Review of current Severe Accident Management (SAM) approaches for Nuclear Power Plants in Europe

The Fukushima accidents highlighted that both the in-depth understanding of such sequences and the development or improvement of adequate Severe Accident Management (SAM) measures are essential in order to further increase the safety of the nuclear power plants operated in Europe. To support this effort, the CESAM (Code for European Severe Accident Management) R&D project, coordinated by GRS, started in April 2013 for 4 years in the 7th EC Framework Programme of research and development of the European Commission. It gathers 18 partners from 12 countries: IRSN, AREVA NP SAS and EDF (France), GRS, KIT, USTUTT and RUB (Germany), CIEMAT (Spain), ENEA (Italy), VUJE and IVS (Slovakia), LEI (Lithuania), NUBIKI (Hungary), INRNE (Bulgaria), JSI (Slovenia), VTT (Finland), PSI (Switzerland), BARC (India) plus the European Commission Joint Research Center (JRC). The CESAM project focuses on the improvement of the ASTEC (Accident Source Term Evaluation Code) computer code. ASTEC,, jointly developed by IRSN and GRS, is considered as the European reference code since it capitalizes knowledge from the European R&D on the domain. The project aims at its enhancement and extension for use in severe accident management (SAM) analysis of the nuclear power plants (NPP) of Generation II-III presently under operation or foreseen in near future in Europe, spent fuel pools included. In the frame of the CESAM project one of the tasks consisted in the preparation of a report providing an overview of the Severe Accident Management (SAM) approaches in European Nuclear Power Plants to serve as a basis for further ASTEC improvements. This report draws on the experience in several countries from introducing SAMGs and on substantial information that has become available within the EU “stress test”. To disseminate this information to a broader audience, the initial CESAM report has been revised to include only public available information. This work has been done with the agreement and in collaboration with all the CESAM project partners. The result of this work is presented here.JRC.F.5-Nuclear Reactor Safety Assessmen

Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information

Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved understanding of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, interrogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain transcriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/

Famílies botàniques de plantes medicinals

Facultat de Farmàcia, Universitat de Barcelona. Ensenyament: Grau de Farmàcia, Assignatura: Botànica Farmacèutica, Curs: 2013-2014, Coordinadors: Joan Simon, Cèsar Blanché i Maria Bosch.Els materials que aquí es presenten són els recull de 175 treballs d’una família botànica d’interès medicinal realitzats de manera individual. Els treballs han estat realitzat per la totalitat dels estudiants dels grups M-2 i M-3 de l’assignatura Botànica Farmacèutica durant els mesos d’abril i maig del curs 2013-14. Tots els treballs s’han dut a terme a través de la plataforma de GoogleDocs i han estat tutoritzats pel professor de l’assignatura i revisats i finalment co-avaluats entre els propis estudiants. L’objectiu principal de l’activitat ha estat fomentar l’aprenentatge autònom i col·laboratiu en Botànica farmacèutica

Joint Observation of the Galactic Center with MAGIC and CTA-LST-1

MAGIC is a system of two Imaging Atmospheric Cherenkov Telescopes (IACTs), designed to detect very-high-energy gamma rays, and is operating in stereoscopic mode since 2009 at the Observatorio del Roque de Los Muchachos in La Palma, Spain. In 2018, the prototype IACT of the Large-Sized Telescope (LST-1) for the Cherenkov Telescope Array, a next-generation ground-based gamma-ray observatory, was inaugurated at the same site, at a distance of approximately 100 meters from the MAGIC telescopes. Using joint observations between MAGIC and LST-1, we developed a dedicated analysis pipeline and established the threefold telescope system via software, achieving the highest sensitivity in the northern hemisphere. Based on this enhanced performance, MAGIC and LST-1 have been jointly and regularly observing the Galactic Center, a region of paramount importance and complexity for IACTs. In particular, the gamma-ray emission from the dynamical center of the Milky Way is under debate. Although previous measurements suggested that a supermassive black hole Sagittarius A* plays a primary role, its radiation mechanism remains unclear, mainly due to limited angular resolution and sensitivity. The enhanced sensitivity in our novel approach is thus expected to provide new insights into the question. We here present the current status of the data analysis for the Galactic Center joint MAGIC and LST-1 observations

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. Methods We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Findings Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). Interpretation These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. Funding The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

Identification of candidate Parkinson disease genes by integrating genome-wide association study, expression, and epigenetic data sets

Importance Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. Objective To investigate what genes and genomic processes underlie the risk of sporadic PD. Design and Setting This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. Main Outcomes and Measures It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role. Results Gene-level analysis of expression revealed 5 genes (WDR6 [OMIM 606031], CD38 [OMIM 107270], GPNMB [OMIM 604368], RAB29 [OMIM 603949], and TMEM163 [OMIM 618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (ZRANB3 [OMIM 615655], PCGF3 [OMIM 617543], NEK1 [OMIM 604588], NUPL2 [NCBI 11097], GALC [OMIM 606890], and CTSB [OMIM 116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen. TMEM163 and ZRANB3 were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance. Conclusions and Relevance Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies

Severe Accident Context Quantification for Long-Term Station Blackout in Boiling Water Reactor Nuclear Power Plants

The realistic study of dynamic accident context is an invaluable tool to address the uncertainties and their impact on safety assessment and management. The capacities of the Performance Evaluation of Teamwork (PET) procedure for dynamic context quantification and determination of alternatives, coordination and monitoring of human performance and decision-making are discussed in this paper. The procedure is based on a thorough description of symptoms during the accident scenario progressions (timelines) with the use of thermo-hydraulic model and severe accident codes (MELCOR and MAAP). The opportunities of PET procedure for context quantification are exemplified for the long-term station blackout (LT SBO) accident scenario at Fukushima Daiichi NPP#1 and an hypothetic unmitigated LT SBO at Peach Bottom #1 Boiling Water Reactor Nuclear Power Plants. The context quantification of these LT SBO scenarios is based on the IAEA Fukushima Daiichi accident report, "State-of-the-Art Reactor Consequence Analysis" and thermo-hydraulic calculations made by using MAAP code at the EC Joint Research Centre.JRC.G.I.4-Nuclear Reactor Safety and Emergency Preparednes

Analysis of LFW & LBLOCA scenarios for a PWR 900 MWe NPP using the integral computer codes ASTEC2.0 and MAAP4.0.8

The present work has been carried out in the context of the development and validation of a set of “reference” ASTEC input decks for the main generic types of nuclear power plants (NPPs) in Europe; in the CESAM (Code for European Severe Accident Management) project, where JRC is contributing in several of the six working packages (WPs) in which it is divided. The JRC team have used the PWR900 model (delivered by IRSN to CESAM partners in February 2014) to simulate two accidents, a LBLOCA (Large-Break, Loss-Of-Coolant Accident) and a LFW (Loss of Feed Water), in order to confirm the ASTEC v2.0r3 capabilities. The assessment was done comparing the evolutions of these accidents vs. MAAP 4.0.8 code. To perform such kind of comparison, JRC developed a specific MAAP4 input deck for a pressurized water reactor (PWR) of 900 MWe. This input deck is based on a generic MAAP4 input deck, which has been adapted to correspond to the best extent possible to the ASTEC V2.0r3 PWR900 model. The comparisons focus only on in-vessel thermal hydraulics phenomena, core degradation and corium behaviour in the lower head. The calculations stop as soon as the reactor pressure vessel fails. The comparisons of the main thermo-hydraulic variables between the two code results are detailed in this paper and are satisfactory overall.JRC.F.5-Nuclear Reactor Safety Assessmen

Anti‐dopamine D2 receptor antibodies in chronic tic disorders

Aim: To investigate the association between circulating anti-dopamine D2 receptor (D2R) autoantibodies and the exacerbation of tics in children with chronic tic disorders (CTDs). Method: One hundred and thirty-seven children with CTDs (108 males, 29 females; mean age [SD] 10y 0mo [2y 7mo], range 4-16y) were recruited over 18 months. Patients were assessed at baseline, at tic exacerbation, and at 2 months after exacerbation. Serum anti-D2R antibodies were evaluated using a cell-based assay and blinded immunofluorescence microscopy scoring was performed by two raters. The association between visit type and presence of anti-D2R antibodies was measured with McNemar's test and repeated-measure logistic regression models, adjusting for potential demographic and clinical confounders. Results: At exacerbation, 11 (8%) participants became anti-D2R-positive ('early peri-exacerbation seroconverters'), and nine (6.6%) became anti-D2R-positive at post-exacerbation ('late peri-exacerbation seroconverters'). The anti-D2R antibodies were significantly associated with exacerbations when compared to baseline (McNemar's odds ratio=11, p=0.003) and conditional logistic regression confirmed this association (Z=3.49, p<0.001) after adjustment for demographic and clinical data and use of psychotropic drugs. Interpretation: There is a potential association between immune mechanisms and the severity course of tics in adolescents with CTDs