Total ion chromatogram and total ion mass spectrum as alternative tools for detection and discrimination (A review)

Gas chromatography (GC) and mass spectrometry (MS) are widely used techniques in the analysis of complex mixtures due to their various advantages, such as high selectivity, reproducibility, precision, and sensitivity. However, the data processing is often complex and time-consuming and requires a great deal of experience, which might be a serious drawback in certain areas, such as quality control, or regarding research in the field of medicine or forensic sciences, where time plays a crucial role. For these reasons, some authors have proposed the use of alternative data processing approaches, such as the total ion chromatogram or total mass spectrum, allowing these techniques to be treated as sensors where each retention time or ratio m/z acts as a sensor collecting total intensities. In this way, the main advantages associated with both techniques are maintained, but the outcomes from the analysis can be reached in a faster, simpler, and an almost automated way. In this review, the main features of the GC- and MS-based analysis methodologies and the ways in which to apply them are highlighted. Moreover, their implementation in different fields, such as agri-food, forensics, environmental sciences, or medicine is discussed, highlighting important advantages as well as limitations.info:eu-repo/semantics/publishedVersio

Rapid Detection and Quantification of Adulterants in Fruit Juices Using Machine Learning Tools and Spectroscopy Data

Fruit juice production is one of the most important sectors in the beverage industry, and its adulteration by adding cheaper juices is very common. This study presents a methodology based on the combination of machine learning models and near-infrared spectroscopy for the detection and quantification of juice-to-juice adulteration. We evaluated 100% squeezed apple, pineapple, and orange juices, which were adulterated with grape juice at different percentages (5%, 10%, 15%, 20%, 30%, 40%, and 50%). The spectroscopic data have been combined with different machine learning tools to develop predictive models for the control of the juice quality. The use of non-supervised techniques, specifically model-based clustering, revealed a grouping trend of the samples depending on the type of juice. The use of supervised techniques such as random forest and linear discriminant analysis models has allowed for the detection of the adulterated samples with an accuracy of 98% in the test set. In addition, a Boruta algorithm was applied which selected 89 variables as significant for adulterant quantification, and support vector regression achieved a regression coefficient of 0.989 and a root mean squared error of 1.683 in the test set. These results show the suitability of the machine learning tools combined with spectroscopic data as a screening method for the quality control of fruit juices. In addition, a prototype application has been developed to share the models with other users and facilitate the detection and quantification of adulteration in juices

Comparison of different processing approaches by SVM and RF on HS-MS eNose and NIR Spectrometry data for the discrimination of gasoline samples

In the quality control of flammable and combustible liquids, such as gasoline, both rapid analysis and automated data processing are of great importance from an economical viewpoint for the petroleum industry. The present work aims to evaluate the chemometric tools to be applied on the Headspace Mass Spectrometry (HS-MS eNose) and Near-Infrared Spectroscopy (NIRS) results to discriminate gasoline according to their Research Octane Number (RON). For this purpose, data from a total of 50 gasoline samples of two types of RON-95 and 98-analyzed by the two above-mentioned techniques were studied. The HS-MS eNose and NIRS data were com-bined with non-supervised exploratory techniques, such as Hierarchical Cluster Analysis (HCA), as well as other supervised classification techniques, namely Support Vector Machine (SVM) and Random Forest (RF). For su-pervised classification, the low-level data fusion was additionally applied to evaluate if the combined use of the data increases the scope of relevant information. The HCA results showed a clear clustering trend of the gasoline samples according to their RON with HS-MS eNose data. SVM in combination with 5-Fold Cross-Validation successfully classified 100% of the samples with the HS-MS eNose data set. The RF algorithm in combination with 5-Fold Cross-Validation achieved the best accuracy rate for the test set with the low-level data fusion system. Furthermore, it allowed us to identify the most important features that could define the differences between RON 95 and RON 98 gasoline. On the other hand, using the HS-MS eNose and NIRS low-level data fusion reached better results than those obtained using NIRS data individually, with accuracy rates of 100% in both SVM and RF performances with the test set. In general, the performance of the SVM and RF algorithms was found to be similar

Exposure to Essential and Toxic Elements via Consumption of Agaricaceae, Amanitaceae, Boletaceae, and Russulaceae Mushrooms from Southern Spain and Northern Morocco

The demand and interest in mushrooms, both cultivated and wild, has increased among consumers in recent years due to a better understanding of the benefits of this food. However, the ability of wild edible mushrooms to accumulate essential and toxic elements is well documented. In this study, a total of eight metallic elements and metalloids (chromium (Cr), arsenic (As), cadmium (Cd), mercury (Hg), lead (Pb), copper (Cu), zinc (Zn), and selenium (Se)) were determined by ICP-MS in five wild edible mushroom species (Agaricus silvicola, Amanita caesarea, Boletus aereus, Boletus edulis, and Russula cyanoxantha) collected in southern Spain and northern Morocco. Overall, Zn was found to be the predominant element among the studied species, followed by Cu and Se. The multivariate analysis suggested that considerable differences exist in the uptake of the essential and toxic elements determined, linked to species-intrinsic factors. Furthermore, the highest Estimated Daily Intake of Metals (EDIM) values obtained were observed for Zn. The Health Risk Index (HRI) assessment for all the mushroom species studied showed a Hg-related cause of concern due to the frequent consumption of around 300 g of fresh mushrooms per day during the mushrooming season

Toxic elements and trace elements in Macrolepiota procera mushrooms from southern Spain and northern Morocco

Anthropogenic activities, such as mining and fossil fuel combustion, produce large amounts of pollutants that affect environmental homeostasis. Wild edible mushrooms fructify exposed to environmental conditions, proving to be efficient accumulators of trace elements and toxic and potentially toxic elements. Due to the increasing consumption of mushrooms worldwide, this is of public health concern. In this work, the total content of chromium (Cr), arsenic (As), cadmium (Cd), mercury (Hg), lead (Pb), copper (Cu), zinc (Zn), and selenium (Se) was determined by ICP-MS in the caps and stipes of the high valued wild edible mushroom Macrolepiota procera collected in several locations of the South of Spain and the North of Morocco. The results obtained have indicated that the cap of M. procera contains a broad spectrum of both toxic elements and trace elements, occurring in higher contents in this part of the fruiting body with respect to the stipe. Moreover, Cu was the predominant element found in the samples studied, followed by Zn in most of the cases. The one-way ANOVA/Kruskal-Wallis test indicated that there were no significant differences in metal and metalloid content between the geographical areas studied. In addition, the results obtained through Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) support the conclusions drawn through univariate statistical studies, indicating that there is no obvious clustering trend for the M. procera cap samples based on the sampling area. The health risk assessment for M. procera caps showed a cause for concern related to Cr, Cd, As, and Hg due to frequent consumption of around 300 g of fresh caps per day during the mushrooming season. © 2022 The Author(s

Ultrasound-Assisted Extraction of Total Phenolic Compounds and Antioxidant Activity in Mushrooms

The consumption of mushrooms has considerably increased in recent years because of their beneficial nutritional properties due to their essential amino acids, proteins, and dietary fiber content. Recent research has shown that they are also rich in polysaccharides and phenolic compounds. These compounds exhibit decisive free radical and ROS scavenging power with potential application to the treatment of neurodegenerative disorders. In addition, they present important properties like antioxidant, antiaging, and immune modulation. In the present research, the optimization for the extraction of total phenolic compounds and the antioxidant activity (DPPH and ABTS), based on ultrasound-assisted techniques has been carried out. Five variables (% MeOH in solvent, extraction temperature, amplitude, cycle, and sample:solvent ratio have been selected; both the total phenolic compounds content as well as the antioxidant activity (DPPH and ABTS)) have been considered as the response variables. The optimal conditions, determined by means of a multiresponse optimization method, were established at 0.2 g of sample extracted with 15.3 mL of solvent (93.6% MeOH) at 60 degrees C for 5 min and using 16.86% amplitude and 0.71 s(-1) cycles. A precision study of the optimized method has been performed with deviations lower than 5%, which proves the repeatability and precision of the extraction method. Finally, the extraction method has been applied to wild and commercial mushrooms from Andalusia and Northern Morocco, which has confirmed its suitability for the extraction of the phenolic compounds from mushroom samples, while ensuring maximum antioxidant activity

Essential Mineral Content (Fe, Mg, P, Mn, K, Ca, and Na) in Five Wild Edible Species of Lactarius Mushrooms from Southern Spain and Northern Morocco: Reference to Daily Intake

Mushroom consumption has increased in recent years due to their beneficial properties to the proper functioning of the body. Within this framework, the high potential of mushrooms as a source of essential elements has been reported. Therefore, the present study aims to determine the mineral content of seven essential metals, Fe, Mg, Mn, P, K, Ca, and Na, in twenty samples of mushrooms of the genus Lactarius collected from various locations in southern Spain and northern Morocco, by FAAS, UV-Vis spectroscopy, and ICP-OES after acid digestion. Statistics showed that K was the macronutrient found at the highest levels in all mushrooms studied. ANOVA showed that there were statistically significant differences among the species for K, P, and Na. The multivariate study suggested that there were differences between the accumulation of the elements according to the geographic location and species. Furthermore, the intake of 300 g of fresh mushrooms of each sample covers a high percentage of the RDI, but does not meet the recommended daily intake (RDI) for any of the metals studied, except for Fe. Even considering these benefits, the consumption of mushrooms should be moderated due to the presence of toxic metals, which may pose health risks.16 página

Assessing Body Esteem in Adolescents: psychometric properties of the Spanish version of the Body Esteem Scale (BESAA-S)

Background: “How do I perceive my own body?“ is a central question during adolescence, which addresses the subjective assessment of body image, called Body Esteem. Although concern about body esteem increases during adolescence, there is a lack of psychometrically validated measures to assess it specifically among Spanish adolescents. Objective: This study aims to validate the Body-Esteem Scale for Adolescents and Adult populations (BESAA), a widely used measure of body esteem across cultures, among the Spanish adolescent population. Methods: The cross-cultural adequacy and acceptability of the Argentinian-Spanish version by Forbes et al., (2012) were pilot tested and the questionnaire was completed by 1,258 students (Mage = 15.56). Next, several psychometric analyses were carried out: exploratory (AFE) and confirmatory (CFA) factorial structure, convergent and discriminant validity, nomological validity, internal consistency, and temporal reliability. Results: The AFE and CFA supported a reduced Spanish version of the BESAA of 14 items (BESAA-S) and maintained the original three-factor structure (BE-Weight, BE-Appearance, and BE-Attribution subscales). The BESAA-S showed acceptable internal consistency and strong test-retest reliability. Discriminant validity between subscales was appropriate, and convergent validity was appropriate except for the BE-Attribution subscale. Nomological validity was supported through significant correlations with body appreciation, general self-esteem, sociocultural attitudes towards appearance, and disordered eating symptoms. Body esteem was negatively associated with weight status. Conclusions: This study presents a culturally appropriate, shortened Spanish BESAA as a reliable instrument for body esteem assessment among Spanish speaking adolescentsFunding information The authors did not receive fnancial support from any organization for the submitted wor

Accelerated aging in ultrathin films of a molecular glass former

We report the thermodynamic measurement of the enthalpy released during the aging of supported films of a molecular glass former, toluene, at temperatures well below the glass transition temperature. By using microfabricated devices with very short equilibration times (below 1 s), we evidence a remarkable variation of the relaxation rate on decreasing film thickness from 100 nm down to a 7 nm thick film. Our results demonstrate that surface atoms are more efficient than bulk atoms in attaining low energy configurations within the potential energy landscape

Brain tyrosinase overexpression implicates age-dependent neuromelanin production in Parkinson's disease pathogenesis

Brain tyrosinase; Neuromelanin production; Parkinson’sTirosinasa cerebral; Producció de neuromelanina; ParkinsonTirosinasa cerebral; Producción de neuromelanina; ParkinsonIn Parkinson's disease (PD) there is a selective degeneration of neuromelanin-containing neurons, especially substantia nigra dopaminergic neurons. In humans, neuromelanin accumulates with age, the latter being the main risk factor for PD. The contribution of neuromelanin to PD pathogenesis remains unknown because, unlike humans, common laboratory animals lack neuromelanin. Synthesis of peripheral melanins is mediated by tyrosinase, an enzyme also present at low levels in the brain. Here we report that overexpression of human tyrosinase in rat substantia nigra results in age-dependent production of human-like neuromelanin within nigral dopaminergic neurons, up to levels reached in elderly humans. In these animals, intracellular neuromelanin accumulation above a specific threshold is associated to an age-dependent PD phenotype, including hypokinesia, Lewy body-like formation and nigrostriatal neurodegeneration. Enhancing lysosomal proteostasis reduces intracellular neuromelanin and prevents neurodegeneration in tyrosinase-overexpressing animals. Our results suggest that intracellular neuromelanin levels may set the threshold for the initiation of PD