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The timing of carbohydrate ingestion and how this influences net muscle glycogen utilization and fatigue has only been investigated in prolonged cycling. Past findings may not translate to running because each exercise mode is distinct both in the metabolic response to carbohydrate ingestion and in the practicalities of carbohydrate ingestion. To this end, a randomized, cross-over design was employed to contrast ingestion of the same sucrose dose either at frequent intervals (15 x 5 g every 5min) or at a late bolus (1 x 75 g after 75 min) during prolonged treadmill running to exhaustion in six well-trained runners (...O2max 61 ± 4 ml⋅kg-1⋅min-1). The muscle glycogen utilization rate was lower in every participant over the first 75 min of running (Δ 0.51 mmol⋅kg dm-1⋅min-1; 95% confidence interval [-0.02, 1.04] mmol⋅kg dm-1⋅min-1) and, subsequently, all were able to run for longer when carbohydrate had been ingested frequently from the start of exercise compared with when carbohydrate was ingested as a single bolus toward the end of exercise (105.6 ± 3.0 vs. 96.4 ± 5.0 min, respectively; Δ 9.3 min, 95% confidence interval [2.8, 15.8] min). A moderate positive correlation was apparent between the magnitude of glycogen sparing over the first 75min and the improvement in running capacity (r = .58), with no significant difference in muscle glycogen concentrations at the point of exhaustion. This study indicates that failure to ingest carbohydrates from the outset of prolonged running increases reliance on limited endogenous muscle glycogen stores--the ergolytic effects of which cannot be rectified by subsequent carbohydrate ingestion late in exercise. [ABSTRACT FROM AUTHOR]

The postsynaptic terminal of vertebrate excitatory synapses contains a highly conserved multiprotein complex that comprises neurotransmitter receptors, cell‐adhesion molecules, scaffold proteins and enzymes, which are essential for brain signalling and plasticity underlying behaviour. Increasingly, mutations in genes that encode postsynaptic proteins belonging to the PSD‐95 protein complex, continue to be identified in neurodevelopmental disorders (NDDs) such as autism spectrum disorder, intellectual disability and epilepsy. These disorders are highly heterogeneous, sharing genetic aetiology and comorbid cognitive and behavioural symptoms. Here, by using genetically engineered mice and innovative touchscreen‐based cognitive testing, we sought to investigate whether loss‐of‐function mutations in genes encoding key interactors of the PSD‐95 protein complex display shared phenotypes in associative learning, updating of learned associations and reaction times. Our genetic dissection of mice with loss‐of‐function mutations in Syngap1, Nlgn3, Dlgap1, Dlgap2 and Shank2 showed that distinct components of the PSD‐95 protein complex differentially regulate learning, cognitive flexibility and reaction times in cognitive processing. These data provide insights for understanding how human mutations in these genes lead to the manifestation of diverse and complex phenotypes in NDDs. [ABSTRACT FROM AUTHOR]

Rain-triggered lahars are a significant secondary hydrological and geomorphic hazard at volcanoes where unconsolidated pyroclastic material produced by explosive eruptions is exposed to intense rainfall, often occurring for years to decades after the initial eruptive activity. Previous studies have shown that secondary lahar initiation is a function of rainfall parameters, source material characteristics and time since eruptive activity. In this study, probabilistic rain-triggered lahar forecasting models are developed using the lahar occurrence and rainfall record of the Belham River valley at the Soufrière Hills volcano (SHV), Montserrat, collected between April 2010 and April 2012. In addition to the use of peak rainfall intensity (PRI) as a base forecasting parameter, considerations for the effects of rainfall seasonality and catchment evolution upon the initiation of raintriggered lahars and the predictability of lahar generation are also incorporated into these models. Lahar probability increases with peak 1 h rainfall intensity throughout the 2-year dataset and is higher under given rainfall conditions in year 1 than year 2. The probability of lahars is also enhanced during the wet season, when large-scale synoptic weather systems (including tropical cyclones) are more common and antecedent rainfall and thus levels of deposit saturation are typically increased. The incorporation of antecedent conditions and catchment evolution into logistic-regression-based raintriggered lahar probability estimation models is shown to enhance model performance and displays the potential for successful real-time prediction of lahars, even in areas featuring strongly seasonal climates and temporal catchment recovery. [ABSTRACT FROM AUTHOR]

J. Myrick Howard Buying Time for Heritage: How to Save an Endangered Historic Property Preservation North Carolina Chapel Hill: University of North Carolina Press, 2007. 16o pages. 64 color and [...]