Is the link from working memory to analogy causal? no analogy improvements following working memory training gains

Analogical reasoning has been hypothesized to critically depend upon working memory through correlational data [1], but less work has tested this relationship through experimental manipulation [2]. An opportunity for examining the connection between working memory and analogical reasoning has emerged from the growing, although somewhat controversial, body of literature suggests complex working memory training can sometimes lead to working memory improvements that transfer to novel working memory tasks. This study investigated whether working memory improvements, if replicated, would increase analogical reasoning ability. We assessed participants' performance on verbal and visual analogy tasks after a complex working memory training program incorporating verbal and spatial tasks [3,4]. Participants' improvements on the working memory training tasks transferred to other short-term and working memory tasks, supporting the possibility of broad effects of working memory training. However, we found no effects on analogical reasoning. We propose several possible explanations for the lack of an impact of working memory improvements on analogical reasoning

Manipulation of drugs to achieve the required dose is intrinsic to paediatric practice but is not supported by guidelines or evidence

Background: A lack of age-appropriate formulations can make it difficult to administer medicines to children. A manipulation of the dosage form may be required to achieve the required dose. This study aimed to describe medicines that are manipulated to achieve the required dose in paediatric practice.Method: A structured, undisguised observational study and postal survey. The observational study investigated drug manipulations occurring in clinical practice across three sites. The questionnaire, administered to a sample of paediatric nurses throughout the UK, surveyed manipulations conducted and nurses' experiences and views.Results: The observational study identified 310 manipulations, of which 62% involved tablets, 21% were intravenous drugs and 10% were sachets. Of the 54 observed manipulations 40 involved tablets with 65% of the tablets being cut and 30% dispersed to obtain a smaller dose. 188 manipulations were reported by questionnaire respondents, of these 46% involved tablets, 12% were intravenous drugs, and 12% were nebuliser solutions. Manipulations were predominantly, but not exclusively, identified in specialist clinical areas with more highly dependent patients. Questionnaire respondents were concerned about the accuracy of the dose achieved following manipulations and the lack of practice guidance.Conclusion: Manipulations to achieve the required dose occur throughout paediatric in-patient settings. The impact of manipulations on the efficacy of the drugs, the accuracy of the dose and any adverse effects on patients is not known. There is a need to develop evidence-based guidance for manipulations of medicines in children

Marked isotopic variability within and between the Amazon River and marine dissolved black carbon pools

Riverine dissolved organic carbon (DOC) contains charcoal byproducts, termed black carbon (BC). To determine the significance of BC as a sink of atmospheric CO2 and reconcile budgets, the sources and fate of this large, slow-cycling and elusive carbon pool must be constrained. The Amazon River is a significant part of global BC cycling because it exports an order of magnitude more DOC, and thus dissolved BC (DBC), than any other river. We report spatially resolved DBC quantity and radiocarbon (Δ14C) measurements, paired with molecular-level characterization of dissolved organic matter from the Amazon River and tributaries during low discharge. The proportion of BC-like polycyclic aromatic structures decreases downstream, but marked spatial variability in abundance and Δ14C values of DBC molecular markers imply dynamic sources and cycling in a manner that is incongruent with bulk DOC. We estimate a flux from the Amazon River of 1.9–2.7 Tg DBC yr−1 that is composed of predominately young DBC, suggesting that loss processes of modern DBC are important

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

Fluvial sediment supply to a mega-delta reduced by shifting tropical-cyclone activity

© 2016 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. The world's rivers deliver 19 billion tonnes of sediment to the coastal zone annually, with a considerable fraction being sequestered in large deltas, home to over 500 million people. Most (more than 70 per cent) large deltas are under threat from a combination of rising sea levels, ground surface subsidence and anthropogenic sediment trapping, and a sustainable supply of fluvial sediment is therefore critical to prevent deltas being 'drowned' by rising relative sea levels. Here we combine suspended sediment load data from the Mekong River with hydrological model simulations to isolate the role of tropical cyclones in transmitting suspended sediment to one of the world's great deltas. We demonstrate that spatial variations in the Mekong's suspended sediment load are correlated (r = 0.765, P < 0.1) with observed variations in tropical-cyclone climatology, and that a substantial portion (32 per cent) of the suspended sediment load reaching the delta is delivered by runoff generated by rainfall associated with tropical cyclones. Furthermore, we estimate that the suspended load to the delta has declined by 52.6 ± 10.2 megatonnes over recent years (1981-2005), of which 33.0 ± 7.1 megatonnes is due to a shift in tropical-cyclone climatology. Consequently, tropical cyclones have a key role in controlling the magnitude of, and variability in, transmission of suspended sediment to the coast. It is likely that anthropogenic sediment trapping in upstream reservoirs is a dominant factor in explaining past, and anticipating future, declines in suspended sediment loads reaching the world's major deltas. However, our study shows that changes in tropical-cyclone climatology affect trends in fluvial suspended sediment loads and thus are also key to fully assessing the risk posed to vulnerable coastal systems

Discharge–calcium concentration relationships in streams of the Amazon and Cerrado of Brazil : soil or land use controlled

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of springer for personal use, not for redistribution. The definitive version was published in Biogeochemistry 105 (2011): 19-35, doi:10.1007/s10533-011-9574-2.Stream discharge-concentration relationships are indicators of terrestrial ecosystem function. Throughout the Amazon and Cerrado regions of Brazil rapid changes in land use and land cover may be altering these hydrochemical relationships. The current analysis focuses on factors controlling the discharge-calcium (Ca) concentration relationship since previous research in these regions has demonstrated both positive and negative slopes in linear log10discharge-log10Ca concentration regressions. The objective of the current study was to evaluate factors controlling stream discharge-Ca concentration relationships including year, season, stream order, vegetation cover, land use, and soil classification. It was hypothesized that land use and soil class are the most critical attributes controlling discharge-Ca concentration relationships. A multilevel, linear regression approach was utilized with data from 28 streams throughout Brazil. These streams come from three distinct regions and varied broadly in watershed size (106 ha) and discharge (10-5.7 to 103.2 m3 sec-1). Linear regressions of log10Ca versus log10discharge in 13 streams have a preponderance of negative slopes with only two streams having significant positive slopes. An ANOVA decomposition suggests the effect of discharge on Ca concentration is large but variable. Vegetation cover, which incorporates aspects of land use, explains the largest proportion of the variance in the effect of discharge on Ca followed by season and year. In contrast, stream order, land use, and soil class explain most of the variation in stream Ca concentration. In the current data set, soil class, which is related to lithology, has an important effect on Ca concentration but land use, likely through its effect on runoff concentration and hydrology, has a greater effect on discharge-concentration relationships.This research was supported by grant #’s NCC5-686 and NNG06GE88A of NASA’s Terrestrial Ecology Program as part of the Large-scale Biosphere-Atmosphere Experiment in Amazonia (LBA-ECO) project

A method for estimation of elasticities in metabolic networks using steady state and dynamic metabolomics data and linlog kinetics

BACKGROUND: Dynamic modeling of metabolic reaction networks under in vivo conditions is a crucial step in order to obtain a better understanding of the (dis)functioning of living cells. So far dynamic metabolic models generally have been based on mechanistic rate equations which often contain so many parameters that their identifiability from experimental data forms a serious problem. Recently, approximative rate equations, based on the linear logarithmic (linlog) format have been proposed as a suitable alternative with fewer parameters. RESULTS: In this paper we present a method for estimation of the kinetic model parameters, which are equal to the elasticities defined in Metabolic Control Analysis, from metabolite data obtained from dynamic as well as steady state perturbations, using the linlog kinetic format. Additionally, we address the question of parameter identifiability from dynamic perturbation data in the presence of noise. The method is illustrated using metabolite data generated with a dynamic model of the glycolytic pathway of Saccharomyces cerevisiae based on mechanistic rate equations. Elasticities are estimated from the generated data, which define the complete linlog kinetic model of the glycolysis. The effect of data noise on the accuracy of the estimated elasticities is presented. Finally, identifiable subset of parameters is determined using information on the standard deviations of the estimated elasticities through Monte Carlo (MC) simulations. CONCLUSION: The parameter estimation within the linlog kinetic framework as presented here allows the determination of the elasticities directly from experimental data from typical dynamic and/or steady state experiments. These elasticities allow the reconstruction of the full kinetic model of Saccharomyces cerevisiae, and the determination of the control coefficients. MC simulations revealed that certain elasticities are potentially unidentifiable from dynamic data only. Addition of steady state perturbation of enzyme activities solved this problem