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Póster presentado en Kohaference 2019, tercer encuentro de la Comunidad Koha en España, organizado y presentado por la Universidad de Cádi

Dossier y guía de autoayuda para la mejora del malestar docente

Este trabajo tiene como objetivo dar una panorámica sobre el burnout en el ámbito docente y aportar herramientas para la prevención y afrontamiento de situaciones de estres laboral del profesorado, así como el desarrollo de altos niveles de resieliencia, todo desde un enfoque multidisciplinar.127 p

ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization

BackgroundWhole-exome sequencing (WES) and whole-genome sequencing (WGS) have become indispensable tools to solve rare Mendelian genetic conditions. Nevertheless, there is still an urgent need for sensitive, fast algorithms to maximise WES/WGS diagnostic yield in rare disease patients. Most tools devoted to this aim take advantage of patient phenotype information for prioritization of genomic data, although are often limited by incomplete gene-phenotype knowledge stored in biomedical databases and a lack of proper benchmarking on real-world patient cohorts.MethodsWe developed ClinPrior, a novel method for the analysis of WES/WGS data that ranks candidate causal variants based on the patient's standardized phenotypic features (in Human Phenotype Ontology (HPO) terms). The algorithm propagates the data through an interactome network-based prioritization approach. This algorithm was thoroughly benchmarked using a synthetic patient cohort and was subsequently tested on a heterogeneous prospective, real-world series of 135 families affected by hereditary spastic paraplegia (HSP) and/or cerebellar ataxia (CA).ResultsClinPrior successfully identified causative variants achieving a final positive diagnostic yield of 70% in our real-world cohort. This includes 10 novel candidate genes not previously associated with disease, 7 of which were functionally validated within this project. We used the knowledge generated by ClinPrior to create a specific interactome for HSP/CA disorders thus enabling future diagnoses as well as the discovery of novel disease genes.ConclusionsClinPrior is an algorithm that uses standardized phenotype information and interactome data to improve clinical genomic diagnosis. It helps in identifying atypical cases and efficiently predicts novel disease-causing genes. This leads to increasing diagnostic yield, shortening of the diagnostic Odysseys and advancing our understanding of human illnesses

Diagnosis of Genetic White Matter Disorders by Singleton Whole-Exome and Genome Sequencing Using Interactome-Driven Prioritization

Background and Objectives Genetic white matter disorders (GWMD) are of heterogeneous origin, with >100 causal genes identified to date. Classic targeted approaches achieve a molecular diagnosis in only half of all patients. We aimed to determine the clinical utility of singleton whole-exome sequencing and whole-genome sequencing (sWES-WGS) interpreted with a phenotype- and interactome-driven prioritization algorithm to diagnose GWMD while identifying novel phenotypes and candidate genes. Methods A case series of patients of all ages with undiagnosed GWMD despite extensive standard-of-care paraclinical studies were recruited between April 2017 and December 2019 in a collaborative study at the Bellvitge Biomedical Research Institute (IDIBELL) and neurology units of tertiary Spanish hospitals. We ran sWES and WGS and applied our interactome-prioritization algorithm based on the network expansion of a seed group of GWMD-related genes derived from the Human Phenotype Ontology terms of each patient. Results We evaluated 126 patients (101 children and 25 adults) with ages ranging from 1 month to 74 years. We obtained a first molecular diagnosis by singleton WES in 59% of cases, which increased to 68% after annual reanalysis, and reached 72% after WGS was performed in 16 of the remaining negative cases. We identified variants in 57 different genes among 91 diagnosed cases, with the most frequent being RNASEH2B, EIF2B5, POLR3A, and PLP1, and a dual diagnosis underlying complex phenotypes in 6 families, underscoring the importance of genomic analysis to solve these cases. We discovered 9 candidate genes causing novel diseases and propose additional putative novel candidate genes for yet-to-be discovered GWMD. Discussion Our strategy enables a high diagnostic yield and is a good alternative to trio WES/WGS for GWMD. It shortens the time to diagnosis compared to the classical targeted approach, thus optimizing appropriate management. Furthermore, the interactome-driven prioritization pipeline enables the discovery of novel disease-causing genes and phenotypes, and predicts novel putative candidate genes, shedding light on etiopathogenic mechanisms that are pivotal for myelin generation and maintenance

Healthcare workers hospitalized due to COVID-19 have no higher risk of death than general population. Data from the Spanish SEMI-COVID-19 Registry

Aim To determine whether healthcare workers (HCW) hospitalized in Spain due to COVID-19 have a worse prognosis than non-healthcare workers (NHCW). Methods Observational cohort study based on the SEMI-COVID-19 Registry, a nationwide registry that collects sociodemographic, clinical, laboratory, and treatment data on patients hospitalised with COVID-19 in Spain. Patients aged 20-65 years were selected. A multivariate logistic regression model was performed to identify factors associated with mortality. Results As of 22 May 2020, 4393 patients were included, of whom 419 (9.5%) were HCW. Median (interquartile range) age of HCW was 52 (15) years and 62.4% were women. Prevalence of comorbidities and severe radiological findings upon admission were less frequent in HCW. There were no difference in need of respiratory support and admission to intensive care unit, but occurrence of sepsis and in-hospital mortality was lower in HCW (1.7% vs. 3.9%; p = 0.024 and 0.7% vs. 4.8%; p<0.001 respectively). Age, male sex and comorbidity, were independently associated with higher in-hospital mortality and healthcare working with lower mortality (OR 0.211, 95%CI 0.067-0.667, p = 0.008). 30-days survival was higher in HCW (0.968 vs. 0.851 p<0.001). Conclusions Hospitalized COVID-19 HCW had fewer comorbidities and a better prognosis than NHCW. Our results suggest that professional exposure to COVID-19 in HCW does not carry more clinical severity nor mortality

Predictive Power of the "Trigger Tool" for the detection of adverse events in general surgery: a multicenter observational validation study

Background In spite of the global implementation of standardized surgical safety checklists and evidence-based practices, general surgery remains associated with a high residual risk of preventable perioperative complications and adverse events. This study was designed to validate the hypothesis that a new “Trigger Tool” represents a sensitive predictor of adverse events in general surgery. Methods An observational multicenter validation study was performed among 31 hospitals in Spain. The previously described “Trigger Tool” based on 40 specific triggers was applied to validate the predictive power of predicting adverse events in the perioperative care of surgical patients. A prediction model was used by means of a binary logistic regression analysis. Results The prevalence of adverse events among a total of 1,132 surgical cases included in this study was 31.53%. The “Trigger Tool” had a sensitivity and specificity of 86.27% and 79.55% respectively for predicting these adverse events. A total of 12 selected triggers of overall 40 triggers were identified for optimizing the predictive power of the “Trigger Tool”. Conclusions The “Trigger Tool” has a high predictive capacity for predicting adverse events in surgical procedures. We recommend a revision of the original 40 triggers to 12 selected triggers to optimize the predictive power of this tool, which will have to be validated in future studies

A regulated deficit irrigation strategy for hedgerow olive orchards with high plant density

Background & Aims There is not a consensus on the best irrigation approach for super-high density (SHD) olive orchards. Our aim was to design and test a regulated deficit irrigation (RDI) strategy for a sustainable balance between water saving, tree vigour and oil production. Methods We tested our RDI strategy for 3 years in an ‘Arbequina’ orchard with 1,667 trees ha−1. Two levels of irrigation reduction were applied, 60RDI and 30RDI, scaled to replacing 60 % and 30 %, respectively, of the of irrigation needs (IN). We also had a full irrigation (FI) treatment as control, with IN totalling 4,701 m3 ha−1 Results The 30RDI treatment showed the best balance between water saving, tree vigour and oil production. With a yearly irrigation amount (IA) of 1,366 m3 ha−1, which meant 72 % water saving as compared to FI, the reduction in oil yield was 26 % only. Conclusions Our results, together with recent knowledge on the effect of water stress on fruit development, allowed us to suggest a potentially improved RDI strategy for which a total IA of ca. 2,100 m3 ha−1 was calculated. Both some management details and the benefits of this suggested RDI strategy are still to be tested

Atlas de las praderas marinas de España

Knowledge of the distribution and extent of seagrass habitats is currently the basis of management and conservation policies of the coastal zones in most European countries. This basic information is being requested through European directives for the establishment of monitoring programmes and the implementation of specific actions to preserve the marine environment. In addition, this information is crucial for the quantification of the ecological importance usually attributed to seagrass habitats due to, for instance, their involvement in biogeochemical cycles, marine biodiversity and quality of coastal waters or global carbon budgets. The seagrass atlas of Spain represents a huge collective effort performed by 84 authors across 30 Spanish institutions largely involved in the scientific research, management and conservation of seagrass habitats during the last three decades. They have contributed to the availability of the most precise and realistic seagrass maps for each region of the Spanish coast which have been integrated in a GIS to obtain the distribution and area of each seagrass species. Most of this information has independently originated at a regional level by regional governments, universities and public research organisations, which explain the elevated heterogeneity in criteria, scales, methods and objectives of the available information. On this basis, seagrass habitats in Spain occupy a total surface of 1,541,63 km2, 89% of which is concentrated in the Mediterranean regions; the rest is present in sheltered estuarine areas of the Atlantic peninsular regions and in the open coastal waters of the Canary Islands, which represents 50% of the Atlantic meadows. Of this surface, 71.5% corresponds to Posidonia oceanica, 19.5% to Cymodocea nodosa, 3.1% to Zostera noltii (=Nanozostera noltii), 0.3% to Zostera marina and 1.2% to Halophila decipiens. Species distribution maps are presented (including Ruppia spp.), together with maps of the main impacts and pressures that has affected or threatened their conservation status, as well as the management tools established for their protection and conservation. Despite this considerable effort, and the fact that Spain has mapped wide shelf areas, the information available is still incomplete and with weak precision in many regions, which will require an investment of major effort in the near future to complete the whole picture and respond to demands of EU directives