An Integrated Physiological Model of the Lung Mechanics and Gas Exchange Using Electrical Impedance Tomography in the Analysis of Ventilation Strategies in ARDS Patients

Mouloud Denai, M. Mahfouf, A. Wang, D. A. Linkens, and G. H. Mills, 'An Integrated Physiological Model of the Lung Mechanics and Gas Exchange Using Electrical Impedance Tomography in the Analysis of Ventilation Strategies in ARDS Patients'. Paper presented at the 3rd International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2010), 20 - 23 January 2010, Valencia, Spain.Peer reviewedFinal Published versio

Twenty eight years of ICP Vegetation: an overview of its activities

Here we look back at the activities and achievements in the 28 years of the International Cooperative Programme on the Effects of Air Pollution on Natural Vegetation and Crops (ICP Vegetation). The ICP Vegetation is a subsidiary body of the Working Group on Effects of the UNECE Convention on Long-range Transboundary Air Pollution (LTRAP), established in 1979. An important role of the ICP Vegetation is to provide evidence for air pollution impacts on vegetation in support of policy development and review of the LRTAP Convention and its Protocols. The activities and participation in the ICP Vegetation have grown over the years. The main activities include: • Collate evidence of ozone impacts on vegetation, assess spatial patterns and temporal trends across Europe; • Develop dose-response relationships, establish critical levels for vegetation and provide European risk maps of ozone impacts; • Reviewing the literature on ozone impacts on vegetation and produce thematic scientific reports and policy-relevant brochures; • Determine spatial patterns and temporal trends of heavy metals, nitrogen and persistent organic pollutants concentrations in mosses as a biomonitoring tool of atmospheric deposition of these compounds

Erratum to: What can ecosystems learn? Expanding evolutionary ecology with learning theory.

BACKGROUND: The structure and organisation of ecological interactions within an ecosystem is modified by the evolution and coevolution of the individual species it contains. Understanding how historical conditions have shaped this architecture is vital for understanding system responses to change at scales from the microbial upwards. However, in the absence of a group selection process, the collective behaviours and ecosystem functions exhibited by the whole community cannot be organised or adapted in a Darwinian sense. A long-standing open question thus persists: Are there alternative organising principles that enable us to understand and predict how the coevolution of the component species creates and maintains complex collective behaviours exhibited by the ecosystem as a whole? RESULTS: Here we answer this question by incorporating principles from connectionist learning, a previously unrelated discipline already using well-developed theories on how emergent behaviours arise in simple networks. Specifically, we show conditions where natural selection on ecological interactions is functionally equivalent to a simple type of connectionist learning, 'unsupervised learning', well-known in neural-network models of cognitive systems to produce many non-trivial collective behaviours. Accordingly, we find that a community can self-organise in a well-defined and non-trivial sense without selection at the community level; its organisation can be conditioned by past experience in the same sense as connectionist learning models habituate to stimuli. This conditioning drives the community to form a distributed ecological memory of multiple past states, causing the community to: a) converge to these states from any random initial composition; b) accurately restore historical compositions from small fragments; c) recover a state composition following disturbance; and d) to correctly classify ambiguous initial compositions according to their similarity to learned compositions. We examine how the formation of alternative stable states alters the community's response to changing environmental forcing, and we identify conditions under which the ecosystem exhibits hysteresis with potential for catastrophic regime shifts. CONCLUSIONS: This work highlights the potential of connectionist theory to expand our understanding of evo-eco dynamics and collective ecological behaviours. Within this framework we find that, despite not being a Darwinian unit, ecological communities can behave like connectionist learning systems, creating internal conditions that habituate to past environmental conditions and actively recalling those conditions. REVIEWERS: This article was reviewed by Prof. Ricard V Solé, Universitat Pompeu Fabra, Barcelona and Prof. Rob Knight, University of Colorado, Boulder

What can ecosystems learn? Expanding evolutionary ecology with learning theory.

BACKGROUND: The structure and organisation of ecological interactions within an ecosystem is modified by the evolution and coevolution of the individual species it contains. Understanding how historical conditions have shaped this architecture is vital for understanding system responses to change at scales from the microbial upwards. However, in the absence of a group selection process, the collective behaviours and ecosystem functions exhibited by the whole community cannot be organised or adapted in a Darwinian sense. A long-standing open question thus persists: Are there alternative organising principles that enable us to understand and predict how the coevolution of the component species creates and maintains complex collective behaviours exhibited by the ecosystem as a whole? RESULTS: Here we answer this question by incorporating principles from connectionist learning, a previously unrelated discipline already using well-developed theories on how emergent behaviours arise in simple networks. Specifically, we show conditions where natural selection on ecological interactions is functionally equivalent to a simple type of connectionist learning, 'unsupervised learning', well-known in neural-network models of cognitive systems to produce many non-trivial collective behaviours. Accordingly, we find that a community can self-organise in a well-defined and non-trivial sense without selection at the community level; its organisation can be conditioned by past experience in the same sense as connectionist learning models habituate to stimuli. This conditioning drives the community to form a distributed ecological memory of multiple past states, causing the community to: a) converge to these states from any random initial composition; b) accurately restore historical compositions from small fragments; c) recover a state composition following disturbance; and d) to correctly classify ambiguous initial compositions according to their similarity to learned compositions. We examine how the formation of alternative stable states alters the community's response to changing environmental forcing, and we identify conditions under which the ecosystem exhibits hysteresis with potential for catastrophic regime shifts. CONCLUSIONS: This work highlights the potential of connectionist theory to expand our understanding of evo-eco dynamics and collective ecological behaviours. Within this framework we find that, despite not being a Darwinian unit, ecological communities can behave like connectionist learning systems, creating internal conditions that habituate to past environmental conditions and actively recalling those conditions. REVIEWERS: This article was reviewed by Prof. Ricard V Solé, Universitat Pompeu Fabra, Barcelona and Prof. Rob Knight, University of Colorado, Boulder

Wick's Theorem at Finite Temperature

We consider Wick's Theorem for finite temperature and finite volume systems. Working at an operator level with a path ordered approach, we show that contrary to claims in the literature, expectation values of normal ordered products can be chosen to be zero and that results obtained are independent of volume. Thus the path integral and operator approaches to finite temperature and finite volume quantum field theories are indeed seen to be identical. The conditions under which normal ordered products have simple symmetry properties are also considered.Comment: 15 pages, LaTeX (no figures), available through anonymous ftp as LaTeX from ftp://euclid.tp.ph.ic.ac.uk/papers/95-6_18.tex or as LaTeX or postscript at http://euclid.tp.ph.ic.ac.uk/Papers/index.htm

Rare variants in optic disc area gene CARD10 enriched in primary open-angle glaucoma

Background: Genome-wide association studies (GWAS) have identified association of common alleles with primary open-angle glaucoma (POAG) and its quantitative endophenotypes near numerous genes. This study aims to determine whether rare pathogenic variants in these disease-associated genes contribute to POAG. Methods: Participants fulfilled strict inclusion criteria of advanced POAG at a young age of diagnosis. Myocilin mutation carriers were excluded using direct sequencing. Whole exome sequencing was performed on 187 glaucoma cases and 103 local screened nonglaucoma controls then joint-called with exomes of 993 previously sequenced Australian controls. GWAS-associated genes were assessed for enrichment of rare predicted pathogenic variants in POAG. Significantly enriched genes were compared against Exome Aggregation Consortium (ExAC) public control. Results: Eighty-six GWAS disease or trait-associated glaucoma genes were captured and sequenced. CARD10 showed enrichment after Bonferroni correction for rare variants in glaucoma cases (OR = 13.2, P = 6.94 × 10−5) with mutations identified in 4.28% of our POAG cohort compared to 0.27% in controls. CARD10 was significantly associated with optic disc parameters in previous GWAS. The whole GWAS gene set showed no enrichment in POAG overall (OR = 1.12, P = 0.51). Conclusion: We report here an enrichment of rare predicted pathogenic coding variants within a GWAS-associated locus in POAG (CARD10). These findings indicate that both common and rare pathogenic coding variants in CARD10 may contribute to POAG pathogenesis.Tiger Zhou, Emmanuelle Souzeau, Shiwani Sharma, Owen M. Siggs, Ivan Goldberg, Paul R. Healey, Stuart Graham, Alex W. Hewitt, David A. Mackey, Robert J. Casson, John Landers, Richard Mills, Jonathan Ellis, Paul Leo, Matthew A. Brown, Stuart MacGregor, Kathryn P. Burdon and Jamie E. Crai

Inhomogeneous States in a Small Magnetic Disk with Single-Ion Surface Anisotropy

We investigate analytically and numerically the ground and metastable states for easy-plane Heisenberg magnets with single-ion surface anisotropy and disk geometry. The configurations with two half-vortices at the opposite points of the border are shown to be preferable for strong anisotropy. We propose a simple analytical description of the spin configurations for all values of a surface anisotropy. The effects of lattice pinning leads to appearance of a set of metastable configurations.Comment: 10 pages, 7 figures; submitted to Phys. Rev.

First Observation of Coherent π0\pi^0 Production in Neutrino Nucleus Interactions with Eν<E_{\nu}< 2 GeV

The MiniBooNE experiment at Fermilab has amassed the largest sample to date of $\pi^0$s produced in neutral current (NC) neutrino-nucleus interactions at low energy. This paper reports a measurement of the momentum distribution of $\pi^0$s produced in mineral oil (CH$_2$) and the first observation of coherent $\pi^0$ production below 2 GeV. In the forward direction, the yield of events observed above the expectation for resonant production is attributed primarily to coherent production off carbon, but may also include a small contribution from diffractive production on hydrogen. Integrated over the MiniBooNE neutrino flux, the sum of the NC coherent and diffractive modes is found to be (19.5 $\pm$1.1 (stat) $\pm$2.5 (sys))% of all exclusive NC $\pi^0$ production at MiniBooNE. These measurements are of immediate utility because they quantify an important background to MiniBooNE's search for $\nu_{\mu} \to \nu_e$ oscillations.Comment: Submitted to Phys. Lett.

Dissecting the contribution of knee joint NGF to spinal nociceptive sensitization in a model of OA pain in the rat

Objective: Although analgesic approaches targeting nerve growth factor (NGF) for the treatment of osteoarthritis (OA) pain remain of clinical interest, neurophysiological mechanisms by which NGF contribute to OA pain remain unclear. We investigated the impact of local elevation of knee joint NGF on knee joint, vs remote (hindpaw), evoked responses of spinal neurones in a rodent model of OA pain. Design: In vivo spinal electrophysiology was carried out in anaesthetised rats with established pain behaviour and joint pathology following intra-articular injection of monosodium iodoacetate (MIA), vs injection of saline. Neuronal responses to knee joint extension and flexion, mechanical punctate stimulation of the peripheral receptive fields over the knee and at a remote site (ipsilateral hind paw) were studied before, and following, intra-articular injection of NGF (10 mg/50 ml) or saline. Results: MIA-injected rats exhibited significant local (knee joint) and remote (lowered hindpaw withdrawal thresholds) changes in pain behaviour, and joint pathology. Intra-articular injection of NGF significantly (P<0.05) increased knee extension-evoked firing of spinal neurones and the size of the peripheral receptive fields of spinal neurones (100% increase) over the knee joint in MIA rats, compared to controls. Intra-articular NGF injection did not significantly alter responses of spinal neurones following noxious stimulation of the ipsilateral hind paw in MIA-injected rats. Conclusion: The facilitatory effects of intra-articular injection of NGF on spinal neurones receiving input from the knee joint provide a mechanistic basis for NGF mediated augmentation of OA knee pain, however additional mechanisms may contribute to the spread of pain to remote site

Heavy metal and nitrogen concentrations in mosses are declining across Europe whilst some “hotspots” remain in 2010

In recent decades, naturally growing mosses have been used successfully as biomonitors of atmospheric deposition of heavy metals and nitrogen. Since 1990, the European moss survey has been repeated at five-yearly intervals. In 2010, the lowest concentrations of metals and nitrogen in mosses were generally found in northern Europe, whereas the highest concentrations were observed in (south-)eastern Europe for metals and the central belt for nitrogen. Averaged across Europe, since 1990, the median concentration in mosses has declined the most for lead (77%), followed by vanadium (55%), cadmium (51%), chromium (43%), zinc (34%), nickel (33%), iron (27%), arsenic (21%, since 1995), mercury (14%, since 1995) and copper (11%). Between 2005 and 2010, the decline ranged from 6% for copper to 36% for lead; for nitrogen the decline was 5%. Despite the Europe-wide decline, no changes or increases have been observed between 2005 and 2010 in some (regions of) countries