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Chisvert A.,University of Valencia | Leon-Gonzalez Z.,Institute Investigacion Sanitaria Fundacion Hospital La Fe | Tarazona I.,University of Valencia | Salvador A.,University of Valencia | Giokas D.,University of Ioannina
Analytica Chimica Acta | Year: 2012

Organic UV filters are chemical compounds added to cosmetic sunscreen products in order to protect users from UV solar radiation. The need of broad-spectrum protection to avoid the deleterious effects of solar radiation has triggered a trend in the cosmetic market of including these compounds not only in those exclusively designed for sun protection but also in all types of cosmetic products.Different studies have shown that organic UV filters can be absorbed through the skin after topical application, further metabolized in the body and eventually excreted or bioaccumulated. These percutaneous absorption processes may result in various adverse health effects, such as genotoxicity caused by the generation of free radicals, which can even lead to mutagenic or carcinogenic effects, and estrogenicity, which is associated with the endocrine disruption activity caused by some of these compounds.Due to the absence of official monitoring protocols, there is a demand for analytical methods that enable the determination of UV filters in biological fluids and tissues in order to retrieve more information regarding their behavior in the human body and thus encourage the development of safer cosmetic formulations. In view of this demand, there has recently been a noticeable increase in the development of sensitive and selective analytical methods for the determination of UV filters and their metabolites in biological fluids (i.e., urine, plasma, breast milk and semen) and tissues. The complexity of the biological matrix and the low concentration levels of these compounds inevitably impose sample treatment processes that afford both sample clean-up to remove potentially interfering matrix components as well as the enrichment of analytes in order to achieve their determination at very low concentration levels.The aim of this review is to provide a comprehensive overview of the recent developments in the determination of UV filters in biological fluids and tissues, with special emphasis on the elucidation of new metabolites, sample preparation and analytical techniques as well as occurrence levels. © 2012 Elsevier B.V. Source

Agudo-Barriuso M.,Hospital Clinico Universitario Virgen Of La Arrixaca | Agudo-Barriuso M.,University of Murcia | Lahoz A.,Institute Investigacion Sanitaria Fundacion Hospital La Fe | Nadal-Nicolas F.M.,Hospital Clinico Universitario Virgen Of La Arrixaca | And 7 more authors.
Investigative Ophthalmology and Visual Science | Year: 2013

PURPOSE. To identify metabolic pathways and metabolites affected by optic nerve crush that can act as predictors of the disease or therapeutic targets. METHODS. The left optic nerve of adult rats was intraorbitally crushed and retinas were dissected 24 hours or 14 days after the lesion (n = 10 per group). Metabolic profiling analysis was carried out by Metabolon, Inc. A total of 195 metabolites were unambiguously detected. Data were normalized and the regulated metabolites were identified after comparing the different conditions. Metabolite concentration changes were analyzed using single and multivariate statistical analysis to detect discriminatory metabolites. Functional clustering and meta-analysis of the regulated metabolites was run through the Metacore platform. RESULTS. Comparison of 24 hours versus control, 14 days versus control samples, and 24 hours versus 14 days identified 9, 19, and 32 regulated metabolites, respectively. Single and multivariate analysis identified a total of 27 and 36 metabolites to discriminate between control and 14 days and between 24 hours and 14 days, respectively. Enrichment analysis showed alterations in the amino acid, carbohydrate, and lipid metabolism, which were further linked to translation, oxidative stress, energy (glucose and tricarboxylic acid cycle), and apoptosis through ceramide pathways. CONCLUSIONS. Our analysis differentiates a set of metabolites that clearly discriminate control and early-injury samples from late-injury samples. These metabolites could have potential use as diagnostic molecules. © 2013 The Association for Research in Vision and Ophthalmology, Inc. Source

Portillo N.,App Quality | Garcia-Canaveras J.C.,University of Valencia | Garcia-Canaveras J.C.,Institute Investigacion Sanitaria Fundacion Hospital La Fe | Castell J.V.,University of Valencia | And 3 more authors.
Metabolomics | Year: 2012

An MS-based metabolomics strategy including variable selection and PLSDA analysis has been assessed as a tool to discriminate between non-steatotic and steatotic human liver profiles. Different chemometric approaches for uninformative variable elimination were performed by using two of the most common software packages employed in the field of metabolomics (i. e., MATLAB and SIMCA-P). The first considered approach was performed with MATLAB where the PLS regression vector coefficient values were used to classify variables as informative or not. The second approach was run under SIMCA-P, where variable selection was performed according to both the PLS regression vector coefficients and VIP scores. PLSDA models performance features, such as model validation, variable selection criteria, and potential biomarker output, were assessed for comparison purposes. One interesting finding is that variable selection improved the classification predictiveness of all the models by facilitating metabolite identification and providing enhanced insight into the metabolic information acquired by the UPLC-MS method. The results prove that the proposed strategy is a potentially straightforward approach to improve model performance. Among others, GSH, lysophospholipids and bile acids were found to be the most important altered metabolites in the metabolomic profiles studied. However, further research and more in-depth biochemical interpretations are needed to unambiguously propose them as disease biomarkers. © 2011 Springer Science+Business Media, LLC. Source

Leon Z.,Institute Investigacion Sanitaria Fundacion Hospital La Fe | Garcia-Canaveras J.C.,University of Valencia | Garcia-Canaveras J.C.,Institute Investigacion Sanitaria Fundacion Hospital La Fe | Donato M.T.,University of Valencia | And 3 more authors.
Electrophoresis | Year: 2013

Metabolomics represents the global assessment of metabolites in a biological sample and reports the closest information to the phenotype of the biological system under study. Mammalian cell metabolomics has emerged as a promising tool with potential applications in many biotechnology and research areas. Metabolomics workflow includes experimental design, sampling, sample processing, metabolite analysis, and data processing. Given their influence on metabolite content and biological interpretation of data, a good experimental design and the appropriate choice of a sample processing method are prerequisites for success in any metabolomic study. The use of mammalian cells in the metabolomics field involves harder sample processing methods, including metabolism quenching and metabolite extraction, as compared to the use of body fluids, although such critical issues are frequently overlooked. This review aims to overview the common experimental procedures used in mammalian cell metabolomics based on mass spectrometry, by placing special emphasis on discussing sample preparation approaches, although other aspects, such as cell metabolomics applications, culture systems, cellular models, analytical platforms, and data analysis, are also briefly covered. This review intends to be a helpful tool to assist researchers in addressing decisions when planning a metabolomics study involving the use of mammalian cells. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Source

Pareja E.,Institute Investigacion Sanitaria Fundacion Hospital La Fe | Cortes M.,Institute Investigacion Sanitaria Fundacion Hospital La Fe | Hervas D.,Institute Investigacion Sanitaria La Fe | Mir J.,Institute Investigacion Sanitaria Fundacion Hospital La Fe | And 3 more authors.
Liver Transplantation | Year: 2015

Early allograft dysfunction (EAD) dramatically influences graft and patient outcomes. A lack of consensus on an EAD definition hinders comparisons of liver transplant outcomes and management of recipients among and within centers. We sought to develop a model for the quantitative assessment of early allograft function [Model for Early Allograft Function Scoring (MEAF)] after transplantation. A retrospective study including 1026 consecutive liver transplants was performed for MEAF score development. Multivariate data analysis was used to select a small number of postoperative variables that adequately describe EAD. Then, the distribution of these variables was mathematically modeled to assign a score for each actual variable value. A model, based on easily obtainable clinical parameters (ie, alanine aminotransferase, international normalized ratio, and bilirubin) and scoring liver function from 0 to 10, was built. The MEAF score showed a significant association with patient and graft survival at 3-, 6- and 12-month follow-ups. Hepatic steatosis and age for donors; cold/warm ischemia times and postreperfusion syndrome for surgery; and intensive care unit and hospital stays, Model for End-Stage Liver Disease and Child-Pugh scores, body mass index, and fresh frozen plasma transfusions for recipients were factors associated significantly with EAD. The model was satisfactorily validated by its application to an independent set of 200 patients who underwent liver transplantation at a different center. In conclusion, a model for the quantitative assessment of EAD severity has been developed and validated for the first time. The MEAF provides a more accurate graft function assessment than current categorical classifications and may help clinicians to make early enough decisions on retransplantation benefits. Furthermore, the MEAF score is a predictor of recipient and graft survival. The standardization of the criteria used to define EAD may allow reliable comparisons of recipients' treatments and transplant outcomes among and within centers. ©VC 2014 AASLD. Source

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