The visual processing of text

The results of an investigation into the nature of the visual information obtained from pages of text and used in the visual processing of text during reading are reported. An initial investigation into the visual processing of text by applying a computational model of early vision (MIRAGE: Watt & Morgan, 1985; Watt, 1988) to pages of text (Computational Analysis 1) is shown to extract a range of features from a text image in the representation it delivers, which are organised across a range of spatial scales similar to those spanning human vision. The features the model extracts are capable of supporting a structured set of text processing tasks of the type required in reading. From the findings of this analysis, a series of psychophysical and computational studies are reported which exan-dne whether the type of information used in the human visual processing of text can be described by this modelled representation of information in text images. Using a novel technique to measure the 'visibility' of the information in text images, a second stage of investigation (Experiments 1-3) shows that information used to perform different text processing tasks of the type performed in reading is contained at different spatial scales of visual analysis. A second computational analysis of the information in text demonstrates how the spatial scale dependency of these text processing tasks can be accounted for by the model of early vision. In a third stage, two further experiments (Experiments 4-5) show how the pattern of text processing performance is determined by typographical parameters, and a third computational analysis of text demonstrates how changes in the pattern of text processing performance can be modelled by changes in the pattern of information represented by the model of vision. A fourth stage (Experiments 6-7 and Computational Analysis 4) examines the time-course of the visual processing of text. The experiments show how the duration required to reach a level of visual text processing performance varies as a function of typographical parameters, and comparison of these data with the model shows that this is consistent with a time-course of visual analysis based on a coarse-to-fine spatial scale of visual processing. A final experiment (Experiment 8) examines how reading performance varies with typographical parameters. It is shown how the pattern of reading performance and the pattern of visual text processing performance are related, and how the model of early vision might describe the visual processing of text in reading. The implications of these findings for theories of reading and theories of vision are finally discussed

A Method to Identify and Analyze Biological Programs through Automated Reasoning.

Predictive biology is elusive because rigorous, data-constrained, mechanistic models of complex biological systems are difficult to derive and validate. Current approaches tend to construct and examine static interaction network models, which are descriptively rich but often lack explanatory and predictive power, or dynamic models that can be simulated to reproduce known behavior. However, in such approaches implicit assumptions are introduced as typically only one mechanism is considered, and exhaustively investigating all scenarios is impractical using simulation. To address these limitations, we present a methodology based on automated formal reasoning, which permits the synthesis and analysis of the complete set of logical models consistent with experimental observations. We test hypotheses against all candidate models, and remove the need for simulation by characterizing and simultaneously analyzing all mechanistic explanations of observed behavior. Our methodology transforms knowledge of complex biological processes from sets of possible interactions and experimental observations to precise, predictive biological programs governing cell function

Selector function of MHC I molecules is determined by protein plasticity

The selection of peptides for presentation at the surface of most nucleated cells by major histocompatibility complex class I molecules (MHC I) is crucial to the immune response in vertebrates. However, the mechanisms of the rapid selection of high affinity peptides by MHC I from amongst thousands of mostly low affinity peptides are not well understood. We developed computational systems models encoding distinct mechanistic hypotheses for two molecules, HLA-B*44:02 (B*4402) and HLA-B*44:05 (B*4405), which differ by a single residue yet lie at opposite ends of the spectrum in their intrinsic ability to select high affinity peptides. We used <em>in vivo</em> biochemical data to infer that a conformational intermediate of MHC I is significant for peptide selection. We used molecular dynamics simulations to show that peptide selector function correlates with protein plasticity, and confirmed this experimentally by altering the plasticity of MHC I with a single point mutation, which altered <em>in vivo</em> selector function in a predictable way. Finally, we investigated the mechanisms by which the co-factor tapasin influences MHC I plasticity. We propose that tapasin modulates MHC I plasticity by dynamically coupling the peptide binding region and {\alpha}<sub>3</sub> domain of MHC I allosterically, resulting in enhanced peptide selector function

Job design and employee engagement

Engage for Success White Paper no. 2014-0

A Method to Identify and Analyze Biological Programs through Automated Reasoning.

Predictive biology is elusive because rigorous, data-constrained, mechanistic models of complex biological systems are difficult to derive and validate. Current approaches tend to construct and examine static interaction network models, which are descriptively rich but often lack explanatory and predictive power, or dynamic models that can be simulated to reproduce known behavior. However, in such approaches implicit assumptions are introduced as typically only one mechanism is considered, and exhaustively investigating all scenarios is impractical using simulation. To address these limitations, we present a methodology based on automated formal reasoning, which permits the synthesis and analysis of the complete set of logical models consistent with experimental observations. We test hypotheses against all candidate models, and remove the need for simulation by characterizing and simultaneously analyzing all mechanistic explanations of observed behavior. Our methodology transforms knowledge of complex biological processes from sets of possible interactions and experimental observations to precise, predictive biological programs governing cell function.G.M. holds a career development award from the Armenise Harvard foundation, and a Telethon-DTI career award. A.G.S. is a Medical Research Council Professor

Programming Light-Harvesting Efficiency Using DNA Origami.

The remarkable performance and quantum efficiency of biological light-harvesting complexes has prompted a multidisciplinary interest in engineering biologically inspired antenna systems as a possible route to novel solar cell technologies. Key to the effectiveness of biological "nanomachines" in light capture and energy transport is their highly ordered nanoscale architecture of photoactive molecules. Recently, DNA origami has emerged as a powerful tool for organizing multiple chromophores with base-pair accuracy and full geometric freedom. Here, we present a programmable antenna array on a DNA origami platform that enables the implementation of rationally designed antenna structures. We systematically analyze the light-harvesting efficiency with respect to number of donors and interdye distances of a ring-like antenna using ensemble and single-molecule fluorescence spectroscopy and detailed Förster modeling. This comprehensive study demonstrates exquisite and reliable structural control over multichromophoric geometries and points to DNA origami as highly versatile platform for testing design concepts in artificial light-harvesting networks.A. W. C. acknowledges support from the Winton Programme for the Physics of Sustainability. U. F. K. was partly supported by an ERC starting grant (PassMembrane, EY 261101). E. A.H. acknowledges support from Janggen-Pöhn Stiftung and the Schweizerischer Nationalfonds (SNF). P. T. acknowledges support by a starting grant (SiMBA, EU 261162) of the European Research Council (ERC). B. W. gratefully acknowledges support by the Braunschweig International Graduate School of Metrology B-IGSM and the DFG Research Training Group GrK1952/1 ‘Metrology for Complex Nanosystems’. P. M. thankfully acknowledges the support of the EPSRC Centre for Doctoral Training in Sensor Technologies and Applications EP/L015889/1.This is the final version of the article. It first appeared from ACS via https://doi.org/10.1021/acs.nanolett.5b0513

IFIT3 and IFIT2/3 promote IFIT1-mediated translation inhibition by enhancing binding to non-self RNA.

Interferon-induced proteins with tetratricopeptide repeats (IFITs) are highly expressed during the cell-intrinsic immune response to viral infection. IFIT1 inhibits translation by binding directly to the 5' end of foreign RNAs, particularly those with non-self cap structures, precluding the recruitment of the cap-binding eukaryotic translation initiation factor 4F and ribosome recruitment. The presence of IFIT1 imposes a requirement on viruses that replicate in the cytoplasm to maintain mechanisms to avoid its restrictive effects. Interaction of different IFIT family members is well described, but little is known of the molecular basis of IFIT association or its impact on function. Here, we reconstituted different complexes of IFIT1, IFIT2 and IFIT3 in vitro, which enabled us to reveal critical aspects of IFIT complex assembly. IFIT1 and IFIT3 interact via a YxxxL motif present in the C-terminus of each protein. IFIT2 and IFIT3 homodimers dissociate to form a more stable heterodimer that also associates with IFIT1. We show for the first time that IFIT3 stabilizes IFIT1 protein expression, promotes IFIT1 binding to a cap0 Zika virus reporter mRNA and enhances IFIT1 translation inhibition. This work reveals molecular aspects of IFIT interaction and provides an important missing link between IFIT assembly and function.This work was supported by a joint Royal Society/Wellcome Trust Sir Henry Dale Fellowship (202471/Z/16/Z) and a Royal Society Research Grant (RG140708) to TRS. HVM is supported by a University of Cambridge, Department of Pathology PhD studentship. XYL is supported by a King’s Scholarship from the Malaysian government. TJS is supported by a Wellcome Trust PhD studentship (105389/Z/14/Z). RCF and DSM are supported by CAPES Computational Biology (23038.010048/2013-27). DSM is also supported by the Academy of Medical Sciences/UK (NAF004/1005). SCG is a Sir Henry Dale Fellow (098406/Z/12/Z) co-funded by the Wellcome Trust and Royal Society

Norovirus translation requires an interaction between the C Terminus of the genome-linked viral protein VPg and eukaryotic translation initiation factor 4G.

Viruses have evolved a variety of mechanisms to usurp the host cell translation machinery to enable translation of the viral genome in the presence of high levels of cellular mRNAs. Noroviruses, a major cause of gastroenteritis in man, have evolved a mechanism that relies on the interaction of translation initiation factors with the virus-encoded VPg protein covalently linked to the 5' end of the viral RNA. To further characterize this novel mechanism of translation initiation, we have used proteomics to identify the components of the norovirus translation initiation factor complex. This approach revealed that VPg binds directly to the eIF4F complex, with a high affinity interaction occurring between VPg and eIF4G. Mutational analyses indicated that the C-terminal region of VPg is important for the VPg-eIF4G interaction; viruses with mutations that alter or disrupt this interaction are debilitated or non-viable. Our results shed new light on the unusual mechanisms of protein-directed translation initiation.This work was supported by funding from the BBSRC (BB/I012303/1) and the Wellcome Trust (WT097997MA) to IG, funding from BBSRC to LR and NL (BB/I01232X/1), as well as to SC (BB/J001708/1). IG is a Wellcome Senior Fellow.This is the final published version. It's also available on the publisher's website at: http://www.jbc.org/content/early/2014/06/13/jbc.M114.550657.abstrac

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures

Ten Simple Rules for Effective Computational Research

<p>Ten Simple Rules for Effective Computational Research</p