Chromatic Illumination Discrimination Ability Reveals that Human Colour Constancy Is Optimised for Blue Daylight Illuminations

The phenomenon of colour constancy in human visual perception keeps surface colours constant, despite changes in their reflected light due to changing illumination. Although colour constancy has evolved under a constrained subset of illuminations, it is unknown whether its underlying mechanisms, thought to involve multiple components from retina to cortex, are optimised for particular environmental variations. Here we demonstrate a new method for investigating colour constancy using illumination matching in real scenes which, unlike previous methods using surface matching and simulated scenes, allows testing of multiple, real illuminations. We use real scenes consisting of solid familiar or unfamiliar objects against uniform or variegated backgrounds and compare discrimination performance for typical illuminations from the daylight chromaticity locus (approximately blue-yellow) and atypical spectra from an orthogonal locus (approximately red-green, at correlated colour temperature 6700 K), all produced in real time by a 10-channel LED illuminator. We find that discrimination of illumination changes is poorer along the daylight locus than the atypical locus, and is poorest particularly for bluer illumination changes, demonstrating conversely that surface colour constancy is best for blue daylight illuminations. Illumination discrimination is also enhanced, and therefore colour constancy diminished, for uniform backgrounds, irrespective of the object type. These results are not explained by statistical properties of the scene signal changes at the retinal level. We conclude that high-level mechanisms of colour constancy are biased for the blue daylight illuminations and variegated backgrounds to which the human visual system has typically been exposed

Measurement of the t(t)over-bar production cross section in the dilepton channel in pp collisions at √s=8 TeV

The top-antitop quark (t (t) over bar) production cross section is measured in proton-proton collisions at root s = 8 TeV with the CMS experiment at the LHC, using a data sample corresponding to an integrated luminosity of 5.3 fb(-1). The measurement is performed by analysing events with a pair of electrons or muons, or one electron and one muon, and at least two jets, one of which is identified as originating from hadronisation of a bottom quark. The measured cross section is 239 +/- 2 (stat.) +/- 11 (syst.) +/- 6 (lum.) pb, for an assumed top-quark mass of 172.5 GeV, in agreement with the prediction of the standard model

Primate TNF Promoters Reveal Markers of Phylogeny and Evolution of Innate Immunity

Background. Tumor necrosis factor (TNF) is a critical cytokine in the immune response whose transcriptional activation is controlled by a proximal promoter region that is highly conserved in mammals and, in particular, primates. Specific single nucleotide polymorphisms (SNPs) upstream of the proximal human TNF promoter have been identified, which are markers of human ancestry. Methodology/Principal findings. Using a comparative genomics approach we show that certain fixed genetic differences in the TNF promoter serve as markers of primate speciation. We also demonstrate that distinct alleles of most human TNF promoter SNPs are identical to fixed nucleotides in primate TNF promoters. Furthermore, we identify fixed genetic differences within the proximal TNF promoters of Asian apes that do not occur in African ape or human TNF promoters. Strikingly, protein-DNA binding assays and gene reporter assays comparing these Asian ape TNF promoters to African ape and human TNF promoters demonstrate that, unlike the fixed differences that we define that are associated with primate phylogeny, these Asian ape-specific fixed differences impair transcription factor binding at an Sp1 site and decrease TNF transcription induced by bacterial stimulation of macrophages. Conclusions/significance. Here, we have presented the broadest interspecies comparison of a regulatory region of an innate immune response gene to date. We have characterized nucleotide positions in Asian ape TNF promoters that underlie functional changes in cell type- and stimulus-specific activation of the TNF gene. We have also identified ancestral TNF promoter nucleotide states in the primate lineage that correspond to human SNP alleles. These findings may reflect evolution of Asian and African apes under a distinct set of infectious disease pressures involving the innate immune response and TNF

A Novel Ecdysone Receptor Mediates Steroid-Regulated Developmental Events during the Mid-Third Instar of Drosophila

The larval salivary gland of Drosophila melanogaster synthesizes and secretes glue glycoproteins that cement developing animals to a solid surface during metamorphosis. The steroid hormone 20-hydroxyecdysone (20E) is an essential signaling molecule that modulates most of the physiological functions of the larval gland. At the end of larval development, it is known that 20E—signaling through a nuclear receptor heterodimer consisting of EcR and USP—induces the early and late puffing cascade of the polytene chromosomes and causes the exocytosis of stored glue granules into the lumen of the gland. It has also been reported that an earlier pulse of hormone induces the temporally and spatially specific transcriptional activation of the glue genes; however, the receptor responsible for triggering this response has not been characterized. Here we show that the coordinated expression of the glue genes midway through the third instar is mediated by 20E acting to induce genes of the Broad Complex (BRC) through a receptor that is not an EcR/USP heterodimer. This result is novel because it demonstrates for the first time that at least some 20E-mediated, mid-larval, developmental responses are controlled by an uncharacterized receptor that does not contain an RXR-like component

Yield and Economic Performance of Organic and Conventional Cotton-Based Farming Systems – Results from a Field Trial in India

The debate on the relative benefits of conventional and organic farming systems has in recent time gained significant interest. So far, global agricultural development has focused on increased productivity rather than on a holistic natural resource management for food security. Thus, developing more sustainable farming practices on a large scale is of utmost importance. However, information concerning the performance of farming systems under organic and conventional management in tropical and subtropical regions is scarce. This study presents agronomic and economic data from the conversion phase (2007–2010) of a farming systems comparison trial on a Vertisol soil in Madhya Pradesh, central India. A cotton-soybean-wheat crop rotation under biodynamic, organic and conventional (with and without Bt cotton) management was investigated. We observed a significant yield gap between organic and conventional farming systems in the 1st crop cycle (cycle 1: 2007–2008) for cotton (229%) and wheat (227%), whereas in the 2nd crop cycle (cycle 2: 2009–2010) cotton and wheat yields were similar in all farming systems due to lower yields in the conventional systems. In contrast, organic soybean (a nitrogen fixing leguminous plant) yields were marginally lower than conventional yields (21% in cycle 1, 211% in cycle 2). Averaged across all crops, conventional farming systems achieved significantly higher gross margins in cycle 1 (+29%), whereas in cycle 2 gross margins in organic farming systems were significantly higher (+25%) due to lower variable production costs but similar yields. Soybean gross margin was significantly higher in the organic system (+11%) across the four harvest years compared to the conventional systems. Our results suggest that organic soybean production is a viable option for smallholder farmers under the prevailing semi-arid conditions in India. Future research needs to elucidate the long-term productivity and profitability, particularly of cotton and wheat, and the ecological impact of the different farming systems

Nanorings and rods interconnected by self-assembly mimicking an artificial network of neurons

[EN] Molecular electronics based on structures ordered as neural networks emerges as the next evolutionary milestone in the construction of nanodevices with unprecedented applications. However, the straightforward formation of geometrically defined and interconnected nanostructures is crucial for the production of electronic circuitry nanoequivalents. Here we report on the molecularly fine-tuned self-assembly of tetrakis-Schiff base compounds into nanosized rings interconnected by unusually large nanorods providing a set of connections that mimic a biological network of neurons. The networks are produced through self-assembly resulting from the molecular conformation and noncovalent intermolecular interactions. These features can be easily generated on flat surfaces and in a polymeric matrix by casting from solution under ambient conditions. The structures can be used to guide the position of electron-transporting agents such as carbon nanotubes on a surface or in a polymer matrix to create electrically conducting networks that can find direct use in constructing nanoelectronic circuits.The research leading to these results has received funding from ICIQ, ICREA, the Spanish Ministerio de Economia y Competitividad (MINECO) through project CTQ2011-27385 and the European Community Seventh Framework Program (FP7-PEOPLE-ITN-2008, CONTACT consortium) under grant agreement number 238363. We acknowledge E. C. Escudero-Adan, M. Martinez-Belmonte and E. Martin from the X-ray department of ICIQ for crystallographic analysis, and M. Moncusi, N. Argany, R. Marimon, M. Stefanova and L. Vojkuvka from the Servei de Recursos Cientifics i Tecnics from Universitat Rovira i Virgili (Tarragona, Spain).Escarcega-Bobadilla, MV.; Zelada-Guillen, GA.; Pyrlin, SV.; Wegrzyn, M.; Ramos, MMD.; Giménez Torres, E.; Stewart, A.... (2013). Nanorings and rods interconnected by self-assembly mimicking an artificial network of neurons. Nature Communications. 4:2648-2648. https://doi.org/10.1038/ncomms3648S264826484Champness, N. R. Making the right connections. Nat. Chem. 4, 149–150 (2012).Hopfield, J. J. & Tank, D. W. Computing with neural circuits: A model. Science 233, 625–633 (1986).Andres, P. R. et al. Self-assembly of a two-dimensional superlattice of molecularly linked metal clusters. Science 273, 1690–1693 (1996).Eichen, Y., Braun, E., Sivan, U. & Ben-Yoseph, G. Self-assembly of nanoelectronic components and circuits using biological templates. Acta Polym. 49, 663–670 (1998).Kawakami, T. et al. Possibilities of molecule-based spintronics of DNA wires, sheets, and related materials. Int. J. Quantum Chem. 105, 655–671 (2005).Kashtan, N., Itzkovitz, S., Milo, R. & Alon, U. Topological generalizations of network motifs. Phys. Rev. E 70, 031909 (2004).Grill, L. et al. Nano-architectures by covalent assembly of molecular building blocks. Nat. Nanotech. 2, 687–691 (2007).Lafferentz, L. et al. Controlling on-surface polymerization by hierarchical and substrate-directed growth. Nat. Chem. 4, 215–220 (2012).Alivisatos, A. P. et al. From molecules to materials: current trends and future directions. Adv. Mater. 10, 1297–1336 (1998).Pauling, L. The principles determining the structure of complex ionic crystals. J. Am. Chem. Soc. 51, 1010–1026 (1929).Damasceno, P. F., Engel, M. & Glotzer, S. C. Predictive self-assembly of polyhedra into complex structures. Science 337, 453–457 (2012).De Graaf, J. & Manna, L. A roadmap for the assembly of polyhedral particles. Science 337, 417–418 (2012).Percec, V. et al. Controlling polymer shape through the self-assembly of dendritic side-groups. Nature 391, 161–164 (1998).Stupp, S. I. et al. Supramolecular materials: self-organized nanostructures. Science 276, 384–389 (1997).Mann, S. The chemistry of form. Angew. Chem. Int. Ed. 39, 3392–3406 (2000).Sakakibara, K., Hill, J. P. & Ariga, K. Thin-film-based nanoarchitectures for soft matter: controlled assemblies into two-dimensional worlds. Small 7, 1288–1308 (2011).Huang, Z. et al. Pulsating tubules from noncovalent macrocycles. Science 337, 1521–1526 (2012).Ackermann, D., Jester, S.-S. & Famulok, M. Design strategy for DNA rotaxanes with a mechanically reinforced PX100 axle. Angew. Chem. Int. Ed. 27, 6771–6775 (2012).Marx, J. L. Microtubules: versatile organelles. Science 181, 1236–1237 (1973).Heus, H. A. & Pardi, A. Structural features that give rise to the unusual stability of RNA hairpins containing GNRA loops. Science 253, 191–194 (1991).Braun, E., Eichen, Y., Sivan, U. & Ben-Yoseph, G. DNA-templated assembly and electrode attachment of a conducting silver wire. Nature 391, 775–778 (1998).Zhang, S. Fabrication of novel biomaterials through molecular self-assembly. Nat. Biotechnol. 21, 1171–1178 (2003).Cai, X. et al. Integrated compact optical vortex beam emitters. Science 338, 363–365 (2012).Clark, A. W. & Cooper, J. M. Nanogap ring antennae as plasmonically coupled SERRS substrates. Small 7, 119–125 (2011).Armani, A. M., Kulkarni, R. P., Fraser, S. E., Flagan, R. C. & Vahala, K. J. Label-free, single-molecule detection with optical microcavities. Science 317, 783–787 (2007).Frischmann, P. D., Guieu, S., Tabeshi, R. & MacLachlan, M. J. Columnar organization of head-to-tail self-assembled Pt4 rings. J. Am. Chem. Soc. 132, 7668–7675 (2010).Frischmann, P. D. et al. Capsule formation, carboxylate exchange, and DFT exploration of cadmium cluster metallocavitands: highly dynamic supramolecules. J. Am. Chem. Soc. 132, 3893–3908 (2010).Akine, S., Hotate, S. & Nabeshima, T. A molecular leverage for helicity control and helix Inversion. J. Am. Chem. Soc. 133, 13868–13871 (2011).Salassa, G. et al. Extremely strong self-assembly of a bimetallic salen complex visualized at the single-molecule level. J. Am. Chem. Soc. 134, 7186–7192 (2012).Escárcega-Bobadilla, M. V., Salassa, G., Martínez Belmonte, M., Escudero-Adán, E. C. & Kleij, A. W. Versatile switching in substrate topicity: supramolecular chirality induction in di- and trinuclear host complexes. Chem. Eur. J. 18, 6805–6810 (2012).Frischmann, P. D., Jiang, J., Hui, J. K.-H., Grzybowski, J. J. & MacLachlan, M. J. Reversible—irreversible approach to Schiff base macrocycles. Access to isomeric macrocycles with multiple salphen pockets. Org. Lett. 10, 1255–1258 (2008).Glaser, T. Rational design of single-molecule magnets: a supramolecular approach. Chem. Commun. 47, 116–130 (2011).Lee, E. C. et al. Understanding of assembly phenomena by aromatic−aromatic interactions: benzene dimer and the substituted systems. J. Phys. Chem. A 111, 3446–3457 (2007).Grybowski, B. A., Wilmer, C. E., Kim, J., Browne, K. P. & Bishop, K. J. M. Self-assembly: from crystals to cells. Soft Matter. 5, 1110–1128 (2009).Martínez Belmonte, M. et al. Self-assembly of Zn(salphen) complexes: steric regulation, stability studies and crystallographic analysis revealing an unexpected dimeric 3,3′-t-Bu-substituted Zn(salphen) complex. Dalton Trans. 39, 4541–4550 (2010).Salassa, G., Castilla, A. M. & Kleij, A. W. Cooperative self-assembly of a macrocyclic Schiff base complex. Dalton Trans. 40, 5236–5243 (2011).Hormoz, S. & Brenner, M. P. Design principles for self-assembly with short-range interactions. Proc. Natl Acad. Sci. 108, 5193–5198 (2011).Biemans, H. A. M. et al. Hexakis porphyrinato benzenes. A new class of porphyrin arrays. J. Am. Chem. Soc. 120, 11054–11060 (1998).Lensen, M. C. et al. Aided self-assembly of porphyrin nanoaggregates into ring-shaped architectures. Chem. Eur. J. 10, 831–839 (2004).Martin, A., Buguin, A. & Brochard-Wyart, F. Dewetting nucleation centers at soft interfaces. Langmuir. 17, 6553–6559 (2001).Schenning, A. P. H. J., Benneker, F. B. G., Geurts, H. P. M., Liu, X. Y. & Nolte, R. J. M. Porphyrin wheels. J. Am. Chem. Soc. 118, 8549–8552 (1996).Deegan, R. D. et al. Capillary flow as the cause of ring strains from dried liquid drops. Nature 389, 827–829 (1997).Scriven, L. E. & Sternling, C. V. The Marangoni effects. Nature 187, 186–188 (1960).Cai, Y. & Newby, B. Z. Marangoni flow-induced self-assembly of hexagonal and stripe-like nanoparticle patterns. J. Am. Chem. Soc. 130, 6076–6077 (2008).Whitesides, G. M. & Grzybowski, B. Self-assembly at all scales. Science 295, 2418–2421 (2002).Mann, S. Self-assembly and transformation of hybrid nano-objects and nanostructures under equilibrium and non-equilibrium conditions. Nat. Mater. 8, 781–792 (2009).Gröschnel, A. H. et al. Precise hierarchical self-assembly of multicompartment micelles. Nat. Commun. 3, 710 (2012).Adam, M., Dogic, Z., Keller, S. L. & Fraden, S. Entropically driven microphase transitions in mixtures of colloidal rods and spheres. Nature 393, 349–352 (1998).Ohara, P. C., Heath, J. R. & Gelbart, W. M. Self-assembly of submicrometer rings of particles from solutions of nanoparticles. Angew. Chem. Int. Ed. 36, 1077–1080 (1997).Xu, J., Xia, J. & Lin, Z. Evaporation-induced self-assembly of nanoparticles from a sphere-on-flat geometry. Angew. Chem. Int. Ed. 46, 1860–1863 (2007).Yosef, G. & Rabani, E. Self-assembly of nanoparticles into rings: A lattice-gas model. J. Phys. Chem. B 110, 20965–20972 (2006).Khanal, B. P. & Zubarev, E. R. Rings of nanorods. Angew. Chem. Int. Ed. 46, 2195–2198 (2007).Wang, Z. et al. One-step, self-assembly, alignment, and patterning of organic semiconductor nanowires by controlled evaporation of confined microfluids. Angew. Chem. Int. Ed. 50, 2811–2815 (2011).Hong, S. W. et al. Directed self-assembly of gradient concentric carbon nanotube rings. Adv. Func. Mater. 18, 2114–2122 (2008).Palma, M. et al. Controlled formation of carbon nanotube junctions via linker-induced assembly in aqueous solution. J. Am. Chem. Soc. 135, 8440–8443 (2013).Horcas, I. et al. WSXM: A software for scanning probe microscopy and a tool for nanotechnology. Rev. Sci. Instrum. 78, 013705 (2007).Soler, J. M. et al. The SIESTA method for ab initio order-n materials simulation. J. Phys. Cond. Matter 14, 2745–2779 (2002).Haynes, P. D., Mostof, A. A., Skylaris, C. & Payne, M. C. ONETEP: Linear-scaling density-functional theory with plane-waves. J. Phys. Conf. Ser. 26, 143–148 (2006).Valiev, M. et al. NWCHEM: A comprehensive and scalable open-source solution for large scale molecular simulations. Comp. Phys. Commun. 181, 1477–1489 (2010).Plimpton, S. Fast parallel algorithms for short-range molecular dynamics. J. Comp. Phys. 117, 1–19 (1995)

Population Genomics of Parallel Adaptation in Threespine Stickleback using Sequenced RAD Tags

Next-generation sequencing technology provides novel opportunities for gathering genome-scale sequence data in natural populations, laying the empirical foundation for the evolving field of population genomics. Here we conducted a genome scan of nucleotide diversity and differentiation in natural populations of threespine stickleback (Gasterosteus aculeatus). We used Illumina-sequenced RAD tags to identify and type over 45,000 single nucleotide polymorphisms (SNPs) in each of 100 individuals from two oceanic and three freshwater populations. Overall estimates of genetic diversity and differentiation among populations confirm the biogeographic hypothesis that large panmictic oceanic populations have repeatedly given rise to phenotypically divergent freshwater populations. Genomic regions exhibiting signatures of both balancing and divergent selection were remarkably consistent across multiple, independently derived populations, indicating that replicate parallel phenotypic evolution in stickleback may be occurring through extensive, parallel genetic evolution at a genome-wide scale. Some of these genomic regions co-localize with previously identified QTL for stickleback phenotypic variation identified using laboratory mapping crosses. In addition, we have identified several novel regions showing parallel differentiation across independent populations. Annotation of these regions revealed numerous genes that are candidates for stickleback phenotypic evolution and will form the basis of future genetic analyses in this and other organisms. This study represents the first high-density SNP–based genome scan of genetic diversity and differentiation for populations of threespine stickleback in the wild. These data illustrate the complementary nature of laboratory crosses and population genomic scans by confirming the adaptive significance of previously identified genomic regions, elucidating the particular evolutionary and demographic history of such regions in natural populations, and identifying new genomic regions and candidate genes of evolutionary significance