The influence of structural inheritance and multiphase extension on rift development, the northern North Sea

The northern North Sea rift evolved through multiple rift phases within a highly heterogeneous crystalline basement. The geometry and evolution of syn‐rift depocentres during this multiphase evolution, and the mechanisms and extent to which they were influenced by pre‐existing structural heterogeneities remain elusive, particularly at the regional scale. Using an extensive database of borehole‐constrained 2D seismic reflection data, we examine how the physiography of the northern North Sea rift evolved throughout late Permian‐Early Triassic (RP1) and Late Jurassic‐Early Cretaceous (RP2) rift phases, and assess the influence of basement structures related to the Caledonian orogeny and subsequent Devonian extension. During RP1, the location of major depocentres, the Stord and East Shetland basins, was controlled by favorably oriented Devonian shear zones. RP2 shows a diminished influence from structural heterogeneities, activity localises along the Viking‐Sogn graben system and the East Shetland Basin, with negligible activity in the Stord Basin and Horda Platform. The Utsira High and the Devonian Lomre Shear Zone form the eastern barrier to rift activity during RP2. Towards the end of RP2, rift activity migrated northwards as extension related to opening of the proto‐North Atlantic becomes the dominant regional stress as rift activity in the northern North Sea decreases. Through documenting the evolving syn‐rift depocentres of the northern North Sea rift, we show how structural heterogeneities and prior rift phases influence regional rift physiography and kinematics, controlling the segmentation of depocentres, as well as the locations, styles and magnitude of fault activity and reactivation during subsequent events

The Building Blocks of Interoperability. A Multisite Analysis of Patient Demographic Attributes Available for Matching.

BackgroundPatient matching is a key barrier to achieving interoperability. Patient demographic elements must be consistently collected over time and region to be valuable elements for patient matching.ObjectivesWe sought to determine what patient demographic attributes are collected at multiple institutions in the United States and see how their availability changes over time and across clinical sites.MethodsWe compiled a list of 36 demographic elements that stakeholders previously identified as essential patient demographic attributes that should be collected for the purpose of linking patient records. We studied a convenience sample of 9 health care systems from geographically distinct sites around the country. We identified changes in the availability of individual patient demographic attributes over time and across clinical sites.ResultsSeveral attributes were consistently available over the study period (2005-2014) including last name (99.96%), first name (99.95%), date of birth (98.82%), gender/sex (99.73%), postal code (94.71%), and full street address (94.65%). Other attributes changed significantly from 2005-2014: Social security number (SSN) availability declined from 83.3% to 50.44% (p<0.0001). Email address availability increased from 8.94% up to 54% availability (p<0.0001). Work phone number increased from 20.61% to 52.33% (p<0.0001).ConclusionsOverall, first name, last name, date of birth, gender/sex and address were widely collected across institutional sites and over time. Availability of emerging attributes such as email and phone numbers are increasing while SSN use is declining. Understanding the relative availability of patient attributes can inform strategies for optimal matching in healthcare

Detection and Identification of Salmonella enterica, Escherichia coli, and Shigella spp. via PCR-ESI-MS: Isolate Testing and Analysis of Food Samples

An assay to identify the common food-borne pathogens Salmonella, Escherichia coli, Shigella, and Listeria monocytogenes was developed in collaboration with Ibis Biosciences (a division of Abbott Molecular) for the Plex-ID biosensor system, a platform that uses electrospray ionization mass spectroscopy (ESI-MS) to detect the base composition of short PCR amplicons. The new food-borne pathogen (FBP) plate has been experimentally designed using four gene segments for a total of eight amplicon targets. Initial work built a DNA base count database that contains more than 140 Salmonella enterica, 139 E. coli, 11 Shigella, and 36 Listeria patterns and 18 other Enterobacteriaceae organisms. This assay was tested to determine the scope of the assay\u27s ability to detect and differentiate the enteric pathogens and to improve the reference database associated with the assay. More than 800 bacterial isolates of S. enterica, E. coli, and Shigella species were analyzed. Overall, 100% of S. enterica, 99% of E. coli, and 73% of Shigella spp. were detected using this assay. The assay was also able to identify 30% of the S. enterica serovars to the serovar level. To further characterize the assay, spiked food matrices and food samples collected during regulatory field work were also studied. While analysis of preenrichment media was inconsistent, identification of S. enterica from selective enrichment media resulted in serovar-level identifications for 8 of 10 regulatory samples. The results of this study suggest that this high-throughput method may be useful in clinical and regulatory laboratories testing for these pathogens

Depth and latitudinal gradients of diversity in seamount benthic communities

Latitudinal and bathymetric species diversity gradients in the deep sea have been identified, but studies have rarely considered these gradients across hard substratum habitats, such as seamount and oceanic island margins. This study aimed to identify whether the current understanding of latitudinal and bathymetric gradients in α-diversity (species richness) apply to seamount ecosystems, as well as ascertaining whether identifiable trends were present in seamount β-diversity along a bathymetric gradient

Filling the data gaps: Transferring models from data-rich to data-poor deep-sea areas to support spatial management

Spatial management of the deep sea is challenging due to limited available data on the distribution of species and habitats to support decision making. In the well-studied North Atlantic, predictive models of species distribution and habitat suitability have been used to fill data gaps and support sustainable management. In the South Atlantic and other poorly studied regions, this is not possible due to a massive lack of data. In this study, we investigated whether models constructed in data-rich areas can be used to inform data-poor regions (with otherwise similar environmental conditions). We used a novel model transfer approach to identify to what extent a habitat suitability model for Desmophyllum pertusum reef, built in a data-rich basin (North Atlantic), could be transferred usefully to a data-poor basin (South Atlantic). The transferred model was built using the Maximum Entropy algorithm and constructed with 227 presence and 3064 pseudo-absence points, and 200 m resolution environmental grids. Performance in the transferred region was validated using an independent dataset of D. pertusum presences and absences, with assessments made using both threshold-dependent and -independent metrics. We found that a model for D. pertusum reef fitted to North Atlantic data transferred reasonably well to the South Atlantic basin, with an area under the curve of 0.70. Suitable habitat for D. pertusum reef was predicted on 20 of the assessed 27 features including seamounts. Nationally managed Marine Protected Areas provide significant protection for D. pertusum reef habitat in the region, affording full protection from bottom trawling to 14 of the 20 suitable features. In areas beyond national jurisdiction (ABNJ), we found four seamounts that provided suitable habitat for D. pertusum reef to be at least partially protected from bottom trawling, whilst two did not fall within fisheries closures. There are factors to consider when developing models for transfer including data resolution and predictor type. Nevertheless, the promising results of this application demonstrate that model transfer approaches stand to provide significant contributions to spatial planning processes through provision of new, best available data. This is particularly true for ABNJ and areas that have previously undergone little scientific exploration such as the global south

The development of a network for community-based obesity prevention: the CO-OPS Collaboration

Background: Community-based interventions are a promising approach and an important component of a comprehensive response to obesity. In this paper we describe the Collaboration of COmmunity-based Obesity Prevention Sites (CO-OPS Collaboration) in Australia as an example of a collaborative network to enhance the quality and quantity of obesity prevention action at the community level. The core aims of the CO-OPS Collaboration are to: identify and analyse the lessons learned from a range of community-based initiatives aimed at tackling obesity, and; to identify the elements that make community-based obesity prevention initiatives successful and share the knowledge gained with other communities.Methods: Key activities of the collaboration to date have included the development of a set of Best Practice Principles and knowledge translation and exchange activities to promote the application (or use) of evidence, evaluation and analysis in practice.Results: The establishment of the CO-OPS Collaboration is a significant step toward strengthening action in this area, by bringing together research, practice and policy expertise to promote best practice, high quality evaluation and knowledge translation and exchange. Future development of the network should include facilitation of furtherevidence generation and translation drawing from process, impact and outcome evaluation of existing communitybased interventions.Conclusions: The lessons presented in this paper may help other networks like CO-OPS as they emerge around the globe. It is important that networks integrate with each other and share the experience of creating these networks.<br /