17 research outputs found
Updates in Rhea - an expert curated resource of biochemical reactions.
Rhea (http://www.rhea-db.org) is a comprehensive and non-redundant resource of expert-curated biochemical reactions designed for the functional annotation of enzymes and the description of metabolic networks. Rhea describes enzyme-catalyzed reactions covering the IUBMB Enzyme Nomenclature list as well as additional reactions, including spontaneously occurring reactions, using entities from the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Here we describe developments in Rhea since our last report in the database issue of Nucleic Acids Research. These include the first implementation of a simple hierarchical classification of reactions, improved coverage of the IUBMB Enzyme Nomenclature list and additional reactions through continuing expert curation, and the development of a new website to serve this improved dataset
Visual parameter optimisation for biomedical image processing
Background: Biomedical image processing methods require users to optimise input parameters to ensure high quality
output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple
input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships
between input and output.
Results: We present a visualisation method that transforms users’ ability to understand algorithm behaviour by
integrating input and output, and by supporting exploration of their relationships. We discuss its application to a
colour deconvolution technique for stained histology images and show how it enabled a domain expert to
identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify
deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying
assumption about the algorithm.
Conclusions: The visualisation method presented here provides analysis capability for multiple inputs and outputs
in biomedical image processing that is not supported by previous analysis software. The analysis supported by our
method is not feasible with conventional trial-and-error approaches
Increase in serotype 19A prevalence and amoxicillin non-susceptibility among paediatric Streptococcus pneumoniae isolates from middle ear fluid in a passive laboratory-based surveillance in Spain, 1997-2009
BACKGROUND: Conjugate vaccines, such as the 7-valent conjugate vaccine (PCV7), alter serotype nasopharyngeal carriage, potentially increasing cases of otitis media by non-vaccine serotypes. METHODS: All paediatric middle ear fluid (MEF) isolates received in the Spanish Reference Laboratory for Pneumococci through a passive, laboratory-based surveillance system from January 1997 to June 2009 were analysed. Data from 1997 to 2000 were pooled as pre-vaccination period. Trends over time were explored by linear regression analysis. RESULTS: A total of 2,077 isolates were analysed: 855 belonging to PCV7 serotypes, 466 to serotype 19A, 215 to serotype 3, 89 to serotype 6A and 452 to other serotypes ( 35% isolates) since PCV7 strains represented < 11% of total clinical isolates. CONCLUSIONS: In contrast to reports on invasive pneumococcal strains, in MEF isolates the reduction in the prevalence of PCV7 serotypes was not associated with decreases in penicillin/erythromycin non-susceptibility. The high prevalence of serotype 19A among paediatric MEF isolates and the amoxicillin non-susceptibility found in this serotype are worrisome since amoxicillin is the most common antibiotic used in the treatment of acute otitis media. These data suggest that non-PCV7 serotypes (mainly serotype 19A followed by serotypes 3 and 6A) are important etiological agents of acute otitis media and support the added value of the broader coverage of the new 13-valent conjugate vaccine.This study was supported in part by an unrestricted grant from Pfizer S.A., Madrid, Spain and PRISM-AG, Madrid, Spain. O.R. belongs to the Spanish Network for the Research in Infectious Diseases (REIPI).S
Grand Challenges in global eye health: a global prioritisation process using Delphi method
Background
We undertook a Grand Challenges in Global Eye Health prioritisation exercise to identify the key issues that must be addressed to improve eye health in the context of an ageing population, to eliminate persistent inequities in health-care access, and to mitigate widespread resource limitations.
Methods
Drawing on methods used in previous Grand Challenges studies, we used a multi-step recruitment strategy to assemble a diverse panel of individuals from a range of disciplines relevant to global eye health from all regions globally to participate in a three-round, online, Delphi-like, prioritisation process to nominate and rank challenges in global eye health. Through this process, we developed both global and regional priority lists.
Findings
Between Sept 1 and Dec 12, 2019, 470 individuals complete round 1 of the process, of whom 336 completed all three rounds (round 2 between Feb 26 and March 18, 2020, and round 3 between April 2 and April 25, 2020) 156 (46%) of 336 were women, 180 (54%) were men. The proportion of participants who worked in each region ranged from 104 (31%) in sub-Saharan Africa to 21 (6%) in central Europe, eastern Europe, and in central Asia. Of 85 unique challenges identified after round 1, 16 challenges were prioritised at the global level; six focused on detection and treatment of conditions (cataract, refractive error, glaucoma, diabetic retinopathy, services for children and screening for early detection), two focused on addressing shortages in human resource capacity, five on other health service and policy factors (including strengthening policies, integration, health information systems, and budget allocation), and three on improving access to care and promoting equity.
Interpretation
This list of Grand Challenges serves as a starting point for immediate action by funders to guide investment in research and innovation in eye health. It challenges researchers, clinicians, and policy makers to build collaborations to address specific challenge