New advances in gluten analysis: application of MALDI-TOF/TOF mass spectrometry and NANOLC-ESI-IT-MS/MS techniques

Comunicaciones a congreso

Prediction of forest fires occurrences with area-level Poisson mixed models

[Abstract] The number of fires in forest areas of Galicia (north-west of Spain) during the summer period is quite high. Local authorities are interested in analyzing the factors that explain this phenomenon. Poisson regression models are good tools for describing and predicting the number of fires per forest areas. This work employs area-level Poisson mixed models for treating real data about fires in forest areas. A parametric bootstrap method is applied for estimating the mean squared errors of fires predictors. The developed methodology and software are applied to a real data set of fires in forest areas of Galicia.Ministerio de Ciencia e Innovación; MTM2013-41383-PXunta de Galicia; CN2012/130Ministerio del Medio Ambiente, Rural y Marino; PSE-310000-2009-4COST European Cooperation in Science and Technology; OC-2008-1-2124Ministerio de Ciencia e Innovación; MTM2012-37077-C02-01Ministerio de Ciencia e Innovación; MTM2011-22392Ministerio de Ciencia e Innovación; MTM2008-03010Xunta de Galicia; 07MRU035291P

Poisson mixed models for predicting number of fires

© 2019. This manuscript version is made available under the CC-BY 4.0 license https://creativecommons.org/ licenses/by/4.0/. This version of the article: M. Boubeta, M. J. Lombardía, M. Marey-Pérez, y D. Morales, «Poisson mixed models for predicting number of fires», Int. J. Wildland Fire, vol. 28, n.º 3, pp. 237-253, mar. 2019, doi: 10.1071/WF17037, has been accepted for publication in International Journal of Wildland Fire. The Version of Record is available online at https://doi.org/10.1071/WF17037[Abstract]: Wildfires are considered one of the main causes of forest destruction. In recent years, the number of forest fires and burned area in Mediterranean regions have increased. This problem particularly affects Galicia (north-west of Spain). Conventional modelling of the number of forest fires in small areas may have a high error. For this reason, four area-level Poisson mixed models with time effects are proposed. The first two models contain independent time effects, whereas the random effects of the other models are distributed according to an autoregressive process AR(1). A parametric bootstrap algorithm is given to measure the accuracy of the plug-in predictor of fire number under the temporal models. A significant prediction improvement is observed when using Poisson regression models with random time effects. Analysis of historical data finds significant meteorological and socioeconomic variables explaining the number of forest fires by area and reveals the presence of a temporal correlation structure captured by the area-level Poisson mixed model with AR(1) time effects

Burned area prediction with semiparametric models

[Abstract] Wildfires are one of the main causes of forest destruction, especially in Galicia (north-west Spain), where the area burned by forest fires in spring and summer is quite high. This work uses two semiparametric time-series models to describe and predict the weekly burned area in a year: autoregressive moving average (ARMA) modelling after smoothing, and smoothing after ARMA modelling. These models can be described as a sum of a parametric component modelled by an autoregressive moving average process and a non-parametric one. To estimate the non-parametric component, local linear and kernel regression, B-splines and P-splines were considered. The methodology and software were applied to a real dataset of burned area in Galicia for the period 1999–2008. The burned area in Galicia increases strongly during summer periods. Forest managers are interested in predicting the burned area to manage resources more efficiently. The two semiparametric models are analysed and compared with a purely parametric model. In terms of error, the most successful results are provided by the first semiparametric time-series model.Ministerio del Medio Ambiente, Rural y Marino; PSE-310000-2009-4Ministerio de Economía y Competitividad; MTM2014-52876-RMinisterio de Economía y Competitividad; MTM2011-22392Ministerio de Economía y Competitividad; MTM2013-41383-PXunta de Galicia; CN2012/130Xunta de Galicia; 07MRU035291PRCOST Action/UE COST-OC-2008-1-2124

Burned area prediction with semiparametric models

Wildfires are one of the main causes of forest destruction, especially in Galicia (north-west Spain), where the area burned by forest fires in spring and summer is quite high. This work uses two semiparametric time-series models to describe and predict the weekly burned area in a year: autoregressive moving average (ARMA) modelling after smoothing, and smoothing after ARMA modelling. These models can be described as a sum of a parametric component modelled by an autoregressive moving average process and a non-parametric one. To estimate the non-parametric component, local linear and kernel regression, B-splines and P-splines were considered. The methodology and software were applied to a real dataset of burned area in Galicia for the period 1999–2008. The burned area in Galicia increases strongly during summer periods. Forest managers are interested in predicting the burned area to manage resources more efficiently. The two semiparametric models are analysed and compared with a purely parametric model. In terms of error, the most successful results are provided by the first semiparametric time-series modelThis work was supported by grants MTM2014–52876-R, MTM2011–22392 and MTM2013–41383-P of the Spanish Ministerio de Economía y Competitividad, by Xunta de Galicia CN2012/130 and 07MRU035291PR, by Ministerio del Medio Ambiente, Rural y Marino PSE-310000–2009–4 and by COST Action/UE COST-OC-2008–1-2124S

Growth hormone remodels the 3D-structure of the mitochondria of inflammatory macrophages and promotes metabolic reprogramming

IntroductionMacrophages are a heterogeneous population of innate immune cells that support tissue homeostasis through their involvement in tissue development and repair, and pathogen defense. Emerging data reveal that metabolism may control macrophage polarization and function and, conversely, phenotypic polarization may drive metabolic reprogramming.MethodsHere we use biochemical analysis, correlative cryogenic fluorescence microscopy and cryo-focused ion-beam scanning electron microscopy.ResultsWe demonstrate that growth hormone (GH) reprograms inflammatory GM-CSF-primed monocyte-derived macrophages (GM-MØ) by functioning as a metabolic modulator. We found that exogenous treatment of GM-MØ with recombinant human GH reduced glycolysis and lactate production to levels similar to those found in anti-inflammatory M-MØ. Moreover, GH treatment of GM-MØ augmented mitochondrial volume and altered mitochondrial dynamics, including the remodeling of the inner membrane to increase the density of cristae.ConclusionsOur data demonstrate that GH likely serves a modulatory role in the metabolism of inflammatory macrophages and suggest that metabolic reprogramming of macrophages should be considered as a new target to intervene in inflammatory diseases

Guía de saúde infantil : actividades preventivas e de promoción da saúde en pediatría de atención primaria

Se trata de una guía de salud infantil dirigida a los profesionales que trabajan en el ámbito de la asistencia sanitaria a los niños y adolescentes en atención primaria del Sistema Público de Salud de Galicia.Trátase dunha guía de saúde infantil dirixida aos profesionais que traballan no ámbito da asistencia sanitaria aos nenos e adolescentes na atención primaria do Sistema Público de Saúde de Galicia

Increased Diversity of the HLA-B40 Ligandome by the Presentation of Peptides Phosphorylated at Their Main Anchor Residue.

The massspectrometry proteomics data have been deposited at the Proteome-Xchange Consortium (http://proteomecentral.proteomexchange.org)via the PRIDE partner repository with the dataset identifier PXD000450and the PRIDE accession number 31118Human leukocyte antigen (HLA) class I molecules bind peptides derived from the intracellular degradation of endogenous proteins and present them to cytotoxic T lymphocytes, allowing the immune system to detect transformed or virally infected cells. It is known that HLA class I-associated peptides may harbor posttranslational modifications. In particular, phosphorylated ligands have raised much interest as potential targets for cancer immunotherapy. By combining affinity purification with high-resolution mass spectrometry, we identified more than 2000 unique ligands bound to HLA-B40. Sequence analysis revealed two major anchor motifs: aspartic or glutamic acid at peptide position 2 (P2) and methionine, phenylalanine, or aliphatic residues at the C terminus. The use of immobilized metal ion and TiO2 affinity chromatography allowed the characterization of 85 phosphorylated ligands. We further confirmed every sequence belonging to this subset by comparing its experimental MS2 spectrum with that obtained upon fragmentation of the corresponding synthetic peptide. Remarkably, three phospholigands lacked a canonical anchor residue at P2, containing phosphoserine instead. Binding assays showed that these peptides bound to HLA-B40 with high affinity. Together, our data demonstrate that the peptidome of a given HLA allotype can be broadened by the presentation of peptides with posttranslational modifications at major anchor positions. We suggest that ligands with phosphorylated residues at P2 might be optimal targets for T-cell-based cancer immunotherapy.S

Tándem : didáctica de la educación física

Resumen basado en el de la publicaciónSe evalúa qué emociones están relacionadas con las respuestas del alumnado ante una experiencia de aprendizaje autodidáctico y colectivo. Los resultados llevan a sugerir que para garantizar la participación activa del alumnado en este tipo de aprendizajes sería conveniente trabajar previamente afectos como la solidaridad y la confianza en su capacidad de aprendizaje autónomo.Biblioteca del Ministerio de Educación y Formación Profesional; Calle San Agustín, 5; 28014 Madrid; Tel. +34917748000; [email protected]

Método para la extracción de gluten nativo e hidrolizado

[ES] La presente invención se refiere a una composición y un método para la extracción de gluten de alimentos. La presente invención pennite la extracción de gluten de alimentos que han sido sometidos a diferentes tratamientos ténnicos y/o hidrolíticos y en los que las proteínas que componen el gluten pueden estar hidrolizadas y su estructura modificada. La extracción de gluten mediante esta invención es compatible con sistemas de enzimoinmunoensayo para la cuantificación de gluten como el ELISA Competitivo, así como con otras técnicas empleadas en el análisis[EN] The invention relates to a composition and a method for extracting gluten from food. The invention can be used to extract gluten from food that has been subjected to different thennal and/or hydrolytic treatments and in which the gluten-fonning proteins can be hydrolysed and the structure thereof modified. The extraction of gluten in accordance with this invention is compatible with enzyme irnmunoassay systems for gluten quantification, such as competitive ELISA, as well as with other techniques used in gluten analysis.Peer reviewedConsejo Superior de Investigaciones Científicas (España)A2 Solicitud de patentes sin informe sobre el estado de la técnic