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Photovoltaic (PV) solar energy is a fundamental technology that will help transition from a fossil fuel–based energy mix to a future with high shares of renewable energy. To do so, PV plants coupled with energy storage systems can accumulate excess power and dispatch it when PV generation changes, performing PV smoothing. While coupling PV plants with battery energy storage systems (BESS) offers a solution, current methodologies often need to thoroughly describe the interplay between BESS energy capacity, power rating, and the long–term impacts of battery degradation. This paper addresses this gap by proposing a four–step methodology that optimizes BESS sizing for PV plants, accounting for both cycling and calendar aging effects on system performance and the economic implications of battery replacements. We use a model that considers the degradation of PV modules and two Li–ion battery types (LiFePO4, LFP, and LiNiMnCoO2, NMC). A 16.3 MW PV plant is simulated along with the BESS to test the methodology. The results indicate that an LFP–based BESS of 2.5 MWh with a rated power of 1.25 MW ensures a stable output power with variation below 10% of the rated PV plant 98 % of the time. In contrast, an NMC–based BESS, while effective in reducing non–compliance, incurs higher costs due to more frequent battery replacements, making it less economically viable. The methodology and results presented in this paper provide valuable insights for designing cost–effective and reliable energy storage solutions in PV plants, ensuring compliance with set power availability.

Fraudulent practices concerning honey are growing fast and involve misrepresentation of origin and adulteration. Simple and feasible methods for honey authentication are needed to ascertain honey compliance and quality. Working on a robust dataset and simultaneously investigating honey traceability and adulterant detection, this study proposed a portable FTNIR fingerprinting approach combined with chemometrics. Multifloral and unifloral honey samples (n = 244) from Spain and Sardinia (Italy) were discriminated by botanical and geographical origin. Qualitative and quantitative methods were developed using linear discriminant analysis (LDA) and partial least squares (PLS) regression to detect adulterated honey with two syrups, consisting of glucose, fructose, and maltose. Botanical and geographical origins were predicted with 90% and 95% accuracy, respectively. LDA models discriminated pure and adulterated honey samples with an accuracy of over 92%, whereas PLS allows for the accurate quantification of over 10% of adulterants in unifloral and 20% in multifloral honey.

ABSTRACT: Psidiummyrtoides fruits food industries produce by-products such as liqueurs, ice cream, jellies, and juices. However, there needs to be more information about the nutritional composition of fruits, as well as the biological potential, mainly of seed flour.Therefore, the present study aimed to evaluate the nutritional composition and antioxidant and cancer chemopreventive activities of pulp and seed of fruits of Psidiummyrtoides. Moisture content, total minerals and mineral profile, total lipids and fatty acids profile, total proteins, dietary fiber (soluble and insoluble) and total carbohydrates were analyzed. Vitamins C and complex B, organic acids and the profile of phenolic compounds were also determined. DPPH and ABTS methods evaluated the antioxidant activity, and cancer chemopreventive activity was evaluated by quinone reductase induction and NF-κB inhibitory activity. The fruits are a good source of thiamine, iron, phosphorus, potassium, fiber, and protein. Linoleic acid was the major fatty acid in both pulp and seed. Quercetin (1600 µg/100g) and pyrogallol(819 µg/100g) were the major phenolic compounds pulp and seed, respectively. The fruits showed strong antioxidant capacity, mainly the seeds, and the ability to induce quinone reductase activity, highlighting a cancer chemopreventive activity. Seed flour has a high potential to enrich food, in addition to valuing agro-industrial by-products, where we can highlight 25%, 13% and 37% of the recommended daily intake for iron (1.6 mg/100g), phosphorus (58 mg/100g) and vitamin B1 (450 µg/100g), respectively, in addition to antioxidant and cancer chemopreventive activities.

Este estudio se enfocó en los trabajos del Consejo Técnico Escolar para explorar e identificar las temáticas, organización e interacción de los docentes de Educación Física y el posible regreso a clases. Se realizó un estudio descriptivo exploratorio con una iniciativa didáctica de micro investigación, participando 15 maestros de una zona escolar, respondiendo una encuesta de opinión. En cuanto a las formas de intervención en la educación a distancia entre los docentes mujeres y hombres, se encontraron diferencias con relación a los recursos tecnológicos y materiales apropiados (p < .025). En el manejo de las emociones de los docentes se observaron diferencias significativas en las mujeres (p < 0.028). La educación a distancia y los programas de mejora son los principales temas abordados, seguidos de la educación socioemocional y evaluación, para lo cual han tenido que desarrollar estrategias de enseñanza aprendizaje de forma remota. Se concluye que se han logrado pocos aprendizajes en la educación virtual.

Discrimination of honey based on geographical origin is a common fraudulent practice and is one of the most investigated topics in honey authentication. This research aims to discriminate honeys according to their geographical origin by combining elemental fingerprinting with machine-learning techniques. In particular, the main objective of this study is to distinguish the origin of unifloral and multifloral honeys produced in neighboring regions, such as Sardinia (Italy) and Spain. The elemental compositions of 247 honeys were determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The origins of honey were differentiated using Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Random Forest (RF). Compared to LDA, RF demonstrated greater stability and better classification performance. The best classification was based on geographical origin, achieving 90% accuracy using Na, Mg, Mn, Sr, Zn, Ce, Nd, Eu, and Tb as predictors.

Nowadays, the quality of natural products is an issue of great interest in our society due to the increase in adulteration cases in recent decades. Coffee, one of the most popular beverages worldwide, is a food product that is easily adulterated. To prevent fraudulent practices, it is necessary to develop feasible methodologies to authenticate and guarantee not only the coffee’s origin but also its variety, as well as its roasting degree. In the present study, a C18 reversed-phase liquid chromatography (LC) technique coupled to high-resolution mass spectrometry (HRMS) was applied to address the characterization and classification of Arabica and Robusta coffee samples from different production regions using chemometrics. The proposed non-targeted LC-HRMS method using electrospray ionization in negative mode was applied to the analysis of 306 coffee samples belonging to different groups depending on the variety (Arabica and Robusta), the growing region (e.g., Ethiopia, Colombia, Nicaragua, Indonesia, India, Uganda, Brazil, Cambodia and Vietnam), and the roasting degree. Analytes were recovered with hot water as the extracting solvent (coffee brewing). The data obtained were considered the source of potential descriptors to be exploited for the characterization and classification of the samples using principal component analysis (PCA) and partial least squares–discriminant analysis (PLS-DA). In addition, different adulteration cases, involving nearby production regions and different varieties, were evaluated by pairs (e.g., Vietnam Arabica—Vietnam Robusta, Vietnam Arabica—Cambodia and Vietnam Robusta—Cambodia). The coffee adulteration studies carried out with partial least squares (PLS) regression demonstrated the good capability of the proposed methodology to quantify adulterant levels down to 15%, accomplishing calibration and prediction errors below 2.7% and 11.6%, respectively.

Los transformadores de potencia inmersos en aceite son máquinas eléctricas altamente confiables, diseñados para alcanzar una vida útil entre 20 a 35 años, para los cuales es necesario realizar una evaluación de su condición basada en estándares internacionales. Existe evidencia de que algunos transformadores han llegado alcanzar hasta los 60 años de operación, incluyendo un mantenimiento adecuado. En general, según datos históricos, se espera que un transformador de potencia opere satisfactoriamente hasta los 40 a 45 años. La evaluación de un transformador de potencia basado en estándares internacionales reconocidos no ha considerado el contexto operativo y las posibles reparaciones realizadas en este. Por tal motivo, se genera un nivel de incertidumbre para los responsables de la operación, en relación con la expectativa de vida y el deterioro progresivo de la máquina de acuerdo con lo que ofrecen los distintos fabricantes. Por lo tanto, contar con una metodología de evaluación no invasiva se hace cada vez más necesario a fin de contemplar factores relacionados con: i) el sistema de aislamiento del transformador de potencia; y, ii) los datos históricos recopilados del mantenimiento basado en la condición, tanto dieléctrica como el monitoreo en línea de la condición. La metodología debe considerar que el deterioro por el efecto térmico ha sido el principal modo de falla, ya que el aumento de temperatura deteriora progresivamente el sistema de aislamiento, de manera irreversible, mayoritariamente en el papel dieléctrico (que puede provocar un envejecimiento prematuro). En este artículo se propone una metodología novedosa, basada en el cálculo un índice de vida útil residual a partir de su condición dieléctrica y los aspectos operativos. Los resultados obtenidos demostraron que la vida residual de un transformador de potencia debe estimarse incluyendo al cálculo su contexto operativo, para considerar sus efectos en los valores estimados.

Debido a la complejidad de los sistemas eólicos, la necesidad de contar con aerogeneradores fiables es de suma importancia, por ello se han desarrollado metodologías para mejorar sus características y desempeño. El método de análisis de modos de falla, efectos y criticidad se ha utilizado para estudiar la confiabilidad de diferentes sistemas de generación de energía. En este documento se presenta la aplicación de dicha metodología a un aerogenerador de inducción doblemente alimentado, para realizar una evaluación cualitativa y cuantitativa de las características de falla en el mismo. Además, para tomar en cuenta consideraciones económicas en el análisis, se presenta el enfoque del método basado en el riesgo, con el fin de mitigar las limitaciones que presenta el método tradicional. Como resultado se determina que la prioridad de atención debe enfocarse en el generador, luego el sistema eléctrico y posteriormente en las palas.

Introduction: Different international guidelines indicate the need for improving educational procedures. This study aims to contribute to the professional development training program of higher education professors from a Physical Education Teacher Education degree in México. Methodology: This qualitative study used a participatory action research design through four cycles: (a) diagnosis; (b) elaboration of the action plan; (c) implementation and evaluation; and (d) feedback. The participants were the professor, six experts, and 17 students. Data were collected from semistructured interviews with students and the professor, the analysis of the class syllabus, and nonparticipatory observations. Findings: The importance of carrying out a diagnostic cycle allowed us to identify the specific needs of the class. Similarly, the model of development and evaluation of academic competencies (M-DECA) allowed the professor to develop specific pedagogical and disciplinary competencies from the training program. Conclusion: A continuous professional development training program for university professors in pedagogical and disciplinary strategies generates better learning results. The inclusion of innovative content in the class syllabus was also crucial.

Tea can be found among the most widely consumed beverages, but it is also highly susceptible to fraudulent practices of adulteration with other plants such as chicory to obtain an illicit economic gain. Simple, feasible and cheap analytical methods to assess tea authentication are therefore required. In the present contribution, a targeted HPLC-UV method for polyphenolic profiling, monitoring 17 polyphenolic and phenolic acids typically described in tea, was proposed to classify and authenticate tea samples versus chicory. For that purpose, the obtained HPLC-UV polyphenolic profiles (based on the peak areas at three different acquisition wavelengths) were employed as sample chemical descriptors for principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) studies. Overall, PLS-DA demonstrated good sample grouping and discrimination of chicory against any tea variety, but also among the five different tea varieties under study, with classification errors below 8% and 10.5% for calibration and cross-validation, respectively. In addition, the potential use of polyphenolic profiles as chemical descriptors to detect and quantify frauds was evaluated by studying the adulteration of each tea variety with chicory, as well as the adulteration of red tea extracts with oolong tea extracts. Excellent results were obtained in all cases, with calibration, cross-validation, and prediction errors below 2.0%, 4.2%, and 3.9%, respectively, when using chicory as an adulterant, clearly improving on previously reported results when using non-targeted HPLC-UV fingerprinting methodologies.

Honey is a very appreciated product for its nutritional characteristics and its benefits for human health, comprising antioxidant, anti-inflammatory, antifungal, and antibacterial activities. These attributes depend on the specific composition of each honey variety, with the botanical origin as one of the distinctive features. Indeed, honeydew and blossom honeys show different physicochemical properties, being the antioxidant capacity, mainly relying on the phenolic compound content, one of the most important. In this work, Folin–Ciocalteu (FC) index, total flavonoid content (TFC), and the antioxidant capacity based on the ferric reducing antioxidant power (FRAP) assay were determined for a total of 73 honeys (50 blossom honeys and 23 honeydew honeys). Mean content of oxidizable species (FC index) ranges from 0.17 to 0.7 mg eq. gallic acid g−1, with honeydew honeys being the ones with higher values. Regarding TFC, mean values above 1.5 mg eq. quercetin g−1 (method applied in the absence of NaNO2) were obtained for honeydew honeys and heather honey. Lower and not discriminatory values (below 0.3 mg eq. epicatechin g−1) were obtained in the presence of NaNO2. The maximum antioxidant capacity was observed for thyme honeys (2.2 mg eq. Trolox g−1) followed by honeydew and heather honeys. Individually, only the FC index was able to discriminate between honeydew and blossom honeys, while the other spectroscopic indexes tested allowed the differentiation of some honey types according to the botanical origin. Thus, a holistic treatment of the results was performed using partial least square discriminant analysis (PLS-DA) for classification purposes using FC, TFC, and FRAP results as data. Honeydew and blossom honey were satisfactorily discriminated (error 5%). In addition, blossom honeys can be perfectly classified according to their botanical origin based on two-class PLS-DA classification models.

The methodological strategy of project-based learning has been implemented in Analytical Chemistry laboratories, specifically in the subject of Basic Analytical Chemistry Laboratory of the Chemistry Degree, with the aim of contextualizing the practices, improving the critical evaluation of the results obtained and promoting collaborative work. For this purpose, five different topics have been proposed for students to elaborate a project, setting out its objective and the analytical determinations (parameters and samples) necessary to achieve it. The implementation of these projects has facilitated the generation of a greater volume of interrelated results that has allowed the students to work on the critical evaluation of the results in greater depth. The achievement of the objectives proposed for the implementation of the PBL has been demonstrated by means of anonymous surveys to the students and by comparison with other four groups of the same subject taught during the same academic year.

A non-targeted LC–HRMS fingerprinting methodology based on a C18 reversed-phase mode under universal gradient elution using an Orbitrap mass analyzer was developed to characterize and classify Spanish honey samples. A simple sample treatment consisting of honey dissolution with water and a 1:1 dilution with methanol was proposed. A total of 136 honey samples belonging to different blossom and honeydew honeys from different botanical varieties produced in different Spanish geographical regions were analyzed. The obtained LC–HRMS fingerprints were employed as sample chemical descriptors for honey pattern recognition by principal component analysis (PCA) and partial least squares–discriminant analysis (PLS–DA). The results demonstrated a superior honey classification and discrimination capability with respect to previous non-targeted HPLC–UV fingerprinting approaches, with them being able to discriminate and authenticate the honey samples according to their botanical origins. Overall, noteworthy cross-validation multiclass predictions were accomplished with sensitivity and specificity values higher than 96.2%, except for orange/lemon blossom (BL) and rosemary (RO) blossom-honeys. The proposed methodology was also able to classify and authenticate the climatic geographical production region of the analyzed honey samples, with cross-validation sensitivity and specificity values higher than 87.1% and classification errors below 10.5%.

The feasibility of non-targeted off-line SPE LC-LRMS polyphenolic fingerprints to address the classification and authentication of Spanish honey samples based on both botanical origin (blossom and honeydew honeys) and geographical production region was evaluated. With this aim, 136 honey samples belonging to different botanical varieties (multifloral and monofloral) obtained from different Spanish geographical regions with specific climatic conditions were analyzed. Polyphenolic compounds were extracted by off-line solid-phase extraction (SPE) using HLB (3 mL, 60 mg) cartridges. The obtained extracts were then analyzed by C18 reversed-phase LC coupled to low-resolution mass spectrometry in a hybrid quadrupole-linear ion trap mass analyzer and using electrospray in negative ionization mode. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were employed to assess the pattern recognition capabilities of the obtained fingerprints to address honey classification and authentication. In general, a good sample discrimination was accomplished by PLS-DA, being able to differentiate both blossom-honey and honeydew-honey samples according to botanical varieties. Multiclass predictions by cross-validation for the set of blossom-honey samples showed sensitivity, specificity, and classification ratios higher than 60%, 85%, and 87%, respectively. Better results were obtained for the set of honeydew-honey samples, exhibiting 100% sensitivity, specificity, and classification ratio values. The proposed fingerprints also demonstrated that they were good honey chemical descriptors to deal with climatic and geographical issues. Characteristic polyphenols of each botanical variety were tentatively identified by LC-MS/MS in multiple-reaction monitoring mode to propose possible honey markers for future experiments (i.e., naringin for orange/lemon blossom honeys, syringic acid in thyme honeys, or galangin in rosemary honeys).

ABSTRACT To understand the self-reported and perception of teaching style used among Mexican physical education teachers. Participants included 104 (n=41 females and 63 males) elementary physical education teachers from northern Mexico. Results showed that a traditional teaching style tends to be mainly used either by male and female’s physical education teachers. Showing differences between genders and teaching styles. Female teachers tend to combine a traditional teaching style with one that connects with students engaging in physical activity, developing positive values and attitudes. Cultural context plays an important aspect when developing a teaching self-perception.

Honey is a natural substance produced by bees of the genus Apis. Depending on the raw material used for its production, honey can be classified into two large groups: blossom honey, which results from the metabolization of nectar extracted from flowers; and honeydew honey, in which bees use plant or insect secretions for its production. The physicochemical characteristics are different between these two types of honey. For example, honeydew honey is darker and is characterized by a high content of phenolic acids. On the contrary, blossom honey stands out for its abundance of flavonoids. Blossom honey can be also classified based on the pollen origin. Thus, honey with more than 45% of the pollen coming from the same species can be considered monofloral; otherwise, it is considered multifloral. Honey is one of the food products with the highest level of fraudulent practices. Most of the adulterations consist of ingredient dilution, adding sweet substances, such as syrups, sugar cane, or corn syrup, among others. In the market, this was reflected in the dubious drop in prices for this product. In the last few years, several instance of honey fraud have come to light. This work aimed to develop a non-targeted ultra-high-performance liquid chromatography–high-resolution mass spectrometry (UHPLC–HRMS) fingerprinting method to address the characterization, classification, and authentication of Spanish honey samples considering their botanical and geographical origin. A total of 136 kinds of honey from different Spanish production regions belonging to different botanical varieties were analyzed, including: blossom honey (orange blossom, rosemary, thyme, eucalyptus, and heather) and honeydew honey (holm oak, forest, and mountain). A simple sample treatment was carried out, consisting of dissolving 1 g of honey in 10 mL of water, followed by a 1:1 dilution with methanol. The chromatographic separation of the obtained extracts was performed using a Kinetex® C-18 core–shell column (100 × 4.6 mm I.D., 2.6 μm), working under gradient elution, using an aqueous solution of 0.1% formic acid and acetonitrile as the mobile phase components. HRMS acquisition was performed using electrospray in negative ionization mode (−2500 V) in an LTQ-Orbitrap working in full scan MS (m/z 100–1000) at a resolution of 50,000 full-width at half maximum (FWHM). The obtained non-targeted UHPLC–HRMS fingerprints (peak signals as a function of retention time and m/z) were considered as chemical descriptors of the analyzed honey samples for principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). PLS-DA revealed good discrimination between blossom and honeydew honey. Furthermore, the obtained chemometric models allowed the achievement of very good classification among the different botanical varieties under study for both blossom and honeydew honey. The discrimination of honey regarding the different Spanish climate production regions was more limited, although some trends were observed. Thus, the non-targeted UHPLC–HRMS fingerprinting approach proved to be an appropriate methodology to address honey characterization, classification, and authentication based on their different botanical origin.

The impact of mild oven treatments (steaming or sous-vide) and boiling for 10 min, 25 min, or 40 min on health-promoting phytochemicals in orange and violet cauliflower (Brassica oleracea L. var. botrytis) was investigated. For this purpose, targeted ultra-high performance liquid chromatography–high-resolution mass spectrometry analysis of phenolics and glycosylates, combined with chemometrics, was employed. Regardless of cooking time, clear differentiation of cooked samples obtained using different procedures was achieved, thus demonstrating the distinct impact of cooking approaches on sample phytochemical profile (both, compound distribution and content). The main responsible components for the observed discrimination were derivatives of hydroxycinnamic acid and kaempferol, organic acids, indolic, and aromatic glucosinolates, with glucosativin that was found, for the first time, as a discriminant chemical descriptor in colored cauliflower submitted to steaming and sous-vide. The obtained findings also highlighted a strict relationship between the impact of the cooking technique used and the type of cauliflower. The boiling process significantly affected the phytochemicals in violet cauliflower whereas orange cauliflower boiled samples were grouped between raw and either steamed or sous-vide-cooked samples. Finally, the results confirm that the proposed methodology is capable of discriminating cauliflower samples based on their phytochemical profiles and identifying the cooking procedure able to preserve bioactive constituents.

Honey is a highly consumed natural product produced by bees which is susceptible to fraudulent practices, some of them regarding its botanical origin. Two HPLC-UV non-targeted fingerprinting approaches were evaluated in this work to address honey characterization, classification, and authentication based on honey botanical variety. The first method used no sample treatment and a universal reversed-phase chromatographic separation. On the contrary, the second method was based on an off-line SPE preconcentration method, optimized for the isolation and extraction of polyphenolic compounds, and a reversed-phase chromatographic separation optimized for polyphenols as well. For the off-line SPE method, the use of HLB (3 mL, 60 mg) cartridges, and 6 mL of methanol as eluent, allowed to achieve acceptable recoveries for the selected polyphenols. The obtained HPLC-UV fingerprints were subjected to an exploratory principal component analysis (PCA) and a classificatory partial least squares-discriminant analysis (PLS-DA) to evaluate their viability as sample chemical descriptors for authentication purposes. Both HPLC-UV fingerprints resulted to be appropriate to discriminate between blossom honeys and honeydew honeys. However, a superior performance was accomplished with off-line SPE HPLC-UV polyphenolic fingerprints, being able to differentiate among the different blossom honey samples under the study (orange/lemon blossom, rosemary, thyme, eucalyptus, and heather). In general, this work demonstrated the feasibility of HPLC-UV fingerprints, especially those obtained after off-line SPE polyphenolic isolation and extraction, to be employed as honey chemical descriptors to address the characterization and classification of honey samples according to their botanical origin.

Introducción. El consumo de sustancias psicoactivas (SPA) es una problemática que afecta a estudiantes desde edades tempranas. Objetivo. Describir las etapas de cambio de comportamiento frente al consumo de SPA en escolares de Bogotá D.C., Colombia. Materiales y métodos. Estudio transversal en 6 965 escolares de Bogotá D.C. El cambio de comportamiento se evaluó por autoreporte a través de un cuestionario estructurado a partir del Modelo Transteórico en las etapas de precontemplación, contemplación, preparación y acción/mantenimiento. Resultados. 58.4% fueron mujeres con edad promedio de 12.7±2.3 años. Frente al consumo de drogas alucinógenas, 6% de los escolares se ubicaron en la categoría de precontemplación, 44% en contemplación, 30% en preparación y 20% en acción/mantenimiento. Respecto al consumo de alcohol, 5% se encontraban en precontemplación, 36% en contemplación, 12% en preparación y 46% en acción/mantenimiento. El tabaquismo mostró prevalencias de 4% para precontemplación, 33% para contemplación, 12% para preparación y 51% para acción/mantenimiento. Conclusiones. El consumo de SPA es una problemática que se presenta cada vez con mayor frecuencia en población escolar. La mayoría de entrevistados se ubican en etapa de mantenimiento en el consumo de tabaco y alcohol y en la etapa de contemplación de consumo de drogas alucinógenas. Se requieren esfuerzos gubernamentales que fomenten programas preventivos de consumo de SPA en el ámbito escolar.

Tea is a broadly consumed beverage worldwide that is susceptible to fraudulent practices, including its adulteration with other plants such as chicory extracts. In the present work, a non-targeted high-throughput flow injection analysis-mass spectrometry (FIA-MS) fingerprinting methodology was employed to characterize and classify different varieties of tea (black, green, red, oolong, and white) and chicory extracts by principal component analysis (PCA) and partial least squares–discriminant analysis (PLS-DA). Detection and quantitation of frauds in black and green tea extracts adulterated with chicory were also evaluated as proofs of concept using partial least squares (PLS) regression. Overall, PLS-DA showed that FIA-MS fingerprints in both negative and positive ionization modes were excellent sample chemical descriptors to discriminate tea samples from chicory independently of the tea product variety as well as to classify and discriminate among some of the analyzed tea groups. The classification rate was 100% in all the paired cases—i.e., each tea product variety versus chicory—by PLS-DA calibration and prediction models showing their capability to assess tea authentication. The results obtained for chicory adulteration detection and quantitation using PLS were satisfactory in the two adulteration cases evaluated (green and black teas adulterated with chicory), with calibration, cross-validation, and prediction errors below 5.8%, 8.5%, and 16.4%, respectively. Thus, the non-targeted FIA-MS fingerprinting methodology demonstrated to be a high-throughput, cost-effective, simple, and reliable approach to assess tea authentication issues.

Essential oils have important functions in nature [...]

Abstract Background The impacts of man-made chemicals, in particular of persistent organic pollutants, are multifactorial as they may affect the integrity of ecosystems, alter biodiversity and have undesirable effects on many organisms. We have previously demonstrated that the belowground mycobiota of forest soils acts as a buffer against the biocide pollutant pentachlorophenol. However, the trade-offs made by mycobiota to mitigate this pollutant remain cryptic. Results Herein, we demonstrate using a culture-dependent approach that exposure to pentachlorophenol led to alterations in the composition and functioning of the metacommunity, many of which were not fully alleviated when most of the biocide was degraded. Proteomic and physiological analyses showed that the carbon and nitrogen metabolisms were particularly affected. This dysregulation is possibly linked to the higher pathogenic potential of the metacommunity following exposure to the biocide, supported by the secretion of proteins related to pathogenicity and reduced susceptibility to a fungicide. Our findings provide additional evidence for the silent risks of environmental pollution, particularly as it may favour the development of pathogenic trade-offs in fungi, which may impose serious threats to animals and plant hosts.

The traditional teaching style in which the teacher is in control and there is a submissive attitude in students is predominant in Mexico. The development of identity in preadolescence is subjected to social groups, which could develop interpersonal difficulties through the controlling teaching style. Although the fear of negative evaluation in students and competitive sport has been studied in education, relatively little research has been done in the area of physical education in relation to the controlling style. The purpose of this study was to investigate the correlation and predictive relationship between controlling teaching and the fear of negative evaluation mediated by the frustration of the basic psychological needs (BPN), controlled motivation, and individualism/competitiveness through the theoretical framework of self-determination theory. Participants were 1132 students in the fifth and sixth grades in public elementary schools in the state of Chihuahua, Mexico, with ages between 10 and 13 (M = 10.51 years; SD = 0.66 years). Results indicate the perceived controlling teaching style positively predicted the fear of negative evaluation in students of this study through BPN frustration, that is positively related to low-quality motivation, which is related to a higher level of individualism/competitiveness. This, in turn, is proven to be a predictor of the fear of negative evaluation. The results also discuss the promotion of the autonomy support style, avoiding the controlling teaching style, for the minimization of negative results related to the perception of fear and the development of student well-being both within and beyond the school context.

Flavanols are a class of polyphenols that have become the focus of much research because of their medicinal properties. For this paper, a new method to determine polyphenols in nutraceutical samples was developed, based on solid-liquid extraction and further analysis by liquid chromatography. Analytes were recovered by ultrasound-assisted extraction, using a mixture of methanol/water/hydrochloric acid (70:29:1, v:v:v) as the solvent. Reversed-phase high-performance liquid chromatography with ultraviolet/visible (HPLC-UV/Vis) and fluorescence detection (HPLC-FLD) were developed to determine the content of the principal flavanols. The HPLC-FLD method showed better selectivity and sensitivity, so it was selected for further studies. The analytical parameters established with FLD were satisfactory in terms of linearity (R2 ≥ 0.993), repeatability (RSD% ≥ 2.2), and limits of detection of 0.1 mg L−1 or below. The nutraceutical samples were analyzed by HPLC-FLD to determine the compositional profiles of flavanols, then they were subsequently treated using chemometric methods, such as principal component analysis (PCA). Results showed that the study of compositional profiles from the selected flavanols was sufficient for description and discrimination purposes. The cranberry samples were the richest in flavanols, procyanidin A2 being the principal flavanol, and artichoke samples the least rich.

Introducción: La diabetes mellitus tipo 2 (DM2) representa un problema de salud pública, debido a su alta incidencia y prevalencia en el mundo. Un método para evaluar el riesgo de desarrollar DM2 es la escala Latin American Finnish Diabetes Risk Score (LA FINDRISC). La DM2 es un factor de riesgo de enfermedad arterial periférica (EAP) la cual puede ser diagnosticada mediante el índice tobillo-brazo (ITB). Objetivo: evaluar la presencia y severidad de enfermedad arterial periférica mediante ITB y relacionarlo con el riesgo de desarrollar DM2 según LA FINDRISC. Métodos: estudio descriptivo, correlacional, de corte transversal. Se evaluaron 134 personas y se les midió glicemia capilar para descartar diabetes. Posteriormente, se realizó el LA FINDRISC y el ITB. Resultados: El puntaje LA FINDRISC y la glicemia alteradas en ayunas aumentaron proporcionalmente (R2=0,5). Esta relación no se observó entre LA FINDRISC y el ITB arrojado por la población general. Sin embargo, al seleccionar los pacientes con vasos no comprimibles aparece una correlación positiva (R2=0,36) entre los dos instrumentos diagnósticos. Conclusión: LA FINDRISC y el ITB son instrumentos de diagnósticos no invasivo, sencillos y válidos para detectar riesgo de desarrollar DM2, y detectar presencia y severidad de enfermedad arterial periférica, respectivamente.

Tea is a widely consumed drink in the world which is susceptible to undergoing adulterations to reduce manufacturing costs and rise financial benefits. The development of simple analytical methodologies to assess tea authenticity, as well as to detect and quantify frauds, is an important matter considering the rise of adulteration issues in recent years. In the present study, untargeted HPLC-UV and HPLC-FLD fingerprinting methods were employed to characterize, classify, and authenticate tea extracts belonging to different varieties (red, green, black, oolong, and white teas) by partial least squares-discriminant analysis (PLS-DA), as well as to detect and quantify adulteration frauds when chicory was used as the adulterant by partial least squares (PLS) regression, to ensure the authenticity and integrity of foodstuffs. Overall, PLS-DA showed a good classification and grouping of the tea samples according to the tea variety and, except for some white tea extracts, perfectly discriminated from the chicory ones. One hundred percent classification rates for the PLS-DA calibration models were achieved, except for green and oolong tea when HPLC-FLD fingerprints were employed, which showed classification rates of 96.43% and 95.45%, respectively. Good predictions were also accomplished, also showing, in almost all the cases, a 100% classification rate for prediction, with the exception of white tea and oolong tea when HPLC-UV fingerprints were employed that exhibited a classification rate of 77.78% and 88.89%, respectively. Good PLS results for chicory adulteration detection and quantitation were also accomplished, with calibration, cross-validation, and external validation errors beneath 1.4%, 6.4%, and 3.7%, respectively. Acceptable prediction errors (below 21.7%) were also observed, except for white tea extracts that showed higher errors which were attributed to the low sample variability available.

Paprika is a red powder seasoning with a characteristic flavour obtained from the drying and grinding of red pepper fruits of the genus Capsicum (Solanaceae family). In Europe, seven paprika products are distinguished with the protected designation of origin (PDO) label, which ensures a high-quality product through strict requirements, leading to higher retail prices than unlabelled paprika and making them susceptible to fraudulent practices. Contents of polyphenol and phenolic compounds depend on several factors, such as the environmental conditions of the production area. Thus, in the present study, a simple and feasible high-performance liquid chromatography with ultraviolet and fluorescent detection (HPLC-UV-FLD) method was developed to determine 17 polyphenols in paprika samples, aiming to authenticate them through chemometrics. Reversed-phase chromatographic separation was optimised, using a C18 column and 0.1% formic acid aqueous solution and acetonitrile as the mobile phase components. The proposed methodology exhibited limits of detection below 0.9 mg L−1, as well as good linearity (R2 ≥ 0.984), precision (RSD day-to-day values below 24%), and trueness (relative errors below 14%). Moreover, compound confirmation was carried out via high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS). The proposed methodology was applied to 109 paprika samples, including samples from Spain (La Vera PDO, Murcia PDO, and Mallorca PDO), Hungary, and the Czech Republic. The obtained HPLC-UV-FLD polyphenolic profiles were employed as sample chemical descriptors to authenticate paprika geographical origin using a classification decision tree constructed via partial least squares regression–discriminant analysis (PLS-DA) models. As a result, a sample classification rate of 87.8% was reached after external validation. Moreover, two different paprika geographical origin blend scenarios (La Vera vs. Murcia and the Czech Republic vs. Murcia) were evaluated through partial least squares (PLS) regression, allowing blend percentage prediction with errors below 10.8% after external validation.

Tea (Camellia sinensis) is one of the most popular beverages, commonly consumed all over the world. Depending on the fermentation process, tea leaves can be categorized into three major groups: unfermented green tea, semifermented Oolong tea, and fully fermented black tea. The latter accounts for over 80% of worldwide production. The quality of tea products is determined by color, freshness, strength, and aroma. Phenolic and polyphenolic components contribute to the color and taste, whereas volatile components are directly related to the aroma. Unfortunately, food fraud is increasing globally. The widespread adulteration is the main concern for commercial functional tea extracts and tea-based nutraceuticals on the market. Especially for powdered extracts, the product quality of functional tea extracts varies highly on the market. The growing demand and interest in functional tea extracts are causing the proliferation of frauds that can seriously affect public health. Chicory, husk of pulses, and cereal starch are non-permitted materials typically employed as adulterants in tea extracts. The aim of this work was to develop an efficient untargeted high-performance liquid chromatography with ultraviolet and fluorescence detection (HPLC-UV-FLD) method in combination with chemometrics to address the characterization, classification, and authentication of tea samples, together with possible adulterants such as chicory extracts. A reversed-phase chromatographic separation was optimized, using a C18 column, and 0.1% formic acid aqueous solution and acetonitrile as the mobile phase components. The proposed methodology was applied to 87 tea samples, differing in variety and production region, and 12 chicory samples. In any case, the sample treatment consisted of sample infusion with hot water and filtration, and the obtained HPLC-UV-FLD fingerprints were subjected to principal component analysis (PCA) and partial least squares regression-discriminant analysis (PLS-DA) chemometric methods. Perfect discrimination was achieved between different tea varieties and chicory demonstrating that untargeted HPLC-UV-FLD fingerprints can be proposed as good sample chemical descriptors to assess tea authentication and to prevent frauds dealing with adulteration with chicory. The poster of this work is provided in the supplementary materials.

Food products are very complex matrices, which makes the quality of these products an issue of great interest in our society. Considering the complexity of the food chain, the adulteration of food is increasing, causing food fraud cases. In this field, drinks are food products that can be very easily adulterated. This work will focus on the theme of fraud detection in coffee, one of the most popular beverages in the world. Coffee contains an elevated number of bioactive substances (phenolic acids, polyphenols, and alkaloids, being especially abundant in ellagic, caffeic and chlorogenic acids) that give rise to its important antioxidant activity, known for its beneficial health effects. The aim of this work was to develop an efficient non-targeted FIA-ESI-MS fingerprinting method in combination with chemometrics to achieve the characterization, classification, and authentication of coffee samples, together with possible adulterants (barley, chicory, and flours) using partial least squares regression discriminant analysis (PLS-DA) chemometric method. In addition, Arabica and Robusta coffee samples were adulterated with barley, chicory and flour and the obtained FIA-ESI-MS data subjected to partial least squares (PLS) regression. Results demonstrated the feasibility of the proposed methodology to assess coffee authenticity and to quantify adulteration levels (down to 15%), showing good calibration and prediction errors. The poster of this work is provided in the supplementary materials.

In recent years, nutraceuticals prepared with cranberry (Vaccinium macrocarpon) have gained special attention because of their beneficial effects on human health (e.g., antioxidant activity and antimicrobial activity against bacteria involved in a wide range of diseases), which are mainly attributed to the high content of specific polyphenols in cranberry. However, these products present a risk of fraud consisting of the total or partial substitution of cranberry extracts with cheaper and more abundant fruit extracts. Therefore, in this study, flow injection analysis coupled with high-resolution mass spectrometry (FIA−HRMS) fingerprinting was proposed as a rapid high-throughput analytical approach to address the classification of berry-based products through chemometrics, focusing on cranberry-based products authentication. Thus, several berry-based natural products (including 18 based on blueberry, 25 on grape, 12 on raspberry, and 28 on cranberry) and 21 cranberry-based nutraceuticals were analyzed. Sample treatment consisted of a simple solid–liquid extraction method, using acetone:water: hydrochloric acid (70:29.9:0.1, v/v/v) as the extracting mix. After both negative and positive electrospray ionization FIA−HRMS sample analysis, raw data were processed with mzMine 2.53 software to obtain the corresponding fingerprints. In this line, four different data matricesincluding negative, positive, low-level data fusion (LLDF), and mid-level data fusion (MLDF) FIA−HRMS fingerprints—were then subjected to principal component analysis (PCA) and partial least squares regression-discriminant analysis (PLS-DA) using Solo 8.6 chemometrics software. PCA results allowed the identification of specific sample groups and trends. Subsequently, the complete sample classification was segregated through a classification decision tree—consecutive two-input class PLS-DA models—leading to excellent assignment accuracies after external validation according to sample botanical origin (independently of the employed data matrix). The poster of this work is provided in the supplementary materials.

Phenolic compounds such as phenolic acids, flavonoids, and stilbenes comprise an enormous family of bioactive molecules with a range of positive properties, including antioxidant, antimicrobial, or anti-inflammatory effects. As a result, plant extracts are often purified to recover phenolic compound-enriched fractions to be used to develop nutraceutical products or dietary supplements. In this article, we review the properties of some remarkable plant-based nutraceuticals in which the active molecules are mainly polyphenols and related compounds. Methods for the characterization of these extracts, the chemical determination of the bioactivities of key molecules, and the principal applications of the resulting products are discussed in detail.

Statins could increase the effectiveness of Helicobacter pylori eradication therapies due to their anti-inflammatory effect. The aim of this study was to analyze the impact of this therapeutic association in real life. This is a multicenter, prospective, non-interventional study aimed at evaluating the management of H. pylori by European gastroenterologists. Patients were registered in an e-CRF by AEG-REDCap from 2013 to 2020. The association between statin use and H. pylori eradication effectiveness was evaluated through multivariate analysis. Overall, 9988 and 705 patients received empirical and culture-guided treatment, respectively. Overall, statin use was associated with higher effectiveness in the empirical group (OR = 1.3; 95%CI = 1.1–1.5), but no association was found with first-line treatment effectiveness (N = 7738); as an exception, statin use was specifically associated with lower effectiveness of standard triple therapy (OR = 0.76; 95%CI = 0.59–0.99). In the rescue therapy empirical group (N = 2228), statins were associated with higher overall effectiveness (OR = 1.9; 95%CI = 1.4–2.6). However, sub-analyses by treatment schemes only confirmed this association for the single-capsule bismuth quadruple therapy (OR = 2.8; 95%CI = 1.3–5.7). No consistent association was found between statin use and H. pylori therapy effectiveness. Therefore, the addition of statins to the usual H. pylori treatment cannot be currently recommended to improve cure rates.

Consumers’ interest in foods that are nutritionally balanced and with health benefits has increased. The food industry is paying attention to the use of the ancestral seed Salvia hispanica L., commonly known as chia. At present, only chia seeds, which are a natural source of omega-3 and omega-6, fiber, proteins, and natural antioxidants, are commercialized. Although some studies reveal the presence of several bioactive compounds, such as polyphenols (e.g., vitexin, orientin, and some hydroxycinnamic acids) in chia leaf methanolic extracts, the chia plant is commonly used as fertilizer or treated as waste after harvest. Therefore, it can represent a by-product that could be considered a great source of bioactive compounds with unexplored potential in medicine and food industry applications. In this work, UHPLC-HRMS (Q-Orbitrap) was employed to tentatively identify and determine the bioactive compounds present in different leaf extracts of chia plants of black and white seed phenotype obtained with solvents of different polarity (ethanol, ethyl acetate, dichloromethane, and hexane) to address chia plant by-product revalorization. The chemical antioxidant capacity was also studied and correlated to the found bioactive compounds. In these experiments, black chia showed a higher antioxidant capacity than white chia in the ethanolic extracts. Moreover, experiments on cellular antioxidant activity were also performed with a predominance of the white chia extract. It is noted that the cellular antioxidant activity results make chia ethanolic extracts promising antioxidants.

Coffee, one of the most popular drinks around the world, is also one of the beverages most susceptible of being adulterated. Untargeted high-performance liquid chromatography with ultraviolet and fluorescence detection (HPLC-UV-FLD) fingerprinting strategies in combination with chemometrics were employed for the authenticity assessment and fraud quantitation of adulterated coffees involving three different and common adulterants: chicory, barley, and flours. The methodologies were applied after a solid–liquid extraction procedure with a methanol:water 50:50 (v/v) solution as extracting solvent. Chromatographic fingerprints were obtained using a Kinetex® C18 reversed-phase column under gradient elution conditions using 0.1% formic acid aqueous solution and methanol as mobile phase components. The obtained coffee and adulterants extract HPLC-UV-FLD fingerprints were evaluated by partial least squares regression-discriminants analysis (PLS-DA) resulting to be excellent chemical descriptors for sample discrimination. One hundred percent classification rates for both PLS-DA calibration and prediction models were obtained. In addition, Arabica and Robusta coffee samples were adulterated with chicory, barley, and flours, and the obtained HPLC-UV-FLD fingerprints subjected to partial least squares (PLS) regression, demonstrating the feasibility of the proposed methodologies to assess coffee authenticity and to quantify adulteration levels (down to 15%), showing both calibration and prediction errors below 1.3% and 2.4%, respectively.

This study presents the application of a suspect screening approach to screen a wide range of natural toxins, including mycotoxins, bacterial toxins, and plant toxins, in surface waters. The method is based on a generic solid-phase extraction procedure, using three sorbent phases in two cartridges that are connected in series, hence covering a wide range of polarities, followed by liquid chromatography coupled to high-resolution mass spectrometry. The acquisition was performed in the full-scan and data-dependent modes while working under positive and negative ionisation conditions. This method was applied in order to assess the natural toxins in the Ter River water reservoirs, which are used to produce drinking water for Barcelona city (Spain). The study was carried out during a period of seven months, covering the expected prior, during, and post-peak blooming periods of the natural toxins. Fifty-three (53) compounds were tentatively identified, and nine of these were confirmed and quantified. Phytotoxins were identified as the most frequent group of natural toxins in the water, particularly the alkaloids group. Finally, the toxins identified to levels 2 and 1 were prioritised according to their bioaccumulation factor, biodegradability, frequency of detection, and toxicity. This screening and prioritisation approach resulted in different natural toxins that should be further assessed for their ecotoxicological effects and considered in future studies.

Food products are very complex mixtures consisting of naturally-occurring compounds and other substances, generally originating from technological processes, agrochemical treatments, or packaging materials [...]

The importance of monitoring bioactive substances as food features to address sample classification and authentication is increasing. In this work, targeted liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) polyphenolic and curcuminoid profiles were evaluated as chemical descriptors to deal with the characterization and classification of turmeric and curry samples. The profiles corresponding to bioactive substances were obtained by TraceFinderTM software using accurate mass databases with 53 and 24 polyphenolic and curcuminoid related compounds, respectively. For that purpose, 21 turmeric and 9 curry samples commercially available were analyzed in triplicate by a simple liquid–solid extraction procedure using dimethyl sulfoxide as extracting solvent. The obtained results demonstrate that the proposed profiles were excellent chemical descriptors for sample characterization and classification by principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), achieving 100% classification rates. Curcuminoids and some specific phenolic acids such as trans-cinnamic, ferulic and sinapic acids, helped on the discrimination of turmeric samples; polyphenols, in general, were responsible for the curry sample distinction. Besides, the combination of both polyphenolic and curcuminoid profiles was necessary for the simultaneous characterization and classification of turmeric and curry samples. Discrimination among turmeric species such as Curcuma longa vs. Curcuma zedoaria, as well as among different Curcuma longa varieties (Alleppey, Madras and Erode) was also accomplished.

In this work, non-targeted ultra-high performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) fingerprints obtained by C18 reversed-phase chromatography were proposed as sample chemical descriptors for the characterization and classification of turmeric and curry samples. A total of 21 turmeric and 9 curry commercially available samples were analyzed in triplicate after extraction with dimethyl sulfoxide (DMSO). The results demonstrated the feasibility of non-targeted UHPLC-HRMS fingerprints for sample classification, showing very good classification capabilities by partial least squares regression-discriminant analysis (PLS-DA), with 100% classification rates being obtained by PLS-DA when randomly selected samples were processed as “unknown” ones. Besides, turmeric curcuma species (Curcuma longa vs. Curcuma zedoaria) and turmeric Curcuma longa varieties (Madras, Erodes, and Alleppey) discrimination was also observed by PLS-DA when using the proposed fingerprints as chemical descriptors. As a conclusion, non-targeted UHPLC-HRMS fingerprinting is a suitable methodology for the characterization, classification, and authentication of turmeric and curry samples, without the requirement of using commercially available standards for quantification nor the necessity of metabolite identification.

In this study, the feasibility of non-targeted UHPLC-HRMS fingerprints as chemical descriptors to address the classification and authentication of paprika samples was evaluated. Non-targeted UHPLC-HRMS fingerprints were obtained after a simple sample extraction method and C18 reversed-phase separation. Fingerprinting data based on signal intensities as a function of m/z values and retention times were registered in negative ion mode using a q-Orbitrap high-resolution mass analyzer, and the obtained non-targeted UHPLC-HRMS fingerprints subjected to unsupervised principal component analysis (PCA) and supervised partial least squares regression-discriminant analysis (PLS-DA) to study sample discrimination and classification. A total of 105 paprika samples produced in three different regions, La Vera PDO and Murcia PDO, in Spain, and the Czech Republic, and all of them composed of samples of at least two different taste varieties, were analyzed. Non-targeted UHPLC-HRMS fingerprints demonstrated to be excellent sample chemical descriptors to achieve the authentication of paprika production regions with 100% sample classification rates by PLS-DA. Besides, the obtained fingerprints were also able to perfectly discriminate among the different paprika taste varieties in all the studied cases, even in the case of the different La Vera PDO paprika tastes (sweet, bittersweet, and spicy) which are produced in a very small region.

Society’s interest in the quality of food products with certain attributes has increased, the attribute of a Protected Designation of Origin (PDO) being an effective tool to guarantee the quality and geographical origin of a given food product. In Spain, two paprika production areas with PDO (La Vera and Murcia) are recognized. In the present work, targeted UHPLC-HRMS polyphenolic and capsaicinoid profiling through the TraceFinderTM screening software, using homemade accurate mass databases, was proposed as a source of chemical descriptors, to address the characterization, classification, and authentication of paprika. A total of 126 paprika samples from different production regions—Spain (La Vera PDO and Murcia PDO) and the Czech Republic, each including different flavor varieties, were analyzed. UHPLC-HRMS polyphenolic profiles showed to be good chemical descriptors to achieve paprika classification and authentication, based on the production region, through principal component analysis and partial least squares regression-discriminant analysis, with classification rates of 82%, 86%, and 100% for La Vera PDO, Murcia PDO, and the Czech Republic, respectively. In addition, a perfect classification was also accomplished among the flavor varieties for the Murcia PDO and Czech Republic samples. By employing the UHPLC-HRMS polyphenolic and capsaicinoid profiles as chemical descriptors, acceptable discrimination among La Vera PDO flavor varieties was also achieved.

The increasing frequency of episodes of harmful algal blooms of cyanobacterial origin is a risk to ecosystems and human health. The main human hazard may arise from drinking water supply and recreational water use. For this reason, efficient multiclass analytical methods are needed to assess the level of cyanotoxins in water reservoirs and tackle these problems. This work describes the development of a fast, sensitive, and robust analytical method for multiclass cyanotoxins determination based on dual solid-phase extraction (SPE) procedure using a polymeric cartridge, Oasis HLB (Waters Corporation, Milford, MA, USA), and a graphitized non-porous carbon cartridge, SupelcleanTM ENVI-CarbTM (Sigma-Aldrich, St. Louis, MO, USA), followed by ultra-high-performance liquid chromatography high-resolution mass spectrometry (SPE-UHPLC-HRMS). This method enabled the analysis of cylindrospermopsin, anatoxin-a, nodularin, and seven microcystins (MC-LR, MC-RR, MC-YR, MC-LA, MC-LY, MC-LW, MC-LF). The method limits of detection (MLOD) of the validated approach were between 4 and 150 pg/L. The analytical method was applied to assess the presence of the selected toxins in 21 samples collected in three natural water reservoirs in the Ter River in Catalonia (NE of Spain) used to produce drinking water for Barcelona city (Spain).

This paper deals with the characterization of turmeric and related products using the compositional fingerprints of curcuminoids (e.g., curcumin, demethoxycurcumin and bisdemethoxycurcumin) and other phenolic compounds (e.g., hydroxybenzoic and hydroxycinnamic acids and flavonoids) as the source of analytical information. Under this approach, the quantitative determination of analytes becomes unnecessary and even data from unknown components can be advantageously exploited for sample exploration and authentication. The methodology relied on sample extraction with hydro-organic solvents to recover the components of interest and further analysis of the corresponding extracts by liquid chromatography with diode array detection (HPLC-DAD). Extraction conditions were optimized focusing on the independent recovery of curcuminoids and polyphenols. Two different HPLC methods under reversed-phase mode were used to generate the chromatographic fingerprints at 420 and 280 nm for the specific monitoring of curcuminoids and polyphenols, respectively. Both extraction and separation steps were optimized under experimental design approaches to achieve the richest compositional fingerprints in terms of variety of components. The resulting data was subsequently treated chemometrically by principal component analysis (PCA) and related classification methods to achieve a better overall description of samples. Polyphenolic fingerprints were appropriate to discriminate among turmeric and mixed spices, while curcuminoid fingerprints could be useful to distinguish turmeric varieties.

In this work, non-targeted approaches relying on HPLC-UV chromatographic fingerprints were evaluated to address coffee characterization, classification, and authentication by chemometrics. In general, high-performance liquid chromatography with ultraviolet detection (HPLC-UV) fingerprints were good chemical descriptors for the classification of coffee samples by partial least squares regression-discriminant analysis (PLS-DA) according to their country of origin, even for nearby countries such as Vietnam and Cambodia. Good classification was also observed according to the coffee variety (Arabica vs. Robusta) and the coffee roasting degree. Sample classification rates higher than 89.3% and 91.7% were obtained in all the evaluated cases for the PLS-DA calibrations and predictions, respectively. Besides, the coffee adulteration studies carried out by partial least squares regression (PLSR), and based on coffees adulterated with other production regions or variety, demonstrated the good capability of the proposed methodology for the detection and quantitation of the adulterant levels down to 15%. Calibration, cross-validation, and prediction errors below 2.9%, 6.5%, and 8.9%, respectively, were obtained for most of the evaluated cases.

This paper presents both an extensive literature review and a qualitative and quantitative study conducted on nearly 200 publications from the last six years (based on international experience and a top-down analysis framework with five classification levels) to establish the main trends in the field of centralized energy management systems (EMS) for microgrids. No systematic trend analyses have been observed in this field in previous literature reviews. EMS attributes for several features such as objective functions, resolution techniques, operating models, integration of uncertainties, optimization horizons, and modeling detail levels are considered for main trend identification. The main contribution of this study is the identification of four specific existing research trends: (i) dealing with uncertainties (comprises 33% of the references), (ii) multi-objective strategy (29%), (iii) traditional paradigm (21%), and (iv) P-Q challenge (17%). Each trend is described and analyzed based on the main drive of these separate research fields. The key challenges and the way to cope with them are described based on the rationality of each trend, the results of previous reviews, and the previous experience of the authors. Overall, finding these main trends, together with a complete paper database and their features, serve as a useful outcome for a better understanding of the current research-specific challenges, opportunities, potential barriers, and open questions regarding the creation of future centralized EMS developments. The traditional numerical analysis is insufficient to identify research trends. Therefore, the need of further analyses based on the clustering approach is emphasized.

Hen eggs are classified into four groups according to their production method: Organic, free-range, barn, or caged. It is known that a fraudulent practice is the misrepresentation of a high-quality egg with a lower one. In this work, high-performance liquid chromatography with ultraviolet detection (HPLC-UV) fingerprints were proposed as a source of potential chemical descriptors to achieve the classification of hen eggs according to their labelled type. A reversed-phase separation was optimized to obtain discriminant enough chromatographic fingerprints, which were subsequently processed by means of principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). Particular trends were observed for organic and caged hen eggs by PCA and, as expected, these groupings were improved by PLS-DA. The applicability of the method to distinguish egg manufacturer and size was also studied by PLS-DA, observing variations in the HPLC-UV fingerprints in both cases. Moreover, the classification of higher class eggs, in front of any other with one lower, and hence cheaper, was studied by building paired PLS-DA models, reaching a classification rate of at least 82.6% (100% for organic vs. non-organic hen eggs) and demonstrating the suitability of the proposed method.

The phenols and fatty acids profile and in vitro antioxidant and hypoglycaemic activity of seed, peel, pulp or pulp plus seeds of Colombian fruits from Solanaceae and Passifloraceae families were investigated. Ultra-High Performance Liquid Chromatography (UHPLC)-High Resolution Mass Spectrometry (HRMS) revealed the presence of chlorogenic acid as dominant phenolic compound in Solanaceae samples. Based on the Relative Antioxidant Score (RACI) and Global Antioxidant Score (GAS) values, Solanum quitoense peel showed the highest antioxidant potential among Solanaceae samples while Passiflora tripartita fruits exhibited the highest antioxidant effects among Passifloraceae samples. P. ligularis seeds were the most active as hypoglycaemic agent with IC50 values of 22.6 and 24.8 μg/mL against α-amylase and α-glucosidase, respectively. Considering that some of the most promising results were obtained by the processing waste portion, its use as functional ingredients should be considered for the development of nutraceutical products intended for patients with disturbance of glucose metabolism.

Recently, the authenticity of food products has become a great social concern. Considering the complexity of the food chain and that many players are involved between production and consumption; food adulteration practices are rising as it is easy to conduct fraud without being detected. This is the case for nut fruit processed products, such as almond flours, that can be adulterated with cheaper nuts (hazelnuts or peanuts), giving rise to not only economic fraud but also important effects on human health. Non-targeted HPLC-UV chromatographic fingerprints were evaluated as chemical descriptors to achieve nut sample characterization and classification using multivariate chemometric methods. Nut samples were extracted by sonication and centrifugation, and defatted with hexane; extracting procedure and conditions were optimized to maximize the generation of enough discriminant features. The obtained HPLC-UV chromatographic fingerprints were then analyzed by means of principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) to carry out the classification of nut samples. The proposed methodology allowed the classification of samples not only according to the type of nut but also based on the nut thermal treatment employed (natural, fried or toasted products).

The development of a simple HPLC-UV method towards the evaluation of Spanish paprika’s phenolic profile and their discrimination based on the former is reported herein. The approach is based on C18 reversed-phase chromatography to generate characteristic fingerprints, in combination with linear discriminant analysis (LDA) to achieve their classification. To this aim, chromatographic conditions were optimized so as to achieve the separation of major phenolic compounds already identified in paprika. Paprika samples were subjected to a sample extraction stage by sonication and centrifugation; extracting procedure and conditions were optimized to maximize the generation of enough discriminant fingerprints. Finally, chromatograms were baseline corrected, compressed employing fast Fourier transform (FFT), and then analyzed by means of principal component analysis (PCA) and LDA to carry out the classification of paprika samples. Under the developed procedure, a total of 96 paprika samples were analyzed, achieving a classification rate of 100% for the test subset (n = 25).

Introducción: En nuestro país, con el incremento en la esperanza de vida, existe una tendencia creciente de enfermedades neurodegenerativas, por lo que se hace necesario realizar estudios sobre factores de riesgo genético en personas afectadas con la enfermedad de Parkinson (EP), entre ellos el gen de la apolipoproteína E (ApoE), ya que esta asociación es desconocida en nuestra población. Objetivo: Determinar la asociación del polimorfismo en el gen ApoE con la EP. Diseño: Estudio asociativo, observacional tipo casos y controles. Lugar: Instituto Nacional de Ciencias Neurológicas, Lima, Perú. Participantes: Personas de ambos sexos, 163 pacientes con la EP y 176 controles. Intervenciones: Extracción de ADN genómico según metodología estándar. Análisis del gen APOE mediante técnica PCR-RFLP. Principales medidas de resultados: Frecuencias genotípicas y alélicas del gen ApoE en los casos y controles, medidas de asociación y de riesgo. Resultados: No se encontró diferencias significativas entre el grupo control y los pacientes según genotipo de ApoE. La frecuencia del alelo ε4 fue similar en pacientes y en controles. El odds ratio para el alelo ε4 de la ApoE fue 1,0852 (IC 95%: 0,5812 a 2,0266). La edad de inicio de la EP no tuvo relaciσn con los genotipos ApoE. Conclusiones: El alelo ε4 de la ApoE no podrνa ser considerado un factor de riesgo para la EP, y los genotipos de la ApoE no se asociaron con la edad de inicio en esta muestra evaluada.

High performance liquid chromatography method with ultra-violet detection (HPLC-UV) fingerprinting was applied for the analysis and characterization of olive oils, and was performed using a Zorbax Eclipse XDB-C8 reversed-phase column under gradient elution, employing 0.1% formic acid aqueous solution and methanol as mobile phase. More than 130 edible oils, including monovarietal extra-virgin olive oils (EVOOs) and other vegetable oils, were analyzed. Principal component analysis results showed a noticeable discrimination between olive oils and other vegetable oils using raw HPLC-UV chromatographic profiles as data descriptors. However, selected HPLC-UV chromatographic time-window segments were necessary to achieve discrimination among monovarietal EVOOs. Partial least square (PLS) regression was employed to tackle olive oil authentication of Arbequina EVOO adulterated with Picual EVOO, a refined olive oil, and sunflower oil. Highly satisfactory results were obtained after PLS analysis, with overall errors in the quantitation of adulteration in the Arbequina EVOO (minimum 2.5% adulterant) below 2.9%.