, respectively, 98,9%, 98.4% and 98.6%, for the calibration set. For the validation group, the classification accuracy was 100%. Correct classification rates for the internal validation set and external test set were 100% and 79.1% respectively. The technique is clean, fast, relatively low-cost, and non-destructive. Damaged regions of the samples were avoided by using the attached microscope. Limiting the age of the samples to a maximum of 10 years was enough to avoid misclassifications due to the natural degradation and weathering of the sample. Since the external test group is formed by underrepresented classes, its correct classification rate (79.1%) can be potentially improved at any time, by including and analyzing more samples.

Properties of the PVA-VAVTD KOH Blend as a Gel Polymer Electrolyte for Zinc Batteries.

Rechargeable zinc-air batteries are promising for energy storage and portable electronic applications because of their good safety, high energy density, material abundance, low cost, and environmental friendliness. A series of alkaline gel polymer electrolytes formed from polyvinyl alcohol (PVA) and different amounts of terpolymer composed of butyl acrylate, vinyl acetate, and vinyl neodecanoate (VAVTD) was synthesized applying a solution casting technique. The thin films were doped with KOH 12M, providing a higher amount of water and free ions inside the electrolyte matrix. The inclusion of VAVTD together with the PVA polymer improved several of the electrical properties of the PVA-based gel polymer electrolytes (GPEs). X-ray diffraction (XRD), thermogravimetric analysis (TGA), and attenuated total reflectance- Fourier-transform infrared spectroscopy (ATR-FTIR) tests, confirming that PVA chains rearrange depending on the VAVTD content and improving the amorphous region. The most conducting electrolyte film was the test specimen 1:4 (PVA-VAVTD) soaked in KOH solution, reaching a conductivity of 0.019 S/cm at room temperature. The temperature dependence of the conductivity agrees with the Arrhenius equation and activation energy of ~0.077 eV resulted, depending on the electrolyte composition. In addition, the cyclic voltammetry study showed a current intensity increase at higher VAVTD content, reaching values of 310 mA. Finally, these gel polymer electrolytes were tested in Zn-air batteries, obtaining capacities of 165 mAh and 195 mAh for PVA-T4 and PVA-T5 sunk in KOH, respectively, at a discharge current of -5 mA.

Rapid classification of chromoblastomycosis agents genera by infrared spectroscopy and chemometrics supervised by sequencing of rDNA regions.

Chromoblastomycosis (CBM) is a skin and subcutaneous infection caused by species of seven fungal genera. Identification of CBM species is performed by DNA sequencing of one or more genes, which becomes a time-consuming work. Fourier Transform Infrared Spectroscopy (FTIR) has been used for the identification of other microorganisms, however, only one CBM genus was evaluated by FTIR analysis to date. Therefore, the study is aimed to differentiate the CBM agents for identification at genera level using FTIR supervised by Internal Transcribed Spacer (ITS) rDNA region. Seventy-seven isolates of the main five CBM genera were prepared for Attenuated Total Reflection FTIR (ATR-FTIR) with a new methodology using slices of dry fungus in glass fixing-modeling proposed in this study. The algorithm Hierarchical Cluster Analysis (HCA) was used to analyze the differences and similarities between species through the spectra. Orthogonal Partial Least Square Discriminant Analysis (OPLS-DA) allowed to correctly classify all samples of five CBM genera. The ATR-FTIR/OPLS-DA models highlighted important contributions of regions attributed to NH and OH stretching, amide I of proteins, polysaccharides bands and fingerprint region for the complete differentiation of the genera investigated. Thus, FTIR can be a fast and inexpensive alternative for identification of CBM agents.

Monitoring of Peripheral Blood Leukocytes and Plasma Samples: A Pilot Study to Examine Treatment Response to Leflunomide in Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a painful inflammatory disease of the joints which affects a considerable proportion of the world population, mostly women. If not adequately treated, RA patients can become permanently disabled. Importantly, not all the patients respond to the available anti-rheumatic therapies, which also present diverse side effects. In this context, monitoring of treatment response is pivotal to avoid unnecessary side effects and costs towards an ineffective therapy. Herein, we performed a pilot study to investigate the potential use of flow cytometry and attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy as measures to identify responders and non-responders to leflunomide, a disease-modifying drug used in the treatment of RA patients. The evaluation of peripheral blood CD62L+ polymorphonuclear cell numbers and ATR-FTIR vibrational modes in plasma were able to discriminate responders to leflunomide (LFN) three-months after therapy has started. Overall, the results indicate that both flow cytometry and ATR-FTIR can potentially be employed as additional measures to monitor early treatment response to LFN in RA patients.

Infrared Spectroscopy Based Study of Biochemical Changes in Saliva during Maximal Progressive Test in Athletes.

This study aims to explore biochemical changes in saliva during cardiorespiratory exercise using attenuated-total-reflectance-Fourier-transform-infrared-spectroscopy (ATR-FTIR). Saliva and blood samples were obtained from six athletes at rest, and after running at speeds of 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, and 20 kilometers-per-hour (km/h) on a treadmill (maximal stress test). Saliva ATR-FTIR spectra were analyzed using deconvolution and multivariate analysis. Area-under-the-curve calculations suggest differential changes in glucose, lactate, protein, lipids, carbohydrate and phosphate content in saliva during the test. Increases in glucose and lactate levels with increasing speeds were verified by simultaneous measurement of blood glucose and lactate levels using standard equipment (Roche®). Multivariate principal-component-analysis (PCA) showed discrete clusters for low (rest-14 km/h) and high (15 - 20 km/h) speeds, and PCA-linear-discriminant-analysis showed 100% classification of 18 - 20 km/h as high speed. Overall, results suggest the possibility of using this non-invasive saliva-based ATR-FTIR method for biochemical assessment during sports exercise and stress tests.