Acute ingestion of beetroot bread increases endothelium-independent vasodilation and lowers diastolic blood pressure in healthy men: a randomized controlled trial

Dietary nitrate, from beetroot, has been reported to lower blood pressure (BP) by the sequential reduction of nitrate to nitrite and further to NO in the circulation. However, the impact of beetroot on microvascular vasodilation and arterial stiffness is unknown. In addition, beetroot is consumed by only 4.5% of the UK population, whereas bread is a staple component of the diet. Thus, we investigated the acute effects of beetroot bread (BB) on microvascular vasodilation, arterial stiffness, and BP in healthy participants. Twenty-three healthy men received 200 g bread containing 100 g beetroot (1.1 mmol nitrate) or 200 g control white bread (CB; 0 g beetroot, 0.01 mmol nitrate) in an acute, randomized, open-label, controlled crossover trial. The primary outcome was postprandial microvascular vasodilation measured by laser Doppler iontophoresis and the secondary outcomes were arterial stiffness measured by Pulse Wave Analysis and Velocity and ambulatory BP measured at regular intervals for a total period of 6 h. Plasma nitrate and nitrite were measured at regular intervals for a total period of 7 h. The incremental area under the curve (0-6 h after ingestion of bread) for endothelium-independent vasodilation was greater (P = 0.017) and lower for diastolic BP (DBP; P = 0.032) but not systolic (P = 0.99) BP after BB compared with CB. These effects occurred in conjunction with increases in plasma and urinary nitrate (P < 0.0001) and nitrite (P < 0.001). BB acutely increased endothelium-independent vasodilation and decreased DBP. Therefore, enriching bread with beetroot may be a suitable vehicle to increase intakes of cardioprotective beetroot in the diet and may provide new therapeutic perspectives in the management of hypertension.

Modelling signatures of pulsed magnetopause reconnection in cusp ion dispersion signatures seen at middle altitudes

It is shown that the open magnetosphere model can reproduce both the down-going and the up-going magnetosheath ions seen in the cusp and mantle regions by the Polar satellite at middle altitudes. ?he pass studied shows a series of discontinuities in the ion dispersion, most of which are shown to arise from pulses of magnetopause reconnection rate. A total of 9 pulses are detected in an interval estimated to be about 30 min long, giving a mean repetition period of about 3 min: they vary in length between 0.5 min and 3.5 min and are separated by periods of much slower reconnection of duration 1-3 min. One step is not as predicted for reconnection rate pulses but is explained in terms of compressive motions caused by a pulse of solar wind dynamic pressure. The reconnection site is found to be 16 +/- 3 R-E from the ionosphere along the separatrix field line, placing it at low latitudes on the dayside magnetopause.

The Met Office Unified Model Global Atmosphere 3.0/3.1 and JULES Global Land 3.0/3.1 configurations

We describe Global Atmosphere 3.0 (GA3.0): a configuration of the Met Office Unified Model (MetUM) developed for use across climate research and weather prediction activities. GA3.0 has been formulated by converging the development paths of the Met Office's weather and climate global atmospheric model components such that wherever possible, atmospheric processes are modelled or parametrized seamlessly across spatial resolutions and timescales. This unified development process will provide the Met Office and its collaborators with regular releases of a configuration that has been evaluated, and can hence be applied, over a variety of modelling régimes. We also describe Global Land 3.0 (GL3.0): a configuration of the JULES community land surface model developed for use with GA3.0.

The Climate-G testbed: towards large scale distributed data management for climate change

Climate-G is a large scale distributed testbed devoted to climate change research. It is an unfunded effort started in 2008 and involving a wide community both in Europe and US. The testbed is an interdisciplinary effort involving partners from several institutions and joining expertise in the field of climate change and computational science. Its main goal is to allow scientists carrying out geographical and cross-institutional data discovery, access, analysis, visualization and sharing of climate data. It represents an attempt to address, in a real environment, challenging data and metadata management issues. This paper presents a complete overview about the Climate-G testbed highlighting the most important results that have been achieved since the beginning of this project.

Ontology modeling for generation of clinical pathways

Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP) as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM) is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM) is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the behavior will occur. To overcome this weakness, a semiotic approach to generation of clinical pathway is introduced. The CP generated from SAM together with norms will enrich the knowledge representation of the domain through ontology modeling, which allows the recognition of human responsibilities and obligations and more importantly, the ultimate power of decision making in exceptional circumstances.

EDITOR'S CHOICE: REVIEW: Trait matching of flower visitors and crops predicts fruit set better than trait diversity

Understanding the relationships between trait diversity, species diversity and ecosystem functioning is essential for sustainable management. For functions comprising two trophic levels, trait matching between interacting partners should also drive functioning. However, the predictive ability of trait diversity and matching is unclear for most functions, particularly for crop pollination, where interacting partners did not necessarily co-evolve. World-wide, we collected data on traits of flower visitors and crops, visitation rates to crop flowers per insect species and fruit set in 469 fields of 33 crop systems. Through hierarchical mixed-effects models, we tested whether flower visitor trait diversity and/or trait matching between flower visitors and crops improve the prediction of crop fruit set (functioning) beyond flower visitor species diversity and abundance. Flower visitor trait diversity was positively related to fruit set, but surprisingly did not explain more variation than flower visitor species diversity. The best prediction of fruit set was obtained by matching traits of flower visitors (body size and mouthpart length) and crops (nectar accessibility of flowers) in addition to flower visitor abundance, species richness and species evenness. Fruit set increased with species richness, and more so in assemblages with high evenness, indicating that additional species of flower visitors contribute more to crop pollination when species abundances are similar. Synthesis and applications. Despite contrasting floral traits for crops world-wide, only the abundance of a few pollinator species is commonly managed for greater yield. Our results suggest that the identification and enhancement of pollinator species with traits matching those of the focal crop, as well as the enhancement of pollinator richness and evenness, will increase crop yield beyond current practices. Furthermore, we show that field practitioners can predict and manage agroecosystems for pollination services based on knowledge of just a few traits that are known for a wide range of flower visitor species.