Long-Range Displacive Reconstruction of Au(110) Triggered by Low Coverage of Sulfur

We propose a new model for the c(4 × 2) phase of sulfur adsorbed on Au(110). This is a reconstruction achieved by short-range rearrangements of Au atoms that create a pseudo-4-fold-hollow (p4fh) site for adsorbed sulfur. The model is based partly upon the agreement between experimental STM images and those predicted from DFT, both within c(4 × 2) domains and at a boundary between two domains. It is also based on the stability of this structure in DFT, where it is not only favored over the chemisorbed phase at its ideal coverage of 0.25 ML, but also at lower coverage (at T = 0 K). This is compatible with the fact that in experiments, it coexists with 0.06 ± 0.03 ML of sulfur chemisorbed on the (1 × 2) surface. The relative stability of the c(4 × 2) phase at 0.25 ML has been verified for a variety of functionals in DFT. In the chemisorbed phase, sulfur adsorbs at a pseudo-3-fold-hollow (p3fh) site near the tops of rows in the (1 × 2) reconstruction. This is similar to the fcc site on an extended (111) surface. Sulfur causes a slight separation between the two topmost Au atoms, which is apparent both in STM images and in DFT-optimized structures. The second-most stable site is also a p3fh site, similar to an hcp site. DFT is used to construct a simple lattice gas model based on pairs of excluded sites. The set of excluded sites is in good qualitative agreement with our STM data. From DFT, the diffusion barrier of a sulfur atom is 0.61 eV parallel to the Au row, and 0.78 eV perpendicular to the Au row. For the two components of the perpendicular diffusion path, that is, crossing a trough and hopping over a row, the former is considerably more difficult than the latter

A Database and Evaluation for Classification of RNA Molecules Using Graph Methods

In this paper, we introduce a new graph dataset based on the representation of RNA. The RNA dataset includes 3178 RNA chains which are labelled in 8 classes according to their reported biological functions. The goal of this database is to provide a platform for investigating the classication of RNA using graph-based methods. The molecules are represented by graphs representing the sequence and base-pairs of the RNA, with a number of labelling schemes using base labels and local shape. We report the results of a number of state-of-the-art graph based methods on this dataset as a baseline comparison and investigate how these methods can be used to categorise RNA molecules on their type and functions. The methods applied are Weisfeiler Lehman and optimal assignment kernels, shortest paths kernel and the all paths and cycle methods. We also compare to the standard Needleman-Wunsch algorithm used in bioinformatics for DNA and RNA comparison, and demonstrate the superiority of graph kernels even on a string representation. The highest classication rate is obtained by the WL-OA algorithm using base labels and base-pair connections

University of Michigan Undergraduate Research Journal, Issue 9, Winter 2012

Articlehttp://deepblue.lib.umich.edu/bitstream/2027.42/97010/1/UMURJ-Issue09_2012.pd

Evolution of Th2 responses : Characterization of IL-4/13 in sea bass (Dicentrarchus labrax L.) and studies of expression and biological activity

Acknowledgements This research was funded by the European Commission under the 7th Framework Programme for Research and Technological Development (FP7) of the European Union (Grant Agreement 311993 TARGETFISH). T.W. received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland). MASTS is funded by the Scottish Funding Council (grant reference number HR09011) and contributing institutions.Peer reviewedPublisher PD

Genome Diversity and the Origin of the Arabian Horse

The Arabian horse, one of the world\u27s oldest breeds of any domesticated animal, is characterized by natural beauty, graceful movement, athletic endurance, and, as a result of its development in the arid Middle East, the ability to thrive in a hot, dry environment. Here we studied 378 Arabian horses from 12 countries using equine single nucleotide polymorphism (SNP) arrays and whole-genome re-sequencing to examine hypotheses about genomic diversity, population structure, and the relationship of the Arabian to other horse breeds. We identified a high degree of genetic variation and complex ancestry in Arabian horses from the Middle East region. Also, contrary to popular belief, we could detect no significant genomic contribution of the Arabian breed to the Thoroughbred racehorse, including Y chromosome ancestry. However, we found strong evidence for recent interbreeding of Thoroughbreds with Arabians used for flat-racing competitions. Genetic signatures suggestive of selective sweeps across the Arabian breed contain candidate genes for combating oxidative damage during exercise, and within the Straight Egyptian subgroup, for facial morphology. Overall, our data support an origin of the Arabian horse in the Middle East, no evidence for reduced global genetic diversity across the breed, and unique genetic adaptations for both physiology and conformation

Mapping Drug Physico-Chemical Features to Pathway Activity Reveals Molecular Networks Linked to Toxicity Outcome

The identification of predictive biomarkers is at the core of modern toxicology. So far, a number of approaches have been proposed. These rely on statistical inference of toxicity response from either compound features (i.e., QSAR), in vitro cell based assays or molecular profiling of target tissues (i.e., expression profiling). Although these approaches have already shown the potential of predictive toxicology, we still do not have a systematic approach to model the interaction between chemical features, molecular networks and toxicity outcome. Here, we describe a computational strategy designed to address this important need. Its application to a model of renal tubular degeneration has revealed a link between physico-chemical features and signalling components controlling cell communication pathways, which in turn are differentially modulated in response to toxic chemicals. Overall, our findings are consistent with the existence of a general toxicity mechanism operating in synergy with more specific single-target based mode of actions (MOAs) and provide a general framework for the development of an integrative approach to predictive toxicology

Data-driven learning of narcosis mode of action identifies a CNS transcriptional signature shared between whole organism Caenorhabditis elegans and a fish gill cell line

Supplementary data related to this article: Supplementary material, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc1.docx (Word document35, 5KB)); Supplementary Data 1. These are the chemicals along with their properties and the calculated doses given for the C. elegans (Caenorhabditis elegans), available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc2.xls (spreadsheet, 68KB); Supplementary Data 2. These are the chemicals and the doses given for the trout gill cell line (Rtgill-WT1). The codes here relate to the same codes on the microarray data, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc3.xlsx (spreadsheet; 11KB); Supplementary Data 3. These are the probes found to be significantly different between exposed and unexposed C. elegans for each of the narcotic chemicals tested, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc4.xlsx (spreadsheet, 363KB); Supplementary Data 4. The file provide the metabolite composition of the three clusters identified by running a metabolic-based predictive model, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc5.xlsx (spreadsheet, 10KB).Copyright © 2022 The Authors. With the large numbers of man-made chemicals produced and released in the environment, there is a need to provide assessments on their potential effects on environmental safety and human health. Current regulatory frameworks rely on a mix of both hazard and risk-based approaches to make safety decisions, but the large number of chemicals in commerce combined with an increased need to conduct assessments in the absence of animal testing makes this increasingly challenging. This challenge is catalysing the use of more mechanistic knowledge in safety assessment from both in silico and in vitro approaches in the hope that this will increase confidence in being able to identify modes of action (MoA) for the chemicals in question. Here we approach this challenge by testing whether a functional genomics approach in C. elegans and in a fish cell line can identify molecular mechanisms underlying the effects of narcotics, and the effects of more specific acting toxicants. We show that narcosis affects the expression of neuronal genes associated with CNS function in C. elegans and in a fish cell line. Overall, we believe that our study provides an important step in developing mechanistically relevant biomarkers which can be used to screen for hazards, and which prevent the need for repeated animal or cross-species comparisons for each new chemical.Unilever Ltd