Staphylococcus aureus infection dynamics

Staphylococcus aureus is a human commensal that can also cause systemic infections. This transition requires evasion of the immune response and the ability to exploit different niches within the host. However, the disease mechanisms and the dominant immune mediators against infection are poorly understood. Previously it has been shown that the infecting S. aureus population goes through a population bottleneck, from which very few bacteria escape to establish the abscesses that are characteristic of many infections. Here we examine the host factors underlying the population bottleneck and subsequent clonal expansion in S. aureus infection models, to identify underpinning principles of infection. The bottleneck is a common feature between models and is independent of S. aureus strain. Interestingly, the high doses of S. aureus required for the widely used "survival" model results in a reduced population bottleneck, suggesting that host defences have been simply overloaded. This brings into question the applicability of the survival model. Depletion of immune mediators revealed key breakpoints and the dynamics of systemic infection. Loss of macrophages, including the liver Kupffer cells, led to increased sensitivity to infection as expected but also loss of the population bottleneck and the spread to other organs still occurred. Conversely, neutrophil depletion led to greater susceptibility to disease but with a concomitant maintenance of the bottleneck and lack of systemic spread. We also used a novel microscopy approach to examine abscess architecture and distribution within organs. From these observations we developed a conceptual model for S. aureus disease from initial infection to mature abscess. This work highlights the need to understand the complexities of the infectious process to be able to assign functions for host and bacterial components, and why S. aureus disease requires a seemingly high infectious dose and how interventions such as a vaccine may be more rationally developed

Representation: Public Servants in Public

In scholarship on public servants, they are represented in various ways across disciplines as we can see from the various contributions to this handbook. This section of the book considers how public servants are represented in broader public culture. A key question addressed is whether we want our public servants to be ideal heroes or whether we need to represent the worst of public servants as part of making them accountable. Looking across public culture, from comedy to political satire, and factual representations in a series of portraits, news stories from autocratic states, and job adverts, the chapters in this section bring together a varied range of theoretical approaches to understanding public servants with these popular representations. In doing so, the chapters tell us a great deal about how such representations reflect society and also illuminate the different ways we can apply theory to understand public servants and public service

Growth temperature and genotype both play important roles in sorghum grain phenolic composition.

Polyphenols in sorghum grains are a source of dietary antioxidants. Polyphenols in six diverse sorghum genotypes grown under two day/night temperature regimes of optimal temperature (OT, 32/21 °C and high temperature (HT, 38/21 °C) were investigated. A total of 23 phenolic compounds were positively or tentatively identified by HPLC-DAD-ESIMS. Compared with other pigmented types, the phenolic profile of white sorghum PI563516 was simpler, since fewer polyphenols were detected. Brown sorghum IS 8525 had the highest levels of caffeic and ferulic acid, but apigenin and luteolin were not detected. Free luteolinidin and apigeninidin levels were lower under HT than OT across all genotypes (p ≤ 0.05), suggesting HT could have inhibited 3-deoxyanthocyanidins formation. These results provide new information on the effects of HT on specific polyphenols in various Australian sorghum genotypes, which might be used as a guide to grow high antioxidant sorghum grains under projected high temperature in the future

The Regulatory Gift: Politics, regulation and governance

Abstract: This article introduces the ‘regulatory gift’ as a conceptual framework for understanding a particular form of government-led deregulation that is presented as central to the public interest. Contra to theories of regulatory capture, government corruption, ‘insider’ personal interest or profit-seeking theories of regulation, the regulatory gift describes reform which is overtly designed by Government to reduce or reorient regulators’ functions to the advantage of the regulated and in line with market objectives on a potentially macro (rather than industry-specific) scale. As a conceptual framework, the regulatory gift is intended to be applicable across regulated sectors of democratic states and in this article the empirical sections evidence the practice of regulatory gifting in contemporary UK politics. Specifically, this article analyses the UK Public Bodies Act (2011), affecting some 900 regulatory public bodies and its correlative legislation, the Regulator’s Code (2014), the Deregulation Act (2015) and the Enterprise Bill (2016). The article concludes that whilst the regulatory gift may, in some cases, be aligned with the public interest - delivering on cost reduction, enhancing efficiency and stimulating innovation - this will not always be the case. As the case study of the regulatory body, the UK Human Fertilisation and Embryology Authority (HFEA) demonstrates, despite the explicit claims made by legislators, the regulatory gift has the potential to significantly undermine the public interest

Plato's Cave Algorithm: Inferring Functional Signaling Networks from Early Gene Expression Shadows

Improving the ability to reverse engineer biochemical networks is a major goal of systems biology. Lesions in signaling networks lead to alterations in gene expression, which in principle should allow network reconstruction. However, the information about the activity levels of signaling proteins conveyed in overall gene expression is limited by the complexity of gene expression dynamics and of regulatory network topology. Two observations provide the basis for overcoming this limitation: a. genes induced without de-novo protein synthesis (early genes) show a linear accumulation of product in the first hour after the change in the cell's state; b. The signaling components in the network largely function in the linear range of their stimulus-response curves. Therefore, unlike most genes or most time points, expression profiles of early genes at an early time point provide direct biochemical assays that represent the activity levels of upstream signaling components. Such expression data provide the basis for an efficient algorithm (Plato's Cave algorithm; PLACA) to reverse engineer functional signaling networks. Unlike conventional reverse engineering algorithms that use steady state values, PLACA uses stimulated early gene expression measurements associated with systematic perturbations of signaling components, without measuring the signaling components themselves. Besides the reverse engineered network, PLACA also identifies the genes detecting the functional interaction, thereby facilitating validation of the predicted functional network. Using simulated datasets, the algorithm is shown to be robust to experimental noise. Using experimental data obtained from gonadotropes, PLACA reverse engineered the interaction network of six perturbed signaling components. The network recapitulated many known interactions and identified novel functional interactions that were validated by further experiment. PLACA uses the results of experiments that are feasible for any signaling network to predict the functional topology of the network and to identify novel relationships

Finding the “Dark Matter” in Human and Yeast Protein Network Prediction and Modelling

Accurate modelling of biological systems requires a deeper and more complete knowledge about the molecular components and their functional associations than we currently have. Traditionally, new knowledge on protein associations generated by experiments has played a central role in systems modelling, in contrast to generally less trusted bio-computational predictions. However, we will not achieve realistic modelling of complex molecular systems if the current experimental designs lead to biased screenings of real protein networks and leave large, functionally important areas poorly characterised. To assess the likelihood of this, we have built comprehensive network models of the yeast and human proteomes by using a meta-statistical integration of diverse computationally predicted protein association datasets. We have compared these predicted networks against combined experimental datasets from seven biological resources at different level of statistical significance. These eukaryotic predicted networks resemble all the topological and noise features of the experimentally inferred networks in both species, and we also show that this observation is not due to random behaviour. In addition, the topology of the predicted networks contains information on true protein associations, beyond the constitutive first order binary predictions. We also observe that most of the reliable predicted protein associations are experimentally uncharacterised in our models, constituting the hidden or “dark matter” of networks by analogy to astronomical systems. Some of this dark matter shows enrichment of particular functions and contains key functional elements of protein networks, such as hubs associated with important functional areas like the regulation of Ras protein signal transduction in human cells. Thus, characterising this large and functionally important dark matter, elusive to established experimental designs, may be crucial for modelling biological systems. In any case, these predictions provide a valuable guide to these experimentally elusive regions

What is the value and impact of quality and safety teams? A scoping review

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to conduct a scoping review of the literature about the establishment and impact of quality and safety team initiatives in acute care.</p> <p>Methods</p> <p>Studies were identified through electronic searches of Medline, Embase, CINAHL, PsycINFO, ABI Inform, Cochrane databases. Grey literature and bibliographies were also searched. Qualitative or quantitative studies that occurred in acute care, describing how quality and safety teams were established or implemented, the impact of teams, or the barriers and/or facilitators of teams were included. Two reviewers independently extracted data on study design, sample, interventions, and outcomes. Quality assessment of full text articles was done independently by two reviewers. Studies were categorized according to dimensions of quality.</p> <p>Results</p> <p>Of 6,674 articles identified, 99 were included in the study. The heterogeneity of studies and results reported precluded quantitative data analyses. Findings revealed limited information about attributes of successful and unsuccessful team initiatives, barriers and facilitators to team initiatives, unique or combined contribution of selected interventions, or how to effectively establish these teams.</p> <p>Conclusions</p> <p>Not unlike systematic reviews of quality improvement collaboratives, this broad review revealed that while teams reported a number of positive results, there are many methodological issues. This study is unique in utilizing traditional quality assessment and more novel methods of quality assessment and reporting of results (SQUIRE) to appraise studies. Rigorous design, evaluation, and reporting of quality and safety team initiatives are required.</p

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons

Reflected near-field blast pressure measurements using high speed video

Background: The design and analysis of protective systems requires a detailed understanding of, and the ability to accurately predict, the distribution of pressure loads acting on an obstacle following an explosive detonation. In particular, there is a pressing need for accurate characterisation of blast loads in the region very close to a detonation, where even small improvised devices can produce serious structural or material damage. Objective: Accurate experimental measurement of these near-field blast events, using intrusive methods, is demanding owing to the high magnitudes (> 100 MPa) and short durations (< 1 ms) of loading. The objective of this article is to develop a non-intrusive method for measuring reflected blast pressure distributions using image analysis. Methods: This article presents results from high speed video analysis of near-field spherical PE4 explosive blasts. The Canny edge detection algorithm is used to track the outer surface of the explosive fireball, with the results used to derive a velocity-radius relationship. Reflected pressure distributions are calculated using this velocity-radius relationship in conjunction with the Rankine-Hugoniot jump conditions. Results: The indirectly measured pressure distributions from high speed video are compared with directly measured pressure distributions and are shown to be in good qualitative agreement with respect to distribution of reflected pressures, and in good quantitative agreement with peak reflected pressures (within 10% of the maximum recorded value). Conclusions: The results indicate that it is possible to accurately measure blast loads in the order of 100s MPa using techniques which do not require sensitive recording equipment to be located close to the source of the explosion