23 research outputs found
Competitiveness in Urban Europe: research based, practice led
Metropolitan regions and cities are often coined as the ‘motors of the economy’. The performance of national economies – and even the EU in general – is increasingly dependent on the cumulative performance of metropolitan regions and/or cities. All around the world, cities are increasingly in competition with one another; interconnected in a network of criss-cross relations between firms and institutions. With respect to urban competitiveness, numerous activities of benchmarking and ‘best practises’ between cities exist. Many policies are based upon these evaluations leading to cherry-picking and the hasty copying of experiences from one specific urban context to another. A deeper understanding of the problems and structural mechanisms behind urban competitiveness is often lacking. This paper aims to analyse the competitiveness of European metropolitan regions via a comparative case study research, defining the main threats and challenges concerning the economic vitality of urban areas. It will be driven by the input of regions and cities with the aim to identify ‘best’ and ‘bad’ practices across Europe. In other words, we will set out the contours of a research framework on economic competitiveness that aims to bridge the gap between academic research and urban practices by means of a policy-driven research agenda. The competitiveness of five European regions will be discussed in more detail: Munich, Warsaw, Madrid, Bucharest and Stockholm. Based on roundtable discussions with stakeholders in these cities, the missing blanks in urban research will be defined. This paper will go beyond the ranking lists based solely on economic productivity figures by discussing cities’ competitiveness from an integral perspective. The underlying determinants of competitiveness (e.g. local economic sectoral structure, labour market) will be analysed to create a better understanding of the economic performance of cities. It is the aim of this study to make academic research on urban competitiveness applicable for urban practice by listing knowledge and research questions that are of interest for both researchers as well as urban practitioners.
Neighborhood-Based social capital and life satisfaction
In this study, we examine the relationship between neighborhood-based social capital and residents’ life satisfaction by considering resident heterogeneity. Using a database of the city of Rotterdam, The Netherlands, we find a small but significant positive association between neighborhood-based social capital and individual life satisfaction. However, we also find considerable differences among residents because neighborhood-based social capital is important mainly for people who are more likely to spend considerable time in the neighborhood or who are more neighborhood dependent (i.e. less-educated people, people who live on welfare, people with poor health, retired people, and those who are divorced or widowed). Our results confirm the importance of neighborhood-based social capital for residents’ life satisfaction in terms of both actual social contacts with neighbors and the perceived social cohesion within a neighborhood. At the same time, the importance of neighborhood-based social capital varies among different groups of residents. These findings have important implications for policy-makers
Spatial structure and subjective well-being in North-West Europe
This study examines the relationship between regions’ spatial organization and subjective well-being in North-West
Europe. Combining data on life satisfaction with data on the spatial structure of regions, we find that the degree of
polycentricism is positively associated and dispersion is negatively associated with life satisfaction. At the same time,
the results indicate that in more dispersed regions, people experience more positive effects of polycentric structures
than in more centralized regions, while residents of more urbanized polycentric regions report lower levels of life
satisfaction compared with residents of less urbanized polycentric regions. Likewise, the findings suggest that urban
residents living in polycentric regions are less satisfied compared with their rural counterparts
Spatial structure and subjective well-being in North-West Europe
This study examines the relationship between regions’ spatial organization and subjective well-being in North-West Europe. Combining data on life satisfaction with data on the spatial structure of regions, we find that the degree of polycentricism is positively associated and dispersion is negatively associated with life satisfaction. At the same time, the results indicate that in more dispersed regions, people experience more positive effects of polycentric structures than in more centralized regions, while residents of more urbanized polycentric regions report lower levels of life satisfaction compared with residents of less urbanized polycentric regions. Likewise, the findings suggest that urban residents living in polycentric regions are less satisfied compared with their rural counterparts
Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases.
For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient's data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe
Solving unsolved rare neurological diseases-a Solve-RD viewpoint.
Funder: Durch Princess Beatrix Muscle Fund Durch Speeren voor Spieren Muscle FundFunder: University of Tübingen Medical Faculty PATE programFunder: European Reference Network for Rare Neurological Diseases | 739510Funder: European Joint Program on Rare Diseases (EJP-RD COFUND-EJP) | 44140962
Twist exome capture allows for lower average sequence coverage in clinical exome sequencing
Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques
Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.
Funder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health); doi: https://doi.org/10.13039/100011272; Grant(s): 305444, 305444Funder: Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness); doi: https://doi.org/10.13039/501100003329Funder: Generalitat de Catalunya (Government of Catalonia); doi: https://doi.org/10.13039/501100002809Funder: EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj); doi: https://doi.org/10.13039/501100008530Funder: Instituto Nacional de Bioinformática ELIXIR Implementation Studies Centro de Excelencia Severo OchoaFunder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health)Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics
A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing
Purpose
Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned.
Methods
Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted.
Results
We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency).
Conclusion
The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock