Quantifying selective pulsed laser cleaning and residual contamination in paper artifacts by ATR spectroscopy

In this study, we report the use of attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FT-IR) for the identification and quantitation of two polymorphs of Aprepitant, a substance P antagonist for chemotherapy-induced emesis. Mixtures of the polymorph pair were prepared by weight and ATR-FT-IR spectra of the powdered samples were obtained over the wavelength range of 700-1500 cm(-1). Significant spectral differences between the two polymorphs at 1140 cm(-1) show that ATR-FT-IR can provide definitive identification of the polymorphs. To investigate the feasibility of ATR-FT-IR for quantitation of polymorphic forms of Aprepitant, a calibration plot was constructed with known mixtures of the two polymorphs by plotting the peak ratio of the second derivative of absorbance spectra against the weight percent of form II in the polymorphic mixture. Using this novel approach, 3 wt % of one crystal form could be detected in mixtures of the two polymorphs. The accuracy of ATR-FT-IR in determining polymorph purity of the drug substance was tested by comparing the results with those obtained by X-ray powder diffractometry (XRPD). Indeed, polymorphic purity results obtained by ATR-FT-IR were found to be in good agreement with the predictions made by XRPD and compared favorably with actual values in the known mixtures. The present study clearly demonstrates the potential of ATR-FT-IR as a quick, easy, and inexpensive alternative to XRPD for the determination of polymorphic identity and purity of solid drug substances. The technique is ideally suited for polymorph analysis, because it is precise, accurate, and requires minimal sample preparation.

A person's age estimation from biological evidence is a crucial aspect of forensic investigations, aiding in victim identification and criminal profiling. In this study, we present a novel approach of utilizing Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) spectroscopy to predict the age of donors based on nail samples. A diverse dataset comprising nails from donors spanning different age groups was analyzed using ATR FT-IR, with subsequent multivariate analysis techniques used for age prediction. The developed partial least squares regression (PLS-R) model demonstrated promising accuracy in age estimation, with a root mean square error of prediction (RMSEP) equal to 11.1 during external validation. Additionally, a partial least squares discriminant analysis (PLS-DA) classification model achieved high accuracy of 88% in classifying donors into younger and older age groups during external validation. This proof-of-concept study highlights the potential of ATR FT-IR spectroscopy as a non-destructive and efficient tool for age estimation in forensic investigations, offering a new approach to forensic analysis with practical implications.

Development of Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy Coupled with Multivariate Classification Chemometric Model for Routine Screening of Paracetamol, Ibuprofen, and Aspirin Adulteration in Herbal Products

Machine learning-enhanced Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy for discrimination of green Arabica and Robusta coffee beans

Attenuated total reflectance Fourier transform infrared (ATR/FT-IR) spectrometry was applied to the determination of calcium carbonate in limestone. Both of the simple and multiple linear regression methods have been investigated. The correlation coefficient was found to be increased to 0.985 when the multiple linear regression analyses using the absorbance values at all of the wavelengths were applied. The standard deviation of calibration for 37 samples by this method was 0.601. In order to test the applicability of the multiple linear regression method to routine analyses of limestones, 31 samples collected from the various mines distributed in Korea were analyzed by chemical and ATR/FT-IR methods. The range of CaCO 3 concentrations of the tested samples were 86-97%. The standard error of prediction (SEP) was found to be 0.294 when the absorbance values at all of the three wavelengths were used, whereas the SEP values were 1.340, 1.072 and 0.961 for the wavenumbers of 711, 1406 and 875 cm -1 , respectively. The results indicate that the ATR/FT-IR method can be applied to the routine determination of CaCO 3 in limestone by mid-infrared spectroscopy. The present method required virtually no pretreatment procedure and thus took less time comparing with the conventional wet chemical methods.

Evaluation of the Moisture Prediction Capability of Near-Infrared and Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy Using Superdisintegrants as Model Compounds

BackgroundChronic respiratory infections with non-fermenting Gram-negative bacilli are a key feature of cystic fibrosis (CF). For microbiology laboratories, rapid and accurate identification of these bacteria is often challenging and labor intensive. This study was undertaken to evaluate whether attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy could rapidly discriminate Pseudomonas aeruginosa (mucoid and non-mucoid), Burkholderia cepacia complex, Burkholderia gladioli, Achromobacter spp. and Stenotrophomonas maltophilia.MethodsA total of 263 well-characterized clinical strains isolated from respiratory samples of patients with CF attending the CHU Sainte-Justine CF clinic were included in this study, consisting of 70 P. aeruginosa, 83 Burkholderia spp., 52 Achromobacter spp. and 58 Stenotrophomonas maltophilia isolates from the biobank. Isolates were thawed and sub-cultured twice on sheep blood (5%) agar. ATR-FTIR spectral acquisition was performed in triplicate for each isolate. Multivariate statistical analysis of the ATR-FTIR spectra was performed by hierarchical cluster analysis (HCA) and principal component analysis (PCA) in conjunction with the use of a feature selection algorithm.ResultsAn ATR-FTIR spectral database consisting of 789 spectra of P. aeruginosa, Burkholderia spp., Achromobacter spp. and Stenotrophomonas maltophilia was created in this study. Complete discrimination among all four genera as well as among three species within the B. cepacia complex and B. gladioli was achieved based on HCA and PCA of the spectra in the database. ATR-FTIR analysis of a validation set consisting of 30 isolates was conducted in parallel with identification by MALDI-TOF mass spectrometry and yielded >95% concordance between the two techniques.ConclusionATR-FTIR spectroscopy is a promising tool for rapid, inexpensive and accurate identification of non-fermenting Gram-negative bacilli. Additional work is needed to further expand the spectral database, particularly with mucoid strains.DisclosuresAll authors: No reported disclosures.

Analyzing the composition of animal hair fibers in textiles is crucial for ensuring the quality of yarns and fabrics made from animal hair. Among others, Fourier transform infrared (FT-IR) spectroscopy is a technique that identifies vibrations associated with chemical bonds, including those found in amino acid groups. Cashmere, mohair, yak, camel, alpaca, vicuña, llama, and sheep hair fibers were analyzed via attenuated total reflection FT-IR (ATR FT-IR) spectroscopy and scanning electron microscopy techniques aiming at the discrimination among them to identify possible commercial frauds. ATR FT-IR, being a novel approach, was coupled with chemometric tools (partial least squares discriminant analysis, PLS-DA), building classification/prediction models, which were cross-validated. PLS-DA models provided an excellent differentiation among animal hair of both camelids and eight animal species. In addition, the combination of ATR FT-IR and PLS-DA was used to discriminate the cashmere hair from different origins (Afghanistan, Australia, China, Iran, and Mongolia). The model showed very good discrimination ability (accuracy 87%), with variance expression of 94.88% and mean squared error of cross-validation of 0.1525.

Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy is a spectrum-based technique that quantifies the absorption of infrared light by molecules present in the microbial cell. The aim of the present study was to evaluate the performance of the ATR-FTIR spectroscopic technique via I-dOne software (Version 2.0) compared with the MALDI-TOF MS in identifying Candida spp. Each infrared spectrum was compared with spectra stored in the software database. The updated version of the I-dOne software was used to analyze ATR-FTIR spectra. All Candida isolates 284/284 (100%) were classified correctly according to the genus. Overall species identification yielded 272/284 (95.8%) concordant identification results with MALDI-TOF MS. Additionally, all 79 isolates belonging to the Candida parapsilosis species complex were identified correctly to the species level with the updated version of the I-dOne software. Only 12 (4.2%) isolates were misidentified at the species level. The present study highlights the potential diagnostic performance of the I-dOne software with ATR-FTIR spectroscopic technique referral spectral database as a real alternative for routine identification of the most frequently isolated Candida spp.

The aim of the present study was to investigate the feasibility and applicability of Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FT-IR) techniques, without extraction, with prior extraction of fat and after hydrolysis and methylation, to fatty acid methyl esters (FAMEs) to evaluate the content of trans fatty acids (TFA) in filled biscuits and to compare the results obtained with those obtained when elaidic acid was determined by the GC-MS technique. Eight commercial brands of chocolate filled biscuits and one package of hydrogenated vegetable fat were selected to be used as secondary standards by ATR-FT-IR. The presence of TFA was identified by ATR-FT-IR by visualization of the band at 966 cm-1. No significant differences were found between the concentrations of TFA determined by the three methods tested. The study indicated that the ATR-FT-IR technique, when used to analyze the lipid extract and the samples in the form of FAMEs, is suitable for estimating the TFA content in chocolate filled biscuits.

An integrated in situ ATR-FTIR and EIS set-up to study buried metal–polymer interfaces exposed to an electrolyte solution

This article describes a rapid, simple and cost-effective technique that could lead to a screening method for colitis without the need for biopsies or in vivo measurements. This screening technique includes the testing of serum using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy for the colitis-induced increased presence of mannose. Chronic (Interleukin 10 knockout) and acute (Dextran Sodium Sulphate-induced) models for colitis are tested using the ATR-FTIR technique. Arthritis (Collagen Antibody Induced Arthritis) and metabolic syndrome (Toll like receptor 5 knockout) models are also tested as controls. The marker identified as mannose uniquely screens and distinguishes the colitic from the non-colitic samples and the controls. The reference or the baseline spectrum could be the pooled and averaged spectra of non-colitic samples or the subject's previous sample spectrum. This shows the potential of having individualized route maps of disease status, leading to personalized diagnosis and drug management.

Analysis of sediment samples in the visible to mid infrared (IR) region requires small amounts of sample material and enables rapid and cost efficient geochemical analysis of mineral and organic sediment components. Here we use geochemical properties (total organic and inorganic carbon, biogenic silica, total nitrogen) from the ICDP deep drilling project PASADO to compare three different IR spectroscopy techniques: Diffuse Reflectance Fourier Transform IR Spectrometry (DRIFTS), Attenuated Total Reflectance Fourier Transform IR Spectroscopy (ATR-FTIRS) and Visible Near IR Spectroscopy (VNIRS). ATR-FTIRS and VNIRS are more rapid techniques compared to DRIFTS. Results show that calibration models developed using DRIFTS are most robust (correlation coefficient: R = 0.92 for TIC, R = 0.84 for BSi, R = 0.97 for TOC, R = 0.95 for TN). However, good statistical performance was also obtained by using ATR-FTIRS and VNIRS. When time and costs are limiting factors, these tools may be given preference for rapid biogeochemical screening.

Bovine, porcine, and fish gelatins have been differentiated based on their spectra collected by attenuated total reflectance FTIR spectroscopy (ATR-FTIRS) coupled with pattern recognition. Three tree-based classification methods, a fuzzy rule-building expert system (FuRES), support vector machine classification trees (SVMTreeG and SVMTreeH), and one reference model, super partial least-squares discriminant analysis (sPLS-DA), were evaluated with and without two preprocessing techniques, namely standard normal variate (SNV) and principal component orthogonal signal correction (PC-OSC). Validation of these methods was obtained with 95% confidence intervals with 10 bootstraps and 4 Latin partitions (10:4). The ATR-FTIR spectra were used with four different ranges: full spectra (4000-650 cm-1), fingerprint region (1731-650 cm-1), specified spectra (4000-800 cm-1), and narrow fingerprint region (1731-800 cm-1). Classification rates for the methods were improved with SNV and PC-OSC when they were used separately or together. The highest classification rates were obtained from the narrow fingerprint region with SNV and PC-OSC at 97.4 ± 1.6% for FuRES, 100 ± 0% for sPLS-DA, and 99.3 ± 0.5% for both SVMTreeG and SVMTreeH. ATR-FTIRS combined with pattern recognition is a potential analytical technique for differentiating the sources of bovine, porcine, and fish gelatins with fast and reliable results.

Rapid quantification of isoflurane in anesthetic nanoemulsions using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR)