Multivariate curve resolution-alternating least-squares and second-order advantage in first-order calibration. A systematic characterisation for three-component analytical systems.

BACKGROUND: Recent interest has been focused on the application of multivariate curve resolution-alternating least-squares (MCR-ALS) to systems involving the measurement of first-order and non-bilinear second-order data. The latter pose important challenges to bilinear decomposition models, due to the phenomenon of rotational ambiguity in the solutions, even under the application of the full set of chemical constraints that is usually employed in MCR-ALS calibration. RESULTS: After the analysis of several simulated and experimental datasets, important conclusions regarding the role of the selectivity patterns in the constituent spectra have been drawn concerning the achievement of the second-order advantage. Theoretical considerations based on the calculation of the areas of feasible solutions helped to support the observations regarding the predictive ability of MCR- ALS in the various datasets. SIGNIFICANCE: The understanding of the impact of rotational ambiguity in obtaining the second-order advantage with both first-order and non-bilinear second-order data is of paramount importance in the future development of analytical protocols of complex samples.

A rapid and direct method for dating blue pen ink in documents using multiset modeling of infrared spectroscopy and mass spectrometry data.

The dating of documents is crucial in forensic chemistry, particularly for verifying their authenticity. This study aimed to develop a rapid and direct method for the dating of pen ink in documents, using a combination of Fourier transform infrared spectroscopy in attenuated reflectance mode (FTIR-ATR), desorption electrospray ionization mass spectrometry (DESI-MS) and multiple ensemble data modeling. Two sets of paper document samples containing writing in blue pen ink were investigated: (I) artificially aged documents and (II) real documents dating from 1960 to 2022. The FTIR-ATR spectra of both sets of samples showed a decrease in absorbance at ∼1584 cm-1, related to the chemical modification of the CN bond in the molecular structure of Basic Violet 3 (BV3), one of the main dyes used in blue pen ink. DESI-MS confirmed the presence of BV3 and its degradation by-products in all the samples, indicating its widespread utilization in blue pen ink production. Moreover, DESI-MS detected combinations of dyes within the ink composition. The models were built using the DESI-MS and FTIR-ATR data separately, but the error and trend were significantly reduced when both sets of data were used. The combination of DESI-MS and FTIR-ATR spectral information resulted in a final predictive model with low error for pen inks from real documents in writing from the years 1960 to 2022. These analyses proved to be effective for the dating of pen inks and are suitable for use in routine forensic analysis, providing a direct and rapid method that allows for accurate prediction.

Design and application of a paper-based optoelectronic nose for the on-site discrimination of essential oils using a chemometric web app.

Essential oils are appreciated worldwide for their pleasant aroma, in addition to their therapeutic, pharmacological, and cosmetic functions. For these reasons, adulteration is a common practice that decreases product quality causing economic and health issues. In this study, we present for the first time the application of a simple, inexpensive and disposable paper-based optoelectronic nose (i.e. colorimetric sensor array) to (i) discriminate sixteen different types of essential oils and (ii) detect adulterated samples. The colorimetric array was prepared by adding 1.5 µL of 9 chemo-responsive dyes with different chemical properties to each circular spot of the paper-based device. 1 mL of each essential oil was transferred to a flask and bubbled with synthetic air at an airflow of 200 mL min-1. Then, the optoelectronic nose was exposed to the airstream containing the volatiles from the sample for 5 minutes. Digital images from before and after exposure were obtained using a smartphone and the RGB values were extracted using appropriate software. The color changes provided a unique color map fingerprint for each essential oil. Hierarchical clustering analysis (HCA) and principal component analysis (PCA) were successfully employed using a customized smartphone app, showing suitable discrimination of all studied essential oils as well as among adulterated and non-adulterated samples. The proof-of-concept showed the potential of the optoelectronic nose approach for the discrimination of different essential oils and the identification of adulterated samples, providing a valuable tool for quality control procedures.

VOCs profile of Colletotrichum spp. as a potential tool for quality control of açaí pulp.

Colletotrichum has been identified as responsible for the "dried fruit" disease in açaí (Euterpe oleracea). Besides concern for açaí pulp quality control, the characterization of Colletotrichum has been difficult, which has motivated the search for chemical markers in the Volatile Organic Compounds (VOCs) profile for use as a tool in the identification of açaí pulp contaminated by the fungus. Extracted VOCs by Headspace - Solid Phase Micro Extraction (HS-SPME) were identified through gas chromatography mass spectrometry (GC-MS). From GC-MS analyzes 26 VOCs were identified, with a predominance of the terpenoids. Chemometrically, menthol and menthone were assigned as potential markers of the genus. The analysis of VOCs in açaí pulps contaminated by Colletotrichum under different cultivation conditions enabled the detection of menthone. This result illustrated the selectivity of the culture medium and the potential of this tool for use in the quality control of açaí pulp.

Multiblock modelling on the study of the kinetic degradation of rosuvastatin calcium in the presence of retention time shifts and rank deficiency.

In pharmaceutical development, forced degradation studies are mandatory before the commercialization of any drug product. They aim at identifying the possible degradation routes and the potential products that may be formed during drug product shelf life. The most widely used techniques for monitoring this in the pharmaceutical industry are hyphenated techniques such as Liquid Chromatography coupled to ultraviolet diode array detector (LC-DAD). There are however some drawbacks, such as long analysis times required for the elution of all compounds and coelution, which is not easily detected since degradation products usually have spectra very similar to that of the drug. Chemometrics methods applied to LC-DAD data are capable of solving this issue, but the approaches described in the literature first require peak alignment to solve the rank deficiency problem, which is a delicate preprocessing method for high order data. The present work describes another approach where extra information - the kinetic degradation profiles - is included for the modelling, generating a third-order data set for each sample, resulting in a four-way array (sample x retention times x spectra x degradation profile). This approach has the advantage of using the information in the third mode to solve the peak co-elution problem without the need for peak alignment among samples. With the proposed approach, it was possible to study the degradation of calcium rosuvastatin, a modern cholesterol lowering drug, using a 2 min-run, despite all the challenges in the modelling of this data. The proposed strategy was compared to an approach based on augmenting the matrix in the spectral/kinetic modes (second order modelling strategy).

1H NMR-based metabonomics for infertility diagnosis in men with varicocele.

PURPOSE: "Omics" techniques have been used to understand and to identify biomarkers of male infertility. We report on the first metabonomics models created to diagnose varicocele and infertility among men with varicocele. METHODS: We recruited 35 infertile men with varicocele (VI group), 21 fertile men with varicocele (VF group) and 24 fertile men without varicocele (C group). All men underwent standard semen analysis, scrotal duplex ultrasonography, and sexual hormone level measurement. Hydrogen-1 nuclear magnetic resonance (1H NMR) spectra of seminal plasma were used to create metabonomics models to discriminate between men with and without varicocele, and between fertile and infertile men with varicocele. RESULTS: Using the statistical formalisms partial least square discriminants analysis and genetic algorithm-based linear discriminant analysis (GA-LDA), we created two models that discriminated the three groups from each other with accuracy of 92.17%. We also created metabonomics models using orthogonal partial least square discriminants analysis and GA-LDA that discriminated VF group from VI group, with an accuracy of 94.64% and 100% respectively. We identified 19 metabolites that were important in group segregation: caprate, 2-hydroxy-3-methylvalerate, leucine, valine, 3-hydroxybutyrate, lactate, alanine, 4-aminobutyrate, isoleucine, citrate, methanol, glucose, glycosides, glycerol-3-phosphocoline, n-acetyltyrosine, glutamine, tyrosine, arginine, and uridine. CONCLUSIONS: 1HNMR-based metabonomics of seminal plasma can be used to create metabonomics models to discriminate between men with varicocele from those without varicocele, and between fertile men with varicocele from those infertile with varicocele. Furthermore, the most important metabolites for group segregation are involved in the oxidative stress caused by varicocele.

Highly sensitive quantitation of pesticides in fruit juice samples by modeling four-way data gathered with high-performance liquid chromatography with fluorescence excitation-emission detection.

A study regarding the acquisition and analytical utilization of four-way data acquired by monitoring excitation-emission fluorescence matrices at different elution time points in a fast HPLC procedure is presented. The data were modeled with three well-known algorithms: PARAFAC, U-PLS/RTL and MCR-ALS, the latter conveniently adapted to model third-order data. The second-order advantage was exploited when analyzing samples containing uncalibrated components. The best results were furnished with the algorithm U-PLS/RTL. This fact is indicative of both no peak time shifts occurrence among samples and high colinearity among spectra. Besides, this latent-variable structured algorithm is capable of better handle the need of achieving high sensitivity for the analysis of one of the analytes. In addition, a significant enhancement in both predictions and analytical figures of merit was observed for carbendazim, thiabendazole, fuberidazole, carbofuran, carbaryl and 1-naphtol, when going from second- to third-order data. LODs obtained were ranged between 0.02 and 2.4µgL(-1).

Handling time misalignment and rank deficiency in liquid chromatography by multivariate curve resolution: Quantitation of five biogenic amines in fish.

Biogenic amines (BAs) are used for identifying spoilage in food. The most common are tryptamine (TRY), 2-phenylethylamine (PHE), putrescine (PUT), cadaverine (CAD) and histamine (HIS). Due to lack of chromophores, chemical derivatization with dansyl was employed to analyze these BAs using high performance liquid chromatography with a diode array detector (HPLC-DAD). However, the derivatization reaction occurs with any primary or secondary amine, leading to co-elution of analytes and interferents with identical spectral profiles, and thus causing rank deficiency. When the spectral profile is the same and peak misalignment is present on the chromatographic runs, it is not possible to handle the data only with Multivariate Curve Resolution and Alternative Least Square (MCR-ALS), by augmenting the time, or the spectral mode. A way to circumvent this drawback is to receive information from another detector that leads to a selective profile for the analyte. To overcome both problems, (tri-linearity break in time, and spectral mode), this paper proposes a new analytical methodology for fast quantitation of these BAs in fish with HPLC-DAD by using the icoshift algorithm for temporal misalignment correction before MCR-ALS spectral mode augmented treatment. Limits of detection, relative errors of prediction (REP) and average recoveries, ranging from 0.14 to 0.50 µg mL(-1), 3.5-8.8% and 88.08%-99.68%, respectively. These are outstanding results obtained, reaching quantification limits for the five BAs much lower than those established by the Food and Agriculture Organization of the United Nations and World Health Organization (FAO/WHO), and the European Food Safety Authority (EFSA), all without any pre-concentration steps. The concentrations of BAs in fish samples ranged from 7.82 to 29.41 µg g(-1), 8.68-25.95 µg g(-1), 4.76-28.54 µg g(-1), 5.18-39.95 µg g(-1) and 1.45-52.62 µg g(-1) for TRY, PHE, PUT, CAD, and HIS, respectively. In addition, the proposed method spends less than 4 min in an isocratic run, consuming less solvent in accordance with the principles of green analytical chemistry.