Human Mycotoxin Biomonitoring: Conclusive remarks on direct or indirect assessment of urinary deoxynivalenol

Deoxynivalenol is one of the most ubiquitous mycotoxins in the Western diet through its presence in cereals and cereal products. A vast amount of studies indicate the worrying level of exposure to this toxin, while even high percentages of the population exceed the tolerable daily intake. To evaluate and assess dietary exposure, analysis of urinary levels of deoxynivalenol and its glucuronides has been proposed as a reliable methodology. An indirect preliminary method was used based on the cleavage of deoxynivalenol glucuronides through the use of enzymes (beta-glucuronidase) and subsequent determination of "total deoxynivalenol" (sum of free and released mycotoxins by hydrolysis). Next, a direct procedure for quantification of deoxynivalenol-3-glucuronide and deoxynivalenol-15-glucuronide was developed. As deoxynivalenol glucuronides reference standards are not commercially available, the indirect method is widely applied. However, to not underestimate the total deoxynivalenol exposure in urine, the direct and indirect methodologies need to be compared. Urinary samples (n = 96) with a confirmed presence of deoxynivalenol and/or deoxynivalenol glucuronides were analysed using both approaches. The indirect method clarified that not all deoxynivalenol glucuronides were transformed to free deoxynivalenol during enzymatic treatment, causing an underestimation of total deoxynivalenol. This short communication concludes on the application of direct or indirect assessment of urinary deoxynivalenol

Stability of DON and DON-3-glucoside during baking as affected by the presence of food additives

The mycotoxin deoxynivalenol (DON) is one of the most common mycotoxins of cereals worldwide, and its occurrence has been widely reported in raw wheat. The free mycotoxin form is not the only route of exposure; modified forms can also be present in cereal products. Deoxynivalenol-3-glucoside (DON-3-glucoside) is a common DON plant conjugate. The mycotoxin concentration could be affected by food processing; here, we studied the stability of DON and DON-3-glucoside during baking of small doughs made from white wheat flour and other ingredients. A range of common food additives and ingredients were added to assess possible interference: ascorbic acid (E300), citric acid (E330), sorbic acid (E200), calcium propionate (E282), lecithin (E322), diacetyltartaric acid esters of fatty acid mono- and diglycerides (E472a), calcium phosphate (E341), disodium diphosphate (E450i), xanthan gum (E415), polydextrose (E1200), sorbitol (E420i), sodium bicarbonate (E500i), wheat gluten and malt flour. The DON content was reduced by 40%, and the DON-3-glucoside concentration increased by >100%, after baking for 20 min at 180°C. This confirmed that DON and DON-3-glucoside concentrations can vary during heating, and DON-3-glucoside could even increase after baking. However, DON and DON- 3-glucoside are not affected significantly by the presence of the food additives tested.The authors are grateful to the Spanish government (project AGL2014-55379-P) for providing financial support. A. Vidal thanks the Spanish government (Ministry of Education) for the pre-doctoral grant

Biomonitoring of deoxynivalenol and deoxynivalenol-3-glucoside in human volunteers : renal excretion profiles

Biomarkers for the determination of the dietary exposure to deoxynivalenol (DON) have been proposed in the past but so far no quantification of their use in humans has been carried out. Following a human intervention study with two mycotoxins, namely DON and deoxynivalenol-3-glucoside (DON3G), the renal excretion of these compounds, including their phase II metabolites, was analysed. The purpose was to develop biokinetic models that can be used to determine: (1) the preferred (set of) urinary biomarker(s), (2) the preferred urinary collection period, and (3) a method to estimate the dietary exposure to these mycotoxins. Twenty adult volunteers were restricted in consuming cereals and cereal-based foods for 4 days. At day 3, a single dose of 1 mu g/kg body weight of DON or DON3G was orally administered to 16 volunteers; 4 volunteers served as control. All individual urine discharges were collected during 24 h after administration. The metabolism and renal excretion could be described by a biokinetic model using three physiological compartments (gastrointestinal tract, liver, and kidneys). Kinetic analysis revealed a complete recovery of the renal excretion of total DON (mainly DON and its glucuronides) within 24 h after administration of DON or DON3G. The so-called 'reverse dosimetry' factor was used to determine the preferred (set of) biomarker(s) and to estimate the dietary intake of the parent compounds in the future. The fact that DON3G was absorbed and mainly excreted as DON and its glucuronides confirms that DON3G (as well as other modified forms) should be taken into account in the exposure and risk assessment of this group of mycotoxins

Generalized Linear Models for Geometrical Current predictors. An application to predict garment fit

The aim of this paper is to model an ordinal response variable in terms of vector-valued functional data included on a vector-valued RKHS. In particular, we focus on the vector-valued RKHS obtained when a geometrical object (body) is characterized by a current and on the ordinal regression model. A common way to solve this problem in functional data analysis is to express the data in the orthonormal basis given by decomposition of the covariance operator. But our data present very important differences with respect to the usual functional data setting. On the one hand, they are vector-valued functions, and on the other, they are functions in an RKHS with a previously defined norm. We propose to use three different bases: the orthonormal basis given by the kernel that defines the RKHS, a basis obtained from decomposition of the integral operator defined using the covariance function, and a third basis that combines the previous two. The three approaches are compared and applied to an interesting problem: building a model to predict the fit of children’s garment sizes, based on a 3D database of the Spanish child population. Our proposal has been compared with alternative methods that explore the performance of other classifiers (Suppport Vector Machine and k-NN), and with the result of applying the classification method proposed in this work, from different characterizations of the objects (landmarks and multivariate anthropometric measurements instead of currents), obtaining in all these cases worst results

Microfibrilación in situ de mezclas biobasadas de plarex-PA10.10 mediante estiramiento en caliente durante el proceso de extrusión

El presente proyecto se centra en la producción y caracterización de mezclas biobasadas de poli(ácido láctico) (PLA), modificado estructuralmente mediante un extensor de cadena (SAmfE), y una biopoliamida (PA). El objetivo es hacer la mezcla mediante un estiramiento en caliente “in situ” durante el proceso de extrusión promover una microfibrilación de poliamida. La selección de los porcentajes de SAmfE para la modificación del PLA fue obtenida mediante un procesado por amasadora Brabender. Posteriormente se obtuvieron las mezclas mediante tres etapas de extrusión. Las dos primeras están centradas en la obtención del PLA modificado estructuralmente, utilizando una cantidad nominal de 1,25% de SAmfE, al cual nos referiremos como PLAREx. Finalmente en la última etapa se hace el procesado de la mezcla, utilizando distintos estiramientos en caliente para promover la microfibrilación y obtener diferentes granzas de la mezcla. Se procede a una caracterización morfológica de las muestras mediante la microscopia electrónica de barrido (SEM) y se observa que existe una fibrilación en la dirección de estiramiento. Con un estudio calorimetría diferencial de barrido (DSC) se obtienen las transiciones térmicas de los materiales. Por último, con un análisis reométrico se verifica que las mezclas modificadas presentan mayor resistencia del fundido

Geometric analysis of planar shapes with applications to cell deformations

Shape analysis is of great importance in many fields such as computer vision, medical imaging, and computational biology. In this paper we focus on a shape space in which shapes are represented by means of planar closed curves. In this shape space a new metric was recently introduced with the result that this shape space has the property of being isometric to an infinite-dimensional Grassmann manifold of 2-dimensional subspaces. Using this isometry it is possible, from Younes et al. (2008), to explicitly describe geodesics, a task that previously was not at all easy. Our aim is twofold, namely: to use this general theory in order to show some applications to the study of erythrocytes, using digital images of peripheral blood smears, in the treatment of sickle cell disease; and, since normal erythrocytes are almost circular and many Sickle cells have elliptical shape, to particularize the computation of geodesics and distances between shapes using this metric to planar objects considered as deformations of a template (circle or ellipse). The applications considered include: shape interpolation, shape classification, and shape clustering

Optimal sizing of a hybrid grid-connected photovoltaic and wind power system

Hybrid renewable energy systems (HRES) have been widely identified as an efficient mechanism to generate electrical power based on renewable energy sources (RES). This kind of energy generation systems are based on the combination of one or more RES allowing to complement the weaknesses of one with strengths of another and, therefore, reducing installation costs with an optimized installation. To do so, optimization methodologies are a trendy mechanism because they allow attaining optimal solutions given a certain set of input parameters and variables. This work is focused on the optimal sizing of hybrid grid-connected photovoltaic-wind power systems from real hourly wind and solar irradiation data and electricity demand from a certain location. The proposed methodology is capable of finding the sizing that leads to a minimum life cycle cost of the system while matching the electricity supply with the local demand. In the present article, the methodology is tested by means of a case study in which the actual hourly electricity retail and market prices have been implemented to obtain realistic estimations of life cycle costs and benefits. A sensitivity analysis that allows detecting to which variables the system is more sensitive has also been performed. Results presented show that the model responds well to changes in the input parameters and variables while providing trustworthy sizing solutions. According to these results, a grid-connected HRES consisting of photovoltaic (PV) and wind power technologies would be economically profitable in the studied rural township in the Mediterranean climate region of central Catalonia (Spain), being the system paid off after 18 years of operation out of 25 years of system lifetime. Although the annual costs of the system are notably lower compared with the cost of electricity purchase, which is the current alternative, a significant upfront investment of over $10 M - roughly two thirds of total system lifetime cost - would be required to install such system. (C) 2015 Elsevier Ltd. All rights reserved.Postprint (author's final draft