Determination by MAD-DM of the structure of the DNA duplex d[ACGTACG(5-BrU)]2 at 1.46 Å and 100 K

A four-wavelength MAD experiment on a new brominated octanucleotide is reported here. d[ACGTACG(5-BrU)], C77H81BrN30O32P7, (DNA) = 2235, tetragonal, P43212 (No. 96), a = 43.597, c = 26.268 Å, V = 49927.5 Å3, Z = 8, T = 100 K, R = 10.91% for 4312 reflections between 15.0 and 1.46 Å resolution. The self-complementary brominated octanucleotide d[ACGTACG(5-BrU)]2 has been crystallized and data measured to 1.45 Å at both 293 K and a second crystal flash frozen at 100 K. The latter data collection was carried out to the same resolution at the four wavelengths 0.9344, 0.9216, 0.9208 and 0.9003 Å, around the Br K edge at 0.92 Å and the structure determined from a map derived from a MAD data analysis using pseudo-MIR methodology, as implemented in the program MLPHARE. This is one of the first successful MAD phasing experiments carried out at Sincrotrone Elettra in Trieste, Italy. The structure was refined using the data measured at 0.9003 Å, anisotropic temperature factors and the restrained least-squares refinement implemented in the program SHELX96, and the helical parameters are compared with those previously determined for the isomorphous d(ACGTACGT)2 analogue. The asymmetric unit consists of a single strand of octamer with 96 water molecules. No countercations were located. The A-DNA helix geometry obtained has been analysed using the CURVES program.

The Mathematics of Control Theory

This text contains papers presented at the Institute of Mathematics and its Applications Conference on Control Theory, held at the University of Strathclyde in Glasgow. The contributions cover a wide range of topics of current interest to theoreticians and practitioners including algebraic systems theory, nonlinear control systems, adaptive control, robustness issues, infinite dimensional systems, applications studies and connections to mathematical aspects of information theory and data-fusion.

Proteomic analyses of a Listeria monocytogenes mutant lacking σB identify new components of the σB regulon and highlight a role for σB in the utilization of glycerol

In Listeria monocytogenes the alternative sigma factor σB plays important roles in both virulence and stress tolerance. In this study a proteomic approach was used to define components of the σB regulon in L. monocytogenes 10403S (serotype 1/2a). Using two-dimensional gel electrophoresis and the recently developed isobaric tags for relative and absolute quantitation technique, the protein expression profiles of the wild type and an isogenic ΔsigB deletion strain were compared. Overall, this study identified 38 proteins whose expression was σB dependent; 17 of these proteins were found to require the presence of σB for full expression, while 21 were expressed at a higher level in the ΔsigB mutant background. The data obtained with the two proteomic approaches showed limited overlap (four proteins were identified by both methods), a finding that highlights the complementarity of the two technologies. Overall, the proteomic data reaffirmed a role for σB in the general stress response and highlighted a probable role for σB in metabolism, especially in the utilization of alternative carbon sources. Proteomic and physiological data revealed the involvement of σB in glycerol metabolism. Five newly identified members of the σB regulon were shown to be under direct regulation of σB using reverse transcription-PCR (RT-PCR), while random amplification of cDNA ends-PCR was used to map four σB-dependent promoters upstream from lmo0796, lmo1830, lmo2391, and lmo2695. Using RT-PCR analysis of known and newly identified σB-dependent genes, as well as proteomic analyses, σB was shown to play a major role in the stationary phase of growth in complex media.

The benefits of a compute cluster approach to high spatial resolution biodiversity richness modelling: projecting the impact of climate change on Mediterranean flora

High spatial resolution environmental data gives us a better understanding of the environmental factors affecting plant distributions at fine spatial scales. However, large environmental datasets dramatically increase compute times and output species model size stimulating the need for an alternative computing solution. Cluster computing offers such a solution, by allowing both multiple plant species Environmental Niche Models (ENMs) and individual tiles of high spatial resolution models to be computed concurrently on the same compute cluster. We apply our methodology to a case study of 4,209 species of Mediterranean flora (around 17% of species believed present in the biome). We demonstrate a 16 times speed-up of ENM computation time when 16 CPUs were used on the compute cluster. Our custom Java ‘Merge’ and ‘Downsize’ programs reduce ENM output files sizes by 94%. The median 0.98 test AUC score of species ENMs is aided by various species occurrence data filtering techniques. Finally, by calculating the percentage change of individual grid cell values, we map the projected percentages of plant species vulnerable to climate change in the Mediterranean region between 1950–2000 and 2020.

Task design and second language performance: the effect of narrative type on learner output

This article reports on a detailed empirical study of the way narrative task design influences the oral performance of second-language (L2) learners. Building on previous research findings, two dimensions of narrative design were chosen for investigation: narrative complexity and inherent narrative structure. Narrative complexity refers to the presence of simultaneous storylines; in this case, we compared single-story narratives with dual-story narratives. Inherent narrative structure refers to the order of events in a narrative; we compared narratives where this was fixed to others where the events could be reordered without loss of coherence. Additionally, we explored the influence of learning context on performance by gathering data from two comparable groups of participants: 60 learners in a foreign language context in Teheran and 40 in an L2 context in London. All participants recounted two of four narratives from cartoon pictures prompts, giving a between-subjects design for narrative complexity and a within-subjects design for inherent narrative structure. The results show clearly that for both groups, L2 performance was affected by the design of the task: Syntactic complexity was supported by narrative storyline complexity and grammatical accuracy was supported by an inherently fixed narrative structure. We reason that the task of recounting simultaneous events leads learners into attempting more hypotactic language, such as subordinate clauses that follow, for example, while, although, at the same time as, etc. We reason also that a tight narrative structure allows learners to achieve greater accuracy in the L2 (within minutes of performing less accurately on a loosely structured narrative) because the tight ordering of events releases attentional resources that would otherwise be spent on finding connections between the pictures. The learning context was shown to have no effect on either accuracy or fluency but an unexpectedly clear effect on syntactic complexity and lexical diversity. The learners in London seem to have benefited from being in the target language environment by developing not more accurate grammar but a more diverse resource of English words and syntactic choices. In a companion article (Foster & Tavakoli, 2009) we compared their performance with native-speaker baseline data and see that, in terms of nativelike selection of vocabulary and phrasing, the learners in London are closing in on native-speaker norms. The study provides empirical evidence that L2 performance is affected by task design in predictable ways. It also shows that living within the target language environment, and presumably using the L2 in a host of everyday tasks outside the classroom, confers a distinct lexical advantage, not a grammatical one.

Genome dynamics explain the evolution of flowering time CCT domain gene families in the Poaceae

Numerous CCT domain genes are known to control flowering in plants. They belong to the CONSTANS-like (COL) and PREUDORESPONSE REGULATOR (PRR) gene families, which in addition to a CCT domain possess B-box or response-regulator domains, respectively. Ghd7 is the most recently identified COL gene to have a proven role in the control of flowering time in the Poaceae. However, as it lacks B-box domains, its inclusion within the COL gene family, technically, is incorrect. Here, we show Ghd7 belongs to a larger family of previously uncharacterized Poaceae genes which possess just a single CCT domain, termed here CCT MOTIF FAMILY (CMF) genes. We molecularly describe the CMF (and related COL and PRR) gene families in four sequenced Poaceae species, as well as in the draft genome assembly of barley (Hordeum vulgare). Genetic mapping of the ten barley CMF genes identified, as well as twelve previously unmapped HvCOL and HvPRR genes, finds the majority map to colinear positions relative to their Poaceae orthologues. Combined inter-/intra-species comparative and phylogenetic analysis of CMF, COL and PRR gene families indicates they evolved prior to the monocot/dicot divergence ~200 mya, with Poaceae CMF evolution described as the interplay between whole genome duplication in the ancestral cereal, and subsequent clade-specific mutation, deletion and duplication events. Given the proven role of CMF genes in the modulation of cereals flowering, the molecular, phylogenetic and comparative analysis of the Poaceae CMF, COL and PRR gene families presented here provides the foundation from which functional investigation can be undertaken.

Integration of retrotransposons-based markers in a linkage map of barley

A deeper understanding of random markers is important if they are to be employed for a range of objectives. The sequence specific amplified polymorphism (S-SAP) technique is a powerful genetic analysis tool which exploits the high copy number of retrotransposon long terminal repeats (LTRs) in the plant genome. The distribution and inheritance of S-SAP bands in the barley genome was studied using the Steptoe × Morex (S × M) double haploid (DH) population. Six S-SAP primer combinations generated 98 polymorphic bands, and map positions were assigned to all but one band. Eight putative co-dominant loci were detected, representing 16 of the mapped markers. Thus at least 81 of the mapped S-SAP loci were dominant. The markers were distributed along all of the seven chromosomes and a tendency to cluster was observed. The distribution of S-SAP markers over the barley genome concurred with the knowledge of the high copy number of retrotransposons in plants. This experiment has demonstrated the potential for the S-SAP technique to be applied in a range of analyses such as genetic fingerprinting, marker assisted breeding, biodiversity assessment and phylogenetic analyses.

Realistic mean field forward predictions for the integration of co-registered EEG/fMRI

Brain activity can be measured non-invasively with functional imaging techniques. Each pixel in such an image represents a neural mass of about 105 to 107 neurons. Mean field models (MFMs) approximate their activity by averaging out neural variability while retaining salient underlying features, like neurotransmitter kinetics. However, MFMs incorporating the regional variability, realistic geometry and connectivity of cortex have so far appeared intractable. This lack of biological realism has led to a focus on gross temporal features of the EEG. We address these impediments and showcase a "proof of principle" forward prediction of co-registered EEG/fMRI for a full-size human cortex in a realistic head model with anatomical connectivity, see figure 1. MFMs usually assume homogeneous neural masses, isotropic long-range connectivity and simplistic signal expression to allow rapid computation with partial differential equations. But these approximations are insufficient in particular for the high spatial resolution obtained with fMRI, since different cortical areas vary in their architectonic and dynamical properties, have complex connectivity, and can contribute non-trivially to the measured signal. Our code instead supports the local variation of model parameters and freely chosen connectivity for many thousand triangulation nodes spanning a cortical surface extracted from structural MRI. This allows the introduction of realistic anatomical and physiological parameters for cortical areas and their connectivity, including both intra- and inter-area connections. Proper cortical folding and conduction through a realistic head model is then added to obtain accurate signal expression for a comparison to experimental data. To showcase the synergy of these computational developments, we predict simultaneously EEG and fMRI BOLD responses by adding an established model for neurovascular coupling and convolving "Balloon-Windkessel" hemodynamics. We also incorporate regional connectivity extracted from the CoCoMac database [1]. Importantly, these extensions can be easily adapted according to future insights and data. Furthermore, while our own simulation is based on one specific MFM [2], the computational framework is general and can be applied to models favored by the user. Finally, we provide a brief outlook on improving the integration of multi-modal imaging data through iterative fits of a single underlying MFM in this realistic simulation framework.

Is optical imaging spectroscopy a viable measurement technique for the investigation of the negative BOLD phenomenon? A concurrent optical imaging spectroscopy and fMRI study at high field (7T)

Traditionally functional magnetic resonance imaging (fMRI) has been used to map activity in the human brain by measuring increases in the Blood Oxygenation Level Dependent (BOLD) signal. Often accompanying positive BOLD fMRI signal changes are sustained negative signal changes. Previous studies investigating the neurovascular coupling mechanisms of the negative BOLD phenomenon have used concurrent 2D-optical imaging spectroscopy (2D-OIS) and electrophysiology (Boorman et al., 2010). These experiments suggested that the negative BOLD signal in response to whisker stimulation was a result of an increase in deoxy-haemoglobin and reduced multi-unit activity in the deep cortical layers. However, Boorman et al. (2010) did not measure the BOLD and haemodynamic response concurrently and so could not quantitatively compare either the spatial maps or the 2D-OIS and fMRI time series directly. Furthermore their study utilised a homogeneous tissue model in which is predominantly sensitive to haemodynamic changes in more superficial layers. Here we test whether the 2D-OIS technique is appropriate for studies of negative BOLD. We used concurrent fMRI with 2D-OIS techniques for the investigation of the haemodynamics underlying the negative BOLD at 7 Tesla. We investigated whether optical methods could be used to accurately map and measure the negative BOLD phenomenon by using 2D-OIS haemodynamic data to derive predictions from a biophysical model of BOLD signal changes. We showed that despite the deep cortical origin of the negative BOLD response, if an appropriate heterogeneous tissue model is used in the spectroscopic analysis then 2D-OIS can be used to investigate the negative BOLD phenomenon.

Conspicuous redemption? Reflections on the promises and perils of the 'celebritization' of climate change

With rising public awareness of climate change, celebrities have become an increasingly important community of non nation-state ‘actors’ influencing discourse and action, thereby comprising an emergent climate science–policy–celebrity complex. Some feel that these amplified and prominent voices contribute to greater public understanding of climate change science, as well as potentially catalyze climate policy cooperation. However, critics posit that increased involvement from the entertainment industry has not served to influence substantive long-term advancements in these arenas; rather, it has instead reduced the politics of climate change to the domain of fashion and fad, devoid of political and public saliency. Through tracking media coverage in Australia, Canada, the United States, and United Kingdom, we map out the terrain of a ‘Politicized Celebrity System’ in attempts to cut through dualistic characterizations of celebrity involvement in politics. We develop a classification system of the various types of climate change celebrity activities, and situate movements in contemporary consumer- and spectacle-driven carbon-based society. Through these analyses, we place dynamic and contested interactions in a spatially and temporally-sensitive ‘Cultural Circuits of Climate Change Celebrities’ model. In so doing, first we explore how these newly ‘authorized’ speakers and ‘experts’ might open up spaces in the public sphere and the science/policy nexus through ‘celebritization’ effects. Second, we examine how the celebrity as the ‘heroic individual’ seeking ‘conspicuous redemption’ may focus climate change actions through individualist frames. Overall, this paper explores potential promises, pitfalls and contradictions of this increasingly entrenched set of ‘agents’ in the cultural politics of climate change. Thus, as a form of climate change action, we consider whether it is more effective to ‘plant’ celebrities instead of trees.

Diverse mechanisms underlying the regulation of ion channels by carbon monoxide

Carbon monoxide is firmly established as an important, physiological signalling molecule as well as a potent toxin. Through its ability to bind metal-containing proteins it is known to interfere with a number of intracellular signalling pathways, and such actions can account for its physiological and pathological effects. In particular, CO can modulate the intracellular production of reactive oxygen species, nitric oxide and cGMP levels, as well as regulate MAP kinase signalling. In this review, we consider ion channels as more recently discovered effectors of CO signalling. CO is now known to regulate a growing number of different ion channel types, and detailed studies of the underlying mechanisms of action are revealing unexpected findings. For example, there are clear areas of contention surrounding its ability to increase the activity of high conductance, Ca2+ -sensitive K+ channels. More recent studies have revealed the ability of CO to inhibit T-type Ca2+ channels and have unveiled a novel signalling pathway underlying tonic regulation of this channel. It is clear that the investigation of ion channels as effectors of CO signalling is in its infancy, and much more work is required to fully understand both the physiological and the toxic actions of this gas. Only then can its emerging use as a therapeutic tool be fully and safely exploited.

Pit clusters and the temporality of occupation: an earlier Neolithic site at Kilverstone, Thetford, Norfolk

This paper discusses 226 earlier Neolithic pits found at Kilverstone in Norfolk. In particular, it focuses on the dynamics involved in the site's creation, investigating what had happened to the material found in the pits prior to deposition, and exploring the material connections (refitting sherds and flints) across the site. As a result of these material insights, it proved possible to shed important light on the character of that place in particular, and on the temporality of Neolithic deposition and occupation in general.

The error of representation: basic understanding

Representation error arises from the inability of the forecast model to accurately simulate the climatology of the truth. We present a rigorous framework for understanding this kind of error of representation. This framework shows that the lack of an inverse in the relationship between the true climatology (true attractor) and the forecast climatology (forecast attractor) leads to the error of representation. A new gain matrix for the data assimilation problem is derived that illustrates the proper approaches one may take to perform Bayesian data assimilation when the observations are of states on one attractor but the forecast model resides on another. This new data assimilation algorithm is the optimal scheme for the situation where the distributions on the true attractor and the forecast attractors are separately Gaussian and there exists a linear map between them. The results of this theory are illustrated in a simple Gaussian multivariate model.