Life Reusing Posidonia

Life Reusing Posidonia es un proyecto de Adaptación al Cambio Climático promovido por el Instituto Balear de la Vivienda (IBAVI) y la DG de Energía y Cambio Climático de las Islas Baleares, financiado por el programa europeo LIFE + en la categoría de Gobernanza Ambiental. El objetivo es ofrecer datos contrastados a las administraciones competentes para mejorar la habitabilidad de las viviendas y reducir los efectos colaterales del sector de la edificación.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

14 Habitatges de protecció pública a Sant Ferran (Formentera)

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A log-ratio biplot approach for exploring genetic relatedness based on identity by state

The detection of cryptic relatedness in large population-based cohorts is of great importance in genome research. The usual approach for detecting closely related individuals is to plot allele sharing statistics, based on identity-by-state or identity-by-descent, in a two-dimensional scatterplot. This approach ignores that allele sharing data across individuals has in reality a higher dimensionality, and neither regards the compositional nature of the underlying counts of shared genotypes. In this paper we develop biplot methodology based on log-ratio principal component analysis that overcomes these restrictions. This leads to entirely new graphics that are essentially useful for exploring relatedness in genetic databases from homogeneous populations. The proposed method can be applied in an iterative manner, acting as a looking glass for more remote relationships that are harder to classify. Datasets from the 1,000 Genomes Project and the Genomes For Life-GCAT Project are used to illustrate the proposed method. The discriminatory power of the log-ratio biplot approach is compared with the classical plots in a simulation study. In a non-inbred homogeneous population the classification rate of the log-ratio principal component approach outperforms the classical graphics across the whole allele frequency spectrum, using only identity by state. In these circumstances, simulations show that with 35,000 independent bi-allelic variants, log-ratio principal component analysis, combined with discriminant analysis, can correctly classify relationships up to and including the fourth degreePostprint (published version

An Eight-Gene Blood Expression Profile Predicts the Response to Infliximab in Rheumatoid Arthritis

BACKGROUND: TNF alpha blockade agents like infliximab are actually the treatment of choice for those rheumatoid arthritis (RA) patients who fail standard therapy. However, a considerable percentage of anti-TNF alpha treated patients do not show a significant clinical response. Given that new therapies for treatment of RA have been recently approved, there is a pressing need to find a system that reliably predicts treatment response. We hypothesized that the analysis of whole blood gene expression profiles of RA patients could be used to build a robust predictor to infliximab therapy. METHODS AND FINDINGS: We performed microarray gene expression analysis on whole blood RNA samples from RA patients starting infliximab therapy (n = 44). The clinical response to infliximab was determined at week 14 using the EULAR criteria. Blood cell populations were determined using flow cytometry at baseline, week 2 and week 14 of treatment. Using complete cross-validation and repeated random sampling we identified a robust 8-gene predictor model (96.6% Leave One Out prediction accuracy, P = 0.0001). Applying this model to an independent validation set of RA patients, we estimated an 85.7% prediction accuracy (75-100%, 95% CI). In parallel, we also observed a significantly higher number of CD4+CD25+ cells (i.e. regulatory T cells) in the responder group compared to the non responder group at baseline (P = 0.0009). CONCLUSIONS: The present 8-gene model obtained from whole blood expression efficiently predicts response to infliximab in RA patients. The application of the present system in the clinical setting could assist the clinician in the selection of the optimal treatment strategy in RA

Bacterial Taxa Associated with High Adherence to Mediterranean Diet in a Spanish Population

The Mediterranean diet (MD) is recognised as one of the healthiest diets worldwide and is associated with the prevention of cardiovascular and metabolic diseases, among others. Dietary habits are considered one of the strongest modulators of the gut microbiota, which seems to play a significant role in the health and disease of the host. The purpose of the present study was to evaluate interactive associations between gut microbiota composition and habitual dietary intake in 360 Spanish adults of the Obekit cohort (normal weight, overweight and obese subjects). Dietary intake and adherence to the MD tests together with faecal samples were collected from each subject. Faecal 16S rRNA sequencing was performed and checked against the dietary habits. MetagenomeSeq was the statistical tool applied to analyse at the species taxonomic level. Results from this study confirm that a strong adherence to the MD increases the population of some beneficial bacteria, improving microbiota status towards a healthier pattern. Bifidobacterium animalis is the species with the strongest association with the MD. One of the highlights is the positive association between several SCFA-producing bacteria and high adherence to the MD. In conclusion, this study shows that MD, fibre, legumes, vegetables, fruit and nuts intakes are associated with an increase in butyrate-producing taxa such as Roseburia faecis, Ruminococcus bromii and Oscillospira (Flavonifractor) plautii

Association of the Gut Microbiota with the Host's Health through an Analysis of Biochemical Markers, Dietary Estimation, and Microbial Composition

This research was funded by Centro Tecnológico para el Desarrollo Industrial (CDTI) through the program Consorcio de Investigación Empresarial Nacional (Programa CIEN, BIOFOOD Project) and by CIBERobn (Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y Nutrición (CB12/03/30002).This study aims to analyze the relationship between gut microbiota composition and health parameters through specific biochemical markers and food consumption patterns in the Spanish population. This research includes 60 Spanish adults aged 47.3 ± 11.2 years old. Biochemical and anthropometric measurements, and a self-referred dietary survey (food frequency questionnaire), were analyzed and compared with the participant's gut microbiota composition analyzed by 16s rDNA sequencing. Several bacterial strains differed significantly with the biochemical markers analyzed, suggesting an involvement in the participant's metabolic health. Lower levels of Lactobacillaceae and Oscillospiraceae and an increase in Pasteurellaceae, Phascolarctobacterium, and Haemophilus were observed in individuals with higher AST levels. Higher levels of the Christensenellaceae and a decrease in Peptococcaceae were associated with higher levels of HDL-c. High levels of Phascolarctobacterium and Peptococcus and low levels of Butyricicoccus were found in individuals with higher insulin levels. This study also identified associations between bacteria and specific food groups, such as an increase in lactic acid bacteria with the consumption of fermented dairy products or an increase in Verrucomicrobiaceae with the consumption of olive oil. In conclusion, this study reinforces the idea that specific food groups can favorably modulate gut microbiota composition and have an impact on host's health

Development of a predictor for human brain tumors based on gene expression values obtained from two types of microarray technologies

Development of molecular diagnostics that can reliably differentiate amongst different subtypes of brain tumors is an important unmet clinical need in postgenomics medicine and clinical oncology. A simple linear formula derived from gene expression values of four genes (GFAP, PTPRZ1, GPM6B, and PRELP) measured from cDNA microarrays (n=35) have distinguished glioblastoma and meningioma cases in a previous study. We herein extend this work further and report that the above predictor formula showed its robustness when applied to Affymetrix microarray data acquired prospectively in our laboratory (n=80) as well as publicly available data (n=98). Importantly, GFAP and GPM6B were both retained as being significant in the predictive model upon using the Affymetrix data obtained in our laboratory, whereas the other two predictor genes were SFRP2 and SLC6A2. These results collectively indicate the importance of the expression values of GFAP and GPM6B genes sampled from the two types of microarray technologies tested. The high prediction accuracy obtained in these instances demonstrates the robustness of the predictors across microarray platforms used. This result would require further validation with a larger population of meningioma and glioblastoma cases. At any rate, this study paves the way for further application of gene signatures to more stringent biopsy discrimination challenges. © 2010, Mary Ann Liebert, Inc.This work was funded by the EU-funded grants eTUMOUR (FP6-2002-LIFESCIHEALTH503094),HealthAgents (IST-2004-27214) and the Spanish grant MEDIVO2 (SAF 2005-03650). CIBER-BNN is an initiative of ‘‘Instituto de Salud Carlos III’’ (ISCIII, Spain).Peer Reviewe

Els noms d'aucells recomanats en l'àmbit balear

Els noms d’aucells recomanats en l’àmbit balear. El present article inclou la llista de noms d’aucells d’ús recomanat a l’àmbit balear, elaborat per ornitòlegs de totes les illes, amb la supervisió de la Universitat de les Illes Balears, i descriu els objectius i el procés amb els quals ha estat elaborada.Recommended names of birds in the Balearic context. This article includes the list of recommended bird names for use in the Balearic context, developed by ornithologists from all the islands, under the supervision of the University of the Balearic Islands, and describes the objectives and the process which led to their determination