Attenuated Total Reflection Fourier Transform Infrared Data Research Articles

Emphasizing the Potential of Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) Spectroscopy Combined with Chemometrics, for Classification of Greek Grape Marc Spirits

Grape marc spirits, such as the Greek tsipouro/tsikoudia, reflect the cultural heritage of winemaking traditions worldwide. This study explored the application of Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy combined with chemometrics for its potential as a fast classification methodology for spirit characterization. ATR-FTIR spectra from thirty-nine products revealed distinctive bands corresponding to various chemical constituents, such as alcohols, organic acids, water, carbohydrates, and phenols. Principal Component Analysis (PCA) was performed on all acquired ATR-FTIR data and 78.50% of the total variance in the data was explained. Also, partial least squares–discriminant analysis (PLS-DA), used for the classification of products based on their major geographic origin, gave a correct classification of 89.5% for the north and 83.3% for the south of Greece. Classification of the type of distillations used was with 74.36% accuracy. Significant markers were identified through analysis, such as those associated with the O-H bending vibrations of phenols or alcohols, contributing to the discrimination of grape marc spirits from Crete when compared with the other four main geographical origin designations. By combining ATR-FTIR spectroscopy with chemometrics, this research gave insights into the origins and compositional variations of the spirits, providing an opportunity for a quality control assessment tool.

Mineral and particle-size chemometric classification using handheld near-infrared instruments for soil in Northeast Brazil

The characterization of soil variations crucial for agriculture is challenging due to soil having different mineral composition and particle-size distribution. Traditional methods are costly and time-consuming for large-sized areas. Spectroscopic techniques coupled with chemometrics are alternative ways to overcome these drawbacks. Miniaturized near-infrared (NIR) spectrophotometers provide fast, cost-effective spectra acquisition for assessing soil chemistry and distribution despite challenges like overlapped bands and reduced spectral range. This study presents a pattern recognition strategy to address these limitations, enhancing the use of handheld NIR instruments for soil analysis. The study analyzed 176 soil samples from 15 soil groups in the Northeast region of Brazil. First, attenuated total reflectance-Fourier transform infrared (ATR-FTIR) and energy-dispersive X-ray fluorescence spectrometry (EDXRF) were employed to characterize the samples, providing complementary vibrational and elemental information, respectively. Common Dimension Analysis (ComDim) identified links between ATR-FTIR and EDXRF data, aiding soil characterization. The Common Components (CCs) from ComDim were used in Partitioning Around Medoids (PAM) clustering, resulting in five distinct classes based on their mineral composition. These classes showed significant differences in clay and sand contents. With the use of ComDim-PAM, samples were labeled for classification via Partial-least Squares-Discriminant Analysis (PLS-DA) and Support Vector Machine (SVM) using NIR spectra (spectral range: 908–1676 nm) from two handheld instruments (Hand 1 and Hand 2). The SVM models outperformed the PLS-DA models, especially by including variable selection for Hand 1, with test accuracy exceeding 90%. These findings highlight the method's advantages for fast and cost-effective assessment, classification, and soil mapping based on their mineral and particle-size distribution.

Complete characterization of RNA biomarker fingerprints using a multi-modal ATR-FTIR and SERS approach for label-free early breast cancer diagnosis.

Breast cancer is a prevalent form of cancer worldwide, and the current standard screening method, mammography, often requires invasive biopsy procedures for further assessment. Recent research has explored microRNAs (miRNAs) in circulating blood as potential biomarkers for early breast cancer diagnosis. In this study, we employed a multi-modal spectroscopy approach, combining attenuated total reflection Fourier transform infrared (ATR-FTIR) and surface-enhanced Raman scattering (SERS) to comprehensively characterize the full-spectrum fingerprints of RNA biomarkers in the blood serum of breast cancer patients. The sensitivity of conventional FTIR and Raman spectroscopy was enhanced by ATR-FTIR and SERS through the utilization of a diamond ATR crystal and silver-coated silicon nanopillars, respectively. Moreover, a wider measurement wavelength range was achieved with the multi-modal approach than with a single spectroscopic method alone. We have shown the results on 91 clinical samples, which comprised 44 malignant and 47 benign cases. Principal component analysis (PCA) was performed on the ATR-FTIR, SERS, and multi-modal data. From the peak analysis, we gained insights into biomolecular absorption and scattering-related features, which aid in the differentiation of malignant and benign samples. Applying 32 machine learning algorithms to the PCA results, we identified key molecular fingerprints and demonstrated that the multi-modal approach outperforms individual techniques, achieving higher average validation accuracy (95.1%), blind test accuracy (91.6%), specificity (94.7%), sensitivity (95.5%), and F-score (94.8%). The support vector machine (SVM) model showed the best area under the curve (AUC) characterization value of 0.9979, indicating excellent performance. These findings highlight the potential of the multi-modal spectroscopy approach as an accurate, reliable, and rapid method for distinguishing between malignant and benign breast tumors in women. Such a label-free approach holds promise for improving early breast cancer diagnosis and patient outcomes.

Elucidating the nanostructure of small interfering RNA-loaded lipidoid-polymer hybrid nanoparticles

We analyzed the structural and material properties of small interfering RNA (siRNA)-loaded lipid-polymer hybrid nanoparticles (LPNs) containing ionizable lipidoid and poly(dl-lactic-co-glycolic acid) (PLGA) using small-angle X-ray scattering, cryogenic transmission electron microscopy, polarized light microscopy, the Langmuir monolayer methodology, differential scanning calorimetry, and attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy. Scattering analyses showed that bulk lipidoid self-assemble into lamellar structures with a d-spacing of 38 Å, whereas lipidoid-siRNA lipoplexes display an in-plane lateral organization of siRNA in between lipidoid bilayers with a repeat distance of approximately 55 Å. The siRNA-loaded LPNs adopted a core–shell structure with an interaxial alignment of siRNA between lipidoid shell bilayers. Langmuir monolayer experiments showed a distinct interaction between the lipidoid headgroups and siRNA, which was dependent on buffer subphase pH. Thermal analyses suggested that PLGA and lipidoid interact, which was evident from a shift in the phase transition temperature of lipidoid, and the thermotropic phase behavior of lipidoid was affected by inclusion of siRNA. ATR-FTIR data confirmed the shift or disappearance of characteristic absorption bands of siRNA after lipidoid binding. In conclusion, siRNA-loaded LPNs display a core–shell structure, wherein the polymeric core functions as a colloid matrix support for siRNA-loaded lipidoid shell layers.

Rapid and Non-Destructive Techniques for the Discrimination of Ripening Stages in Candonga Strawberries.

Electronic nose (e-nose), attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy and image analysis (IA) were used to discriminate the ripening stage (half-red or red) of strawberries (cv Sabrosa, commercially named Candonga), harvested at three different times (H1, H2 and H3). Principal component analysis (PCA) performed on the e-nose, ATR-FTIR and IA data allowed us to clearly discriminate samples based on the ripening stage, as in the score space they clustered in distinct regions of the plot. Moreover, a correlation analysis between the e-nose sensor and 57 volatile organic compounds (VOCs), which were overall detected in all the investigated fruit samples by headspace solid-phase microextraction coupled to gas chromatography-mass spectrometry (HS-SPME/GC-MS), allowed us to distinguish half-red and red strawberries, as the e-nose sensors gave distinct responses to samples with different flavours. Three suitable broad bands were individuated by PCA in the ATR-FTIR spectra to discriminate half-red and red samples: the band centred at 3295 cm−1 is generated by compounds that decline, whereas those at 1717 cm−1 and at 1026 cm−1 stem from compounds that accumulate during ripening. Among the chemical parameters (titratable acidity, total phenols, antioxidant activity and total soluble solid) assayed in this study, only titratable acidity was somehow correlated to ATR-FTIR and IA patterns. Thus, ATR-FTIR spectroscopy and IA might be exploited to rapidly assess titratable acidity, which is an objective indicator of the ripening stage.

Synthesis and Characterization of Acrylamide/Acrylic Acid Co-Polymers and Glutaraldehyde Crosslinked pH-Sensitive Hydrogels.

This project aims to synthesize and characterize the pH-sensitive controlled release of 5-fluorouracil (5-FU) loaded hydrogels (5-FULH) by polymerization of acrylamide (AM) and acrylic acid (AA) in the presence of glutaraldehyde (GA) as a crosslinker with ammonium persulphate as an initiator. The formulation’s code is named according to acrylamide (A1, A2, A3), acrylic acid (B1, B2, B3) and glutaraldehyde (C1, C2, C3). The optimized formulations were exposed to various physicochemical tests, namely swelling, diffusion, porosity, sol gel analysis, and attenuated total reflection-Fourier transform infrared (ATR-FTIR). These 5-FULH were subjected to kinetic models for drug release data. The 5-FU were shown to be soluble in distilled water and phosphate buffer media at pH 7.4, and sparingly soluble in an acidic media at pH 1.2. The ATR-FTIR data confirmed that the 5-FU have no interaction with other ingredients. The lowest dynamic (0.98 ± 0.04% to 1.90 ± 0.03%; 1.65 ± 0.01% to 6.88 ± 0.03%) and equilibrium swelling (1.85 ± 0.01% to 6.68 ± 0.03%; 10.12 ± 0.02% to 27.89 ± 0.03%) of formulations was observed at pH 1.2, whereas the higher dynamic (4.33 ± 0.04% to 10.21 ± 0.01%) and equilibrium swelling (22.25 ± 0.03% to 55.48 ± 0.04%) was recorded at pH 7.4. These findings clearly indicated that the synthesized 5-FULH have potential swelling characteristics in pH 6.8 that will enhance the drug’s release in the same pH medium. The porosity values of formulated 5-FULH range from 34% to 62% with different weight ratios of AM, AA, and GA. The gel fractions data showed variations ranging from 74 ± 0.4% (A1) to 94 ± 0.2% (B3). However, formulation A1 reported the highest 24 ± 0.1% and B3 the lowest 09 ± 0.3% sol fractions rate among the formulations. Around 20% drug release from the 5-FULH was found at 1 h in an acidic media (pH1.2), whereas >65% of drug release (pH7.4) was observed at around 25 h. These findings concluded that GA crosslinked 5-FU loaded AM and AA based hydrogels would be a potential pH-sensitive oral controlled colon drug delivery carrier.

Nondestructive assessment of tissue engineered cartilage based on biochemical markers in cell culture media: application of attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy.

Tissue engineering of cartilage for tissue repair has many challenges, including the inability to assess when the developing construct has reached compositional maturity for implantation. The goal of this study was to provide a novel analytical approach to nondestructively assess tissue engineered cartilage (TEC) during in vitro development. We applied attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy to establish a quick and straightforward method to evaluate consumption of glucose and secretion of the metabolite lactate in the culture media, processes that are associated with tissue development. Using a series of standards, we showed by principal component analysis (PCA) that ATR-FTIR data was able to distinguish culture media with varying amounts of glucose and lactate. The 2nd derivative spectra displayed specific peaks of glucose at 1035 cm-1 and lactate at 1122 cm-1, and both the spectral first principal component (PC-1) scores and the 1122/1035 peak ratio very strongly correlated with the concentration of these components. TEC was prepared using chondrogenic cells grown in hydrogels, and analyzed for cell viability, distribution, and formation of proteoglycan (PG, a major cartilage protein). ATR-FTIR data of the cell culture media harvested during TEC development showed that the spectral PC-1 and the 1122/1035 peak ratio could significantly distinguish cultures with different amounts of constructs (1, 3 or 5 constructs per well) or with constructs at different developmental stages (3 or 5 weeks of culture). Interestingly, we also found that the PG content of the TEC was significantly correlated with both spectral PC-1 (r = -0.79) and the 1122/1035 peak ratio (r = 0.80). Therefore, monitoring relative glucose and lactate concentrations in cell culture media by ATR-FTIR provides a novel nondestructive approach to assess development of TEC.

Forensic Discrimination of Blue Ballpoint, Gel and Oil-Gel Pens: Application of Chemometrics to ATR-FTIR Data

The combination of advanced techniques with multivariate analysis methods are being used with great confidence by forensics experts due to their high precision and accuracy. The prime objective of present work was to explore the potential of chemometric tools in discriminating and predicting the blue pen inks when applied on Attenuated total reflectance Fourier transform infrared (ATR-FTIR) data of pen strokes of different brands and models commercially available in Pakistani markets. The pen strokes on fine A4 paper and recycled A4 paper were obtained from 86 samples including ballpoints, gel, oil- gel and roller ball pens. ATR-FTIR spectra were first characterized for different functional groups present in ink pigments however, they were apparently indistinguishable having some common functional groups. After spectra preprocessing the principal component analysis (PCA) and agglomerative hierarchical cluster analysis (AHC) showed that pen strokes could be distinguished. Both PCA and AHC analyses showed that ballpoints and gel pen could be discriminated and grouped separately. PCA analyses also showed the discrimination between local and foreign brands of ballpoints. Finally, classification method partial least squares-discriminant analysis (PLS-DA) was successfully applied for the classification and subsequently for the identification of type of pen used in personnel’s signature to mimic a forensic case. To evaluate PLS-DA classification performance, the classification parameters such as sensitivity, specificity, accuracy and precision were also derived from confusion matrix. Overall, this work emphasized the worth of multivariate analysis in classification and prediction of type of writing pen in a document as a forensic study.

Comparison of chemometric assisted targeted and untargeted approaches for the prediction of radical scavenging activity of ylang-ylang essential oils

Essential oils have been used for centuries for their preservative properties. An example is ylang-ylang Cananga odorata [Lam.] Hook. f. & Thomson essential oil, which exists in four different distillation grades, where the fraction with the longest distillation time has the highest radical scavenging activity (RSA). Gas chromatography mass spectrometry (GC-MS) followed by multivariate statistical analysis is a powerful approach for determination of RSA. Herein the performance of such multivariate statistical analysis using three data sets derived from gas chromatography mass spectrometry (GC-MS) analysis, is compared to that achieved using two direct and fast spectroscopic techniques, for the prediction of RSA using partial least squares (PLS) regression analysis. The three GC-MS data sets were, ‘full chemical composition’, ‘total chromatogram average mass spectra (TCAMS)’ and ‘segment average mass spectra (SAMS)’, whilst two spectroscopic techniques, namely attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy and Raman spectroscopy, provided the spectroscopic data sets for comparison. PLS models created using ATR-FTIR and ‘full chemical composition’ data sets provided the lowest relative error of prediction (REP) and mean error of prediction (MEP) in validation, whilst in independent test sets, the PLS models created using ATR-FTIR and SAMS data sets delivered the lowest REP and MEP. The three GC-MS derived data sets were further compared for value in determination of compounds contributing to the RSA. PLS regression analysis of the full chemical composition data set revealed that germacrene D and (E,E)-α-farnesene were the major contributors to the RSA, whilst average mass spectrum based data sets, TCAMS and SAMS, also highlighted eugenol as another contributor to the RSA.

ATR-FTIR spectroscopy for the routine quality control of exosome isolations

Exosomes are nanosized vesicles containing specific cargos of DNA, RNA, proteins, metabolites, and intracellular and membrane lipids. Exosome isolation needs to be optimized carefully depending on the type of biofluid and tissue and the retrieved exosomes need to be characterized. The main objective of this study was to determine the feasibility of a multimodal analysis of Attenuated Total Reflectance – Fourier Transform Infrared (ATR-FTIR) spectroscopy and UPLC–QqTOF-MSMS for the development of a routine quality control tool of isolated exosomes and the rapid characterization of their lipid profiles and total protein content. Using human milk as model example, exosomes were isolated by multi-stage ultracentrifugation. After single-phase extraction, lipidomic analysis was carried out by UPLC–QqTOF-MSMS with automated MSMS-based annotation using HMDB, METLIN, LipidBlast and MSDIAL databases. The classes with the largest number of annotated features were glycerophospholipids, sphingolipids, and glycerolipids. Then, dry films of 2 ​μL exosomes were directly analyzed by ATR-FTIR. Multivariate analysis showed significant associations between ATR-FTIR specific regions and the concentrations of different lipid classes. Principal component analysis and Hierarchical Cluster Analysis of IR and lipidomic data showed that ATR−FTIR renders valuable qualitative descriptors of the lipid content of isolated exosomes. Total LC-MS lipid and total protein contents could also be quantified by using the area of CHs and CO stretching bands as well as the amide I band. As a conclusion, results obtained show that multimodal analysis of ATR-FTIR and UPLC-MS data is a useful tool for the development of spectroscopic methods. ATR-FTIR provided both, qualitative and quantitative chemical descriptors of isolated exosomes, enabling a fast and direct quantification of total protein and lipid contents.

Rapid Classification of COVID-19 Severity by ATR-FTIR Spectroscopy of Plasma Samples.

The coronavirus disease 2019 (COVID-19) pandemic continues to ravage the world, with many hospitals overwhelmed by the large number of patients presenting during major outbreaks. A rapid triage for COVID-19 patient requiring hospitalization and intensive care is urgently needed. Age and comorbidities have been associated with a higher risk of severe COVID-19 but are not sufficient to triage patients. Here, we investigated the potential of attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy as a rapid blood test for classification of COVID-19 disease severity using a cohort of 160 COVID-19 patients. A simple plasma processing and ATR-FTIR data acquisition procedure was established using 75% ethanol for viral inactivation. Next, partial least-squares-discriminant analysis (PLS-DA) models were developed and tested using data from 130 and 30 patients, respectively. Addition of the ATR-FTIR spectra to the clinical parameters (age, sex, diabetes mellitus, and hypertension) increased the area under the ROC curve (C-statistics) for both the training and test data sets, from 69.3% (95% CI 59.8–78.9%) to 85.7% (78.6–92.8%) and 77.8% (61.3–94.4%) to 85.1% (71.3–98.8%), respectively. The independent test set achieved 69.2% specificity (42.4–87.3%) and 94.1% sensitivity (73.0–99.0%). Diabetes mellitus was the strongest predictor in the model, followed by FTIR regions 1020–1090 and 1588–1592 cm–1. In summary, this study demonstrates the potential of ATR-FTIR spectroscopy as a rapid, low-cost COVID-19 severity triage tool to facilitate COVID-19 patient management during an outbreak.

Rapid non-destructive techniques to identify the traces of Kajal using chemometrics; A comparison of ATR-FTIR and Raman spectroscopy

Analytical chemistry finds application in forensic science when traces of cosmetic products are left on various substrates at crime scenes, and it is important to link them to the source. A rapid and more importantly, non-destructive approach is needed, that can be used to associate these trace samples to the source. We demonstrate for the first time, the application of two novel vibrational spectroscopy techniques namely; Attenuated Total Reflectance - Fourier Transform Infrared (ATR-FTIR) and Raman spectroscopy, combined with chemometric modeling using Partial Least Squares Discriminant Analysis (PLS-DA) for the discrimination of 45 kajal/kohl samples. The trained PLS-DA model could classify all the samples with high degree of accuracy using ATR-FTIR data, but the performance on the Raman data was found to be perfect. Importantly, when the spectral data of all these traces on different substrates (wet tissue, wall, plastic, nylon, dry tissue, cotton, and polyester) commonly found in crime scenes, were analysed with the trained PLS-DA model, 100% accuracy in predictions of source was obtained in case of the Raman data. However, this figure was slightly lesser for the ATR-FTIR data. Overall, this is a proof of concept study demonstrating that Raman and ATR-FTIR spectroscopy combined with chemometric model (PLS-DA) has great potential for the discrimination of the source of kajal/kohl samples. When the traces of Kajal/kohl are recovered as an evidence from the crime scene, the identification of these traces could provide a significant association between the trace and the source and therefore will be helpful as corroborative evidence in forensic context.

Drug-Smectite Clay Amorphous Solid Dispersions Processed by Hot Melt Extrusion.

The aim of this study was to introduce smectite clay matrices as a drug delivery carrier for the development of amorphous solid dispersions (ASD). Indomethacin (IND) was processed with two different smectite clays, magnesium aluminium and lithium magnesium sodium silicates, using hot melt extrusion (HME) to prepare solid dispersions. Scanning electron microscopy (SEM), powdered X-ray diffraction (PXRD), and differential scanning calorimetry (DSC) were used to examine the physical form of the drug. Energy-dispersive X-ray (EDX) spectroscopy was used to investigate the drug distribution, and attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopic analysis was done to detect any chemical interaction between these two kinds. Both PXRD and DSC analyses showed that drug-clay solid dispersion contained IND in amorphous form. EDX analysis showed a uniform IND dispersion in the extruded powders. ATR-FTIR data presented possible drug and clay interactions via hydrogen bonding. In vitro drug dissolution studies revealed a lag time of about 2h in the acidic media and a rapid release of IND at pH7.4. The work demonstrates that preparation of amorphous solid dispersion using inorganic smectite clay particles can effectively increase the dissolution rate of IND.

RAMAN AND ATR-FTIR SPECTROSCOPY TOWARDS CLASSIFICATION OF WET BLUE BOVINE LEATHER USING RATIOMETRIC AND CHEMOMETRIC ANALYSIS

There is a substantial loss of value in bovine leather every year due to a leather quality defect known as “looseness”. Data show that 7% of domestic hide production is affected to some degree, with a loss of $35 m in export returns. This investigation is devoted to gaining a better understanding of tight and loose wet blue leather based on vibrational spectroscopy observations of its structural variations caused by physical and chemical changes that also affect the tensile and tear strength. Several regions from the wet blue leather were selected for analysis. Samples of wet blue bovine leather were collected and studied in the sliced form using Raman spectroscopy (using 532 nm excitation laser) and Attenuated Total Reflectance - Fourier Transform InfraRed (ATR-FTIR) spectroscopy. The purpose of this study was to use ATR-FTIR and Raman spectra to classify distal axilla (DA) and official sampling position (OSP) leather samples and then employ univariate or multivariate analysis or both. For univariate analysis, the 1448 cm− 1 (CH2 deformation) band and the 1669 cm− 1 (Amide I) band were used for evaluating the lipid-to-protein ratio from OSP and DA Raman and IR spectra as indicators of leather quality. Curve-fitting by the sums-of-Gaussians method was used to calculate the peak area ratios of 1448 and 1669 cm− 1 band. The ratio values obtained for DA and OSP are 0.57 ± 0.099, 0.73 ± 0.063 for Raman and 0.40 ± 0.06 and 0.50 ± 0.09 for ATR-FTIR. The results provide significant insight into how these regions can be classified. Further, to identify the spectral changes in the secondary structures of collagen, the Amide I region (1600–1700 cm− 1) was investigated and curve-fitted-area ratios were calculated. The 1648:1681 cm− 1 (non-reducing: reducing collagen types) band area ratios were used for Raman and 1632:1650 cm− 1 (triple helix: α-like helix collagen) for IR. The ratios show a significant difference between the two classes. To support this qualitative analysis, logistic regression was performed on the univariate data to classify the samples quantitatively into one of the two groups. Accuracy for Raman data was 90% and for ATR-FTIR data 100%. Both Raman and ATR-FTIR complemented each other very well in differentiating the two groups. As a comparison, and to reconfirm the classification, multivariate analysis was performed using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). The results obtained indicate good classification between the two leather groups based on protein and lipid content. Principal component score 2 (PC2) distinguishes OSP and DA by symmetrically grouping samples at positive and negative extremes. The study demonstrates an excellent model for wider research on vibrational spectroscopy for early and rapid diagnosis of leather quality.Graphical abstract

Spectral profiles of commercial omega-3 supplements: an exploratory analysis by ATR-FTIR and 1H NMR.

Most of the population is dependent on supplemental products to reach the recommended level of omega-3 polyunsaturated fatty acid (ω-3 PUFA) intake. Thus, knowledge about the quality of ω-3 supplements is important for their safe consumption. In this work, attenuated total reflectance-Fourier transform infrared (ATR-FTIR) and nuclear magnetic resonance (NMR) spectroscopy were applied to assess the quality of fourteen commercial ω-3 supplements. Using ATR-FTIR data, we could identify whether ω-3 PUFA was esterified as either triacylglyceride (71%) or ethyl (29%) esters in ω-3 supplements. The type of esterification is rarely included in the product labels, although the consumer should have the right to choose which form of the supplement to consume. On the other hand, 1H NMR spectra were useful to determine the relative concentration of eicosapentaenoic (EPA) and docosahexaenoic (DHA) acids, and ω-3 PUFA in these commercial samples. Ethyl esters have higher concentrations of unsaturated fatty acids. The NMR results showed a good agreement between the obtained and declared DHA and EPA amounts on the product labels, except for one sample whose high level of ω-3 PUFA indicated it to be a vegetable oil-enriched supplement. Moreover, ω-3 supplements from Schizochytrium sp. microalgae oil revealed higher levels of DHA and ω-3 PUFA, but lower levels of EPA than fish oil. These findings indicate the need for a constant assessment of the quality of commercial products whose ATR-FTIR spectra could be routinely used for the evaluation of PUFA esterification, and NMR analysis could be used to provide advanced quantitative information on commercial ω-3 supplements.

Infrared Spectroscopy as a Tool to Study the Antioxidant Activity of Polyphenolic Compounds in Isolated Rat Enterocytes.

The protective effect of different polyphenols, catechin (Cat), quercetin (Qc) (flavonoids), gallic acid (GA), caffeic acid (CfA), chlorogenic acid (ChA) (phenolic acids), and capsaicin (Cap), against H2O2-induced oxidative stress was evaluated in rat enterocytes using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) Spectroscopy and Fourier Transform Infrared Microspectroscopy (FTIRM), and results were compared to standard lipid peroxidation techniques: conjugated dienes (CD) and Thiobarbituric Acid Reactive Substances (TBARS). Analysis of ATR-FTIR and FTIRM spectral data allowed the simultaneous evaluation of the effects of H2O2 and polyphenols on lipid and protein oxidation. All polyphenols showed a protective effect against H2O2-induced oxidative stress in enterocytes, when administered before or after H2O2. Cat and capsaicin showed the highest protective effect, while phenolic acids had weaker effects and Qc presented a mild prooxidative effect (IR spectral profile of biomolecules between control and H2O2-treated cells) according to FTIR analyses. These results demonstrated the viability to use infrared spectroscopy to evaluate the oxidant and antioxidant effect of molecules in cell systems assays.

Infrared biospectroscopy for a fast qualitative evaluation of sample preparation in metabolomics

Liquid chromatography-mass spectrometry (LC-MS) has been increasingly used in biomedicine to study the dynamic metabolomic responses of biological systems under different physiological or pathological conditions. To obtain an integrated snapshot of the system, metabolomic methods in biomedicine typically analyze biofluids (e.g. plasma) that require clean-up before being injected into LC-MS systems. However, high resolution LC-MS is costly in terms of resources required for sample and data analysis and care must be taken to prevent chemical (e.g. ion suppression) or statistical artifacts. Because of that, the effect of sample preparation on the metabolomic profile during metabolomic method development is often overlooked. This work combines an Attenuated Total Reflectance-Fourier transform infrared (ATR-FTIR) and a multivariate exploratory data analysis for a cost-effective qualitative evaluation of major changes in sample composition during sample preparation. ATR-FTIR and LC-time of flight mass spectrometry (TOFMS) data from the analysis of a set of plasma samples precipitated using acetonitrile, methanol and acetone performed in parallel were used as a model example. Biochemical information obtained from the analysis of the ATR-FTIR and LC-TOFMS data was thoroughly compared to evaluate the strengths and shortcomings of FTIR biospectroscopy for assessing sample preparation in metabolomics studies. Results obtained show the feasibility of ATR-FTIR for the evaluation of major trends in the plasma composition changes among different sample pretreatments, providing information in terms of e.g., amino acids, proteins, lipids and carbohydrates overall contents comparable to those found by LC-TOFMS.

Real-Time Monitoring of in Situ Polyethyleneimine-Silica Particle Formation

Silica particles are traditionally made via the hydrolysis and condensation of tetraalkoxysilanes with the use of methanol and ammonia as a basic catalyst. More recently, bioinspired polyamines have been used in place of ammonia. Particle formation via the use of tetraalkoxysilanes typically occurs extremely quickly with cloudy precipitates forming immediately, making it practically impossible to characterize the reaction in real time. Our study uses trimethoxymethylsilane (TMOMS) and the polyamine polyethyleneimine (PEI) to form PEI-silica particles via a reaction that takes place over several minutes, allowing us to study the reaction in real time. The acidic hydrolysis of TMOMS and basic polymerization condensation of TMOMS via PEI to form solid PEI-silica particles were observed in situ over time using attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy and dynamic light scattering (DLS) for the first time. The ATR-FTIR data suggest that dimer formation occurs during acidic hydrolysis followed by PEI-catalyzed condensation to form silsesquioxane structures. The results for the particles formed in situ were then compared with those for particle samples that had been washed to remove excess reactants. The ATR-FTIR results were corroborated via scanning electron microscopy and DLS, which suggest that the growth of PEI-silica particles occurs by aggregation of smaller particles to larger ones, because the data show the presence of small particles and much larger particles at the same time throughout the whole particle growth process.

Effect of silicic acid on arsenate and arsenite retention mechanisms on 6-L ferrihydrite: A spectroscopic and batch adsorption approach

The competitive adsorption of arsenate and arsenite with silicic acid at the ferrihydrite–water interface was investigated over a wide pH range using batch sorption experiments, attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, extended X-ray absorption fine structure (EXAFS) spectroscopy, and density functional theory (DFT) modeling. Batch sorption results indicate that the adsorption of arsenate and arsenite on the 6-L ferrihydrite surface exhibits a strong pH-dependence, and the effect of pH on arsenic sorption differs between arsenate and arsenite. Arsenate adsorption decreases consistently with increasing pH; whereas arsenite adsorption initially increases with pH to a sorption maximum at pH 7–9, where after sorption decreases with further increases in pH. Results indicate that competitive adsorption between silicic acid and arsenate is negligible under the experimental conditions; whereas strong competitive adsorption was observed between silicic acid and arsenite, particularly at low and high pH. In situ, flow-through ATR-FTIR data reveal that in the absence of silicic acid, arsenate forms inner-sphere, binuclear bidentate, complexes at the ferrihydrite surface across the entire pH range. Silicic acid also forms inner-sphere complexes at ferrihydrite surfaces throughout the entire pH range probed by this study (pH 2.8–9.0). The ATR-FTIR data also reveal that silicic acid undergoes polymerization at the ferrihydrite surface under the environmentally-relevant concentrations studied (e.g., 1.0mM). According to ATR-FTIR data, arsenate complexation mode was not affected by the presence of silicic acid. EXAFS analyses and DFT modeling confirmed that arsenate tetrahedra were bonded to Fe metal centers via binuclear bidentate complexation with average As(V)-Fe bond distance of 3.27Å. The EXAFS data indicate that arsenite forms both mononuclear bidentate and binuclear bidentate complexes with 6-L ferrihydrite as indicated by two As(III)–Fe bond distances of ∼2.92–2.94 and 3.41–3.44Å, respectively. The As–Fe bond distances in both arsenate and arsenite EXAFS spectra remained unchanged in the presence of Si, suggesting that whereas Si diminishes arsenite adsorption preferentially, it has a negligible effect on As–Fe bonding mechanisms.

Counterfeit Cialis and Viagra fingerprinting by ATR-FTIR spectroscopy with chemometry: Can the same pharmaceutical powder mixture be used to falsify two medicines?

This paper proposes a direct and efficient method to discriminate between counterfeit and authentic Cialis and Viagra samples by combining attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy with multivariate techniques. The chemical profile of 53 commercial samples (Viagra®, Cialis®) and 104 counterfeit samples (Viagra and Cialis) from distinct seizures were obtained from ATR-FTIR data derived from 10mg of crushed core tablets. Principal component analysis (PCA) technique was employed to classify samples based on the fingerprint region mid-infrared spectra (1800–525cm−1) using OMNIC v.7.2 software; PCA enabled categorizing samples in groups with different chemical profiles, successfully distinguishing between authentic and counterfeits samples in forensic routine. The existence of active pharmaceutical ingredients (API) and technological adjuvant others than specified on the medicine package were also detected in counterfeit samples. In addition, we applied the similarity match (SM) method to demonstrate that a mixture of pharmaceutical powders deriving from a common origin may have been used to manufacture both counterfeit Cialis and Viagra tablets from distinct seizures.