A stochastic model for estimating sustainable limits to wildlife mortality in a changing world

Human-caused mortality of wildlife is a pervasive threat to biodiversity. Assessing the population-level impact of fisheries bycatch and other human-caused mortality of wildlife has typically relied upon deterministic methods. However, population declines are often accelerated by stochastic factors that are not accounted for in such conventional methods. Building on the widely applied potential biological removal (PBR) equation, we devised a new population modeling approach for estimating sustainable limits to human-caused mortality and applied it in a case study of bottlenose dolphins affected by capture in an Australian demersal otter trawl fishery. Our approach, termed sustainable anthropogenic mortality in stochastic environments (SAMSE), incorporates environmental and demographic stochasticity, including the dependency of offspring on their mothers. The SAMSE limit is the maximum number of individuals that can be removed without causing negative stochastic population growth. We calculated a PBR of 16.2 dolphins per year based on the best abundance estimate available. In contrast, the SAMSE model indicated that only 2.3–8.0 dolphins could be removed annually without causing a population decline in a stochastic environment. These results suggest that reported bycatch rates are unsustainable in the long term, unless reproductive rates are consistently higher than average. The difference between the deterministic PBR calculation and the SAMSE limits showed that deterministic approaches may underestimate the true impact of human-caused mortality of wildlife. This highlights the importance of integrating stochasticity when evaluating the impact of bycatch or other human-caused mortality on wildlife, such as hunting, lethal control measures, and wind turbine collisions. Although population viability analysis (PVA) has been used to evaluate the impact of human-caused mortality, SAMSE represents a novel PVA framework that incorporates stochasticity for estimating acceptable levels of human-caused mortality. It offers a broadly applicable, stochastic addition to the demographic toolbox to evaluate the impact of human-caused mortality on wildlife

A school-based intervention incorporating smartphone technology to improve health-related fitness among adolescents: Rationale and study protocol for the NEAT and ATLAS 2.0 cluster randomised controlled trial and dissemination study

Introduction Physical inactivity has been described as a global pandemic. Interventions aimed at developing skills in lifelong physical activities may provide the foundation for an active lifestyle into adulthood. In general, school-based physical activity interventions targeting adolescents have produced modest results and few have been designed to be \u27scaled-up\u27 and disseminated. This study aims to: (1) assess the effectiveness of two physical activity promotion programmes (ie, NEAT and ATLAS) that have been modified for scalability; and (2) evaluate the dissemination of these programmes throughout government funded secondary schools. Methods and analysis The study will be conducted in two phases. In the first phase (cluster randomised controlled trial), 16 schools will be randomly allocated to the intervention or a usual care control condition. In the second phase, the Reach, Effectiveness, Adoption, Implementation and Maintenance (Re-AIM) framework will be used to guide the design and evaluation of programme dissemination throughout New South Wales (NSW), Australia. In both phases, teachers will be trained to deliver the NEAT and ATLAS programmes, which will include: (1) interactive student seminars; (2) structured physical activity programmes; (3) lunch-time fitness sessions; and (4) web-based smartphone apps. In the cluster RCT, study outcomes will be assessed at baseline, 6 months (primary end point) and 12-months. Muscular fitness will be the primary outcome and secondary outcomes will include: objectively measured body composition, cardiorespiratory fitness, flexibility, resistance training skill competency, physical activity, self-reported recreational screen-time, sleep, sugar-sweetened beverage and junk food snack consumption, self-esteem and well-being

Protocol for PIT: a phase III trial of prophylactic irradiation of tracts in patients with malignant pleural mesothelioma following invasive chest wall intervention.

INTRODUCTION: Histological diagnosis of malignant mesothelioma requires an invasive procedure such as CT-guided needle biopsy, thoracoscopy, video-assisted thorascopic surgery (VATs) or thoracotomy. These invasive procedures encourage tumour cell seeding at the intervention site and patients can develop tumour nodules within the chest wall. In an effort to prevent nodules developing, it has been widespread practice across Europe to irradiate intervention sites postprocedure--a practice known as prophylactic irradiation of tracts (PIT). To date there has not been a suitably powered randomised trial to determine whether PIT is effective at reducing the risk of chest wall nodule development. METHODS AND ANALYSIS: In this multicentre phase III randomised controlled superiority trial, 374 patients who can receive radiotherapy within 42 days of a chest wall intervention will be randomised to receive PIT or no PIT. Patients will be randomised on a 1:1 basis. Radiotherapy in the PIT arm will be 21 Gy in three fractions. Subsequent chemotherapy is given at the clinicians' discretion. A reduction in the incidence of chest wall nodules from 15% to 5% in favour of radiotherapy 6 months after randomisation would be clinically significant. All patients will be followed up for up to 2 years with monthly telephone contact and at least four outpatient visits in the first year. ETHICS AND DISSEMINATION: PIT was approved by NRES Committee North West-Greater Manchester West (REC reference 12/NW/0249) and recruitment is currently on-going, the last patient is expected to be randomised by the end of 2015. The analysis of the primary end point, incidence of chest wall nodules 6 months after randomisation, is expected to be published in 2016 in a peer reviewed journal and results will also be presented at scientific meetings and summary results published online. A follow-up analysis is expected to be published in 2018. TRIAL REGISTRATION NUMBER: ISRCTN04240319; NCT01604005; Pre-results

A Dynamic Model of Interactions of Ca^(2+), Calmodulin, and Catalytic Subunits of Ca^(2+)/Calmodulin-Dependent Protein Kinase II

During the acquisition of memories, influx of Ca^(2+) into the postsynaptic spine through the pores of activated N-methyl-D-aspartate-type glutamate receptors triggers processes that change the strength of excitatory synapses. The pattern of Ca^(2+) influx during the first few seconds of activity is interpreted within the Ca^(2+)-dependent signaling network such that synaptic strength is eventually either potentiated or depressed. Many of the critical signaling enzymes that control synaptic plasticity, including Ca^(2+)/calmodulin-dependent protein kinase II (CaMKII), are regulated by calmodulin, a small protein that can bind up to 4 Ca^(2+) ions. As a first step toward clarifying how the Ca^(2+)-signaling network decides between potentiation or depression, we have created a kinetic model of the interactions of Ca^(2+), calmodulin, and CaMKII that represents our best understanding of the dynamics of these interactions under conditions that resemble those in a postsynaptic spine. We constrained parameters of the model from data in the literature, or from our own measurements, and then predicted time courses of activation and autophosphorylation of CaMKII under a variety of conditions. Simulations showed that species of calmodulin with fewer than four bound Ca^(2+) play a significant role in activation of CaMKII in the physiological regime, supporting the notion that processing ofCa^(2+) signals in a spine involves competition among target enzymes for binding to unsaturated species of CaM in an environment in which the concentration of Ca^(2+) is fluctuating rapidly. Indeed, we showed that dependence of activation on the frequency of Ca^(2+) transients arises from the kinetics of interaction of fluctuating Ca^(2+) with calmodulin/CaMKII complexes. We used parameter sensitivity analysis to identify which parameters will be most beneficial to measure more carefully to improve the accuracy of predictions. This model provides a quantitative base from which to build more complex dynamic models of postsynaptic signal transduction during learning

A user-friendly web portal for T-Coffee on supercomputers

<p>Abstract</p> <p>Background</p> <p>Parallel T-Coffee (PTC) was the first parallel implementation of the T-Coffee multiple sequence alignment tool. It is based on MPI and RMA mechanisms. Its purpose is to reduce the execution time of the large-scale sequence alignments. It can be run on distributed memory clusters allowing users to align data sets consisting of hundreds of proteins within a reasonable time. However, most of the potential users of this tool are not familiar with the use of grids or supercomputers.</p> <p>Results</p> <p>In this paper we show how PTC can be easily deployed and controlled on a super computer architecture using a web portal developed using Rapid. Rapid is a tool for efficiently generating standardized portlets for a wide range of applications and the approach described here is generic enough to be applied to other applications, or to deploy PTC on different HPC environments.</p> <p>Conclusions</p> <p>The PTC portal allows users to upload a large number of sequences to be aligned by the parallel version of TC that cannot be aligned by a single machine due to memory and execution time constraints. The web portal provides a user-friendly solution.</p

Structure-guided selection of specificity determining positions in the human kinome

Background: The human kinome contains many important drug targets. It is well-known that inhibitors of protein kinases bind with very different selectivity profiles. This is also the case for inhibitors of many other protein families. The increased availability of protein 3D structures has provided much information on the structural variation within a given protein family. However, the relationship between structural variations and binding specificity is complex and incompletely understood. We have developed a structural bioinformatics approach which provides an analysis of key determinants of binding selectivity as a tool to enhance the rational design of drugs with a specific selectivity profile. Results: We propose a greedy algorithm that computes a subset of residue positions in a multiple sequence alignment such that structural and chemical variation in those positions helps explain known binding affinities. By providing this information, the main purpose of the algorithm is to provide experimentalists with possible insights into how the selectivity profile of certain inhibitors is achieved, which is useful for lead optimization. In addition, the algorithm can also be used to predict binding affinities for structures whose affinity for a given inhibitor is unknown. The algorithm’s performance is demonstrated using an extensive dataset for the human kinome. Conclusion: We show that the binding affinity of 38 different kinase inhibitors can be explained with consistently high precision and accuracy using the variation of at most six residue positions in the kinome binding site. We show for several inhibitors that we are able to identify residues that are known to be functionally important

Species-level functional profiling of metagenomes and metatranscriptomes.

Functional profiles of microbial communities are typically generated using comprehensive metagenomic or metatranscriptomic sequence read searches, which are time-consuming, prone to spurious mapping, and often limited to community-level quantification. We developed HUMAnN2, a tiered search strategy that enables fast, accurate, and species-resolved functional profiling of host-associated and environmental communities. HUMAnN2 identifies a community's known species, aligns reads to their pangenomes, performs translated search on unclassified reads, and finally quantifies gene families and pathways. Relative to pure translated search, HUMAnN2 is faster and produces more accurate gene family profiles. We applied HUMAnN2 to study clinal variation in marine metabolism, ecological contribution patterns among human microbiome pathways, variation in species' genomic versus transcriptional contributions, and strain profiling. Further, we introduce 'contributional diversity' to explain patterns of ecological assembly across different microbial community types

Proactive environmental strategy in a supply chain context: The mediating role of investments

Abstract: There is a growing body of knowledge on the link between environmental management and supply chain management, but there is contradicting evidence on the impact of a proactive environmental strategy on environmental performance. Therefore, this paper investigates the impact of proactive environmental strategy on environmental performance as mediated by environmental investments. We also consider the antecedents of the adoption of proactive environmental strategy. We develop and test hypotheses, using data collected from 96 Turkish manufacturers through an online questionnaire. The model was tested using Partial Least Squares (PLS), a structural equation modelling method. The results show that a proactive environmental strategy leads to higher environmental investments; both internally and externally in collaboration with suppliers. Our findings support our hypothesis that environmental investments acts as a mediating variable between proactive environmental strategy and environmental performance. The results also show that customer pressure and, particularly, organizational commitment positively impact the extent to which firms adopt a proactive environmental strategy

Bordetella pertussis Autotransporter Vag8 Binds Human C1 Esterase Inhibitor and Confers Serum Resistance

Bordetella pertussis employs numerous strategies to evade the immune system, including the ability to resist killing via complement. Previously we have shown that B. pertussis binds a complement regulatory protein, C1 esterase inhibitor (C1inh) to its surface in a Bvg-regulated manner (i.e. during its virulence phase), but the B. pertussis factor was not identified. Here we set out to identify the B. pertussis C1inh-binding factor. Using a serum overlay assay, we found that this factor migrates at approximately 100 kDa on an SDS-PAGE gel. To identify this factor, we isolated proteins of approximately 100 kDa from wild type strain BP338 and from BP347, an isogenic Bvg mutant that does not bind C1inh. Using mass spectrometry and bioinformatics, we identified the autotransporter protein Vag8 as the putative C1inh binding protein. To prove that Vag8 binds C1inh, vag8 was disrupted in two different B. pertussis strains, namely BP338 and 18–323, and the mutants were tested for their ability to bind C1inh in a surface-binding assay. Neither mutant strain was capable of binding C1inh, whereas a complemented strain successfully bound C1inh. In addition, the passenger domain of Vag8 was expressed and purified as a histidine-tagged fusion protein and tested for C1inh-binding in an ELISA assay. Whereas the purified Vag8 passenger bound C1inh, the passenger domain of BrkA (a related autotransporter protein) failed to do so. Finally, serum assays were conducted to compare wild type and vag8 mutants. We determined that vag8 mutants from both strains were more susceptible to killing compared to their isogenic wild type counterparts. In conclusion, we have discovered a novel role for the previously uncharacterized protein Vag8 in the immune evasion of B. pertussis. Vag8 binds C1inh to the surface of the bacterium and confers serum resistance