Design and Development of an In-Vehicle Human Machine Interface to Improve Fuel Efficiency & Safety

Road transport plays a significant role in various industries and mobility services around the globe and has a vital impact on our daily lives. However it also has serious impacts on both public health and the environment. In-vehicle feedback systems are a relatively new approach to encouraging driver behaviour change for improving fuel efficiency and safety in automotive environments. While many studies claim that the adoption of eco-driving practices, such as eco-driving training programs and in-vehicle feedback to drivers, has the potential to improve fuel efficiency, limited research has integrated safety and eco-driving. Therefore, this research seeks to use human factors related theories and practices to inform the design and evaluation of an in-vehicle Human Machine Interface (HMI) providing real-time driver feedback with the aim of improving both fuel efficiency and safety.

Urinary tract infection of mice to model human disease: Practicalities, implications and limitations

Urinary tract infections (UTIs) are among the most common bacterial infections in humans. Murine models of human UTI are vital experimental tools that have helped to elucidate UTI pathogenesis and advance knowledge of potential treatment and infection prevention strategies. Fundamentally, several variables are inherent in different murine models, and understanding the limitations of these variables provides an opportunity to understand how models may be best applied to research aimed at mimicking human disease. In this review, we discuss variables inherent in murine UTI model studies and how these affect model usage, data analysis and data interpretation. We examine recent studies that have elucidated UTI host–pathogen interactions from the perspective of gene expression, and review new studies of biofilm and UTI preventative approaches. We also consider potential standards for variables inherent in murine UTI models and discuss how these might expand the utility of models for mimicking human disease and uncovering new aspects of pathogenesis

The mechanisms of human renal epithelial cell modulation of autologous dendritic cell phenotype and function

Proximal tubule epithelial cells (PTEC) of the kidney line the proximal tubule downstream of the glomerulus and play a major role in the re-absorption of small molecular weight proteins that may pass through the glomerular filtration process. In the perturbed disease state PTEC also contribute to the inflammatory disease process via both positive and negative mechanisms via the production of inflammatory cytokines which chemo-attract leukocytes and the subsequent down-modulation of these cells to prevent uncontrolled inflammatory responses. It is well established that dendritic cells are responsible for the initiation and direction of adaptive immune responses. Both resident and infiltrating dendritic cells are localised within the tubulointerstitium of the renal cortex, in close apposition to PTEC, in inflammatory disease states. We previously demonstrated that inflammatory PTEC are able to modulate autologous human dendritic cell phenotype and functional responses. Here we extend these findings to characterise the mechanisms of this PTEC immune-modulation using primary human PTEC and autologous monocyte-derived dendritic cells (MoDC) as the model system. We demonstrate that PTEC express three inhibitory molecules: (i) cell surface PD-L1 that induces MoDC expression of PD-L1; (ii) intracellular IDO that maintains the expression of MoDC CD14, drives the expression of CD80, PD-L1 and IL-10 by MoDC and inhibits T cell stimulatory capacity; and (iii) soluble HLA-G (sHLA-G) that inhibits HLA-DR and induces IL-10 expression by MoDC. Collectively the results demonstrate that primary human PTEC are able to modulate autologous DC phenotype and function via multiple complex pathways. Further dissection of these pathways is essential to target therapeutic strategies in the treatment of inflammatory kidney disorders.

Human bladder uroepithelial cells synergize with monocytes to promote IL-10 synthesis and other cytokine responses to Uropathogenic Escherichia coli

Urinary tract infections are a major source of morbidity for women and the elderly, with Uropathogenic Escherichia coli (UPEC) being the most prevalent causative pathogen. Studies in recent years have defined a key anti-inflammatory role for Interleukin-10 (IL-10) in urinary tract infection mediated by UPEC and other uropathogens. We investigated the nature of the IL-10-producing interactions between UPEC and host cells by utilising a novel co-culture model that incorporated lymphocytes, mononuclear and uroepithelial cells in histotypic proportions. This co-culture model demonstrated synergistic IL-10 production effects between monocytes and uroepithelial cells following infection with UPEC. Membrane inserts were used to separate the monocyte and uroepithelial cell types during infection and revealed two synergistic IL-10 production effects based on contact-dependent and soluble interactions. Analysis of a comprehensive set of immunologically relevant biomarkers in monocyte-uroepithelial cell co-cultures highlighted that multiple cytokine, chemokine and signalling factors were also produced in a synergistic or antagonistic fashion. These results demonstrate that IL-10 responses to UPEC occur via multiple interactions between several cells types, implying a complex role for infection-related IL-10 during UTI. Development and application of the co-culture model described in this study is thus useful to define the degree of contact dependency of biomarker production to UPEC, and highlights the relevance of histotypic co-cultures in studying complex host-pathogen interactions.

Mary Robinson's declaration of climate justice: Climate change, human rights and fossil fuel divestment

In her biography, Everybody Matters: My Life Giving Voice, Mary Robinson explained how she became interested in the topic of human rights and climate change, after hearing testimony from African farmers, with Archbishop Desmond Tutu.

Defining the role of common variation in the genomic and biological architecture of adult human height

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated approximately 2,000, approximately 3,700 and approximately 9,500 SNPs explained approximately 21%, approximately 24% and approximately 29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

Common SNPs explain a large proportion of the heritability for human height

SNPs discovered by genome-wide association studies (GWASs) account for only a small fraction of the genetic variation of complex traits in human populations. Where is the remaining heritability? We estimated the proportion of variance for human height explained by 294,831 SNPs genotyped on 3,925 unrelated individuals using a linear model analysis, and validated the estimation method with simulations based on the observed genotype data. We show that 45% of variance can be explained by considering all SNPs simultaneously. Thus, most of the heritability is not missing but has not previously been detected because the individual effects are too small to pass stringent significance tests. We provide evidence that the remaining heritability is due to incomplete linkage disequilibrium between causal variants and genotyped SNPs, exacerbated by causal variants having lower minor allele frequency than the SNPs explored to date.

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.