Centro Superior Of Investigacion En Salud Publica

Valencia, Spain

Centro Superior Of Investigacion En Salud Publica

Valencia, Spain
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Ubeda C.,Centro Superior Of Investigacion En Salud Publica | Pamer E.G.,Memorial Sloan Kettering Institute
Nature Immunology | Year: 2012

The axis of lymphotoxin and its receptor LTβR influences the composition of the host gut microbiome, leading to excessive weight gain in hosts fed a high-fat diet. © 2012 Nature America, Inc. All rights reserved.

Agency: European Commission | Branch: FP7 | Program: CP-IP | Phase: ENV.2011.1.2.2-1 | Award Amount: 9.25M | Year: 2012

Various recent epidemiological studies have indicated that exposure to low doses of environmental biologically active contaminants during human development can alter gene expression and have deleterious effects on cognitive development in childhood. The DENAMIC project is ultimately focused on reducing such effects of environmental contamination on learning and developmental disorders in children. It aims to study and evaluate environment-health relationships in children. Key elements are: development of sophisticated tools and methods for early warning and screening of compounds for neurotoxicity, to study mechanisms of disease development and the role of individual susceptibility, to improve assessment of exposures and effects, focus on combined exposures to environmental agents that can interact to enhance adverse effects and reduction of health inequalities of children through Europe. One of the main aims of DENAMIC is to develop tools and methods for neurotoxic effects of mixtures of environmental pollutants at low levels, possibly resulting in (subclinical) effects on learning (cognitive skills) and developmental disorders in children (e.g ADHD, autism spectrum disorders and anxiety disorders). A broad suite of contaminants will be included in the studies, with options to bring in new chemicals in case evidence comes up during the project. With 14 partners from ten different countries DENAMIC has a true international character. It is a comprehensive, multi-disciplinary project. Six SMEs will play a key role in the development of biotechnological screening tools. The most modern techniques in the fields of genomics, proteomics, metabolomics and transcriptomics will be applied. Dissemination will ensure the project results to arrive at policymakers desks, and will also illustrate the subject for a scientific audience and the public. The very large network of the consortium ensures dissemination to European industries, and every other interested stakeholder.

Botella-Rocamora P.,CEU Cardenal Herrera University | Lopez-Quilez A.,University of Valencia | Martinez-Beneito M.A.,Centro Superior Of Investigacion En Salud Publica | Martinez-Beneito M.A.,CIBER ISCIII
Statistics in Medicine | Year: 2013

This paper introduces spatial moving average risk smoothing (SMARS) as a new way of carrying out disease mapping. This proposal applies the moving average ideas of time series theory to the spatial domain, making use of a spatial moving average process of unknown order to define dependence on the risk of a disease occurring. Correlation of the risks for different locations will be a function of m values (m being unknown), providing a rich class of correlation functions that may be reproduced by SMARS. Moreover, the distance (in terms of neighborhoods) that should be covered for two units to be found to make the correlation of their risks 0 is a quantity to be fitted by the model. This way, we reproduce patterns that range from spatially independent to long-range spatially dependent.We will also show a theoretical study of the correlation structure induced by SMARS, illustrating the wide variety of correlation functions that this proposal is able to reproduce. We will also present three applications of SMARS to both simulated and real datasets. These applications will show SMARS to be a competitive disease mapping model when compared with alternative proposals that have already appeared in the literature. Finally, the application of SMARS to the study of mortality for 21 causes of death in the Comunitat Valenciana will allow us to identify some qualitative differences in the patterns of those diseases. © 2012 John Wiley & Sons, Ltd.

Catala-Lopez F.,Centro Superior Of Investigacion En Salud Publica
BMC health services research | Year: 2011

The allocation of limited available healthcare resources demands an agreed rational allocation principle and the consequent priority setting. We assessed the association between economic evaluations of healthcare interventions published in Spain (1983-2008) and the disease burden in the population. Electronic databases (e.g., PubMed/MEDLINE, SCOPUS, ISI Web of Knowledge, CRD, IME, IBECS) and reports from health technology assessment agencies were systematically reviewed. For each article, multiple variables were recorded such as: year and journal of publication, type of study, health intervention targetted, perspective of analysis, type of costs and sources of information, first author's affiliation, explicit recommendations aimed at decision-making, and the main disease cause to which the intervention was addressed. The following disease burden measures were calculated: years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life years (DALYs), and mortality by cause. Correlation and linear regression models were fitted. Four hundred and seventy-seven economic evaluations were identified. Cardiovascular diseases (15.7%), infectious diseases (15.3%), malignant neoplasms (13.2%), and neuropsychiatric diseases (9.6%) were the conditions most commonly addressed. Accidents and injuries, congenital anomalies, oral conditions, nutritional deficiencies and other neoplasms were the categories with a lowest number of studies (0.6% for each of them). For the main disease categories (n = 20), a correlation was seen with: mortality 0.67 (p = 0.001), DALYs 0.63 (p = 0.003), YLLs 0.54 (p = 0.014), and YLDs 0.51 (p = 0.018). By disease sub-categories (n = 51), the correlations were generally low and non statistically significant. Examining discrepancies between economic evaluations in particular diseases and the overall burden of disease helps shed light on whether there are potentially over- and under-investigated areas. The approach taken could help policy-makers understand whether resources for economic evaluation are being allocated by using summary measures of population health.

Catala-Lopez F.,Centro Superior Of Investigacion En Salud Publica
PloS one | Year: 2012

Cost-Effectiveness Analysis (CEA) has been promoted as an important research methodology for determining the efficiency of healthcare technology and guiding medical decision-making. Our aim was to characterize the collaborative patterns of CEA conducted over the past two decades in Spain. A systematic analysis was carried out with the information obtained through an updated comprehensive literature review and from reports of health technology assessment agencies. We identified CEAs with outcomes expressed as a time-based summary measure of population health (e.g. quality-adjusted life-years or disability-adjusted life-years), conducted in Spain and published between 1989 and 2011. Networks of coauthorship and institutional collaboration were produced using PAJEK software. One-hundred and thirty-one papers were analyzed, in which 526 authors and 230 institutions participated. The overall signatures per paper index was 5.4. Six major groups (one with 14 members, three with 7 members and two with 6 members) were identified. The most prolific authors were generally affiliated with the private-for-profit sector (e.g. consulting firms and the pharmaceutical industry). The private-for-profit sector maintains profuse collaborative networks including public hospitals and academia. Collaboration within the public sector (e.g. healthcare administration and primary care) was weak and fragmented. This empirical analysis reflects critical practices among collaborative networks that contributed substantially to the production of CEA, raises challenges for redesigning future policies and provides a framework for similar analyses in other regions.

INTRODUCTION. Traumatic brain injuries (TBI) are a major cause of morbidity and mortality in children and adolescents but there are hardly any studies on the incidence and temporal evolution. AIM. To describe recent trends (2002-2009) in the incidence of hospitalization for TBI in children and adolescents in the region of Valencia. PATIENTS AND METHODS. Emergency admissions were identified in hospitals in the Valencian Health Agency from patients aged 0-19 years with a diagnosis of TBI (codes of the International Classification of Diseases 800, 801, 803, 804 and 850 to 854) during 2002 to 2009. The severity was classified using the fifth digit of these codes and the crude and standardized rates per 100,000 children were estimated stratified by age, sex and severity. RESULTS. From 2002 to 2009 a total of 5,504 TBI in children up to age of 19 years were hospitalized (mild: 92.9%; moderate to severe: 7.1%). In-hospital mortality was 0.6% for mild TBI and 15.7% for moderate-severe. Crude rates of mild head injury per 100,000 children fell from 85.9 to 55.4 in 2002-2009 (boys: 114.1 to 68.3, girls: 56.1 to 41.8), especially in the 15-19 years. For moderate-severe TBI, rates decreased from 5.73 to 2.78 per 100,000 in 2002-2009 (boys: 8.69 to 3.67; girls: 2.59 to 1.84). CONCLUSIONS. The incidence of pediatric TBI in the Valencia region has decreased significantly in the period 2002-2009, but their medical, legal, societal and family consequences still represents a substantial burden.

Martinez-Beneito M.A.,Centro Superior Of Investigacion En Salud Publica
Biometrika | Year: 2013

This paper deals with multivariate disease mapping. We propose a novel framework that encompasses most of the models already proposed. Our framework starts with a simple identity, reformulating Kronecker products of covariance matrices as simple matrix products. This formula is computationally convenient, and its generalizations reproduce most of the proposals in the disease mapping literature. Use of the identity leads to a flexible, general and computationally convenient modelling framework, making it possible to combine spatial dependence structures and different relationships between diseases with limited effort. Moreover, as the proposed modelling framework covers most of the Gaussian Markov random field-based multivariate disease mapping models in the literature, it allows comparison of all these models in a common context, thus helping us to understand them better. © 2013 Biometrika Trust.

Agency: European Commission | Branch: FP7 | Program: MC-CIG | Phase: FP7-PEOPLE-2011-CIG | Award Amount: 100.00K | Year: 2011

Antibiotic resistant bacteria, such as Vancomycin-resistant Enterococcus (VRE) or carbapenem-resistant Klebsiella pneumoniae (KPC), are an increasing problem in hospitalized patients and commonly cause infections following antibiotic therapy. Infections with these opportunistic pathogens generally begin by colonization of the intestinal epithelium. Our intestinal tract is inhabited by hundreds of commensal bacterial species that suppress intestinal colonization by antibiotic resistant pathogens. Commensal microbes might prevent infection by releasing inhibitory molecules or by competing for nutrients. In addition, we have shown that the microbiota confers protection against intestinal pathogens by inducing the immune response. Disruption of the microbiota after antibiotic administration enhances intestinal colonization by antibiotic resistant bacteria. However, not much is known about how antibiotic-induced changes in the microbiota increase the risk of infection. Using high-throughput 16S rDNA sequencing, We have begun to study the effect of antibiotic treatment on intestinal microbial populations and VRE/KPC colonization. We have shown that ampicillin treatment induces changes on the commensal flora that extend beyond the course of antibiotic administration. These long-lasting changes allowed establishment and persistence of VRE and KPC in the intestine. We hypothesize that some of the specific populations, lost after antibiotic administration, are key in suppressing VRE and KPC colonization. The goal of this proposal is to identify those specific microbial populations that confer protection against VRE or KPC. The mechanisms by which those bacterial species confer protection will also be studied. We will use a combination of microbiology, immunology and high-throughput sequencing techniques to pursue this goal. The results obtained in this proposal may lead to new therapeutic approaches to treat and prevent infections with antibiotic resistant pathogens.

Agency: European Commission | Branch: FP7 | Program: MC-IEF | Phase: FP7-PEOPLE-2010-IEF | Award Amount: 166.56K | Year: 2011

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis in humans, is estimated to infect one third of the human population leading to circa two million deaths a year. While many work has been done onto the socio-economic and host factors affecting the different outcomes of the disease, little is still known about the possible influence of Mycobacterium tuberculosis strain variation. Compare to other bacteria, Mtb has very low polymorphism which have prevented until now a detailed study of the evolutionary forces behind this pathogen. With the advent of next-generation sequencing this gap in our knowledge on the population genetics of Mtb with respect other bacteria is starting to close. This project will be aimed to analyze 100 Mtb strains currently being sequenced by the Sanger institute using Illumina technology which added to our previous panel of 30 strains already generated will allow detail population genetics and evolutionary studies with an special focus on the evolution of known Mtb antigens. Collaborations with laboratories with expertise in immunology, transcriptomics and molecular epidemiology will allow us to put in context the consequences of the Mtb genomic variation found in this study.

Thompson J.A.,Instituto Gulbenkian Of Ciencia | Oliveira R.,Instituto Gulbenkian Of Ciencia | Djukovic A.,Centro Superior Of Investigacion En Salud Publica | Ubeda C.,Centro Superior Of Investigacion En Salud Publica | And 2 more authors.
Cell Reports | Year: 2015

The mammalian gut microbiota harbors a diverse ecosystem where hundreds of bacterial species interact with each other and their host. Given that bacteria use signals to communicate and regulate group behaviors (quorum sensing), we asked whether such communication between different commensal species can influence the interactions occurring in this environment. We engineered the enteric bacterium, Escherichia coli, to manipulate the levels of the interspecies quorum sensing signal, autoinducer-2 (AI-2), in the mouse intestine and investigated the effect upon antibiotic-induced gut microbiota dysbiosis. E.coli that increased intestinal AI-2 levels altered the composition of the antibiotic-treated gut microbiota, favoring the expansion of the Firmicutes phylum. This significantly increased the Firmicutes/Bacteroidetes ratio, to oppose the strong effect of the antibiotic, which had almost cleared the Firmicutes. This demonstrates that AI-2 levels influence the abundance of the major phyla of the gut microbiota, the balance of which is known to influence human health. © 2015 The Authors.

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