164 research outputs found

    Predicting consumer biomass, size-structure, production, catch potential, responses to fishing and associated uncertainties in the world's marine ecosystems

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    Existing estimates of fish and consumer biomass in the world’s oceans are disparate. This creates uncertainty about the roles of fish and other consumers in biogeochemical cycles and ecosystem processes, the extent of human and environmental impacts and fishery potential. We develop and use a size-based macroecological model to assess the effects of parameter uncertainty on predicted consumer biomass, production and distribution. Resulting uncertainty is large (e.g. median global biomass 4.9 billion tonnes for consumers weighing 1 g to 1000 kg; 50% uncertainty intervals of 2 to 10.4 billion tonnes; 90% uncertainty intervals of 0.3 to 26.1 billion tonnes) and driven primarily by uncertainty in trophic transfer efficiency and its relationship with predator-prey body mass ratios. Even the upper uncertainty intervals for global predictions of consumer biomass demonstrate the remarkable scarcity of marine consumers, with less than one part in 30 million by volume of the global oceans comprising tissue of macroscopic animals. Thus the apparently high densities of marine life seen in surface and coastal waters and frequently visited abundance hotspots will likely give many in society a false impression of the abundance of marine animals. Unexploited baseline biomass predictions from the simple macroecological model were used to calibrate a more complex size- and trait-based model to estimate fisheries yield and impacts. Yields are highly dependent on baseline biomass and fisheries selectivity. Predicted global sustainable fisheries yield increases ≈4 fold when smaller individuals (< 20 cm from species of maximum mass < 1kg) are targeted in all oceans, but the predicted yields would rarely be accessible in practice and this fishing strategy leads to the collapse of larger species if fishing mortality rates on different size classes cannot be decoupled. Our analyses show that models with minimal parameter demands that are based on a few established ecological principles can support equitable analysis and comparison of diverse ecosystems. The analyses provide insights into the effects of parameter uncertainty on global biomass and production estimates, which have yet to be achieved with complex models, and will therefore help to highlight priorities for future research and data collection. However, the focus on simple model structures and global processes means that non-phytoplankton primary production and several groups, structures and processes of ecological and conservation interest are not represented. Consequently, our simple models become increasingly less useful than more complex alternatives when addressing questions about food web structure and function, biodiversity, resilience and human impacts at smaller scales and for areas closer to coasts

    Factors affecting exhaled nitric oxide measurements: the effect of sex

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    <p>Abstract</p> <p>Background</p> <p>Exhaled nitric oxide (F<sub>E</sub>NO) measurements are used as a surrogate marker for eosinophilic airway inflammation. However, many constitutional and environmental factors affect F<sub>E</sub>NO, making it difficult to devise reference values. Our aim was to evaluate the relative importance of factors affecting F<sub>E</sub>NO in a well characterised adult population.</p> <p>Methods</p> <p>Data were obtained from 895 members of the Dunedin Multidisciplinary Health and Development Study at age 32. The effects of sex, height, weight, lung function indices, smoking, atopy, asthma and rhinitis on F<sub>E</sub>NO were explored by unadjusted and adjusted linear regression analyses.</p> <p>Results</p> <p>The effect of sex on F<sub>E</sub>NO was both statistically and clinically significant, with F<sub>E</sub>NO levels approximately 25% less in females. Overall, current smoking reduced F<sub>E</sub>NO up to 50%, but this effect occurred predominantly in those who smoked on the day of the F<sub>E</sub>NO measurement. Atopy increased F<sub>E</sub>NO by 60%. The sex-related differences in F<sub>E</sub>NO remained significant (p < 0.001) after controlling for all other significant factors affecting F<sub>E</sub>NO.</p> <p>Conclusion</p> <p>Even after adjustment, F<sub>E</sub>NO values are significantly different in males and females. The derivation of reference values and the interpretation of F<sub>E</sub>NO in the clinical setting should be stratified by sex. Other common factors such as current smoking and atopy also require to be taken into account.</p

    Integrating Quantitative Knowledge into a Qualitative Gene Regulatory Network

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    Despite recent improvements in molecular techniques, biological knowledge remains incomplete. Any theorizing about living systems is therefore necessarily based on the use of heterogeneous and partial information. Much current research has focused successfully on the qualitative behaviors of macromolecular networks. Nonetheless, it is not capable of taking into account available quantitative information such as time-series protein concentration variations. The present work proposes a probabilistic modeling framework that integrates both kinds of information. Average case analysis methods are used in combination with Markov chains to link qualitative information about transcriptional regulations to quantitative information about protein concentrations. The approach is illustrated by modeling the carbon starvation response in Escherichia coli. It accurately predicts the quantitative time-series evolution of several protein concentrations using only knowledge of discrete gene interactions and a small number of quantitative observations on a single protein concentration. From this, the modeling technique also derives a ranking of interactions with respect to their importance during the experiment considered. Such a classification is confirmed by the literature. Therefore, our method is principally novel in that it allows (i) a hybrid model that integrates both qualitative discrete model and quantities to be built, even using a small amount of quantitative information, (ii) new quantitative predictions to be derived, (iii) the robustness and relevance of interactions with respect to phenotypic criteria to be precisely quantified, and (iv) the key features of the model to be extracted that can be used as a guidance to design future experiments

    Conserved and variable correlated mutations in the plant MADS protein network

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    <p>Abstract</p> <p>Background</p> <p>Plant MADS domain proteins are involved in a variety of developmental processes for which their ability to form various interactions is a key requisite. However, not much is known about the structure of these proteins or their complexes, whereas such knowledge would be valuable for a better understanding of their function. Here, we analyze those proteins and the complexes they form using a correlated mutation approach in combination with available structural, bioinformatics and experimental data.</p> <p>Results</p> <p>Correlated mutations are affected by several types of noise, which is difficult to disentangle from the real signal. In our analysis of the MADS domain proteins, we apply for the first time a correlated mutation analysis to a family of interacting proteins. This provides a unique way to investigate the amount of signal that is present in correlated mutations because it allows direct comparison of mutations in various family members and assessing their conservation. We show that correlated mutations in general are conserved within the various family members, and if not, the variability at the respective positions is less in the proteins in which the correlated mutation does not occur. Also, intermolecular correlated mutation signals for interacting pairs of proteins display clear overlap with other bioinformatics data, which is not the case for non-interacting protein pairs, an observation which validates the intermolecular correlated mutations. Having validated the correlated mutation results, we apply them to infer the structural organization of the MADS domain proteins.</p> <p>Conclusion</p> <p>Our analysis enables understanding of the structural organization of the MADS domain proteins, including support for predicted helices based on correlated mutation patterns, and evidence for a specific interaction site in those proteins.</p

    Hemolymph microbiome of Pacific oysters in response to temperature, temperature stress and infection

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    Microbiota provide their hosts with a range of beneficial services, including defense from external pathogens. However, host-associated microbial communities themselves can act as a source of opportunistic pathogens depending on the environment. Marine poikilotherms and their microbiota are strongly influenced by temperature, but experimental studies exploring how temperature affects the interactions between both parties are rare. To assess the effects of temperature, temperature stress and infection on diversity, composition and dynamics of the hemolymph microbiota of Pacific oysters (Crassostrea gigas), we conducted an experiment in a fully-crossed, three-factorial design, in which the temperature acclimated oysters (8 or 22 °C) were exposed to temperature stress and to experimental challenge with a virulent Vibrio sp. Strain. We monitored oyster survival and repeatedly collected hemolymph of dead and alive animals to determine the microbiome composition by 16s rRNA gene amplicon pyrosequencing. We found that the microbial dynamics and composition of communities in healthy animals (including infection survivors) were significantly affected by temperature and temperature stress, but not by infection. The response was mediated by changes in the incidence and abundance of operational taxonomic units (OTUs) and accompanied by little change at higher taxonomic levels, indicating dynamic stability of the hemolymph microbiome. Dead and moribund oysters, on the contrary, displayed signs of community structure disruption, characterized by very low diversity and proliferation of few OTUs. We can therefore link short-term responses of host-associated microbial communities to abiotic and biotic factors and assess the potential feedback between microbiota dynamics and host survival during disease

    Emergency department triage: an ethical analysis

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    <p>Abstract</p> <p>Background</p> <p>Emergency departments across the globe follow a triage system in order to cope with overcrowding. The intention behind triage is to improve the emergency care and to prioritize cases in terms of clinical urgency.</p> <p>Discussion</p> <p>In emergency department triage, medical care might lead to adverse consequences like delay in providing care, compromise in privacy and confidentiality, poor physician-patient communication, failing to provide the necessary care altogether, or even having to decide whose life to save when not everyone can be saved. These consequences challenge the ethical quality of emergency care. This article provides an ethical analysis of "routine" emergency department triage. The four principles of biomedical ethics - viz. respect for autonomy, beneficence, nonmaleficence and justice provide the starting point and help us to identify the ethical challenges of emergency department triage. However, they do not offer a <it>comprehensive </it>ethical view. To address the ethical issues of emergency department triage from a more comprehensive ethical view, the care ethics perspective offers additional insights.</p> <p>Summary</p> <p>We integrate the results from the analysis using four principles of biomedical ethics into care ethics perspective on triage and propose an integrated clinically and ethically based framework of emergency department triage planning, as seen from a comprehensive ethics perspective that incorporates both the principles-based and care-oriented approach.</p

    Correlated Mutations: A Hallmark of Phenotypic Amino Acid Substitutions

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    Point mutations resulting in the substitution of a single amino acid can cause severe functional consequences, but can also be completely harmless. Understanding what determines the phenotypical impact is important both for planning targeted mutation experiments in the laboratory and for analyzing naturally occurring mutations found in patients. Common wisdom suggests using the extent of evolutionary conservation of a residue or a sequence motif as an indicator of its functional importance and thus vulnerability in case of mutation. In this work, we put forward the hypothesis that in addition to conservation, co-evolution of residues in a protein influences the likelihood of a residue to be functionally important and thus associated with disease. While the basic idea of a relation between co-evolution and functional sites has been explored before, we have conducted the first systematic and comprehensive analysis of point mutations causing disease in humans with respect to correlated mutations. We included 14,211 distinct positions with known disease-causing point mutations in 1,153 human proteins in our analysis. Our data show that (1) correlated positions are significantly more likely to be disease-associated than expected by chance, and that (2) this signal cannot be explained by conservation patterns of individual sequence positions. Although correlated residues have primarily been used to predict contact sites, our data are in agreement with previous observations that (3) many such correlations do not relate to physical contacts between amino acid residues. Access to our analysis results are provided at http://webclu.bio.wzw.tum.de/~pagel/supplements/correlated-positions/
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