Eco-evolutionary dynamics on deformable fitness landscapes

Conventional approaches to modelling ecological dynamics often do not include evolutionary changes in the genetic makeup of component species and, conversely, conventional approaches to modelling evolutionary changes in the genetic makeup of a population often do not include ecological dynamics. But recently there has been considerable interest in understanding the interaction of evolutionary and ecological dynamics as coupled processes. However, in the context of complex multi-species ecosytems, especially where ecological and evolutionary timescales are similar, it is difficult to identify general organising principles that help us understand the structure and behaviour of complex ecosystems. Here we introduce a simple abstraction of coevolutionary interactions in a multi-species ecosystem. We model non-trophic ecological interactions based on a continuous but low-dimensional trait/niche space, where the location of each species in trait space affects the overlap of its resource utilisation with that of other species. The local depletion of available resources creates, in effect, a deformable fitness landscape that governs how the evolution of one species affects the selective pressures on other species. This enables us to study the coevolution of ecological interactions in an intuitive and easily visualisable manner. We observe that this model can exhibit either of the two behavioural modes discussed in the literature; namely, evolutionary stasis or Red Queen dynamics, i.e., continued evolutionary change. We find that which of these modes is observed depends on the lag or latency between the movement of a species in trait space and its effect on available resources. Specifically, if ecological change is nearly instantaneous compared to evolutionary change, stasis results; but conversely, if evolutionary timescales are closer to ecological timescales, such that resource depletion is not instantaneous on evolutionary timescales, then Red Queen dynamics result. We also observe that in the stasis mode, the overall utilisation of resources by the ecosystem is relatively efficient, with diverse species utilising different niches, whereas in the Red Queen mode the organisation of the ecosystem is such that species tend to clump together competing for overlapping resources. These models thereby suggest some basic conditions that influence the organisation of inter-species interactions and the balance of individual and collective adaptation in ecosystems, and likewise they also suggest factors that might be useful in engineering artificial coevolution

Seasonal size variation in the predatory cladoceran Bythotrephes cederstroemii in Lake Michigan

1.  Dry weight, body length and spine length were measured for the exotic cladoceran Bythotrephes cederstroemii collected from offshore and inshore stations in southeastern Lake Michigan. Average dry weight of each developmental stage exhibited seasonal variation by a factor of more than 5. 2.  Mean dry weight of Bythotrephes was closely correlated with water temperature. Contrary to the inverse relationship between water temperature and body size frequently observed for other invertebrates, the dry weight of Bythotrephes increased at higher ambient temperatures. 3.  No significant correlation was observed between abundances of major zooplankton taxa and the dry weight of Bythotrephes . An indirect effect of temperature on prey consumption may cause seasonal variation in dry weight of Bythotrephes in Lake Michigan. 4.  Distances between adjacent pairs of barbs, added to the caudal spine with each moult, are significantly shorter in Bythotrephes which produce resting eggs. Less material investment in the exoskeleton of sexually reproducing females was observed in favour of growth and reproduction.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74641/1/j.1365-2427.1994.tb00842.x.pd

Identification of IgG1 isotype phosphorylcholine antibodies for the treatment of inflammatory cardiovascular diseases

Background Phosphorylcholine (PC) is an important pro-inflammatory damage-associated molecular pattern. Previous data have shown that natural IgM anti-PC protects against cardiovascular disease. We aimed to develop a monoclonal PC IgG antibody with anti-inflammatory and anti-atherosclerotic properties.Methods Using various techniques PC antibodies were validated and optimized. In vivo testing was performed in a femoral artery cuff model in ApoE3*Leiden mice. Safety studies are performed in rats and cynomolgus monkeys.Results A chimeric anti-PC (PC-mAb(T15), consisting of a human IgG1 Fc and a mouse T15/E06 Fab) was produced, and this was shown to bind specifically to epitopes in human atherosclerotic tissues. The cuff model results in rapid induction of inflammatory genes and altered expression of genes associated with ER stress and choline metabolism in the lesions. Treatment with PC-mAb(T15) reduced accelerated atherosclerosis via reduced expression of endoplasmic reticulum stress markers and CCL2 production. Recombinant anti-PC Fab fragments were identified by phage display and cloned into fully human IgG1 backbones creating a human monoclonal IgG1 anti-PC (PC-mAbs) that specifically bind PC, apoptotic cells and oxLDL. Based on preventing macrophage oxLDL uptake and CCL2 production, four monoclonal PC-mAbs were selected, which to various extent reduced vascular inflammation and lesion development. Additional optimization and validation of two PC-mAb antibodies resulted in selection of PC-mAb X19-A05, which inhibited accelerated atherosclerosis. Clinical grade production of this antibody (ATH3G10) significantly attenuated vascular inflammation and accelerated atherosclerosis and was tolerated in safety studies in rats and cynomolgus monkeys.Conclusions Chimeric anti-PCs can prevent accelerated atherosclerosis by inhibiting vascular inflammation directly and through reduced macrophage oxLDL uptake resulting in decreased lesions. PC-mAb represents a novel strategy for cardiovascular disease prevention.Cardiolog

Overview of the Lost Meteorites of Antarctica field campaigns

The Lost Meteorites of Antarctica project was the first UK-led Antarctic meteorite recovery expedition. The project has successfully confirmed two new high-density meteorite stranding zones in the Hutchison Icefield and Outer Recovery Icefields areas and investigated the geology of three previously unvisited Antarctic nunataks (Turner Nunatak, Pillinger Nunatak, Halliday Nunatak). The project undertook meteorite searching on the ice surface via skidoo reconnaissance and systematic searching and developed a novel pulse induction metal detection system to search for englacial iron-rich meteorites trapped within the upper one meter of ice. In total, 121 meteorites have been recovered from the ice surface searching activities, which are now curated in the United Kingdom at the Natural History Museum London and are available for scientific analysis

Machine learning for estimation of building energy consumption and performance:a review

Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy eciency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption. One most eective approach to reducing CO2 emission and energy consumption with regards to new buildings is to consider energy eciency at a very early design stage. On the other hand, ecient energy management and smart refurbishments can enhance energy performance of the existing stock. All these solutions entail accurate energy prediction for optimal decision making. In recent years, articial intelligence (AI) in general and machine learning (ML) techniques in specic terms have been proposed for forecasting of building energy consumption and performance. This paperprovides a substantial review on the four main ML approaches including articial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved