Successional changes of epibiont fouling communities of the cultivated kelp Alaria esculenta: predictability and influences

There has been an increase in commercial-scale kelp cultivation in Europe, with fouling of cultivated kelp fronds presenting a major challenge to the growth and development of the industry. The presence of epibionts decreases productivity and impacts the commercial value of the crop. Several abiotic and biotic factors may influence the occurrence and degree of fouling of wild and cultivated fronds. Using a commercial kelp farm on the SW coast of Ireland, we studied the development of fouling communities on cultivated Alaria esculenta fronds over 2 typical growing seasons. The predictability of community development was assessed by comparing mean occurrence-day. Hypotheses that depth, kelp biomass, position within the farm and the hydrodynamic environment affect the fouling communities were tested using species richness and community composition. Artificial kelp mimics were used to test whether local frond density could affect the fouling communities. Species richness increased over time during both years, and species composition was consistent over years with early successional communities converging into later communities (no significant differences between June 2014 and June 2015 communities, ANOSIM; R = -0.184, p > 0.05). The timing of species occurrences was predictable across years for all shared species. Variations in biomass, depth and position within the farm had no significant effect on species richness and composition. Results from artificial kelp mimics suggest possible hydrodynamic effects. The ability to understand succession and the timing of occurrences of fouling organisms and predict their arrival has significant benefits for the seaweed cultivation industry

Heterotic domain wall solutions and SU(3) structure manifolds

We examine compactifications of heterotic string theory on manifolds with SU(3) structure. In particular, we study N = 1/2 domain wall solutions which correspond to the perturbative vacua of the 4D, N =1 supersymmetric theories associated to these compactifications. We extend work which has appeared previously in the literature in two important regards. Firstly, we include two additional fluxes which have been, heretofore, omitted in the general analysis of this situation. This allows for solutions with more general torsion classes than have previously been found. Secondly, we provide explicit solutions for the fluxes as a function of the torsion classes. These solutions are particularly useful in deciding whether equations such as the Bianchi identities can be solved, in addition to the Killing spinor equations themselves. Our work can be used to straightforwardly decide whether any given SU(3) structure on a six-dimensional manifold is associated with a solution to heterotic string theory. To illustrate how to use these results, we discuss a number of examples taken from the literature.Comment: 34 pages, minor corrections in second versio

Automatic estimation of harmonic tension by distributed representation of chords

The buildup and release of a sense of tension is one of the most essential aspects of the process of listening to music. A veridical computational model of perceived musical tension would be an important ingredient for many music informatics applications. The present paper presents a new approach to modelling harmonic tension based on a distributed representation of chords. The starting hypothesis is that harmonic tension as perceived by human listeners is related, among other things, to the expectedness of harmonic units (chords) in their local harmonic context. We train a word2vec-type neural network to learn a vector space that captures contextual similarity and expectedness, and define a quantitative measure of harmonic tension on top of this. To assess the veridicality of the model, we compare its outputs on a number of well-defined chord classes and cadential contexts to results from pertinent empirical studies in music psychology. Statistical analysis shows that the model's predictions conform very well with empirical evidence obtained from human listeners.Comment: 12 pages, 4 figures. To appear in Proceedings of the 13th International Symposium on Computer Music Multidisciplinary Research (CMMR), Porto, Portuga

Use of Cell Viability Assay Data Improves the Prediction Accuracy of Conventional Quantitative Structure–Activity Relationship Models of Animal Carcinogenicity

BackgroundTo develop efficient approaches for rapid evaluation of chemical toxicity and human health risk of environmental compounds, the National Toxicology Program (NTP) in collaboration with the National Center for Chemical Genomics has initiated a project on high-throughput screening (HTS) of environmental chemicals. The first HTS results for a set of 1,408 compounds tested for their effects on cell viability in six different cell lines have recently become available via PubChem.ObjectivesWe have explored these data in terms of their utility for predicting adverse health effects of the environmental agents.Methods and resultsInitially, the classification k nearest neighbor (kNN) quantitative structure–activity relationship (QSAR) modeling method was applied to the HTS data only, for a curated data set of 384 compounds. The resulting models had prediction accuracies for training, test (containing 275 compounds together), and external validation (109 compounds) sets as high as 89%, 71%, and 74%, respectively. We then asked if HTS results could be of value in predicting rodent carcinogenicity. We identified 383 compounds for which data were available from both the Berkeley Carcinogenic Potency Database and NTP–HTS studies. We found that compounds classified by HTS as “actives” in at least one cell line were likely to be rodent carcinogens (sensitivity 77%); however, HTS “inactives” were far less informative (specificity 46%). Using chemical descriptors only, kNN QSAR modeling resulted in 62.3% prediction accuracy for rodent carcinogenicity applied to this data set. Importantly, the prediction accuracy of the model was significantly improved (72.7%) when chemical descriptors were augmented by HTS data, which were regarded as biological descriptors.ConclusionsOur studies suggest that combining NTP–HTS profiles with conventional chemical descriptors could considerably improve the predictive power of computational approaches in toxicology

Effects of behavioral intervention content on HIV prevention outcomes: a meta-review of meta-analyses

Objective: Numerous meta-analyses have examined the success of trials of interventions to reduce the behavioral risk of acquiring or transmitting HIV. Yet, to date, meta-reviews have not systematically examined which type of intervention content is more likely to lead to successful HIV outcomes. The current study addresses this gap. / Methods: Published meta-analyses on HIV prevention (k = 56) were retrieved, then coded, and analyzed in terms of the intervention content. / Results: Past meta-analyses have examined relatively few dimensions of intervention content. Larger meta-analyses were more likely to find that information content dimensions, especially skill provision and motivational enhancement, relate to risk reduction. / Conclusions: Fully incorporating behavior change technique (BCT) taxonomies into both intervention research and systematic reviews of this research offers considerable potential. It can improve the precision of conclusions about which specific types of content best promote HIV prevention behaviors and help to lower the cost of interventions. International efforts to improve reporting standards and generate the scholarly expertise necessary to discern BCTs reliably and validly help to address some of the challenges to including BCTs in study reports. Contextualizing research on effective strategies for HIV prevention by reporting and including in analyses community, social, and sample factors is also recommended. Together, such efforts can help refocus the field of HIV prevention on improved research strategies to further improve future interventions by discerning the content design factors related to success for particular populations, rather than merely to assess whether interventions have been successful

Ecological priming of artificial aquaculture structures: Kelp farms as an example

Copyright © Marine Biological Association of the United Kingdom 2018. The continued development of the aquaculture industry is contributing to the proliferation of artificial structures in the marine environment. Observations of seaweed farms (infrastructure and biomass) suggest they act as a habitat for associated species. Seaweed farms differ from other forms of artificial infrastructure as the material deployed already has marine organisms (i.e. culture species) growing on it. This 'priming' of ropes with juvenile sporophytes may affect future development of communities by facilitating colonizing species or suppressing competitors. We call this process 'ecological priming': the provision of a biological platform that influences the successional development of specific communities. The communities that developed on ropes primed with Alaria esculenta individuals were compared with unprimed ropes to assess the ecological priming effect, at a commercial kelp farm in south-west Ireland. Species richness increased over two cultivation seasons and species composition was consistent between years, with distinct communities developing on primed and unprimed treatments. Timing of species occurrence on primed ropes was predictable with no predictable pattern occurring on unprimed ropes. Multivariate tests indicated distinct communities between treatments, with suppression of other algal species and potential facilitation of some species that have a particular association with A. esculenta on primed ropes. Communities from primed holdfasts contained a lower diversity of algal species compared with unprimed communities. Cultivated kelp holdfasts represent a habitat for distinct assemblages that reflect ecological priming of the substratum

Milling plant and soil material in plastic tubes over-estimates carbon and under-estimates nitrogen concentrations

Peer reviewedPostprin

The molecular characterisation of Escherichia coli K1 isolated from neonatal nasogastric feeding tubes

Background: The most common cause of Gram-negative bacterial neonatal meningitis is E. coli K1. It has a mortality rate of 10–15%, and neurological sequelae in 30– 50% of cases. Infections can be attributable to nosocomial sources, however the pre-colonisation of enteral feeding tubes has not been considered as a specific risk factor. Methods: Thirty E. coli strains, which had been isolated in an earlier study, from the residual lumen liquid and biofilms of neonatal nasogastric feeding tubes were genotyped using pulsed-field gel electrophoresis, and 7-loci multilocus sequence typing. Potential pathogenicity and biofilm associated traits were determined using specific PCR probes, genome analysis, and in vitro tissue culture assays. Results: The E. coli strains clustered into five pulsotypes, which were genotyped as sequence types (ST) 95, 73, 127, 394 and 2076 (Achman scheme). The extra-intestinal pathogenic E. coli (ExPEC) phylogenetic group B2 ST95 serotype O1:K1:NM strains had been isolated over a 2 week period from 11 neonates who were on different feeding regimes. The E. coli K1 ST95 strains encoded for various virulence traits associated with neonatal meningitis and extracellular matrix formation. These strains attached and invaded intestinal, and both human and rat brain cell lines, and persisted for 48 h in U937 macrophages. E. coli STs 73, 394 and 2076 also persisted in macrophages and invaded Caco-2 and human brain cells, but only ST394 invaded rat brain cells. E. coli ST127 was notable as it did not invade any cell lines. Conclusions: Routes by which E. coli K1 can be disseminated within a neonatal intensive care unit are uncertain, however the colonisation of neonatal enteral feeding tubes may be one reservoir source which could constitute a serious health risk to neonates following ingestion

Headwater Influences on Downstream Water Quality

We investigated the influence of riparian and whole watershed land use as a function of stream size on surface water chemistry and assessed regional variation in these relationships. Sixty-eight watersheds in four level III U.S. EPA ecoregions in eastern Kansas were selected as study sites. Riparian land cover and watershed land use were quantified for the entire watershed, and by Strahler order. Multiple regression analyses using riparian land cover classifications as independent variables explained among-site variation in water chemistry parameters, particularly total nitrogen (41%), nitrate (61%), and total phosphorus (63%) concentrations. Whole watershed land use explained slightly less variance, but riparian and whole watershed land use were so tightly correlated that it was difficult to separate their effects. Water chemistry parameters sampled in downstream reaches were most closely correlated with riparian land cover adjacent to the smallest (first-order) streams of watersheds or land use in the entire watershed, with riparian zones immediately upstream of sampling sites offering less explanatory power as stream size increased. Interestingly, headwater effects were evident even at times when these small streams were unlikely to be flowing. Relationships were similar among ecoregions, indicating that land use characteristics were most responsible for water quality variation among watersheds. These findings suggest that nonpoint pollution control strategies should consider the influence of small upland streams and protection of downstream riparian zones alone is not sufficient to protect water quality

Does self-monitoring reduce blood pressure? Meta-analysis with meta-regression of randomized controlled trials

Introduction. Self-monitoring of blood pressure (BP) is an increasingly common part of hypertension management. The objectives of this systematic review were to evaluate the systolic and diastolic BP reduction, and achievement of target BP, associated with self-monitoring. Methods. MEDLINE, Embase, Cochrane database of systematic reviews, database of abstracts of clinical effectiveness, the health technology assessment database, the NHS economic evaluation database, and the TRIP database were searched for studies where the intervention included self-monitoring of BP and the outcome was change in office/ambulatory BP or proportion with controlled BP. Two reviewers independently extracted data. Meta-analysis using a random effects model was combined with meta-regression to investigate heterogeneity in effect sizes. Results. A total of 25 eligible randomized controlled trials (RCTs) (27 comparisons) were identified. Office systolic BP (20 RCTs, 21 comparisons, 5,898 patients) and diastolic BP (23 RCTs, 25 comparisons, 6,038 patients) were significantly reduced in those who self-monitored compared to usual care (weighted mean difference (WMD) systolic −3.82 mmHg (95% confidence interval −5.61 to −2.03), diastolic −1.45 mmHg (−1.95 to −0.94)). Self-monitoring increased the chance of meeting office BP targets (12 RCTs, 13 comparisons, 2,260 patients, relative risk = 1.09 (1.02 to 1.16)). There was significant heterogeneity between studies for all three comparisons, which could be partially accounted for by the use of additional co-interventions. Conclusion. Self-monitoring reduces blood pressure by a small but significant amount. Meta-regression could only account for part of the observed heterogeneity