An Iterative CT Reconstruction Algorithm for Fast Fluid Flow Imaging

The study of fluid flow through solid matter by computed tomography (CT) imaging has many applications, ranging from petroleum and aquifer engineering to biomedical, manufacturing, and environmental research. To avoid motion artifacts, current experiments are often limited to slow fluid flow dynamics. This severely limits the applicability of the technique. In this paper, a new iterative CT reconstruction algorithm for improved a temporal/spatial resolution in the imaging of fluid flow through solid matter is introduced. The proposed algorithm exploits prior knowledge in two ways. First, the time-varying object is assumed to consist of stationary (the solid matter) and dynamic regions (the fluid flow). Second, the attenuation curve of a particular voxel in the dynamic region is modeled by a piecewise constant function over time, which is in accordance with the actual advancing fluid/air boundary. Quantitative and qualitative results on different simulation experiments and a real neutron tomography data set show that, in comparison with the state-of-the-art algorithms, the proposed algorithm allows reconstruction from substantially fewer projections per rotation without image quality loss. Therefore, the temporal resolution can be substantially increased, and thus fluid flow experiments with faster dynamics can be performed

A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks

Graph neural networks (GNNs) have known an increasing success recently, with many GNN variants achieving state-of-the-art results on node and graph classification tasks. The proposed GNNs, however, often implement complex node and graph embedding schemes, which makes challenging to explain their performance. In this paper, we investigate the link between a GNN's expressiveness, that is, its ability to map different graphs to different representations, and its generalization performance in a graph classification setting. In particular , we propose a principled experimental procedure where we (i) define a practical measure for expressiveness, (ii) introduce an expressiveness-based loss function that we use to train a simple yet practical GNN that is permutation-invariant, (iii) illustrate our procedure on benchmark graph classification problems and on an original real-world application. Our results reveal that expressiveness alone does not guarantee a better performance, and that a powerful GNN should be able to produce graph representations that are well separated with respect to the class of the corresponding graphs

Comparisons of host mitochondrial, nuclear and endosymbiont bacterial genes reveal cryptic fig wasp species and the effects of Wolbachia on host mtDNA evolution and diversity

Background Figs and fig-pollinating wasp species usually display a highly specific one-to-one association. However, more and more studies have revealed that the "one-to-one" rule has been broken. Co-pollinators have been reported, but we do not yet know how they evolve. They may evolve from insect speciation induced or facilitated by Wolbachia which can manipulate host reproduction and induce reproductive isolation. In addition, Wolbachia can affect host mitochondrial DNA evolution, because of the linkage between Wolbachia and associated mitochondrial haplotypes, and thus confound host phylogeny based on mtDNA. Previous research has shown that fig wasps have the highest incidence of Wolbachia infection in all insect taxa, and Wolbachia may have great influence on fig wasp biology. Therefore, we look forward to understanding the influence of Wolbachia on mitochondrial DNA evolution and speciation in fig wasps. Results We surveyed 76 pollinator wasp specimens from nine Ficus microcarpa trees each growing at a different location in Hainan and Fujian Provinces, China. We found that all wasps were morphologically identified as Eupristina verticillata, but diverged into three clades with 4.22-5.28% mtDNA divergence and 2.29-20.72% nuclear gene divergence. We also found very strong concordance between E. verticillata clades and Wolbachia infection status, and the predicted effects of Wolbachia on both mtDNA diversity and evolution by decreasing mitochondrial haplotypes. Conclusions Our study reveals that the pollinating wasp E. verticillata on F. microcarpa has diverged into three cryptic species, and Wolbachia may have a role in this divergence. The results also indicate that Wolbachia strains infecting E. verticillata have likely resulted in selective sweeps on host mitochondrial DNA

A bidentate Polycomb Repressive-Deubiquitinase complex is required for efficient activity on nucleosomes

Attachment of ubiquitin to lysine 119 of Histone 2A (H2AK119Ub) is an epigenetic mark characteristic of repressed developmental genes, which is removed by the Polycomb Repressive-Deubiquitinase (PR-DUB) complex. Here we report the crystal structure of the Drosophila PR-DUB, revealing that the deubiquitinase Calypso and its activating partner ASX form a 2:2 complex. The bidentate Calypso–ASX complex is generated by dimerisation of two activated Calypso proteins through their coiled-coil regions. Disrupting the Calypso dimer interface does not affect inherent catalytic activity, but inhibits removal of H2AK119Ub as a consequence of impaired recruitment to nucleosomes. Mutating the equivalent surface on the human counterpart, BAP1, also compromises activity on nucleosomes. Together, this suggests that high local concentrations drive assembly of bidentate PR-DUB complexes on chromatin—providing a mechanistic basis for enhanced PR-DUB activity at specific genomic foci, and the impact of distinct classes of PR-DUB mutations in tumorigenesis

Structural diversity of biologically interesting datasets: a scaffold analysis approach

ABSTRACT:The recent public availability of the human metabolome and natural product datasets has revitalized "metabolite-likeness" and "natural product-likeness" as a drug design concept to design lead libraries targeting specific pathways. Many reports have analyzed the physicochemical property space of biologically important datasets, with only a few comprehensively characterizing the scaffold diversity in public datasets of biological interest. With large collections of high quality public data currently available, we carried out a comparative analysis of current day leads with other biologically relevant datasets.In this study, we note a two-fold enrichment of metabolite scaffolds in drug dataset (42%) as compared to currently used lead libraries (23%). We also note that only a small percentage (5%) of natural product scaffolds space is shared by the lead dataset. We have identified specific scaffolds that are present in metabolites and natural products, with close counterparts in the drugs, but are missing in the lead dataset. To determine the distribution of compounds in physicochemical property space we analyzed the molecular polar surface area, the molecular solubility, the number of rings and the number of rotatable bonds in addition to four well-known Lipinski properties. Here, we note that, with only few exceptions, most of the drugs follow Lipinski's rule. The average values of the molecular polar surface area and the molecular solubility in metabolites is the highest while the number of rings is the lowest. In addition, we note that natural products contain the maximum number of rings and the rotatable bonds than any other dataset under consideration.Currently used lead libraries make little use of the metabolites and natural products scaffold space. We believe that metabolites and natural products are recognized by at least one protein in the biosphere therefore, sampling the fragment and scaffold space of these compounds, along with the knowledge of distribution in physicochemical property space, can result in better lead libraries. Hence, we recommend the greater use of metabolites and natural products while designing lead libraries. Nevertheless, metabolites have a limited distribution in chemical space that limits the usage of metabolites in library design.14 page(s

Crystal, Solution and In silico Structural Studies of Dihydrodipicolinate Synthase from the Common Grapevine

Dihydrodipicolinate synthase (DHDPS) catalyzes the rate limiting step in lysine biosynthesis in bacteria and plants. The structure of DHDPS has been determined from several bacterial species and shown in most cases to form a homotetramer or dimer of dimers. However, only one plant DHDPS structure has been determined to date from the wild tobacco species, Nicotiana sylvestris (Blickling et al. (1997) J. Mol. Biol. 274, 608–621). Whilst N. sylvestris DHDPS also forms a homotetramer, the plant enzyme adopts a ‘back-to-back’ dimer of dimers compared to the ‘head-to-head’ architecture observed for bacterial DHDPS tetramers. This raises the question of whether the alternative quaternary architecture observed for N. sylvestris DHDPS is common to all plant DHDPS enzymes. Here, we describe the structure of DHDPS from the grapevine plant, Vitis vinifera, and show using analytical ultracentrifugation, small-angle X-ray scattering and X-ray crystallography that V. vinifera DHDPS forms a ‘back-to-back’ homotetramer, consistent with N. sylvestris DHDPS. This study is the first to demonstrate using both crystal and solution state measurements that DHDPS from the grapevine plant adopts an alternative tetrameric architecture to the bacterial form, which is important for optimizing protein dynamics as suggested by molecular dynamics simulations reported in this study

Introduction to the Conceptualisation of Environmental Citizenship for Twenty-First-Century Education

The EU’s growth strategy (Europe 2020) and the European vision for green, circular and low-carbon economy in line with the EU 2050 (EU-roadmap 2050) give par- ticular attention to citizens’ participation and engagement and therefore to Environmental Citizenship. Environmental Citizenship has been an influential con- cept in many different arenas such as economy, policy, philosophy, corporation management and marketing, which could also be better exploited and established in the field of education. Environmental Citizenship is recognized as an important aspect in addressing global environmental problems such as climate change (Stern 2011; Ockwell et al. 2009) whilst providing support to pro-environmental organisa- tions and individuals, contributing also to public pressure for political action (sign- ing petitions, writing to politicians and newspapers). Many varied definitions of Environmental Citizenship can be found within the literature. Some of them are quite similar, and important overlaps can be observed; however, others can be quite different with contradictions in their philosophy and approach. According to Dobson (2010), Environmental Citizenship refers to pro-environmental behaviour, in public and in private, driven by a belief in fairness of the distribution of environmental goods, in participation and in the co-creation of sustainability policy. It is about the active participation of citizens in moving towards sustainability. Education and especially environmental discourses in science education have a lot to contribute in adopting and promoting Environmental Citizenship. However, the conceptualisation of Environmental Citizenship in educational context remains an imperative need. The under-explored (until now) potential for pro-environmental behaviour change through Environmental Citizenship should be further emphasised (Dobson 2010) and can contribute greatly to a more sustainable world.info:eu-repo/semantics/publishedVersio

Physiochemical property space distribution among human metabolites, drugs and toxins

<p>Abstract</p> <p>Background</p> <p>The current approach to screen for drug-like molecules is to sieve for molecules with biochemical properties suitable for desirable pharmacokinetics and reduced toxicity, using predominantly biophysical properties of chemical compounds, based on empirical rules such as Lipinski's "rule of five" (Ro5). For over a decade, Ro5 has been applied to combinatorial compounds, drugs and ligands, in the search for suitable lead compounds. Unfortunately, till date, a clear distinction between drugs and non-drugs has not been achieved. The current trend is to seek out drugs which show metabolite-likeness. In identifying similar physicochemical characteristics, compounds have usually been clustered based on some characteristic, to reduce the search space presented by large molecular datasets. This paper examines the similarity of current drug molecules with human metabolites and toxins, using a range of computed molecular descriptors as well as the effect of comparison to clustered data compared to searches against complete datasets.</p> <p>Results</p> <p>We have carried out statistical and substructure functional group analyses of three datasets, namely human metabolites, drugs and toxin molecules. The distributions of various molecular descriptors were investigated. Our analyses show that, although the three groups are distinct, present-day drugs are closer to toxin molecules than to metabolites. Furthermore, these distributions are quite similar for both clustered data as well as complete or unclustered datasets.</p> <p>Conclusion</p> <p>The property space occupied by metabolites is dissimilar to that of drugs or toxin molecules, with current drugs showing greater similarity to toxins than to metabolites. Additionally, empirical rules like Ro5 can be refined to identify drugs or drug-like molecules that are clearly distinct from toxic compounds and more metabolite-like. The inclusion of human metabolites in this study provides a deeper insight into metabolite/drug/toxin-like properties and will also prove to be valuable in the prediction or optimization of small molecules as ligands for therapeutic applications.</p

L,L-Diaminopimelate Aminotransferase from Chlamydomonas reinhardtii: A Target for Algaecide Development

In some bacterial species and photosynthetic cohorts, including algae, the enzyme l,l-diaminopimelate aminotransferase (DapL) (E.C. 2.6.1.83) is involved in the anabolism of the essential amino acid L-lysine. DapL catalyzes the conversion of tetrahydrodipicolinate (THDPA) to l,l-diaminopimelate (l,l-DAP), in one step bypassing the DapD, DapC and DapE enzymatic reactions present in the acyl DAP pathways. Here we present an in vivo and in vitro characterization of the DapL ortholog from the alga Chlamydomonas reinhardtii (Cr-DapL). The in vivo analysis illustrated that the enzyme is able to functionally complement the E. coli dap auxotrophs and was essential for plant development in Arabidopsis. In vitro, the enzyme was able to inter-convert THDPA and l,l-DAP, showing strong substrate specificity. Cr-DapL was dimeric in both solution and when crystallized. The structure of Cr-DapL was solved in its apo form, showing an overall architecture of a α/β protein with each monomer in the dimer adopting a pyridoxal phosphate-dependent transferase-like fold in a V-shaped conformation. The active site comprises residues from both monomers in the dimer and shows some rearrangement when compared to the apo-DapL structure from Arabidopsis. Since animals do not possess the enzymatic machinery necessary for the de novo synthesis of the amino acid l-lysine, enzymes involved in this pathway are attractive targets for the development of antibiotics, herbicides and algaecides