Predicting ecosystem responses to changes in fisheries catch, temperature, and primary productivity with a dynamic Bayesian network model

The recent adoption of Bayesian networks (BNs) in ecology provides an opportunity to make advances because complex interactions can be recovered from field data and then used to predict the environmental response to changes in climate and biodiversity. In this study, we use a dynamic BN model with a hidden variable and spatial autocorrelation to explore the future of different fish and zooplankton species, given alternate scenarios, and across spatial scales within the North Sea. For most fish species, we were able to predict a trend of increase or decline in response to change in fisheries catch; however, this varied across the different areas, outlining the importance of trophic interactions and the spatial relationship between neighbouring areas. We were able to predict trends in zooplankton biomass in response to temperature change, with the spatial patterns of these effects varying by species. In contrast, there was high variability in terms of response to productivity changes and consequently knock-on effects on higher level trophic species. Finally, we were able to provide a new data-driven modelling approach that accounts for multispecies associations and interactions and their changes over space and time, which might be beneficial to give strategic advice on potential response of the system to pressure.We gratefully acknowledge the Natural Environment Research Council UK that has funded this research, along with support from the European Commission (OCEANCERTAIN, FP7-ENV-2013-6.1-1; no: 603773) for David Maxwell and from CEFAS for Andrew Kenny and David Maxwell

Generic harvest control rules for European fisheries

In European fisheries, most stocks are overfished and many are below safe biological limits, resulting in a call from the European Commission for new long-term fisheries management plans. Here, we propose a set of intuitive harvest control rules that are economically sound, compliant with international fishery agreements, based on relevant international experiences, supportive of ecosystem-based fisheries management and compatible with the biology of the fish stocks. The rules are based on the concept of maximum sustainable yield (MSY), with a precautionary target biomass that is 30% larger than that which produces MSY and with annual catches of 91% MSY. Allowable catches decline steeply when stocks fall below MSY levels and are set to zero when stocks fall below half of MSY levels. We show that the proposed rules could have prevented the collapse of the North Sea herring in the 1970s and that they can deal with strong cyclic variations in recruitment such as known for blue whiting. Compared to the current system, these rules would lead to higher long-term catches from larger stocks at lower cost and with less adverse environmental impact

Monocyte NOTCH2 expression predicts interferon-beta immunogenicity in multiple sclerosis patients

Multiple sclerosis (MS) is an autoimmune disease characterized by CNS inflammation leading to demyelination and axonal damage. IFN-β is an established treatment for MS; however, up to 30% of IFN-β–treated MS patients develop neutralizing antidrug antibodies (nADA), leading to reduced drug bioactivity and efficacy. Mechanisms driving antidrug immunogenicity remain uncertain, and reliable biomarkers to predict immunogenicity development are lacking. Using high-throughput flow cytometry, NOTCH2 expression on CD14+ monocytes and increased frequency of proinflammatory monocyte subsets were identified as baseline predictors of nADA development in MS patients treated with IFN-β. The association of this monocyte profile with nADA development was validated in 2 independent cross-sectional MS patient cohorts and a prospective cohort followed before and after IFN-β administration. Reduced monocyte NOTCH2 expression in nADA+ MS patients was associated with NOTCH2 activation measured by increased expression of Notch-responsive genes, polarization of monocytes toward a nonclassical phenotype, and increased proinflammatory IL-6 production. NOTCH2 activation was T cell dependent and was only triggered in the presence of serum from nADA+ patients. Thus, nADA development was driven by a proinflammatory environment that triggered activation of the NOTCH2 signaling pathway prior to first IFN-β administration

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

A genetic algorithm-Bayesian network approach for the analysis of metabolomics and spectroscopic data: application to the rapid detection of Bacillus spores and identification of Bacillus species

Background The rapid identification of Bacillus spores and bacterial identification are paramount because of their implications in food poisoning, pathogenesis and their use as potential biowarfare agents. Many automated analytical techniques such as Curie-point pyrolysis mass spectrometry (Py-MS) have been used to identify bacterial spores giving use to large amounts of analytical data. This high number of features makes interpretation of the data extremely difficult We analysed Py-MS data from 36 different strains of aerobic endospore-forming bacteria encompassing seven different species. These bacteria were grown axenically on nutrient agar and vegetative biomass and spores were analyzed by Curie-point Py-MS. Results We develop a novel genetic algorithm-Bayesian network algorithm that accurately identifies sand selects a small subset of key relevant mass spectra (biomarkers) to be further analysed. Once identified, this subset of relevant biomarkers was then used to identify Bacillus spores successfully and to identify Bacillus species via a Bayesian network model specifically built for this reduced set of features. Conclusions This final compact Bayesian network classification model is parsimonious, computationally fast to run and its graphical visualization allows easy interpretation of the probabilistic relationships among selected biomarkers. In addition, we compare the features selected by the genetic algorithm-Bayesian network approach with the features selected by partial least squares-discriminant analysis (PLS-DA). The classification accuracy results show that the set of features selected by the GA-BN is far superior to PLS-DA

Forms of knowledge and eco-innovation modes: Evidence from Spanish manufacturing firms

The paper investigates the knowledge drivers of firms' eco-innovations (EI) by retaining the diverse nature of their target. Different internal and external knowledge sources are examined and the evidence of EI-modes is searched for with respect to a sample of Spanish manufacturing firms covering the 2007–2009 and 2010–2012 periods. An “attenuated” Science, Technology, EI-mode prevails internally, with R&D more pivotal than either embodied or disembodied non-R&D knowledge, depending on the EI strategy. Externally, synthetic knowledge matters more than the analytical one, suggesting instead a Doing, Using, Interacting EI-mode. Hence, a dichotomic combination of the two modes emerges across the firm's boundaries. However, remarkable differences are in place, depending on whether EIs target efficiency or non-efficiency related environmental improvements. Our evidence also shows that internal and external knowledge turn out difficult to combine, both within and across modes

Utilisation of Mucin Glycans by the Human Gut Symbiont Ruminococcus gnavus Is Strain-Dependent

Commensal bacteria often have an especially rich source of glycan-degrading enzymes which allow them to utilize undigested carbohydrates from the food or the host. The species Ruminococcus gnavus is present in the digestive tract of ≥90% of humans and has been implicated in gut-related diseases such as inflammatory bowel diseases (IBD). Here we analysed the ability of two R. gnavus human strains, E1 and ATCC 29149, to utilize host glycans. We showed that although both strains could assimilate mucin monosaccharides, only R. gnavus ATCC 29149 was able to grow on mucin as a sole carbon source. Comparative genomic analysis of the two R. gnavus strains highlighted potential clusters and glycoside hydrolases (GHs) responsible for the breakdown and utilization of mucin-derived glycans. Transcriptomic and functional activity assays confirmed the importance of specific GH33 sialidase, and GH29 and GH95 fucosidases in the mucin utilisation pathway. Notably, we uncovered a novel pathway by which R. gnavus ATCC 29149 utilises sialic acid from sialylated substrates. Our results also demonstrated the ability of R. gnavus ATCC 29149 to produce propanol and propionate as the end products of metabolism when grown on mucin and fucosylated glycans. These new findings provide molecular insights into the strain-specificity of R. gnavus adaptation to the gut environment advancing our understanding of the role of gut commensals in health and disease

An enzyme-linked immunosorbent assay for detection of avian influenza virus subtypes H5 and H7 antibodies

BACKGROUND: Avian influenza virus (AIV) subtypes H5 and H7 attracts particular attention because of the risk of their potential pathogenicity in poultry. The haemagglutination inhibition (HI) test is widely used as subtype specific test for serological diagnostics despite the laborious nature of this method. However, enzyme-linked immunosorbent assays (ELISAs) are being explored as an alternative test method. H5 and H7 specific monoclonal antibodies were experimentally raised and used in the development of inhibition ELISAs for detection of serological response specifically directed against AIV subtypes H5 and H7. The ELISAs were evaluated with polyclonal chicken anti-AIV antibodies against AIV subtypes: H1N2, H5N2, H5N7, H7N1, H7N7, H9N9, H10N4 and H16N3. RESULTS: Both the H5 and H7 ELISA proved to have a high sensitivity and specificity and the ELISAs detected H5 and H7 antibodies earlier during experimental infection than the HI test did. The reproducibility of the ELISA’s performed at different times was high with Pearson correlation coefficients of 0.96-0.98. CONCLUSIONS: The ELISAs are a potential alternative to the HI test for screening of large amounts of avian sera, although only experimental sera were tested in this study