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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.


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.


Garcia-Canaveras J.C.,Institute Investigacion Sanitaria Fundacion Hospital la Fe | Garcia-Canaveras J.C.,University of Valencia | Donato M.T.,Institute Investigacion Sanitaria Fundacion Hospital la Fe | Donato M.T.,University of Valencia | And 7 more authors.
Journal of Lipid Research | Year: 2012

Bile acids (BAs) are a group of chemically related steroids recognized as regulatory molecules whose profiles can change in different physio-pathological situations. We have developed a sensitive, fast, and reproducible ultraperformance liquid chromatography/multiple reaction monitoring/ mass spectrometry method to determine the tissue and sera BA profiles in different species (human, rat, and mouse) by quantifying 31 major and minor BA species in a single 21-min run. The method has been validated according to FDA guidelines, and it generally provides good results in terms of intra- and interday precision (less than 8.6% and 16.0%, respectively), accuracy (relative error measurement between -11.9% and 8.6%), and linearity (R2 > 0.996 and dynamic ranges between two and four orders of magnitude), with limits of quantification between 2.5 and 20 nM. The new analytical approach was applied to determine BA concentrations in human, rat, and mouse serum and in liver tissue. Our comparative study confirmed and extended previous reports, showing marked interspecies differences in circulating and hepatic BA composition. The targeted analysis revealed the presence of unexpected minoritary BAs, such as tauro-alpha-Muricholic acid in human serum, thus allowing us to obtain a thorough profiling of human samples. Its great sensitivity, low sample requirements (25 μl of serum, 5 mg of tissue), and comprehensive capacity to profile a considerable number of BAs make the present method a good choice to study BA metabolism in physiological and pathological situations, particularly in toxicological studies. Copyright © 2012 by the American Society for Biochemistry and Molecular Biology, Inc.


Quintas G.,Fundacion Hospital La Fe | Portillo N.,App Quality | Garcia-Canaveras J.C.,University of Valencia | Garcia-Canaveras J.C.,Institute Investigacion Sanitaria Fundacion Hospital La Fe | And 4 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.


PubMed | Leiden University, Maastricht University, Genedata AG and Institute Investigacion Sanitaria Fundacion Hospital La Fe
Type: | Journal: Archives of toxicology | Year: 2016

Differentiated human bronchial epithelial cells in air liquid interface cultures (ALI-PBEC) represent a promising alternative for inhalation studies with rodents as these 3D airway epithelial tissue cultures recapitulate the human airway in multiple aspects, including morphology, cell type composition, gene expression and xenobiotic metabolism. We performed a detailed longitudinal gene expression analysis during the differentiation of submerged primary human bronchial epithelial cells into ALI-PBEC to assess the reproducibility and inter-individual variability of changes in transcriptional activity during this process. We generated ALI-PBEC cultures from four donors and focussed our analysis on the expression levels of 362 genes involved in biotransformation, which are of primary importance for toxicological studies. Expression of various of these genes (e.g., GSTA1, ADH1C, ALDH1A1, CYP2B6, CYP2F1, CYP4B1, CYP4X1 and CYP4Z1) was elevated following the mucociliary differentiation of airway epithelial cells into a pseudo-stratified epithelial layer. Although a substantial number of genes were differentially expressed between donors, the differences in fold changes were generally small. Metabolic activity measurements applying a variety of different cytochrome p450 substrates indicated that epithelial cultures at the early stages of differentiation are incapable of biotransformation. In contrast, mature ALI-PBEC cultures were proficient in the metabolic conversion of a variety of substrates albeit with considerable variation between donors. In summary, our data indicate a distinct increase in biotransformation capacity during differentiation of PBECs at the air-liquid interface and that the generation of biotransformation competent ALI-PBEC cultures is a reproducible process with little variability between cultures derived from four different donors.


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.


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.


PubMed | Institute Investigacion Sanitaria Fundacion Hospital La Fe
Type: Journal Article | Journal: Analytical and bioanalytical chemistry | Year: 2014

Multiple analytical methods are required to comprehensively assess oxidative homeostasis and specific damage to macromolecules. Our aim was to develop a straightforward strategy for the fast assessment of global oxidative status and specific damage to DNA, proteins, and lipids. To this end, an analytical method, based on ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS/MS), was developed and validated for the quantification of 16 oxidative stress (OS) biomarkers. Some of these markers were unstable; thus, an easy sample treatment procedure, including fractionation and derivatization, was set up. The method was validated according to Food and Drug Administration (FDA) guidelines, and it provided good results in terms of intra- and inter-day precision (17.2 and 16%, respectively), accuracy (relative error measurement between -16.6 and 19.8%), and linearity (R (2)>0.994). The approach was applied to determine the oxidative insult provoked to cultured rat hepatocytes by cumene hydroperoxide and to analyze the liver and serum samples from patients diagnosed with nonalcoholic steatohepatitis. In both studies, significant differences were found if compared to the corresponding control groups; interestingly, ophthalmic acid was shown as an OS biomarker in both models for the first time. A key advantage of the novel approach in comparison with former multi-method approaches is that now a single method is applied to assess the 16 OS biomarkers. Its comprehensive capacity to profile oxidative homeostasis and damage in both in vitro and clinical samples has been illustrated, which indicates that the proposed approach is a good choice to evaluate whether OS is involved in physiological signals, diseases, or toxic events and to what extent.


PubMed | Institute Investigacion Sanitaria Fundacion Hospital La Fe
Type: | Journal: Electrophoresis | Year: 2015

Hepatotoxicity is the number one cause for agencies not approving and withdrawing drugs for the market. Drug-induced human hepatotoxicity frequently goes undetected in preclinical safety evaluations using animal models. Human-derived in vitro models represent a common alternative to in vivo tests to detect toxic effects during preclinical testing. Most current in vitro toxicity assays rely on the measurement of nonspecific or low sensitive endpoints, which result in poor concordance with human liver toxicity. Therefore, making more accurate predictions of the potential hepatotoxicity of new drugs remains a challenge. Metabolomics, whose aim is to globally assess all the metabolites present in a biological sample, may represent an alternative in the search for sensitive sublethal markers of drug-induced hepatotoxicity. To this end, a comprehensive LC-MS-based untargeted metabolite profiling analysis of HepG2 cells, exposed to a set of well-described model hepatotoxins and innocuous compounds, was performed. It allowed to determine meaningful metabolic changes triggered by a toxic insult and gave a first estimation of the main toxicity-related pathways. Based on these metabolic patterns, a partial least squares-discriminant analysis model, able to discriminate between nontoxic and hepatotoxic compounds, was constructed. The approach described herein may provide an alternative for animal testing in preclinical stages of drug development and a controlled experimental approach to gain a better understanding of the underlying causes of hepatotoxicity.


PubMed | Institute Investigacion Sanitaria Fundacion Hospital La Fe
Type: | Journal: Scientific reports | Year: 2016

In preclinical stages of drug development, anticipating potential adverse drug effects such as toxicity is an important issue for both saving resources and preventing public health risks. Current in vitro cytotoxicity tests are restricted by their predictive potential and their ability to provide mechanistic information. This study aimed to develop a metabolomic mass spectrometry-based approach for the detection and classification of drug-induced hepatotoxicity. To this end, the metabolite profiles of human derived hepatic cells (i.e., HepG2) exposed to different well-known hepatotoxic compounds acting through different mechanisms (i.e., oxidative stress, steatosis, phospholipidosis, and controls) were compared by multivariate data analysis, thus allowing us to decipher both common and mechanism-specific altered biochemical pathways. Briefly, oxidative stress damage markers were found in the three mechanisms, mainly showing altered levels of metabolites associated with glutathione and -glutamyl cycle. Phospholipidosis was characterized by a decreased lysophospholipids to phospholipids ratio, suggestive of phospholipid degradation inhibition. Whereas, steatosis led to impaired fatty acids -oxidation and a subsequent increase in triacylglycerides synthesis. The characteristic metabolomic profiles were used to develop a predictive model aimed not only to discriminate between non-toxic and hepatotoxic drugs, but also to propose potential drug toxicity mechanism(s).

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