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Background: Biomarkers of atopic dermatitis (AD) are largely lacking, especially in infant AD. Those that have been examined to date have focused mostly on serum cytokines, with few on noninvasive biomarkers in the skin. Objectives: We aimed to explore biomarkers obtainable from noninvasive sampling of infant skin. We compared these with plasma biomarkers and structural and functional measures of the skin barrier. Methods: We recruited 100 infants at first presentation with AD, who were treatment naive to topical or systemic anti-inflammatory therapies, and 20 healthy children. We sampled clinically unaffected skin by tape stripping the stratum corneum (SC). Multiple cytokines and chemokines and natural moisturizing factor were measured in the SC and plasma. We recorded disease severity and skin barrier function. Results: Nineteen SC and 12 plasma biomarkers showed significant differences between healthy and AD skin. Some biomarkers were common to both the SC and plasma, and others were compartment specific. Identified biomarkers of AD severity included T helper 2-skewed markers [interleukin (IL)-13, CCL17, CCL22, IL-5]; markers of innate activation (IL-18, IL-1α, IL1β, CXCL8) and angiogenesis (Flt-1, vascular endothelial growth factor); and others (soluble intercellular adhesion molecule-1, soluble vascular cell adhesion molecule-1, IL-16, IL-17A). Conclusions: We identified clinically relevant biomarkers of AD, including novel markers, easily sampled and typed in infants. These markers may provide objective assessment of disease severity and suggest new therapeutic targets, or response measurement targets for AD. Future studies will be required to determine whether these biomarkers, seen in very early AD, can predict disease outcomes or comorbidities.

Fossil fuels such as coal, oil and gas generate carbon emissions that contribute to global warming and climate change. Taxes on carbon emissions can mitigate their effects on the environment by changing demand and supply. For taxes to be effective, accurate carbon emissions prices are required. The paper uses an innovative KLEM production function approach to calculate carbon emissions prices for Japan, where carbon emissions are the output, and capital (K), labour (L), energy (E) (or electricity), and materials (M), are the inputs. The variables capital, labour and materials are essentially fixed on a daily, weekly or monthly basis, whereas energy can be changed more frequently, such as daily, weekly or monthly, so that changes in carbon emissions essentially depend on changes in energy. If prices are set according to average cost pricing, the prices of carbon emissions and energy may be approximated by an energy production model with a constant factor of proportionality, so that carbon emissions prices will depend on energy prices. Using this innovative approach, the paper estimates carbon emissions prices for Japan using seasonally adjusted and unadjusted monthly data on the volumes of carbon emissions and energy, and energy prices, from December 2008 to April 2018.

This work was supported by grants from the Wellcome Trust (104241/z/14/z to C.P.H., and 098731/z/11/z to St Andrews University Bioinformatics Unit), and the Chief Scientists Office (SIRN10 to M.T.G.H.). Background Carriage rates of Staphylococcus aureus on affected skin in atopic dermatitis (AD) are approximately 70%. Increasing disease severity during flares and overall disease severity correlate with increased burden of S. aureus. Treatment in AD therefore often targets S. aureus with topical and systemic antimicrobials. Objectives To determine whether antimicrobial sensitivities and genetic determinants of resistance differed in S. aureus isolates from the skin of children with AD and healthy child nasal carriers. Methods In this case–control study, we compared S. aureus isolates from children with AD (n = 50) attending a hospital dermatology department against nasal carriage isolates from children without skin disease (n = 49) attending a hospital emergency department for noninfective conditions. Using whole genome sequencing we generated a phylogenetic framework for the isolates based on variation in the core genome, then compared antimicrobial resistance phenotypes and genotypes between disease groups. Results Staphylococcus aureus from cases and controls had on average similar numbers of phenotypic resistances per isolate. Case isolates differed in their resistance patterns, with fusidic acid resistance (FusR) being significantly more frequent in AD (P = 0·009). The genetic basis of FusR also differentiated the populations, with chromosomal mutations in fusA predominating in AD (P = 0·049). Analysis revealed that FusR evolved multiple times and via multiple mechanism in the population. Carriage of plasmid‐derived qac genes, which have been associated with reduced susceptibility to antiseptics, was eight times more frequent in AD (P = 0·016). Conclusions The results suggest that strong selective pressure drives the emergence and maintenance of specific resistances in AD. Publisher PDF

The recent and rapidly growing interest in biofuel as a green energy source has raised concerns about its impact on the prices, returns and volatility of related agricultural commodities. Analyzing the spillover effects on agricultural commodities and biofuel helps commodity suppliers hedge their portfolios, and manage the risk and co-risk of their biofuel and agricultural commodities. There have been many papers concerned with analyzing crude oil and agricultural commodities separately. The purpose of this paper is to examine the volatility spillovers for spot and futures returns on bio-ethanol and related agricultural commodities, specifically corn and sugarcane, using the multivariate diagonal BEKK conditional volatility model. The daily data used are from 31 October 2005 to 14 January 2015. The empirical results show that in 2 of 6 cases for the spot market, there were significant negative co-volatility spillover effects, specifically corn on subsequent sugarcane co-volatility with corn, and sugarcane on subsequent corn co-volatility with sugarcane. In the other 4 cases, there are no significant co-volatility spillover effects. There are significant positive co-volatility spillover effects in all 6 cases, namely between corn and sugarcane, corn and ethanol, and sugarcane and ethanol, and vice-versa, for each of the three pairs of commodities. It is clear that the futures prices of bio-ethanol and the two agricultural commodities, corn and sugarcane, have stronger co-volatility spillovers than their spot price counterparts. These empirical results suggest that the bio-ethanol and agricultural commodities should be considered as viable futures products in financial portfolios for risk management.

This article explains how to obtain straightforward extensions of the most popular univariate non-nested statistics, and of the RESET-test, to a multivariate context and examines how to use these tests to compare alternative factor demand systems. The empirical application involves the classical Berndt-Khaled KLEM data set. A statistically adequate specification is determined for each competing factor demand system. The empirical results are interpreted for each system, the models are compared on the basis of multivariate paired and joint non-nested procedures and practical indications about what to expect if these tests are applied to alternative factor demand specifications are provide. © Blackwell Publishing Ltd and the Board of Trustees of the Bulletin of Economic Research 2005.

This paper examines the practical usefulness of two new journal performance metrics, namely the Eigenfactor score, which may be interpreted as measuring “Journal Influence”, and the Article Influence score, using the Thomson Reuters ISI Web of Science (hereafter ISI) data for 2009 for the 200 most highly cited journals in each of the Sciences and Social Sciences, and compares them with two existing ISI metrics, namely Total Citations and the 5- year Impact Factor (5YIF) of a journal (including journal self citations). It is shown that the Sciences and Social Sciences are different in terms of the strength of the relationship of journal performance metrics, although the actual relationships are very similar. Moreover, the journal influence and article influence journal performance metrics are shown to be closely related empirically to the two existing ISI metrics, and hence add little in practical usefulness to what is already known. These empirical results are compared with existing results in the literature.