Jenson Button is not expecting to repeat his race-winning Australian Grand Prix performance at the coming rounds of the championship

Governments and the chemical industry spend millions of dollars every year testing the safety of chemicals that people use in their everyday lives. Computer modelling, through the OECD-designed QSAR Toolbox software, now replaces many of the tests traditionally done in the laboratory. This allows regulators and industry to save money and use fewer animals to predict the hazardous properties of chemicals.

11/07/2013 –Recently the OECD released the third generation of the QSAR Toolbox. For this purpose, the guidance document for grouping chemicals to fill data gaps for genetic toxicity and genotoxic carcinogenicity have been updated. This guidance document should support the user of the QSAR Toolbox to build categories that are mechanistically and structurally robust.

11/07/2013 –Recently the OECD released the third generation of the QSAR Toolbox. For this purpose, the guidance document for grouping chemicals to fill data gaps for acute aquatic toxicity have been updated. This guidance document should support the user of the QSAR Toolbox to build categories that are mechanistically and structurally robust.

This document compiles information on the current methodologies, tools and models and helps readers identify appropriate models/ and methodologies for estimating substance-specific removal/emissions from wastewater treatment systems. It could support efforts to improve these models and tools.

Once a medical approach is accepted, its use tends to spread across the population and income groups. We therefore need to start preparing for the advance of personalised medicine, writes Sujatha Byravan

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Ancient underwater landslides help Brit scientists predict tsunamis  Metro.co.uk

Ancient underwater landslides help predict tsunami risk  Aberdeen Evening Express

This study describes a method to estimate the likelihood of success in determining a macromolecular structure by X-ray crystallography and experimental single-wavelength anomalous dispersion (SAD) or multiple-wavelength anomalous dispersion (MAD) phasing based on initial data-processing statistics and sample crystal properties. Such a predictive tool can rapidly assess the usefulness of data and guide the collection of an optimal data set. The increase in data rates from modern macromolecular crystallography beamlines, together with a demand from users for real-time feedback, has led to pressure on computational resources and a need for smarter data handling. Statistical and machine-learning methods have been applied to construct a classifier that displays 95% accuracy for training and testing data sets compiled from 440 solved structures. Applying this classifier to new data achieved 79% accuracy. These scores already provide clear guidance as to the effective use of computing resources and offer a starting point for a personalized data-collection assistant.

Current software tools for the automated building of models for macro­molecular X-ray crystal structures are capable of assembling high-quality models for ordered macromolecule and small-molecule scattering components with minimal or no user supervision. Many of these tools also incorporate robust functionality for modelling the ordered water molecules that are found in nearly all macromolecular crystal structures. However, no current tools focus on differentiating these ubiquitous water molecules from other frequently occurring multi-atom solvent species, such as sulfate, or the automated building of models for such species. PeakProbe has been developed specifically to address the need for such a tool. PeakProbe predicts likely solvent models for a given point (termed a `peak') in a structure based on analysis (`probing') of its local electron density and chemical environment. PeakProbe maps a total of 19 resolution-dependent features associated with electron density and two associated with the local chemical environment to a two-dimensional score space that is independent of resolution. Peaks are classified based on the relative frequencies with which four different classes of solvent (including water) are observed within a given region of this score space as determined by large-scale sampling of solvent models in the Protein Data Bank. Designed to classify peaks generated from difference density maxima, PeakProbe also incorporates functionality for identifying peaks associated with model errors or clusters of peaks likely to correspond to multi-atom solvent, and for the validation of existing solvent models using solvent-omit electron-density maps. When tasked with classifying peaks into one of four distinct solvent classes, PeakProbe achieves greater than 99% accuracy for both peaks derived directly from the atomic coordinates of existing solvent models and those based on difference density maxima. While the program is still under development, a fully functional version is publicly available. PeakProbe makes extensive use of cctbx libraries, and requires a PHENIX licence and an up-to-date phenix.python environment for execution.

Molecular replacement (MR) is the predominant route to solution of the phase problem in macromolecular crystallography. Where the lack of a suitable homologue precludes conventional MR, one option is to predict the target structure using bioinformatics. Such modelling, in the absence of homologous templates, is called ab initio or de novo modelling. Recently, the accuracy of such models has improved significantly as a result of the availability, in many cases, of residue-contact predictions derived from evolutionary covariance analysis. Covariance-assisted ab initio models representing structurally uncharacterized Pfam families are now available on a large scale in databases, potentially representing a valuable and easily accessible supplement to the PDB as a source of search models. Here, the unconventional MR pipeline AMPLE is employed to explore the value of structure predictions in the GREMLIN and PconsFam databases. It was tested whether these deposited predictions, processed in various ways, could solve the structures of PDB entries that were subsequently deposited. The results were encouraging: nine of 27 GREMLIN cases were solved, covering target lengths of 109–355 residues and a resolution range of 1.4–2.9 Å, and with target–model shared sequence identity as low as 20%. The cluster-and-truncate approach in AMPLE proved to be essential for most successes. For the overall lower quality structure predictions in the PconsFam database, remodelling with Rosetta within the AMPLE pipeline proved to be the best approach, generating ensemble search models from single-structure deposits. Finally, it is shown that the AMPLE-obtained search models deriving from GREMLIN deposits are of sufficiently high quality to be selected by the sequence-independent MR pipeline SIMBAD. Overall, the results help to point the way towards the optimal use of the expanding databases of ab initio structure predictions.

The program Mercury, developed at the Cambridge Crystallographic Data Centre, was originally designed primarily as a crystal structure visualization tool. Over the years the fields and scientific communities of chemical crystallography and crystal engineering have developed to require more advanced structural analysis software. Mercury has evolved alongside these scientific communities and is now a powerful analysis, design and prediction platform which goes a lot further than simple structure visualization.

This work presents the crystal structure determination of two elusive polymorphs of furazidin, an antibacterial agent, employing a combination of crystal structure prediction (CSP) calculations and an NMR crystallography approach. Two previously uncharacterized neat crystal forms, one of which has two symmetry-independent molecules (form I), whereas the other one is a Z' = 1 polymorph (form II), crystallize in P21/c and P1 space groups, respectively, and both are built by different conformers, displaying different intermolecular interactions. It is demonstrated that the usage of either CSP or NMR crystallography alone is insufficient to successfully elucidate the above-mentioned crystal structures, especially in the case of the Z' = 2 polymorph. In addition, cases of serendipitous agreement in terms of 1H or 13C NMR data obtained for the CSP-generated crystal structures different from the ones observed in the laboratory (false-positive matches) are analyzed and described. While for the majority of analyzed crystal structures the obtained agreement with the NMR experiment is indicative of some structural features in common with the experimental structure, the mentioned serendipity observed in exceptional cases points to the necessity of caution when using an NMR crystallography approach in crystal structure determination.

Ecologists at the Smithsonian Environmental Research Center measure the growth rate of sedge grass in a brackish Chesapeake Bay marsh. Fed a diet rich in […]

The post SERC sedge grass experiment mimics predicted global-change scenario appeared first on Smithsonian Insider.

When most people look at a forest, they see walking trails, deer yards, or firewood for next winter. But scientists at the Harvard Forest and […]

The post Development will reduce carbon stored in forests, Smithsonian & Harvard scientists predict appeared first on Smithsonian Insider.

A July 12 news alert from NASA indicates a X1.4 class solar flare erupted from the center of the Sun, peaking July 12 at 12:52 P.M.

The post Coronal mass ejection from July 12 solar flare headed toward Earth; minor geomagnetic storm activity predicted appeared first on Smithsonian Insider.

Hundreds of experiments have shown biodiversity fosters healthier, more productive ecosystems. But many experts doubted whether these experiments would hold up in the real world. […]

The post In the wild, biodiversity’s power surpasses what experiments predict appeared first on Smithsonian Insider.

A new report from the National Academies of Sciences, Engineering, and Medicine calls for an international, multi-institutional comprehensive campaign of research, observation, and analysis activities that would help improve understanding and prediction of the Gulf of Mexico’s Loop Current System (LCS).

The emergence of inexpensive small unmanned aircraft systems (sUASs) that operate without a human pilot, commonly known as drones, has led to adversarial groups threatening deployed U.S. forces, especially infantry units.

The Gulf Research Program (GRP) of the National Academies of Sciences, Engineering, and Medicine today announced a new funding opportunity to provide up to $2.5 million in grants to foster innovative approaches that support its ongoing efforts to improve understanding and prediction of the Gulf of Mexico Loop Current System (LCS).

Urban flooding is a complex and distinct kind of flooding, compounded by land use and high population density, and it requires a different approach to assess and manage, says Framing the Challenge of Urban Flooding in the United States, a new report from the National Academies of Sciences, Engineering, and Medicine.

International thought leaders will join the next generation of engineers in London from Sept. 16 to 18 for the Global Grand Challenges Summit 2019. The summit aims to help inspire and equip future engineering leaders to address the rapidly evolving challenges of an unpredictable world.

The Gulf Research Program (GRP) of the National Academies of Sciences, Engineering, and Medicine today announced $2 million in grant awards for seven new projects through its Understanding Gulf Ocean Systems (UGOS) Grants 2 competition.

A cleaning crew disinfects a New York City subway train on May 4, 2020 in New York City. ; Credit: Stephanie Keith/Getty Images

As of Monday afternoon, L.A. County has at least 1,260 deaths and 26,238 confirmed cases of coronavirus. The United States has more than a million cases of the virus with more than 67,000 deaths. Meanwhile, new models put together by FEMA project that we could see up to 200,000 new cases a day by the end of the month, according to the New York Times. 

The L.A. Times reports that scientists have discovered a new strain of the deadly coronavirus that is even more contagious. The study finds that the new strain first appeared in February in Europe and has been the dominant strain across the world since mid-March. Plus, some COVID-19 patients are experiencing issues with blood clotting even after respiratory issues have died down. Today on AirTalk, we get the latest with an infectious disease specialist who will take your questions. Call 866-893-5722 to join the conversation. 

With files from LAist. Read the full story here.

Guest:

Dean Blumberg, M.D., professor of medicine and chief of Pediatric Infectious Diseases at UC Davis Children’s Hospital

This content is from Southern California Public Radio. View the original story at SCPR.org.

There is a common assumption that plant species are more inclined to thrive in a non-native community than a native one, sometimes becoming 'invasive'. However, this behaviour is likely to be quite unusual and invasive alien plants are actually an important exception, according to a new study. Much can be learned from the population of a species 'at home' and should be included in official assessment criteria.

Wealthier nations protect biodiversity no better than poorer nations, suggests new research. The study found no link between national GDP and the effectiveness of countries at conserving the species for which they have responsibility.

An early-warning system developed by researchers could help forest managers in Europe predict which trees are at greatest risk of bark- beetle infestation. The study looked at the probability of bark-beetle outbreaks on two important conifer-tree species in Slovenia: the Norway spruce (Picea abies) and silver fir (Abies alba). It found that high temperatures, and extreme weather linked to climate change — including droughts and ice storms — weakened trees, making them more vulnerable to attack by bark beetles.

An early warning system to predict the overfishing of individual species, far in advance of severe population decline, has been developed by researchers. The ‘eventual threat index’ was applied by the researchers to historical data on tuna and billfish populations, and accurately predicted their current declines as early as the 1950s.

Researchers have developed a prototype system to predict the impact of storms on European coastlines. The MICORE Early Warning System aims to improve civil defence and coastal evacuation plans and could pave the way for an autonomous early warning system to save countless lives and protect infrastructure worldwide.

Natural predators of agricultural pests are influenced by the type and range of habitats within a farming landscape. A new study has developed an approach which predicts the risk of pest infestation and natural predation according to landscape features, to help land managers structure landscapes that encourage natural pest control.

Noise pollution in urban areas can harm our physical and mental wellbeing, and can have damaging effects on urban wildlife. Now, researchers from China have shown for the first time how a ‘land use regression method’ can be used to model urban noise and predict the effects of future planning decisions on noise levels.

Research from the US helps paint a clearer picture of the extent of global sea level rise, by considering new satellite data on the Earth’s gravity. Its findings support reports of accelerating ice melt and suggest that most of the change in sea levels is caused by receding polar ice sheets and mountain glaciers.

Phytoplankton are essential to marine food webs and fisheries. However, a new study indicates that their levels have declined in the North Atlantic since the beginning of the 19th century. This coincides with weakening ocean-circulation patterns, partly caused by melting ice caps. If the melting continues, the study warns of a dramatic fall in North Atlantic plankton levels that could have cascading effects across marine food webs, reducing the ocean’s ability to absorb carbon and threatening the supply of seafood for humans.

Simple characteristics of plant species - such as height or leaf size - can be used to predict the ecosystem services provided by the green roofs they grow on, a new study suggests. The researchers suggest that their method could be used to screen the thousands of potential plant species in order to optimize green roof design.

Which types of buildings will require the least energy for heating and cooling under climate change? A study in Vienna, Austria, looked at the balance between heating and cooling demand in four different types of buildings. The research provides a method that could be useful for other European cities trying to adapt to climate change.

5G will cover more than 20 percent of the global population six years from now, according to the latest Ericsson Mobility Report

Openwave Mobility released predictions for 2018 based on two major pieces of analysis- the mobile video index (MVI) based on live data gathered from over 30 global mobile operators and the NFV Playbook, based on NFV trials and deployments with insight from leading industry analysts.

Recent research suggests that increasing the number of private electric vehicles would have very little impact on electricity consumption in Milan, Italy. However, unless there are suitable regulations, the daily demand for power to recharge the vehicles at peak times could overload the capacity of the electric supply system.

A new study has identified the factors that cause deterioration of Mediterranean pine plantations, to develop a model of that can predict the risk of forest decline to help inform forests management strategies under a changing climate. It suggests that loss of needles is the most useful predictor of decline for the species studied.

The North American pine wood nematode (PWN), Bursaphelenchus xylophilus, is a pest worm species that causes a disease known as pine wilt. It was discovered for the first time in the EU in Portuguese forests in 1999. Today, the entire territory of Portugal is demarcated for the presence of PWN, with a 20 km buffer zone, free from the pest, established along the Spanish border with the aim of preventing its further spread. The spread and establishment of PWN in the rest of EU territory is very likely if no strict measures are taken, as required by Decision 2012/535/EU of the European Commission, with serious economic and environmental consequences. To date, Spain has experienced five outbreaks of PWN, three of which have been successfully eradicated thanks to the EU measures and the effective work of the Spanish forest administration; and two outbreaks are currently being eradicated.

With ever-increasing global consumption, the impacts of resource depletion, land use change and pollution are being felt worldwide. A new study reveals how international trade is shifting the environmental burden from the consuming nation to other parts of the world, and calls for changes in the way national material use is accounted for.

To assess the impact on ecosystems of chemical contamination in aquatic environments, scientists need to measure not only the concentration of the contaminants, but also the extent to which they can disrupt biological processes at a cellular level in plants and animals and at an ecosystem level. According to a new study, considering these complex inter-relationships in combination will help improve the ecological status of waterways, in line with Water Framework Directive (WFD) commitments.

A tool to calculate the risk of food and waterborne diseases under current or future climate change conditions has been presented in a recent study. Free to use, the online tool can help guide climate change adaptation, such as improvements to water management, by estimating the likelihood of contracting four diseases under a range of environmental conditions.

Unusually warm or cool Pacific sea surface temperatures, known as El Niño and La Niña, can be used to reliably predict anomalies in flood risk for river basins that cover 44% of the Earth’s land surface, a new study has shown. The researchers also quantified overall flood damage by combining information on flood risk with estimates of damage to economies and numbers of people at risk. This could help improve flood disaster planning, they say.