Methane emission by Camelids

Methane emissions from ruminant livestock have been intensively studied in order to reduce contribution to the greenhouse effect. Ruminants were found to produce more enteric methane than other mammalian herbivores. As camelids share some features of their digestive anatomy and physiology with ruminants, it has been proposed that they produce similar amounts of methane per unit of body mass. This is of special relevance for countrywide greenhouse gas budgets of countries that harbor large populations of camelids like Australia. However, hardly any quantitative methane emission measurements have been performed in camelids. In order to fill this gap, we carried out respiration chamber measurements with three camelid species (Vicugna pacos, Lama glama, Camelus bactrianus; n = 16 in total), all kept on a diet consisting of food produced from alfalfa only. The camelids produced less methane expressed on the basis of body mass (0.3260.11 L kg21 d21) when compared to literature data on domestic ruminants fed on roughage diets (0.5860.16 L kg21 d21). However, there was no significant difference between the two suborders when methane emission was expressed on the basis of digestible neutral detergent fiber intake (92.7633.9 L kg21 in camelids vs. 86.2612.1 L kg21 in ruminants). This implies that the pathways of methanogenesis forming part of the microbial digestion of fiber in the foregut are similar between the groups, and that the lower methane emission of camelids can be explained by their generally lower relative food intake. Our results suggest that the methane emission of Australia’s feral camels corresponds only to 1 to 2% of the methane amount produced by the countries’ domestic ruminants and that calculations of greenhouse gas budgets of countries with large camelid populations based on equations developed for ruminants are generally overestimating the actual levels

HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Evaluation of the Frails' Fall Efficacy by Comparing Treatments (EFFECT) on reducing fall and fear of fall in moderately frail older adults: study protocol for a randomised control trial

<p>Abstract</p> <p>Background</p> <p>Falls are common in frail older adults and often result in injuries and hospitalisation. The Nintendo^®Wii™ is an easily available exercise modality in the community which has been shown to improve lower limb strength and balance. However, not much is known on the effectiveness of the Nintendo^®Wii™ to improve fall efficacy and reduce falls in a moderately frail older adult. Fall efficacy is the measure of fear of falling in performing various daily activities. Fear contributes to avoidance of activities and functional decline.</p> <p>Methods</p> <p>This randomised active-control trial is a comparison between the Nintendo WiiActive programme against standard gym-based rehabilitation of the older population. Eighty subjects aged above 60, fallers and non-fallers, will be recruited from the hospital outpatient clinic. The primary outcome measure is the Modified Falls Efficacy Scale and the secondary outcome measures are self-reported falls, quadriceps strength, walking agility, dynamic balance and quality of life assessments.</p> <p>Discussions</p> <p>The study is the first randomised control trial using the Nintendo Wii as a rehabilitation modality investigating a change in fall efficacy and self-reported falls. Longitudinally, the study will investigate if the interventions can successfully reduce falls and analyse the cost-effectiveness of the programme.</p> <p>Trial registration</p> <p>Australia and New Zealand Clinical Trials Register (ANZCTR): <a href="http://www.anzctr.org.au/ACTRN12610000576022.aspx">ACTRN12610000576022</a></p

Environmental sensing and response genes in cnidaria : the chemical defensome in the sea anemone Nematostella vectensis

Author Posting. © The Author(s), 2008. 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 Cell Biology and Toxicology 24 (2008): 483-502, doi:10.1007/s10565-008-9107-5.The starlet sea anemone Nematostella vectensis has been recently established as a new model system for the study of the evolution of developmental processes, as cnidaria occupy a key evolutionary position at the base of the bilateria. Cnidaria play important roles in estuarine and reef communities, but are exposed to many environmental stressors. Here I describe the genetic components of a ‘chemical defensome’ in the genome of N. vectensis, and review cnidarian molecular toxicology. Gene families that defend against chemical stressors and the transcription factors that regulate these genes have been termed a ‘chemical defensome,’ and include the cytochromes P450 and other oxidases, various conjugating enyzymes, the ATP-dependent efflux transporters, oxidative detoxification proteins, as well as various transcription factors. These genes account for about 1% (266/27200) of the predicted genes in the sea anemone genome, similar to the proportion observed in tunicates and humans, but lower than that observed in sea urchins. While there are comparable numbers of stress-response genes, the stress sensor genes appear to be reduced in N. vectensis relative to many model protostomes and deuterostomes. Cnidarian toxicology is understudied, especially given the important ecological roles of many cnidarian species. New genomic resources should stimulate the study of chemical stress sensing and response mechanisms in cnidaria, and allow us to further illuminate the evolution of chemical defense gene networks.WHOI Ocean Life Institute and NIH R01-ES01591

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics