Multi-site evaluation of an urban land-surface model: intra-urban heterogeneity, seasonality and parameter complexity requirements

An extensive off-line evaluation of the Noah/Single Layer Urban Canopy Model (Noah/SLUCM) urban land-surface model is presented using data from 15 sites to assess (1) the ability of the scheme to reproduce the surface energy balance observed in a range of urban environments, including seasonal changes, and (2) the impact of increasing complexity of input parameter information. Model performance is found to be most dependent on representation of vegetated surface area cover; refinement of other parameter values leads to smaller improvements. Model biases in net all-wave radiation and trade-offs between turbulent heat fluxes are highlighted using an optimization algorithm. Here we use the Urban Zones to characterize Energy partitioning (UZE) as the basis to assign default SLUCM parameter values. A methodology (FRAISE) to assign sites (or areas) to one of these categories based on surface characteristics is evaluated. Using three urban sites from the Basel Urban Boundary Layer Experiment (BUBBLE) dataset, an independent evaluation of the model performance with the parameter values representative of each class is performed. The scheme copes well with both seasonal changes in the surface characteristics and intra-urban heterogeneities in energy flux partitioning, with RMSE performance comparable to similar state-of-the-art models for all fluxes, sites and seasons. The potential of the methodology for high-resolution atmospheric modelling application using the Weather Research and Forecasting (WRF) model is highlighted. This analysis supports the recommendations that (1) three classes are appropriate to characterize the urban environment, and (2) that the parameter values identified should be adopted as default values in WRF.

Meta-analysis of the INSIG2 association with obesity including 74,345 individuals: does heterogeneity of estimates relate to study design?

The INSIG2 rs7566605 polymorphism was identified for obesity (BMI> or =30 kg/m(2)) in one of the first genome-wide association studies, but replications were inconsistent. We collected statistics from 34 studies (n = 74,345), including general population (GP) studies, population-based studies with subjects selected for conditions related to a better health status ('healthy population', HP), and obesity studies (OB). We tested five hypotheses to explore potential sources of heterogeneity. The meta-analysis of 27 studies on Caucasian adults (n = 66,213) combining the different study designs did not support overall association of the CC-genotype with obesity, yielding an odds ratio (OR) of 1.05 (p-value = 0.27). The I(2) measure of 41% (p-value = 0.015) indicated between-study heterogeneity. Restricting to GP studies resulted in a declined I(2) measure of 11% (p-value = 0.33) and an OR of 1.10 (p-value = 0.015). Regarding the five hypotheses, our data showed (a) some difference between GP and HP studies (p-value = 0.012) and (b) an association in extreme comparisons (BMI> or =32.5, 35.0, 37.5, 40.0 kg/m(2) versus BMI<25 kg/m(2)) yielding ORs of 1.16, 1.18, 1.22, or 1.27 (p-values 0.001 to 0.003), which was also underscored by significantly increased CC-genotype frequencies across BMI categories (10.4% to 12.5%, p-value for trend = 0.0002). We did not find evidence for differential ORs (c) among studies with higher than average obesity prevalence compared to lower, (d) among studies with BMI assessment after the year 2000 compared to those before, or (e) among studies from older populations compared to younger. Analysis of non-Caucasian adults (n = 4889) or children (n = 3243) yielded ORs of 1.01 (p-value = 0.94) or 1.15 (p-value = 0.22), respectively. There was no evidence for overall association of the rs7566605 polymorphism with obesity. Our data suggested an association with extreme degrees of obesity, and consequently heterogeneous effects from different study designs may mask an underlying association when unaccounted for. The importance of study design might be under-recognized in gene discovery and association replication so far.

Role of genetic polymorphism peroxisome proliferator-activated receptor-gamma2 Pro12Ala on ethnic susceptibility to diabetes in South-Asian and Caucasian subjects: Evidence for heterogeneity

OBJECTIVE: To determine whether the peroxisome proliferator-activated receptor (PPAR)-gamma Pro12ala polymorphism modulates susceptibility to diabetes in South Asians. RESEARCH DESIGN AND METHODS: South Asians (n = 697) and Caucasians (n = 457) living in Dallas/Forth Worth, Texas, and South Asians living in Chennai, India (n = 1,619), were enrolled for this study. PPAR-gamma Pro12Ala was determined using restriction fragment-length polymorphism. Insulin responsiveness to an oral glucose tolerance test (OGTT) was measured in nondiabetic subjects. RESULTS: The Caucasian diabetic subjects had significantly lower prevalence of PPAR-gamma 12Ala when compared with the Caucasian nondiabetic subjects (20 vs. 9%, P = 0.006). However, there were no significant differences between diabetic and nondiabetic subjects with reference to the Pro12Ala polymorphism among the South Asians living in Dallas (20 vs. 23%) and in India (19 vs. 19.3%). Although Caucasians carrying PPAR-gamma Pro12Ala had lower plasma insulin levels at 2 h of OGTT than the wild-type (Pro/Pro) carriers (76 +/- 68 and 54 +/- 33 microU/ml, respectively, P = 0.01), no differences in either fasting or 2-h plasma insulin concentrations were found between South Asians carrying the PPAR-gamma Pro12Ala polymorphism and those with the wild-type genotype at either Chennai or Dallas. CONCLUSIONS: Although further replication studies are necessary to test the validity of the described genotype-phenotype relationship, our study supports the hypothesis that the PPAR-gamma Pro12Ala polymorphism is protective against diabetes in Caucasians but not in South Asians.

Genetic heterogeneity in erythropoietic protoporphyria: a study of the enzymatic defect in nine affected families

Erythropoietic protoporphyria (EPP) is associated with a deficiency of protohaem ferrolyase. We have used a novel assay for this enzyme based on its ability to utilize zinc as a substrate to investigate the inheritance of EPP in nine affected families. Zinc chelatase activity was markedly reduced in peripheral blood mononuclear cells from 14 EPP patients (mean, 3.3 nmol Zn protohaem/h/mg protein; range, 0.3-8.0) when compared with 41 controls (16.8 +/- 3.6) p less than 0.01. In three families with parent-to-child transmission of disease, the asymptomatic parent had an enzymatic activity within the normal range. In three pedigrees where the parents were asymptomatic, enzymatic activities were below the 95% confidence limits in both. Zinc chelatase activity was below the mean control value in 17 of the 18 parents in nine affected pedigrees, and six of seven asymptomatic offspring of patients with protoporphyria. The findings suggest that EPP is not transmitted as a simple dominant trait and that inheritance of more than one gene may be required for disease expression.

An industry viewpoint on the role of farm assurance in delivering food safety to the consumer: the case of the dairy sector in England and Wales

Food safety, alongside food quality, remains a primary concern of both consumers and those along the whole food supply chain, leading to regulation by government alongside private third party certification. Much has been written about the value of these systems primarily from the perception of the consumer. This paper reports on a study that examined industry perceptions on the regulatory and assurance systems within the dairy sector of England and Wales. It found that the primary producer found value in both systems, although from a food hygiene focus regulation was seen to be more rigorous. Other stakeholders along the dairy food supply chain saw the assurance scheme as more rigorous. All stakeholders recognised the need to reduce duplication in delivering food safety through combining key elements of both systems with the added potential for better communication of both food safety and quality to the final consumer.

Energy exchange in a dense urban environment Part II: impact of spatial heterogeneity of the surface

The centre of cities, characterised by spatial and temporal complexity, are challenging environments for micrometeorological research. This paper considers the impact of sensor location and heterogeneity of the urban surface on flux observations in the dense city centre of London, UK. Data gathered at two sites in close vicinity, but with different measurement heights, were analysed to investigate the influence of source area characteristics on long-term radiation and turbulent heat fluxes. Combining consideration of diffuse radiation and effects of specular reflections, the non-Lambertian urban surface is found to impact the measurements of surface albedo. Comparisons of observations from the two sites reveal that turbulent heat fluxes are similar under some flow conditions. However, they mostly observe processes at different scales due to their differing measurement heights, highlighting the critical impact of siting sensors in urban areas. A detailed source area analysis is presented to investigate the surface controls influencing the energy exchanges at the different scales

Monopolistic product line competition with ex post consumer heterogeneity

We model monopolistic competition in product lines, assuming that consumer heterogeneity is the result rather than the cause of product variety. Our results contradict some well-known policy implications yielded by the standard monopolistic competition framework.

Sequence analysis of a CTX-M-1 IncI1 plasmid found in Salmonella enterica 4,5,12,i:-, Escherichia coli and Klebsiella pneumoniae on a single UK pig farm

OBJECTIVES: In 2009, CTX-M Enterobacteriaceae and Salmonella isolates were recovered from a UK pig farm, prompting studies into the dissemination of the resistance and to establish any relationships between the isolates. METHODS: PFGE was used to elucidate clonal relationships between isolates whilst plasmid profiling, restriction analysis, sequencing and PCR were used to characterize the CTX-M-harbouring plasmids. RESULTS: Escherichia coli, Klebsiella pneumoniae and Salmonella 4,5,12:i:- and Bovismorbificans resistant to cefotaxime (n = 65) were recovered and 63 were shown by PCR to harbour a group 1 CTX-M gene. The harbouring hosts were diverse, but the group 1 CTX-M plasmids were common. Three sequenced CTX-M plasmids from E. coli, K. pneumoniae and Salmonella enterica serotype 4,5,12:i:- were identical except for seven mutations and highly similar to IncI1 plasmid ColIb-P9. Two antimicrobial resistance regions were identified: one inserted upstream of yacABC harbouring ISCR2 transposases, sul2 and floR; and the other inserted within shfB of the pilV shufflon harbouring the ISEcp1 transposase followed by blaCTX-M-1. CONCLUSIONS: These data suggest that an ST108 IncI1 plasmid encoding a blaCTX-M-1 gene had disseminated across multiple genera on this farm, an example of horizontal gene transfer of the blaCTX-M-1 gene.

An aggregated wind power generation model based on MERRA reanalysis data: MATLAB model and example data for the April 2014 wind farm distribution of Great Britain.

The MATLAB model is contained within the compressed folders (versions are available as .zip and .tgz). This model uses MERRA reanalysis data (>34 years available) to estimate the hourly aggregated wind power generation for a predefined (fixed) distribution of wind farms. A ready made example is included for the wind farm distribution of Great Britain, April 2014 ("CF.dat"). This consists of an hourly time series of GB-total capacity factor spanning the period 1980-2013 inclusive. Given the global nature of reanalysis data, the model can be applied to any specified distribution of wind farms in any region of the world. Users are, however, strongly advised to bear in mind the limitations of reanalysis data when using this model/data. This is discussed in our paper: Cannon, Brayshaw, Methven, Coker, Lenaghan. "Using reanalysis data to quantify extreme wind power generation statistics: a 33 year case study in Great Britain". Submitted to Renewable Energy in March, 2014. Additional information about the model is contained in the model code itself, in the accompanying ReadMe file, and on our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/

Farmers' interest in growing GM crops in the UK, in the context of a range of on-farm coexistence issues

Although no GM crops currently are licensed for commercial production in the UK, as opposition to GM crops by consumers softens, this could change quickly. Although past studies have examined attitudes of UK farmers toward GM technologies in general, there has been little work on the impact of possible coexistence measures on their attitudes toward GM crop production. This could be because the UK Government has not engaged in any public dialogue on the coexistence measures that might be applied on farms. Based on a farm survey, this article examines farmers’ attitudes toward GM technologies and planting intentions for three crops (maize, oilseed rape, and sugar beet) based on a GM availability scenario. The article then nuances this analysis with a review of farmer perceptions of the level of constraint associated with a suite of notional farm-level coexistence measures and issues, based on current European Commission guidelines and practice in other EU Member States.

Intra-tumor heterogeneity: lessons from microbial evolution and clinical implications

Multiple subclonal populations of tumor cells can coexist within the same tumor. This intra-tumor heterogeneity will have clinical implications and it is therefore important to identify factors that drive or suppress such heterogeneous tumor progression. Evolutionary biology can provide important insights into this process. In particular, experimental evolution studies of microbial populations, which exist as clonal populations that can diversify into multiple subclones, have revealed important evolutionary processes driving heterogeneity within a population. There are transferrable lessons that can be learnt from these studies that will help us to understand the process of intra-tumor heterogeneity in the clinical setting. In this review, we summarize drivers of microbial diversity that have been identified, such as mutation rate and environmental influences, and discuss how knowledge gained from microbial experimental evolution studies may guide us to identify and understand important selective factors that promote intra-tumor heterogeneity. Furthermore, we discuss how these factors could be used to direct and optimize research efforts to improve patient care, focusing on therapeutic resistance. Finally, we emphasize the need for longitudinal studies to address the impact of these potential tumor heterogeneity-promoting factors on drug resistance, metastatic potential and clinical outcome.