Comparative effects of glucagon-like peptide-1 receptors agonists, 4-dipeptidyl peptidase inhibitors, and metformin on metabolic syndrome

Funding sponsor Funding number Acronym Balearic Islands Health Research InstituteEU-COST 35/2011, CA16112Fondo de Investigación para la SaludIDISBA CB12/03, CIBEROBN CB06/03Margalida Comas DG R+D+IMinistry of Science, SpainEuropean Commission 201630.10, EAT2BENICE_H2020_SFS2016European Research Council 2013–2018, 340918Generalitat Valenciana PROMETEO/2017/017Instituto de Salud Carlos IIIFunding sponsor Funding number Acronym Balearic Islands Health Research Institute EU-COST 35/2011, CA16112 Fondo de Investigación para la Salud IDISBA CB12/03, CIBEROBN CB06/03 Margalida Comas DG R+D+I Ministry of Science, Spain European Commission See opportunities by EC See opportunities (opens in new window) 201630.10, EAT2BENICE_H2020_SFS2016 EC European Research Council See opportunities by ERC See opportunities (opens in new window) 2013–2018, 340918 ERC Generalitat Valenciana See opportunities by GVA See opportunities (opens in new window) PROMETEO/2017/017 GVA Instituto de Salud Carlos III 2013ACUP00194, PI13/00233, PI13/00272, PI13/00462, PI13/00492, PI13/00673, PI13/00728, PI13/01056, PI13/01090, PI13/01123, PI13/02184, PI14/00618, PI14/00636, PI14/00696, PI14/00728, PI14/00853, PI14/00972, PI14/01206, PI14/01374, PI14/01471, PI14/01722, PI14/01919, PI16/00366, PI16/00381, PI16/00473, PI16/00501, PI16/00533, PI16/00662, PI16/01094, PI16/01120, PI16/01522, PI16/01873, PI17/00215, PI17/00508, PI17/00525, PI17/00532, PI17/00764, PI17/00855, PI17/00926, PI17/01183, PI17/01347, PI17/01441, PI17/01732, PI17/01827, PI19/00017, PI19/00309, PI19/00386, PI19/00576, PI19/00781, PI19/00957, PI19/01032, PI19/01226, PI19/01332, PI19/01560, PI20/00138, PI20/00339, PI20/00456, PI20/00557, PI20/00886, PI20/01158, PI20/01532, PI20/01802Consejería de Salud y Familias, Junta de Andalucía PI0137/2018, PI0458/2013, PS0358/201

Infarto agudo de miocardio con elevación del segmento ST: estrategias de reperfusión en el Hospital Clínico de Valladolid

La cardiopatía isquémica es la principal causa de mortalidad en los países desarrollados. El síndrome coronario agudo con elevación del segmento ST (SCACEST) es una de sus manifestaciones más graves. Existen diferentes estrategias de reperfusión en el SCACEST. En 2013 se aprobó el Código Infarto en la Comunidad de Castilla y León, cuyo objetivo principal es disminuir la morbimortalidad del SCACEST promoviendo estrategias de reperfusión eficaces y precoces. El objetivo de este trabajo fin de grado es analizar las diferentes estrategias de reperfusión utilizadas en el Hospital Clínico de Valladolid entre los años 2016 y 2018 y ver si se cumplen las directrices de las guías de práctica clínica y recomendaciones del código infarto.Grado en Medicin

Telemonitoring ADL platform based on non-intrusive and privacy-friendly sensors for the care of the elderly in smart homes

International audienceDuring the last years, several sensor-based monitoring systems have been developed to detect in real time frequent problems in older people, such as falls and nocturia. Some devices can also measure different variables of the environment (e.g. temperature, pollution, etc.) to generate alarms and thus help the user's welfare. All these devices generate numerous sensitive data related to the health and behavior of user/patients. The presence of some of these sensors in homes can mean a vulnerability of the user’s privacy. In this article we propose a telemonitoring ADL platform based on non-intrusive sensors for the care of the elderly, restricted by a user-centered protocol that guarantees their privacy and facilitates their acceptance by the user

Desired weight loss and its association with health, health behaviors and perceptions in an adult population with weight excess: One-year follow-up

Background: Metabolic syndrome (MetS) worsens quality of life and increases mortality. Dissatisfaction with weight in patients with MetS may modify the effect of lifestyle interventions to achieve changes in health-related behaviors. Objective: To assess 1-year changes in cardiovascular risk scores, self-perceived general health and health-related behaviors according to observed changes in desired weight loss during the first year of intervention in a large cardiovascular prevention trial. Design: Prospective analysis of the PREDIMED-PLUS trial, including 5,499 adults (55-75 years old) with overweight or obesity at baseline. Methods: The desired weight loss was the difference between ideal and measured weight. Tertiles of change in desired weight loss (1 year vs. baseline) were defined by the following cut-off points: >= 0.0 kg (T1, n = 1,638); 0.0 to -4.0 kg (T2, n = 1,903); <=-4.0 kg (T3, n = 1,958). A food frequency questionnaire assessed diet and the Minnesota-REGICOR questionnaire assessed physical activity. The Framingham equation assessed cardiovascular risks. The changes in the severity of MetS were also assessed. The Beck Depression Inventory assessed depressive symptoms and the SF-36 assessed health-related quality of life. Data were analyzed using general linear models. Results: BMI decreased at T2 and T3 (T1: 0.3, T2: -0.7, T3: -1.9). The most significant improvement in diet quality was observed at T3. Cardiovascular risk decreased at T2 and T3. Mean reductions in MetS severity score were: -0.02 at T1, -0.39 at T2 and -0.78 at T3. The perception of physical health increases in successive tertiles. Conclusions: In older adults with MetS, more ambitious desired weight loss goals were associated with improvements in diet, cardiovascular health and perceived physical health during the first year of a healthy lifestyle intervention programme. Weight dissatisfaction needs to be considered by health professionals.European Research Council (ERC) European Commission 20132018 340918Spanish government, ISCIII, through the Fondo de Investigacion para la Salud (FIS) - European Regional Development Fund PI13/00673 PI13/00492 PI13/00272 PI13/01123 PI13/00462 PI13/00233 PI13/02184 PI13/00728 PI13/01090 PI13/01056 PI14/01722 PI14/00636 PI14/00618 PI14/00696 PI14/01206 PI14/01919Especial Action Project entitled: Implementacion y evaluacion de una intervencion intensive sobre la actividad fisica Cohorte PREDIMED-Plus grantRecercaixa Grant 2013ACUP00194Junta de Andalucia PI0458/2013 PS0358/2016 PI0137/2018Center for Forestry Research & Experimentation (CIEF)European Commission PROMETEO/2017/017 European Cooperation in Science and Technology (COST) European Commission CA16112Balearic Islands Health Research Institute (IDISBA)European Commission CIBEROBN CB06/03 CB12/03 European Commission European Commission Joint Research Centre EAT2BENICE_H2020_SFS2016Fundacio La Marato TV3 201630.10Fernando Tarongi Bauza Grant'Spanish government, ISCIII, through the Fondo de Investigacion para la Salud (FIS) - European Regional Development Fund' PI17/00855 PI17/01347 PI17/00525 PI17/01827 PI17/00532 PI17/00215 PI17/01441 PI17/00508 PI17/01732 PI17/00926 PI19/00957 PI19/00386 PI19/00309 PI19/01032 PI19/00576 PI19/00017the Spanish government, ISCIII, through the Fondo de Investigacion para la Salud (FIS) - European Regional Development Fund PI14/00853 PI14/01374 PI14/00972 PI14/00728 PI14/01471 PI16/00473 PI16/00662 PI16/01873 PI16/01094 PI16/00501 PI16/00533 PI16/00381 PI16/00366 PI16/01522 PI16/01120 PI17/00764 PI17/01183 PI19/01226"Spanish government, ISCIII, through the Fondo de Investigacion para la Salud (FIS) - European Regional Development Fund" PI19/00781 PI19/01560 PI19/01332 PI20/01802 PI20/00138 PI20/01532 PI20/00456 PI20/00339 PI20/00557 PI20/00886 PI20/0115

Revisiting the Yeast Cell Cycle Problem with the Improved TriGen Algorithm

Analyzing microarray data represents a computational challenge due to the characteristics of these data. Clustering techniques are widely applied to create groups of genes that exhibit a similar behavior under the conditions tested. Biclustering emerges as an improvement of classical clustering since it relaxes the constraints for grouping allowing genes to be evaluated only under a subset of the conditions and not under all of them. However, this technique is not appropriate for the analysis of temporal microarray data in which the genes are evaluated under certain conditions at several time points. On a previous work we presented the TriGen algorithm, a genetic algorithm that finds triclusters of gene expression that take into account the experimental conditions and the time points simultaneously, and was applied to the yeast (Saccharomyces Cerevisiae) cell cycle problem. In this article we present some improvements on the genetic algorithm and we also present the results of applying the improved TriGen algorithm to the yeast cell cycle problem, where the goal is to identify all genes whose expression levels are regulated by the cell cycle

Triclustering on TemporaryMicroarray Data using the TriGen Algorithm

The analysis of microarray data is a computational challenge due to the characteristics of these data. Clustering techniques are widely applied to create groups of genes that exhibit a similar behavior under the conditions tested. Biclustering emerges as an improvement of classical clustering since it relaxes the constraints for grouping allowing genes to be evaluated only under a subset of the conditions and not under all of them. However, this technique is not appropriate for the analysis of temporal microarray data in which the genes are evaluated under certain conditions at several time points. In this paper, we propose the TriGen algorithm, which finds triclusters that take into account the experimental conditions and the time points, using evolutionary computation, in particular genetic algorithms, enabling the evaluation of the gene’s behavior under subsets of conditions and of time points

TriGen: A genetic algorithm to mine triclusters in temporal gene expression data

Analyzing microarray data represents a computational challenge due to the characteristics of these data. Clustering techniques are widely applied to create groups of genes that exhibit a similar behavior under the conditions tested. Biclustering emerges as an improvement of classical clustering since it relaxes the constraints for grouping genes to be evaluated only under a subset of the conditions and not under all of them. However, this technique is not appropriate for the analysis of longitudinal experiments in which the genes are evaluated under certain conditions at several time points. We present the TriGen algorithm, a genetic algorithm that finds triclusters of gene expression that take into account the experimental conditions and the time points simultaneously. We have used TriGen to mine datasets related to synthetic data, yeast (Saccharomyces cerevisiae) cell cycle and human inflammation and host response to injury experiments. TriGen has proved to be capable of extracting groups of genes with similar patterns in subsets of conditions and times, and these groups have shown to be related in terms of their functional annotations extracted from the Gene Ontology.Ministerio de Ciencia y Tecnología TIN2011-28956-C00Ministerio de Ciencia y Tecnología TIN2009-13950Junta de Andalucía TIC-752

Probiotic<i> Bacillus subtilis</i> protects against α-synuclein aggregation in <i>C. elegans</i>

How the gut microbiome affects Parkinson's disease remains unclear. Goya et al. show that the probiotic B. subtilis strain PXN21 inhibits and clears α-synuclein aggregation in a C. elegans model. The bacterium acts via metabolites and biofilm formation to activate protective pathways in the host, including DAF-16/FOXO and sphingolipid metabolism.Fil: Goya, María Eugenia. University of Edinburgh; Reino UnidoFil: Xue, Feng. University of Edinburgh; Reino UnidoFil: Sampedro Torres Quevedo, Cristina. University of Edinburgh; Reino UnidoFil: Arnaouteli, Sofia. University Of Dundee; Reino UnidoFil: Riquelme Dominguez, Lourdes. University of Edinburgh; Reino UnidoFil: Romanowski, Andrés. University of Edinburgh; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Brydon, Jack. University of Edinburgh; Reino UnidoFil: Ball, Kathryn L.. University of Edinburgh; Reino UnidoFil: Stanley-Wall, Nicola R.. University Of Dundee; Reino UnidoFil: Doitsidou, Maria. University of Edinburgh; Reino Unid

On the use of algorithms to discover motifs in DNA sequences

Many approaches are currently devoted to find DNA motifs in nucleotide sequences. However, this task remains challenging for specialists nowadays due to the difficulties they find to deeply understand gene regulatory mechanisms, especially when analyzing binding sites in DNA. These sites or specific nucleotide sequences are known to be responsible for transcription processes. Thus, this work aims at providing an updated overview on strategies developed to discover meaningful motifs in DNA-related sequences, and, in particular, their attempts to find out relevant binding sites. From all existing approaches, this work is focused on dictionary, ensemble, and artificial intelligence-based algorithms since they represent the classical and the leading ones, respectively.Ministerio de Ciencia y Tecnología TIN2007- 68084-C-00Junta de Andalucia P07-TIC- 02611