Consequences of selecting technology pathways on cumulative carbon dioxide emissions for the United Kingdom

The UK has an ambitious target of an 80% reduction in carbon dioxide emissions by 2050, to be reached using a series of ‘carbon budgets’ to aid policy development. Current energy systems modelling methods do not explore, or are unable to account for, physical (thermodynamic) limits to the rate of change of infrastructure. The power generation sector has a variety of technological options for this low-carbon transition. We compare physically constrained scenarios that accentuate either carbon capture and storage, fastest plausible nuclear new build, or fastest plausible build rate of offshore wind. We set these in the context of the UK’s legislated fifth carbon budget, which has a comprehensive range of carbon reduction measures with respect to business-as-usual. The framework for our scenario comparison uses our novel system dynamics model to substantiate the policy’s ability to meet 2035 emissions targets while maintaining financial productivity and socially expected employment levels. For an ambitious nuclear new build programme we find that even if it stays on track it is more expensive than offshore wind generation and delays emissions reductions. This affects the cumulative emissions and impacts on the UK’s ability to contribute to international climate change targets. If delays or cancellation occur to the deployment programmes of carbon capture and storage technologies or nuclear new build, we suggest the electricity and decarbonisation targets can by met by a fast growth of offshore wind generation with no change to financial and employment levels.Arup’s internal Design and Technical Fun

Modelling socio-economic and energy data to generate business-as-usual scenarios for carbon emissions

The UK Government is legally committed to achieving an 80% reduction in carbon dioxide emissions compared with 1990 by 2050. The use of scenarios is wide ranging to inform policy development and forming a businessas-usual scenario helps to understand possible effects of different policy interventions. However, the term business-as-usual is frequently misused. We show how econo-physical business-as-usual scenarios can be developed by examining the historical behaviour of coefficients which manifest the relationship between components of an economy. We endogenise economic growth by mimicking national level policies that focus on a target level of unemployment. Our case-study demonstrates the ‘trendability’ of coefficients which for one example coefficient is replicated for Australia, Colombia, Taiwan and the USA. We manifest a gross domestic product growth of 2% falling to 1% which contrasts with an exogenous growth of 2.3% of a comparator business-as-usual scenario. We suggest that it may be possible to achieve a greater reduction in the business-asusual carbon dioxide emissions in the UK fifth carbon budget than currently projected.Arup’s internal Design and Technical Fun

Indian Ocean Dipole drives malaria resurgence in East African highlands

Malaria resurgence in African highlands in the 1990s has raised questions about the underlying drivers of the increase in disease incidence including the role of El-Niño-Southern Oscillation (ENSO). However, climatic anomalies other than the ENSO are clearly associated with malaria outbreaks in the highlands. Here we show that the Indian Ocean Dipole (IOD), a coupled ocean-atmosphere interaction in the Indian Ocean, affected highland malaria re-emergence. Using cross-wavelet coherence analysis, we found four-year long coherent cycles between the malaria time series and the dipole mode index (DMI) in the 1990s in three highland localities. Conversely, we found a less pronounced coherence between malaria and DMI in lowland localities. The highland/lowland contrast can be explained by the effects of mesoscale systems generated by Lake Victoria on its climate basin. Our results support the need to consider IOD as a driving force in the resurgence of malaria in the East African highlands

Limits to the Rate of Adaptive Substitution in Sexual Populations

In large populations, many beneficial mutations may be simultaneously available and may compete with one another, slowing adaptation. By finding the probability of fixation of a favorable allele in a simple model of a haploid sexual population, we find limits to the rate of adaptive substitution, , that depend on simple parameter combinations. When variance in fitness is low and linkage is loose, the baseline rate of substitution is , where is the population size, is the rate of beneficial mutations per genome, and is their mean selective advantage. Heritable variance in log fitness due to unlinked loci reduces by under polygamy and under monogamy. With a linear genetic map of length Morgans, interference is yet stronger. We use a scaling argument to show that the density of adaptive substitutions depends on , , , and only through the baseline density: . Under the approximation that the interference due to different sweeps adds up, we show that , implying that interference prevents the rate of adaptive substitution from exceeding one per centimorgan per 200 generations. Simulations and numerical calculations confirm the scaling argument and confirm the additive approximation for ; for higher , the rate of adaptation grows above , but only very slowly. We also consider the effect of sweeps on neutral diversity and show that, while even occasional sweeps can greatly reduce neutral diversity, this effect saturates as sweeps become more common—diversity can be maintained even in populations experiencing very strong interference. Our results indicate that for some organisms the rate of adaptive substitution may be primarily recombination-limited, depending only weakly on the mutation supply and the strength of selection

Meredys, a multi-compartment reaction-diffusion simulator using multistate realistic molecular complexes

<p>Abstract</p> <p>Background</p> <p>Most cellular signal transduction mechanisms depend on a few molecular partners whose roles depend on their position and movement in relation to the input signal. This movement can follow various rules and take place in different compartments. Additionally, the molecules can form transient complexes. Complexation and signal transduction depend on the specific states partners and complexes adopt. Several spatial simulator have been developed to date, but none are able to model reaction-diffusion of realistic multi-state transient complexes.</p> <p>Results</p> <p><it>Meredys </it>allows for the simulation of multi-component, multi-feature state molecular species in two and three dimensions. Several compartments can be defined with different diffusion and boundary properties. The software employs a Brownian dynamics engine to simulate reaction-diffusion systems at the reactive particle level, based on compartment properties, complex structure, and hydro-dynamic radii. Zeroth-, first-, and second order reactions are supported. The molecular complexes have realistic geometries. Reactive species can contain user-defined feature states which can modify reaction rates and outcome. Models are defined in a versatile NeuroML input file. The simulation volume can be split in subvolumes to speed up run-time.</p> <p>Conclusions</p> <p><it>Meredys </it>provides a powerful and versatile way to run accurate simulations of molecular and sub-cellular systems, that complement existing multi-agent simulation systems. <it>Meredys </it>is a Free Software and the source code is available at <url>http://meredys.sourceforge.net/</url>.</p

NMR Analysis of the Dynamic Exchange of the NS2B Cofactor between Open and Closed Conformations of the West Nile Virus NS2B-NS3 Protease

Dengue and West Nile virus infections put an estimated 2.5 billion people at risk. Neither drugs nor vaccines are currently available against these diseases. The non-structural protein NS3 is a protease that, together with the cofactor NS2B, is essential for viral maturation. The NS2B-NS3 proteases of dengue and West Nile viruses are highly homologous and present promising drug targets. Crystal structures of the West Nile virus protease with and without bound inhibitor revealed large structural differences in NS2B, while no crystal structure of the dengue virus protease could be determined with a bound inhibitor. We investigated the structural change in solution and found that the C-terminal segment (CTS) of the NS2B cofactor is prone to dissociation from NS3. In the case of the West Nile virus protease, the CTS of NS2B is mostly associated with NS3, especially in the presence of inhibitors. In the case of the dengue virus protease and in the absence of inhibitors, the CTS of NS2B is mostly dissociated from NS3. Finding drug candidates to inhibit the association of the NS2B cofactor may thus be easier for the dengue virus protease

Python as a Federation Tool for GENESIS 3.0

The GENESIS simulation platform was one of the first broad-scale modeling systems in computational biology to encourage modelers to develop and share model features and components. Supported by a large developer community, it participated in innovative simulator technologies such as benchmarking, parallelization, and declarative model specification and was the first neural simulator to define bindings for the Python scripting language. An important feature of the latest version of GENESIS is that it decomposes into self-contained software components complying with the Computational Biology Initiative federated software architecture. This architecture allows separate scripting bindings to be defined for different necessary components of the simulator, e.g., the mathematical solvers and graphical user interface. Python is a scripting language that provides rich sets of freely available open source libraries. With clean dynamic object-oriented designs, they produce highly readable code and are widely employed in specialized areas of software component integration. We employ a simplified wrapper and interface generator to examine an application programming interface and make it available to a given scripting language. This allows independent software components to be ‘glued’ together and connected to external libraries and applications from user-defined Python or Perl scripts. We illustrate our approach with three examples of Python scripting. (1) Generate and run a simple single-compartment model neuron connected to a stand-alone mathematical solver. (2) Interface a mathematical solver with GENESIS 3.0 to explore a neuron morphology from either an interactive command-line or graphical user interface. (3) Apply scripting bindings to connect the GENESIS 3.0 simulator to external graphical libraries and an open source three dimensional content creation suite that supports visualization of models based on electron microscopy and their conversion to computational models. Employed in this way, the stand-alone software components of the GENESIS 3.0 simulator provide a framework for progressive federated software development in computational neuroscience

Molecular architecture and activation of the insecticidal protein Vip3Aa from Bacillus thuringiensis

Bacillus thuringiensis Vip3 (Vegetative Insecticidal Protein 3) toxins are widely used in biotech crops to control Lepidopteran pests. These proteins are produced as inactive protoxins that need to be activated by midgut proteases to trigger cell death. However, little is known about their three-dimensional organization and activation mechanism at the molecular level. Here, we have determined the structures of the protoxin and the protease-activated state of Vip3Aa at 2.9 Å using cryo-electron microscopy. The reconstructions show that the protoxin assembles into a pyramid-shaped tetramer with the C-terminal domains exposed to the solvent and the N-terminal region folded into a spring-loaded apex that, after protease activation, drastically remodels into an extended needle by a mechanism akin to that of influenza haemagglutinin. These results provide the molecular basis for Vip3 activation and function, and serves as a strong foundation for the development of more efficient insecticidal proteins

NMR Studies of the C-Terminus of alpha4 Reveal Possible Mechanism of Its Interaction with MID1 and Protein Phosphatase 2A

Alpha4 is a regulatory subunit of the protein phosphatase family of enzymes and plays an essential role in regulating the catalytic subunit of PP2A (PP2Ac) within the rapamycin-sensitive signaling pathway. Alpha4 also interacts with MID1, a microtubule-associated ubiquitin E3 ligase that appears to regulate the function of PP2A. The C-terminal region of alpha4 plays a key role in the binding interaction of PP2Ac and MID1. Here we report on the solution structure of a 45-amino acid region derived from the C-terminus of alpha4 (alpha45) that binds tightly to MID1. In aqueous solution, alpha45 has properties of an intrinsically unstructured peptide although chemical shift index and dihedral angle estimation based on chemical shifts of backbone atoms indicate the presence of a transient α-helix. Alpha45 adopts a helix-turn-helix HEAT-like structure in 1% SDS micelles, which may mimic a negatively charged surface for which alpha45 could bind. Alpha45 binds tightly to the Bbox1 domain of MID1 in aqueous solution and adopts a structure consistent with the helix-turn-helix structure observed in 1% SDS. The structure of alpha45 reveals two distinct surfaces, one that can interact with a negatively charged surface, which is present on PP2A, and one that interacts with the Bbox1 domain of MID1