The family Plectopylidae (Gastropoda, Pulmonata) in Laos with the description of two new genera and a new species

Previously only a single plectopylid species, Helix laomontana L. Pfeiffer, 1862 was reported from Laos. Here we erect Naggsia Páll-Gergely & Muratov, gen. n. for H. laomontana based on the description of its reproductive anatomy and radula. Another species, Hunyadiscus saurini Páll-Gergely, gen. & sp. n. is described from Northern Laos based on conchological data. Helix (Plectopylis) andersoni Blanford, 1869, which is known from the Burmese-Chinese border region, is also classified within Hunyadiscus Páll-Gergely, gen. n. A third species, Gudeodiscus (Gudeodiscus) messageri raheemi Páll-Gergely & Hunyadi, 2015 is reported from Laos for the first time. The new localities represent the westernmost sites of the genus Gudeodiscus. The reproductive anatomy of the latter species is described.ArticleZooKeys.592:1-26(2016)journal articl

Biofunctionality with a twist: the importance of molecular organisation, handedness and configuration in synthetic biomaterial design

The building blocks of life – nucleotides, amino acids and saccharides – give rise to a large variety of components and make up the hierarchical structures found in Nature. Driven by chirality and non-covalent interactions, helical and highly organised structures are formed and the way in which they fold correlates with specific recognition and hence function. A great amount of effort is being put into mimicking these highly specialised biosystems as biomaterials for biomedical applications, ranging from drug discovery to regenerative medicine. However, as well as lacking the complexity found in Nature, their bio-activity is sometimes low and hierarchical ordering is missing or underdeveloped. Moreover, small differences in folding in natural biomolecules (e.g., caused by mutations) can have a catastrophic effect on the function they perform. In order to develop biomaterials that are more efficient in interacting with biomolecules, such as proteins, DNA and cells, we speculate that incorporating order and handedness into biomaterial design is necessary. In this review, we first focus on order and handedness found in Nature in peptides, nucleotides and saccharides, followed by selected examples of synthetic biomimetic systems based on these components that aim to capture some aspects of these ordered features. Computational simulations are very helpful in predicting atomic orientation and molecular organisation, and can provide invaluable information on how to further improve on biomaterial designs. In the last part of the review, a critical perspective is provided along with considerations that can be implemented in next-generation biomaterial designs

Concurrent and Adaptive Extreme Scale Binding Free Energy Calculations

The efficacy of drug treatments depends on how tightly small molecules bind to their target proteins. The rapid and accurate quantification of the strength of these interactions (as measured by binding affinity) is a grand challenge of computational chemistry, surmounting which could revolutionize drug design and provide the platform for patient-specific medicine. Recent evidence suggests that molecular dynamics (MD) can achieve useful predictive accuracy (< 1 kcal/mol). For this predictive accuracy to impact clinical decision making, binding free energy computational campaigns must provide results rapidly and without loss of accuracy. This demands advances in algorithms, scalable software systems, and efficient utilization of supercomputing resources. We introduce a framework called HTBAC, designed to support accurate and scalable drug binding affinity calculations, while marshaling large simulation campaigns. We show that HTBAC supports the specification and execution of free-energy protocols at scale. This paper makes three main contributions: (1) shows the importance of adaptive execution for ensemble-based free energy protocols to improve binding affinity accuracy; (2) presents and characterizes HTBAC -- a software system that enables the scalable and adaptive execution of binding affinity protocols at scale; and (3) for a widely used free-energy protocol (TIES), shows improvements in the accuracy of simulations for a fixed amount of resource, or reduced resource consumption for a fixed accuracy as a consequence of adaptive execution

A practical method for optimum seismic design of friction wall dampers

Friction control systems have been widely used as one of the efficient and cost effective solutions to control structural damage during strong earthquakes. However, the height-wise distribution of slip loads can significantly affect the seismic performance of the strengthened frames. In this study, a practical design methodology is developed for more efficient design of friction wall dampers by performing extensive nonlinear dynamic analyses on 3, 5, 10, 15, and 20-story RC frames subjected to seven spectrum-compatible design earthquakes and five different slip load distribution patterns. The results show that a uniform cumulative distribution can provide considerably higher energy dissipation capacity than the commonly used uniform slip load pattern. It is also proved that for a set of design earthquakes, there is an optimum range for slip loads that is a function of number of stories. Based on the results of this study, an empirical equation is proposed to calculate a more efficient slip load distribution of friction wall dampers for practical applications. The efficiency of the proposed method is demonstrated through several design examples

Enabling trade-offs between accuracy and computational cost: Adaptive algorithms to reduce time to clinical insight

The efficacy of drug treatments depends on how tightly small molecules bind to their target proteins. Quantifying the strength of these interactions (the so called 'binding affinity') is a grand challenge of computational chemistry, surmounting which could revolutionize drug design and provide the platform for patient specific medicine. Recently, evidence from blind challenge predictions and retrospective validation studies has suggested that molecular dynamics (MD) can now achieve useful predictive accuracy (1 kcal/mol) This accuracy is sufficient to greatly accelerate hit to lead and lead optimization. To translate these advances in predictive accuracy so as to impact clinical and/or industrial decision making requires that binding free energy results must be turned around on reduced timescales without loss of accuracy. This demands advances in algorithms, scalable software systems, and intelligent and efficient utilization of supercomputing resources. This work is motivated by the real world problem of providing insight from drug candidate data on a time scale that is as short as possible. Specifically, we reproduce results from a collaborative project between UCL and GlaxoSmithKline to study a congeneric series of drug candidates binding to the BRD4 protein-inhibitors of which have shown promising preclinical efficacy in pathologies ranging from cancer to inflammation. We demonstrate the use of a framework called HTBAC, designed to support the aforementioned requirements of accurate and rapid drug binding affinity calculations. HTBAC facilitates the execution of the numbers of simulations while supporting the adaptive execution of algorithms. Furthermore, HTBAC enables the selection of simulation parameters during runtime which can, in principle, optimize the use of computational resources whilst producing results within a target uncertainty

The Highly Energetic Expansion of SN2010bh Associated with GRB 100316D

We present the spectroscopic and photometric evolution of the nearby (z = 0.059) spectroscopically confirmed type Ic supernova, SN 2010bh, associated with the soft, long-duration gamma-ray burst (X-ray flash) GRB 100316D. Intensive follow-up observations of SN 2010bh were performed at the ESO Very Large Telescope (VLT) using the X-shooter and FORS2 instruments. Owing to the detailed temporal coverage and the extended wavelength range (3000--24800 A), we obtained an unprecedentedly rich spectral sequence among the hypernovae, making SN 2010bh one of the best studied representatives of this SN class. We find that SN 2010bh has a more rapid rise to maximum brightness (8.0 +/- 1.0 rest-frame days) and a fainter absolute peak luminosity (L_bol~3e42 erg/s) than previously observed SN events associated with GRBs. Our estimate of the ejected (56)Ni mass is 0.12 +/- 0.02 Msun. From the broad spectral features we measure expansion velocities up to 47,000 km/s, higher than those of SNe 1998bw (GRB 980425) and 2006aj (GRB 060218). Helium absorption lines He I lambda5876 and He I 1.083 microm, blueshifted by ~20,000--30,000 km/s and ~28,000--38,000 km/s, respectively, may be present in the optical spectra. However, the lack of coverage of the He I 2.058 microm line prevents us from confirming such identifications. The nebular spectrum, taken at ~186 days after the explosion, shows a broad but faint [O I] emission at 6340 A. The light-curve shape and photospheric expansion velocities of SN 2010bh suggest that we witnessed a highly energetic explosion with a small ejected mass (E_k ~ 1e52 erg and M_ej ~ 3 Msun). The observed properties of SN 2010bh further extend the heterogeneity of the class of GRB supernovae.Comment: 37 pages and 12 figures (one-column pre-print format), accepted for publication in Ap

Predicting climate change using response theory: global averages and spatial patterns

The provision of accurate methods for predicting the climate response to anthropogenic and natural forcings is a key contemporary scientific challenge. Using a simplified and efficient open-source general circulation model of the atmosphere featuring O(105105) degrees of freedom, we show how it is possible to approach such a problem using nonequilibrium statistical mechanics. Response theory allows one to practically compute the time-dependent measure supported on the pullback attractor of the climate system, whose dynamics is non-autonomous as a result of time-dependent forcings. We propose a simple yet efficient method for predicting—at any lead time and in an ensemble sense—the change in climate properties resulting from increase in the concentration of CO22 using test perturbation model runs. We assess strengths and limitations of the response theory in predicting the changes in the globally averaged values of surface temperature and of the yearly total precipitation, as well as in their spatial patterns. The quality of the predictions obtained for the surface temperature fields is rather good, while in the case of precipitation a good skill is observed only for the global average. We also show how it is possible to define accurately concepts like the inertia of the climate system or to predict when climate change is detectable given a scenario of forcing. Our analysis can be extended for dealing with more complex portfolios of forcings and can be adapted to treat, in principle, any climate observable. Our conclusion is that climate change is indeed a problem that can be effectively seen through a statistical mechanical lens, and that there is great potential for optimizing the current coordinated modelling exercises run for the preparation of the subsequent reports of the Intergovernmental Panel for Climate Change

Amplified mid-latitude planetary waves favour particular regional weather extremes

Copyright © 2014 Nature Publishing GroupThere has been an ostensibly large number of extreme weather events in the Northern Hemisphere mid-latitudes during the past decade [1]. An open question that is critically important for scientists and policy makers is whether any such increase in weather extremes is natural or anthropogenic in origin [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]. One mechanism proposed to explain the increased frequency of extreme weather events is the amplification of mid-latitude atmospheric planetary waves [14, 15, 16, 17]. Disproportionately large warming in the northern polar regions compared with mid-latitudes—and associated weakening of the north–south temperature gradient—may favour larger amplitude planetary waves [14, 15, 16, 17], although observational evidence for this remains inconclusive [18, 19, 20, 21]. A better understanding of the role of planetary waves in causing mid-latitude weather extremes is essential for assessing the potential environmental and socio-economic impacts of future planetary wave changes. Here we show that months of extreme weather over mid-latitudes are commonly accompanied by significantly amplified quasi-stationary mid-tropospheric planetary waves. Conversely, months of near-average weather over mid-latitudes are often accompanied by significantly attenuated waves. Depending on geographical region, certain types of extreme weather (for example, hot, cold, wet, dry) are more strongly related to wave amplitude changes than others. The findings suggest that amplification of quasi-stationary waves preferentially increases the probabilities of heat waves in western North America and central Asia, cold outbreaks in eastern North America, droughts in central North America, Europe and central Asia, and wet spells in western Asia.Natural Environment Research Council (NERC

The Fittest versus the Flattest: Experimental Confirmation of the Quasispecies Effect with Subviral Pathogens

The “survival of the fittest” is the paradigm of Darwinian evolution in which the best-adapted replicators are favored by natural selection. However, at high mutation rates, the fittest organisms are not necessarily the fastest replicators but rather are those that show the greatest robustness against deleterious mutational effects, even at the cost of a low replication rate. This scenario, dubbed the “survival of the flattest”, has so far only been shown to operate in digital organisms. We show that “survival of the flattest” can also occur in biological entities by analyzing the outcome of competition between two viroid species coinfecting the same plant. Under optimal growth conditions, a viroid species characterized by fast population growth and genetic homogeneity outcompeted a viroid species with slow population growth and a high degree of variation. In contrast, the slow-growth species was able to outcompete the fast species when the mutation rate was increased. These experimental results were supported by an in silico model of competing viroid quasispecies

The sequences of 150,119 genomes in the UK Biobank

Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data(1,2). Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank(3). This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation