Drivers of Cape Verde archipelagic endemism in keyhole limpets

Oceanic archipelagos are the ideal setting for investigating processes that shape species assemblages. Focusing on keyhole limpets, genera Fissurella and Diodora from Cape Verde Islands, we used an integrative approach combining molecular phylogenetics with ocean transport simulations to infer species distribution patterns and analyse connectivity. Dispersal simulations, using pelagic larval duration and ocean currents as proxies, showed a reduced level of connectivity despite short distances between some of the islands. It is suggested that dispersal and persistence driven by patterns of oceanic circulation favouring self-recruitment played a primary role in explaining contemporary species distributions. Mitochondrial and nuclear data revealed the existence of eight Cape Verde endemic lineages, seven within Fissurella, distributed across the archipelago, and one within Diodora restricted to Boavista. The estimated origins for endemic Fissurella and Diodora were 10.2 and 6.7 MY, respectively. Between 9.5 and 4.5 MY, an intense period of volcanism in Boavista might have affected Diodora, preventing its diversification. Having originated earlier, Fissurella might have had more opportunities to disperse to other islands and speciate before those events. Bayesian analyses showed increased diversification rates in Fissurella possibly promoted by low sea levels during Plio-Pleistocene, which further explain differences in species richness between both genera.FCT - Portuguese Science Foundation [SFRH/BPD/109685/2015, SFRH/BPD/111003/2015]; Norte Portugal Regional Operational Program (NORTE), under the PORTUGAL Partnership Agreement, through the European Regional Development Fund (ERDF) [MARINFO - NORTE-01-0145-FEDER-000031]info:eu-repo/semantics/publishedVersio

Evolutionary genomics of a cold-adapted diatom: Fragilariopsis cylindrus

The Southern Ocean houses a diverse and productive community of organisms1, 2. Unicellular eukaryotic diatoms are the main primary producers in this environment, where photosynthesis is limited by low concentrations of dissolved iron and large seasonal fluctuations in light, temperature and the extent of sea ice3, 4, 5, 6, 7. How diatoms have adapted to this extreme environment is largely unknown. Here we present insights into the genome evolution of a cold-adapted diatom from the Southern Ocean, Fragilariopsis cylindrus8, 9, based on a comparison with temperate diatoms. We find that approximately 24.7 per cent of the diploid F. cylindrus genome consists of genetic loci with alleles that are highly divergent (15.1 megabases of the total genome size of 61.1 megabases). These divergent alleles were differentially expressed across environmental conditions, including darkness, low iron, freezing, elevated temperature and increased CO2. Alleles with the largest ratio of non-synonymous to synonymous nucleotide substitutions also show the most pronounced condition-dependent expression, suggesting a correlation between diversifying selection and allelic differentiation. Divergent alleles may be involved in adaptation to environmental fluctuations in the Southern Ocean

Molecular signature for receptor engagement in the metabolic peptide hormone amylin

The pancreatic peptide hormone, amylin, plays a critical role in the control of appetite, and synergizes with other key metabolic hormones such as glucagon-like peptide 1 (GLP-1). There is opportunity to develop potent and long-acting analogs of amylin or hybrids between these and GLP-1 mimetics for treating obesity. To achieve this, interrogation of how the 37 amino acid amylin peptide engages with its complex receptor system is required. We synthesized an extensive library of peptides to profile the human amylin sequence, determining the role of its disulfide loop, amidated C-terminus and receptor “capture” and “activation” regions in receptor signaling. We profiled four signaling pathways with different ligands at multiple receptor subtypes, in addition to exploring selectivity determinants between related receptors. Distinct roles for peptide sub-regions in receptor binding and activation were identified, resulting in peptides with greater activity than the native sequence. Enhanced peptide activity was preserved in the brainstem, the major biological target for amylin. Interpretation of our data using full-length active receptor models supported by molecular dynamics, metadynamics and supervised molecular dynamics simulations guided the synthesis of a potent dual agonist of GLP-1 and amylin receptors. The data offer new insights into the function of peptide amidation, how allostery drives peptide-receptor interactions, and provide a valuable resource for the development of novel amylin agonists for treating diabetes and obesity

Split-based computation of majority-rule supertrees

<p>Abstract</p> <p>Background</p> <p>Supertree methods combine overlapping input trees into a larger supertree. Here, I consider split-based supertree methods that first extract the split information of the input trees and subsequently combine this split information into a phylogeny. Well known split-based supertree methods are matrix representation with parsimony and matrix representation with compatibility. Combining input trees on the same taxon set, as in the consensus setting, is a well-studied task and it is thus desirable to generalize consensus methods to supertree methods.</p> <p>Results</p> <p>Here, three variants of majority-rule (MR) supertrees that generalize majority-rule consensus trees are investigated. I provide simple formulas for computing the respective score for bifurcating input- and supertrees. These score computations, together with a heuristic tree search minmizing the scores, were implemented in the python program PluMiST (Plus- and Minus SuperTrees) available from <url>http://www.cibiv.at/software/plumist</url>. The different MR methods were tested by simulation and on real data sets. The search heuristic was successful in combining compatible input trees. When combining incompatible input trees, especially one variant, MR(-) supertrees, performed well.</p> <p>Conclusions</p> <p>The presented framework allows for an efficient score computation of three majority-rule supertree variants and input trees. I combined the score computation with a heuristic search over the supertree space. The implementation was tested by simulation and on real data sets and showed promising results. Especially the MR(-) variant seems to be a reasonable score for supertree reconstruction. Generalizing these computations to multifurcating trees is an open problem, which may be tackled using this framework.</p

Effectiveness of classroom based crew resource management training in the intensive care unit: study design of a controlled trial

<p>Abstract</p> <p>Background</p> <p>Crew resource management (CRM) has the potential to enhance patient safety in intensive care units (ICU) by improving the use of non-technical skills. However, CRM evaluation studies in health care are inconclusive with regard to the effect of this training on behaviour and organizational outcomes, due to weak study designs and the scarce use of direct observations. Therefore, the aim of this study is to determine the effectiveness and cost-effectiveness of CRM training on attitude, behaviour and organization after one year, using a multi-method approach and matched control units. The purpose of the present article is to describe the study protocol and the underlying choices of this evaluation study of CRM in the ICU in detail.</p> <p>Methods/Design</p> <p>Six ICUs participated in a paired controlled trial, with one pre-test and two post test measurements (respectively three months and one year after the training). Three ICUs were trained and compared to matched control ICUs. The 2-day classroom-based training was delivered to multidisciplinary groups. Typical CRM topics on the individual, team and organizational level were discussed, such as situational awareness, leadership and communication. All levels of Kirkpatrick's evaluation framework (reaction, learning, behaviour and organisation) were assessed using questionnaires, direct observations, interviews and routine ICU administration data.</p> <p>Discussion</p> <p>It is expected that the CRM training acts as a generic intervention that stimulates specific interventions. Besides effectiveness and cost-effectiveness, the assessment of the barriers and facilitators will provide insight in the implementation process of CRM.</p> <p>Trial registration</p> <p>Netherlands Trial Register (NTR): <a href="http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=1976">NTR1976</a></p

Beyond quantitative and qualitative traits: three telling cases in the life sciences

This paper challenges the common assumption that some phenotypic traits are quantitative while others are qualitative. The distinction between these two kinds of traits is widely influential in biological and biomedical research as well as in scientific education and communication. This is probably due to both historical and epistemological reasons. However, the quantitative/qualitative distinction involves a variety of simplifications on the genetic causes of phenotypic variability and on the development of complex traits. Here, I examine three cases from the life sciences that show inconsistencies in the distinction: Mendelian traits (dwarfism and pigmentation in plant and animal models), Mendelian diseases (phenylketonuria), and polygenic mental disorders (schizophrenia). I show that these traits can be framed both quantitatively and qualitatively depending, for instance, on the methods through which they are investigated and on specific epistemic purposes (e.g., clinical diagnosis versus causal explanation). This suggests that the received view of quantitative and qualitative traits has a limited heuristic power—limited to some local contexts or to the specific methodologies adopted. Throughout the paper, I provide directions for framing phenotypes beyond the quantitative/qualitative distinction. I conclude by pointing at the necessity of developing a principled characterisation of what phenotypic traits, in general, are

Non-technical Skills in Healthcare

AbstractNon-technical Skills (NTS) are a set of generic cognitive and social skills, exhibited by individuals and teams, that support technical skills when performing complex tasks. Typical NTS training topics include performance shaping factors, planning and preparation for complex tasks, situation awareness, perception of risk, decision-making, communication, teamwork and leadership. This chapter provides a framework for understanding these skills in theory and practice, how they interact, and how they have been applied in healthcare, as well as avenues for future research

Denial of long-term issues with agriculture on tropical peatlands will have devastating consequences

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