High speed e-beam writing for large area photonic nanostructures-a choice of parameters

Photonic nanostructures are used for many optical systems and applications. However, some high-end applications require the use of electron-beam lithography (EBL) to generate such nanostructures. An important technological bottleneck is the exposure time of the EBL systems, which can exceed 24 hours per 1 cm2. Here, we have developed a method based on a target function to systematically increase the writing speed of EBL. As an example, we use as the target function the fidelity of the Fourier Transform spectra of nanostructures that are designed for thin film light trapping applications, and optimize the full parameter space of the lithography process. Finally, we are able to reduce the exposure time by a factor of 5.5 without loss of photonic performance. We show that the performances of the fastest written structures are identical to the original ones within experimental error. As the target function can be varied according to different purposes, the method is also applicable to guided mode resonant grating and many other areas. These findings contribute to the advancement of EBL and point towards making the technology more attractive for commercial applications

Evolutionary Games with Affine Fitness Functions: Applications to Cancer

We analyze the dynamics of evolutionary games in which fitness is defined as an affine function of the expected payoff and a constant contribution. The resulting inhomogeneous replicator equation has an homogeneous equivalent with modified payoffs. The affine terms also influence the stochastic dynamics of a two-strategy Moran model of a finite population. We then apply the affine fitness function in a model for tumor-normal cell interactions to determine which are the most successful tumor strategies. In order to analyze the dynamics of concurrent strategies within a tumor population, we extend the model to a three-strategy game involving distinct tumor cell types as well as normal cells. In this model, interaction with normal cells, in combination with an increased constant fitness, is the most effective way of establishing a population of tumor cells in normal tissue.Comment: The final publication is available at http://www.springerlink.com, http://dx.doi.org/10.1007/s13235-011-0029-

Optimal flux spaces of genome-scale stoichiometric models are determined by a few subnetworks

The metabolism of organisms can be studied with comprehensive stoichiometric models of their metabolic networks. Flux balance analysis (FBA) calculates optimal metabolic performance of stoichiometric models. However, detailed biological interpretation of FBA is limited because, in general, a huge number of flux patterns give rise to the same optimal performance. The complete description of the resulting optimal solution spaces was thus far a computationally intractable problem. Here we present CoPE-FBA: Comprehensive Polyhedra Enumeration Flux Balance Analysis, a computational method that solves this problem. CoPE-FBA indicates that the thousands to millions of optimal flux patterns result from a combinatorial explosion of flux patterns in just a few metabolic sub-networks. The entire optimal solution space can now be compactly described in terms of the topology of these sub-networks. CoPE-FBA simplifies the biological interpretation of stoichiometric models of metabolism, and provides a profound understanding of metabolic flexibility in optimal states

Chromatin loop anchors are associated with genome instability in cancer and recombination hotspots in the germline

Abstract Background Chromatin loops form a basic unit of interphase nuclear organization, with chromatin loop anchor points providing contacts between regulatory regions and promoters. However, the mutational landscape at these anchor points remains under-studied. Here, we describe the unusual patterns of somatic mutations and germline variation associated with loop anchor points and explore the underlying features influencing these patterns. Results Analyses of whole genome sequencing datasets reveal that anchor points are strongly depleted for single nucleotide variants (SNVs) in tumours. Despite low SNV rates in their genomic neighbourhood, anchor points emerge as sites of evolutionary innovation, showing enrichment for structural variant (SV) breakpoints and a peak of SNVs at focal CTCF sites within the anchor points. Both CTCF-bound and non-CTCF anchor points harbour an excess of SV breakpoints in multiple tumour types and are prone to double-strand breaks in cell lines. Common fragile sites, which are hotspots for genome instability, also show elevated numbers of intersecting loop anchor points. Recurrently disrupted anchor points are enriched for genes with functions in cell cycle transitions and regions associated with predisposition to cancer. We also discover a novel class of CTCF-bound anchor points which overlap meiotic recombination hotspots and are enriched for the core PRDM9 binding motif, suggesting that the anchor points have been foci for diversity generated during recent human evolution. Conclusions We suggest that the unusual chromatin environment at loop anchor points underlies the elevated rates of variation observed, marking them as sites of regulatory importance but also genomic fragility

Female Behaviour Drives Expression and Evolution of Gustatory Receptors in Butterflies

Secondary plant compounds are strong deterrents of insect oviposition and feeding, but may also be attractants for specialist herbivores. These insect-plant interactions are mediated by insect gustatory receptors (Grs) and olfactory receptors (Ors). An analysis of the reference genome of the butterfly Heliconius melpomene, which feeds on passion-flower vines (Passiflora spp.), together with whole-genome sequencing within the species and across the Heliconius phylogeny has permitted an unprecedented opportunity to study the patterns of gene duplication and copy-number variation (CNV) among these key sensory genes. We report in silico gene predictions of 73 Gr genes in the H. melpomene reference genome, including putative CO2, sugar, sugar alcohol, fructose, and bitter receptors. The majority of these Grs are the result of gene duplications since Heliconius shared a common ancestor with the monarch butterfly or the silkmoth. Among Grs but not Ors, CNVs are more common within species in those gene lineages that have also duplicated over this evolutionary time-scale, suggesting ongoing rapid gene family evolution. Deep sequencing (∼1 billion reads) of transcriptomes from proboscis and labial palps, antennae, and legs of adult H. melpomene males and females indicates that 67 of the predicted 73 Gr genes and 67 of the 70 predicted Or genes are expressed in these three tissues. Intriguingly, we find that one-third of all Grs show female-biased gene expression (n = 26) and nearly all of these (n = 21) are Heliconius-specific Grs. In fact, a significant excess of Grs that are expressed in female legs but not male legs are the result of recent gene duplication. This difference in Gr gene expression diversity between the sexes is accompanied by a striking sexual dimorphism in the abundance of gustatory sensilla on the forelegs of H. melpomene, suggesting that female oviposition behaviour drives the evolution of new gustatory receptors in butterfly genomes

Perspectives and Integration in SOLAS Science

Why a chapter on Perspectives and Integration in SOLAS Science in this book? SOLAS science by its nature deals with interactions that occur: across a wide spectrum of time and space scales, involve gases and particles, between the ocean and the atmosphere, across many disciplines including chemistry, biology, optics, physics, mathematics, computing, socio-economics and consequently interactions between many different scientists and across scientific generations. This chapter provides a guide through the remarkable diversity of cross-cutting approaches and tools in the gigantic puzzle of the SOLAS realm. Here we overview the existing prime components of atmospheric and oceanic observing systems, with the acquisition of ocean–atmosphere observables either from in situ or from satellites, the rich hierarchy of models to test our knowledge of Earth System functioning, and the tremendous efforts accomplished over the last decade within the COST Action 735 and SOLAS Integration project frameworks to understand, as best we can, the current physical and biogeochemical state of the atmosphere and ocean commons. A few SOLAS integrative studies illustrate the full meaning of interactions, paving the way for even tighter connections between thematic fields. Ultimately, SOLAS research will also develop with an enhanced consideration of societal demand while preserving fundamental research coherency. The exchange of energy, gases and particles across the air-sea interface is controlled by a variety of biological, chemical and physical processes that operate across broad spatial and temporal scales. These processes influence the composition, biogeochemical and chemical properties of both the oceanic and atmospheric boundary layers and ultimately shape the Earth system response to climate and environmental change, as detailed in the previous four chapters. In this cross-cutting chapter we present some of the SOLAS achievements over the last decade in terms of integration, upscaling observational information from process-oriented studies and expeditionary research with key tools such as remote sensing and modelling. Here we do not pretend to encompass the entire legacy of SOLAS efforts but rather offer a selective view of some of the major integrative SOLAS studies that combined available pieces of the immense jigsaw puzzle. These include, for instance, COST efforts to build up global climatologies of SOLAS relevant parameters such as dimethyl sulphide, interconnection between volcanic ash and ecosystem response in the eastern subarctic North Pacific, optimal strategy to derive basin-scale CO2 uptake with good precision, or significant reduction of the uncertainties in sea-salt aerosol source functions. Predicting the future trajectory of Earth’s climate and habitability is the main task ahead. Some possible routes for the SOLAS scientific community to reach this overarching goal conclude the chapter

The multicellularity genes of dictyostelid social amoebas

The evolution of multicellularity enabled specialization of cells, but required novel signalling mechanisms for regulating cell differentiation. Early multicellular organisms are mostly extinct and the origins of these mechanisms are unknown. Here using comparative genome and transcriptome analysis across eight uni- and multicellular amoebozoan genomes, we find that 80% of proteins essential for the development of multicellular Dictyostelia are already present in their unicellular relatives. This set is enriched in cytosolic and nuclear proteins, and protein kinases. The remaining 20%, unique to Dictyostelia, mostly consists of extracellularly exposed and secreted proteins, with roles in sensing and recognition, while several genes for synthesis of signals that induce cell-type specialization were acquired by lateral gene transfer. Across Dictyostelia, changes in gene expression correspond more strongly with phenotypic innovation than changes in protein functional domains. We conclude that the transition to multicellularity required novel signals and sensors rather than novel signal processing mechanisms

Stoichiometric representation of geneproteinreaction associations leverages constraint-based analysis from reaction to gene-level phenotype prediction

Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: flux distribution prediction, gene essentiality analysis, random flux sampling, elementary mode analysis, transcriptomics data integration, and rational strain design. In each case we demonstrate how this approach can lead to improved phenotype predictions and a deeper understanding of the genotype-to-phenotype link. In particular, we show that a large fraction of reaction-based designs obtained by current strain design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions result in improved prediction accuracy. The model transformation proposed in this work enables existing constraint-based methods to be used at the gene level without modification. This automatically leverages phenotype analysis from reaction to gene level, improving the biological insight that can be obtained from genome-scale models.DM was supported by the Portuguese Foundationfor Science and Technologythrough a post-doc fellowship (ref: SFRH/BPD/111519/ 2015). This study was supported by the PortugueseFoundationfor Science and Technology (FCT) under the scope of the strategic fundingof UID/BIO/04469/2013 unitand COMPETE2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145FEDER-000004) fundedby EuropeanRegional Development Fund under the scope of Norte2020Programa Operacional Regional do Norte. This project has received fundingfrom the European Union’s Horizon 2020 research and innovation programme under grant agreementNo 686070. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Exposure to the tsunami disaster, PTSD symptoms and increased substance use – an Internet based survey of male and female residents of Switzerland

BACKGROUND: After the tsunami disaster in the Indian Ocean basin an Internet based self-screening test was made available in order to facilitate contact with mental health services. Although primarily designed for surviving Swiss tourists as well as relatives and acquaintances of the victims, the screening instrument was open to anyone who felt psychologically affected by this disaster. The aim of this study was to evaluate the influences between self-declared increased substance use in the aftermath of the tsunami disaster, trauma exposure and current PTSD symptoms. METHODS: One section of the screening covered addiction related behavior. We analyzed the relationship between increased substance use, the level of PTSD symptoms and trauma exposure using multivariable logistic regression with substance use as the dependent variable. Included in the study were only subjects who reported being residents of Switzerland and the analyses were stratified by gender in order to control for possible socio-cultural or gender differences in the use of psychotropic substances. RESULTS: In women PTSD symptoms and degree of exposure enlarged the odds of increased alcohol, pharmaceuticals and cannabis use significantly. In men the relationship was more specific: PTSD symptoms and degree of exposure only enlarged the odds of increased pharmaceutical consumption significantly. Increases in alcohol, cannabis and tobacco use were only significantly associated with the degree of PTSD symptoms. CONCLUSION: The tsunami was associated with increased substance use. This study not only replicates earlier findings but also suggests for a gender specificity of post-traumatic substance use increase