Distribution patterns of three sodium channel mutations associated with pyrethroid resistance in Rhipicephalus (Boophilus) microplus populations from North and South America, South Africa and Australia

AbstractResistance to synthetic pyrethroids (SP) in the cattle tick Rhipicephalus (Boophilus) microplus is widespread throughout its distribution area. Three single nucleotide substitutions identified in Domains II and III of the sodium channel gene of R. (B.) microplus are known to be associated with target site pyrethroid resistance. We developed a multiplex PCR using allele-specific primers to amplify wild type or mutated genotypes of the three mutations simultaneously. This assay was used to screen tick samples originating from Brazil, Argentina, Mexico, South Africa and Australia whose phenotype to flumethrin and cypermethrin had been determined by the use of the Larval Tarsal test (LTT) or the Larval Packet Test (LPT). These mutations were found to have distinct geographical distributions and result in different resistance phenotypes. The L64I Domain II mutation conferring resistance to several SP compounds was found in all the Brazilian, Argentinean and Australian populations and in one South African population, with frequencies between 38% and 100% in flumethrin and cypermethrin resistant populations. In contrast, this mutation was not found in samples from Mexico, while the Domain III mutation was found exclusively in this country. The G72V Domain II flumethrin-specific mutation was found in a single Australian population, with a very low resistant allele frequency (3%). The homozygous resistant RR genotype of the L64I Domain II mutation correlated significantly with the survival rates at the discriminating doses of flumethrin and cypermethrin. This survey shows the widespread distribution of the L64I Domain II mutation and provides evidence of its geographic separation from the Domain III mutation

Source Attribution and Interannual Variability of Arctic Pollution in Spring Constrained by Aircraft (ARCTAS, ARCPAC) and Satellite (AIRS) Observations of Carbon Monoxide

We use aircraft observations of carbon monoxide (CO) from the NASA ARCTAS and NOAA ARCPAC campaigns in April 2008 together with multiyear (2003–2008) CO satellite data from the AIRS instrument and a global chemical transport model (GEOS-Chem) to better understand the sources, transport, and interannual variability of pollution in the Arctic in spring. Model simulation of the aircraft data gives best estimates of CO emissions in April 2008 of $26 Tg month^{−1}$ for Asian anthropogenic, 9.4 for European anthropogenic, 4.1 for North American anthropogenic, 15 for Russian biomass burning (anomalously large that year), and 23 for Southeast Asian biomass burning. We find that Asian anthropogenic emissions are the dominant source of Arctic CO pollution everywhere except in surface air where European anthropogenic emissions are of similar importance. Russian biomass burning makes little contribution to mean CO (reflecting the long CO lifetime) but makes a large contribution to CO variability in the form of combustion plumes. Analysis of two pollution events sampled by the aircraft demonstrates that AIRS can successfully observe pollution transport to the Arctic in the mid-troposphere. The 2003–2008 record of CO from AIRS shows that interannual variability averaged over the Arctic cap is very small. AIRS CO columns over Alaska are highly correlated with the Ocean Niño Index, suggesting a link between El Niño and Asian pollution transport to the Arctic. AIRS shows lower-than-average CO columns over Alaska during April 2008, despite the Russian fires, due to a weakened Aleutian Low hindering transport from Asia and associated with the moderate 2007–2008 La Niña. This suggests that Asian pollution influence over the Arctic may be particularly large under strong El Niño conditions.Engineering and Applied Science

Recommendations for the clinical management of patients receiving macitentan for pulmonary arterial hypertension (PAH): A Delphi consensus document

In patients treated with macitentan (Opsumit®, Actelion Pharmaceuticals Ltd., Basel, Switzerland) for pulmonary arterial hypertension (PAH), prevention and/or effective management of treatment-related adverse events may improve adherence. However, management of these adverse events can be challenging and the base of evidence and clinical experience for macitentan is limited. In the absence of evidence, consensus recommendations from physicians experienced in using macitentan to treat PAH may benefit patients and physicians who are using macitentan. Consensus recommendations were developed by a panel of physicians experienced with macitentan and PAH using a modified Delphi process. Over three iterations, panelists developed and refined a series of statements on the use of macitentan in PAH and rated their agreement with each statement on a Likert scale. The panel of 18 physicians participated and developed a total of 118 statements on special populations, add-on therapy, drug-drug interactions, warnings and precautions, hospitalization and functional class, and adverse event management. The resulting consensus recommendations are intended to provide practical guidance on real-world issues in using macitentan to treat patients with PAH

HighResMIP versions of EC-Earth: EC-Earth3P and EC-Earth3P-HR - Description, model computational performance and basic validation

A new global high-resolution coupled climate model, EC-Earth3P-HR has been developed by the EC-Earth consortium, with a resolution of approximately 40 km for the atmosphere and 0.25° for the ocean, alongside with a standard-resolution version of the model, EC-Earth3P (80 km atmosphere, 1.0 ° ocean). The model forcing and simulations follow the High Resolution Model Intercomparison Project (HighResMIP) protocol. According to this protocol, all simulations are made with both high and standard resolutions. The model has been optimized with respect to scalability, performance, data storage and post-processing. In accordance with the HighResMIP protocol, no specific tuning for the high-resolution version has been applied. Increasing horizontal resolution does not result in a general reduction of biases and overall improvement of the variability, and deteriorating impacts can be detected for specific regions and phenomena such as some Euro-Atlantic weather regimes, whereas others such as the El Niño-Southern Oscillation show a clear improvement in their spatial structure. The omission of specific tuning might be responsible for this. The shortness of the spin-up, as prescribed by the HighResMIP protocol, prevented the model from reaching equilibrium. The trend in the control and historical simulations, however, appeared to be similar, resulting in a warming trend, obtained by subtracting the control from the historical simulation, close to the observational one

Climate and air quality impacts due to mitigation of non-methane near-term climate forcers

It is important to understand how future environmental policies will impact both climate change and air pollution. Although targeting near-term climate forcers (NTCFs), defined here as aerosols, tropospheric ozone, and precursor gases, should improve air quality, NTCF reductions will also impact climate. Prior assessments of the impact of NTCF mitigation on air quality and climate have been limited. This is related to the idealized nature of some prior studies, simplified treatment of aerosols and chemically reactive gases, as well as a lack of a sufficiently large number of models to quantify model diversity and robust responses. Here, we quantify the 2015-2055 climate and air quality effects of non-methane NTCFs using nine state-of-the-art chemistry-climate model simulations conducted for the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). Simulations are driven by two future scenarios featuring similar increases in greenhouse gases (GHGs) but with weak (SSP3-7.0) versus strong (SSP3-7.0-lowNTCF) levels of air quality control measures. As SSP3-7.0 lacks climate policy and has the highest levels of NTCFs, our results (e.g., surface warming) represent an upper bound. Unsurprisingly, we find significant improvements in air quality under NTCF mitigation (strong versus weak air quality controls). Surface fine particulate matter (PM2:5) and ozone (O3) decrease by 2:20:32 ugm3 and 4:60:88 ppb, respectively (changes quoted here are for the entire 2015-2055 time period; uncertainty represents the 95% confidence interval), over global land surfaces, with larger reductions in some regions including south and southeast Asia. Non-methane NTCF mitigation, however, leads to additional climate change due to the removal of aerosol which causes a net warming effect, including global mean surface temperature and precipitation increases of 0:250:12K and 0:030:012mmd1, respectively. Similarly, increases in extreme weather indices, including the hottest and wettest days, also occur. Regionally, the largest warming and wetting occurs over Asia, including central and north Asia (0:660:20K and 0:030:02mmd1), south Asia (0:470:16K and 0:170:09mmd1), and east Asia (0:460:20K and 0:150:06mmd1). Relatively large warming and wetting of the Arctic also occur at 0:590:36K and 0:040:02mmd1, respectively. Similar surface warming occurs in model simulations with aerosol-only mitigation, implying weak cooling due to ozone reductions. Our findings suggest that future policies that aggressively target non-methane NTCF reductions will improve air quality but will lead to additional surface warming, particularly in Asia and the Arctic. Policies that address other NTCFs including methane, as well as carbon dioxide emissions, must also be adopted to meet climate mitigation goals. © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License

Mining clinical relationships from patient narratives

Background The Clinical E-Science Framework (CLEF) project has built a system to extract clinically significant information from the textual component of medical records in order to support clinical research, evidence-based healthcare and genotype-meets-phenotype informatics. One part of this system is the identification of relationships between clinically important entities in the text. Typical approaches to relationship extraction in this domain have used full parses, domain-specific grammars, and large knowledge bases encoding domain knowledge. In other areas of biomedical NLP, statistical machine learning (ML) approaches are now routinely applied to relationship extraction. We report on the novel application of these statistical techniques to the extraction of clinical relationships. Results We have designed and implemented an ML-based system for relation extraction, using support vector machines, and trained and tested it on a corpus of oncology narratives hand-annotated with clinically important relationships. Over a class of seven relation types, the system achieves an average F1 score of 72%, only slightly behind an indicative measure of human inter annotator agreement on the same task. We investigate the effectiveness of different features for this task, how extraction performance varies between inter- and intra-sentential relationships, and examine the amount of training data needed to learn various relationships. Conclusion We have shown that it is possible to extract important clinical relationships from text, using supervised statistical ML techniques, at levels of accuracy approaching those of human annotators. Given the importance of relation extraction as an enabling technology for text mining and given also the ready adaptability of systems based on our supervised learning approach to other clinical relationship extraction tasks, this result has significance for clinical text mining more generally, though further work to confirm our encouraging results should be carried out on a larger sample of narratives and relationship types

Asymmetric shallow mantle structure beneath the Hawaiian Swell—evidence from Rayleigh waves recorded by the PLUME network

Author Posting. © The Author(s), 2011. This article is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Geophysical Journal International 187 (2011): 1725–1742, doi:10.1111/j.1365-246X.2011.05238.x.We present models of the 3-D shear velocity structure of the lithosphere and asthenosphere beneath the Hawaiian hotspot and surrounding region. The models are derived from long-period Rayleigh-wave phase velocities that were obtained from the analysis of seismic recordings collected during two year-long deployments for the Hawaiian Plume-Lithosphere Undersea Mantle Experiment. For this experiment, broad-band seismic sensors were deployed at nearly 70 seafloor sites as well as 10 sites on the Hawaiian Islands. Our seismic images result from a two-step inversion of path-averaged dispersion curves using the two-station method. The images reveal an asymmetry in shear velocity structure with respect to the island chain, most notably in the lower lithosphere at depths of 60 km and greater, and in the asthenosphere. An elongated, 100-km-wide and 300-km-long low-velocity anomaly reaches to depths of at least 140 km. At depths of 60 km and shallower, the lowest velocities are found near the northern end of the island of Hawaii. No major velocity anomalies are found to the south or southeast of Hawaii, at any depth. The low-velocity anomaly in the asthenosphere is consistent with an excess temperature of 200–250 °C and partial melt at the level of a few percent by volume, if we assume that compositional variations as a result of melt extraction play a minor role. We also image small-scale low-velocity anomalies within the lithosphere that may be associated with the volcanic fields surrounding the Hawaiian Islands.This research was financed by the National Science Foundation under grants OCE-00-02470 and OCE-00-02819. Markee was partly sponsored by a SIO graduate student fellowship

Significant climate benefits from near-term climate forcer mitigation in spite of aerosol reductions

Near-term climate forcers (NTCFs), including aerosols and chemically reactive gases such as tropospheric ozone and methane, offer a potential way to mitigate climate change and improve air quality-so called "win-win" mitigation policies. Prior studies support improved air quality under NTCF mitigation, but with conflicting climate impacts that range from a significant reduction in the rate of global warming to only a modest impact. Here, we use state-of-the-art chemistry-climate model simulations conducted as part of the Aerosol and Chemistry Model Intercomparison project (AerChemMIP) to quantify the 21st-century impact of NTCF reductions, using a realistic future emission scenario with a consistent air quality policy. Non-methane NTCF (NMNTCF; aerosols and ozone precursors) mitigation improves air quality, but leads to significant increases in global mean precipitation of 1.3% by mid-century and 1.4% by end-of-the-century, and corresponding surface warming of 0.23 and 0.21 K. NTCF (all-NTCF; including methane) mitigation further improves air quality, with larger reductions of up to 45% for ozone pollution, while offsetting half of the wetting by mid-century (0.7% increase) and all the wetting by end-of-the-century (non-significant 0.1% increase) and leading to surface cooling of -0.15 K by mid-century and -0.50 K by end-of-the-century. This suggests that methane mitigation offsets warming induced from reductions in NMNTCFs, while also leading to net improvements in air quality

The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6

The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond