Estimating and displaying population attributable fractions using the R package: graphPAF.

Here we introduce graphPAF, a comprehensive R package designed for estimation, inference and display of population attributable fractions (PAF) and impact fractions. In addition to allowing inference for standard population attributable fractions and impact fractions, graphPAF facilitates display of attributable fractions over multiple risk factors using fan-plots and nomograms, calculations of attributable fractions for continuous exposures, inference for attributable fractions appropriate for specific risk factor → mediator → outcome pathways (pathway-specific attributable fractions) and Bayesian network-based calculations and inference for joint, sequential and average population attributable fractions in multi-risk factor scenarios. This article can be used as both a guide to the theory of attributable fraction estimation and a tutorial regarding how to use graphPAF in practical examples.

The University of Limerick Education and Research Network for General Practice (ULEARN-GP): practice characteristics and general practitioner perspectives.

BACKGROUND: A well-functioning general practice sector that has a strong research component is recognised as a key foundation of any modern health system. General practitioners (GPs) are more likely to collaborate in research if they are part of an established research network. The primary aims of this study are to describe Ireland's newest general practice-based research network and to analyse the perspectives of the network's members on research engagement. METHOD: A survey was sent to all GPs participating in the network in order to document practice characteristics so that this research network's profile could be compared to other national profiles of Irish general practice. In depth interviews were then conducted and analysed thematically to explore the experiences and views of a selection of these GPs on research engagement. RESULTS: All 134 GPs responded to the survey. Practices have similar characteristics to the national profile in terms of location, size, computerisation, type of premises and out of hours arrangements. Twenty-two GPs were interviewed and the resulting data was categorised into subthemes and four related overarching themes: GPs described catalysts for research in their practices, the need for coherence in how research is understood in this context, systems failures, whereby the current health system design is prohibitive of GP participation and aspirations for a better future. CONCLUSION: This study has demonstrated that the research network under examination is representative of current trends in Irish general practice. It has elucidated a better understanding of factors that need to be addressed in order to encourage more GPs to engage in the research process.

Pathway-specific population attributable fractions.

INTRODUCTION: A population attributable fraction represents the relative change in disease prevalence that one might expect if a particular exposure was absent from the population. Often, one might be interested in what percentage of this effect acts through particular pathways. For instance, the effect of a sedentary lifestyle on stroke risk may be mediated by blood pressure, body mass index and several other intermediate risk factors. METHODS: We define a new metric, the pathway-specific population attributable fraction (PS-PAF), for mediating pathways of interest. PS-PAFs can be informally defined as the relative change in disease prevalence from an intervention that shifts the distribution of the mediator to its expected distribution if the risk factor were eliminated, and sometimes more simply as the relative change in disease prevalence if the mediating pathway were disabled. A potential outcomes framework is used for formal definitions and associated estimands are derived via relevant identifiability conditions. Computationally efficient estimators for PS-PAFs are derived based on these identifiability conditions. RESULTS: Calculations are demonstrated using INTERSTROKE-an international case-control study designed to quantify disease burden attributable to a number of known causal risk factors. The applied results suggest that mediating pathways from physical activity through blood pressure, blood lipids and body size explain comparable proportions of stroke disease burden, but a large proportion of the disease burden due to physical inactivity may be explained by alternative pathways. CONCLUSION: PS-PAFs measure disease burden attributable to differing mediating pathways and can generate insights into the dominant mechanisms by which a risk factor affects disease at a population level.

Revisiting sequential attributable fractions.

BACKGROUND: In 1995, Eide and Gefeller introduced the concepts of sequential and average attributable fractions as methods to partition the risk of disease among differing exposures. In particular, sequential attributable fractions are interpreted in terms of an incremental reduction in disease prevalence associated with removing a particular risk factor from the population, having removed other risk factors. Clearly, both concepts are causal entities, but are not usually estimated within a causal inference framework. METHODS: We propose causal definitions of sequential and average attributable fractions using the potential outcomes framework. To estimate these quantities in practice, we model exposure-exposure and exposure-disease interrelationships using a causal Bayesian network, assuming no unmeasured latent confounders. This allows us to model not only the direct impact of removing a risk factor on disease, but also the indirect impact through the effect on the prevalence of causally downstream risk factors that are typically ignored when calculating sequential and average attributable fractions. The procedure for calculating sequential attributable fractions involves repeated applications of Pearl's do-operator over a fitted Bayesian network, and simulation from the resulting joint probability distributions. RESULTS: The methods are applied to the INTERSTROKE study, which was designed to quantify disease burden attributable to the major risk factors for stroke. The resulting sequential and average attributable fractions are compared with results from a prior estimation approach which uses a single logistic model and which does not properly account for differing causal pathways. CONCLUSIONS: In contrast to estimation using a single regression model, the proposed approaches allow consistent estimation of sequential, joint and average attributable fractions under general causal structures.

Use phase signals to promote lifetime extension for Windows PCs.

This paper proposes a signaling methodology for personal computers. Signaling may be viewed as an ecodesign strategy that can positively influence the consumer to consumer (C2C) market process. A number of parameters are identified that can provide the basis for signal implementation. These include operating time, operating temperature, operating voltage, power cycle counts, hard disk drive (HDD) self-monitoring, and reporting technology (SMART) attributes and operating system (OS) event information. All these parameters are currently attainable or derivable via embedded technologies in modern desktop systems. A case study detailing a technical implementation of how the development of signals can be achieved in personal computers that incorporate Microsoft Windows operating systems is presented. Collation of lifetime temperature data from a system processor is demonstrated as a possible means of characterizing a usage profile for a desktop system. In addition, event log data is utilized for devising signals indicative of OS quality. The provision of lifetime usage data in the form of intuitive signals indicative of both hardware and software quality can in conjunction with consumer education facilitate an optimal remarketing strategy for used systems. This implementation requires no additional hardware.

Model for substrate interactions in C5a peptidase from Streptococcus pyogenes: A 1.9 A crystal structure of the active form of ScpA.

The crystal structure of an active form of ScpA has been solved to 1.9 A resolution. ScpA is a multidomain cell-envelope subtilase from Streptococcus pyogenes that cleaves complement component C5a. The catalytic triad of ScpA is geometrically consistent with other subtilases, clearly demonstrating that the additional activation mechanism proposed for the Streptococcus agalactiae homologue (ScpB) is not required for ScpA. The ScpA structure revealed that access to the catalytic site is restricted by variable regions in the catalytic domain (vr7, vr9, and vr11) and by the presence of the inserted protease-associated (PA) domain and the second fibronectin type III domains (Fn2). Modeling of the ScpA-C5a complex indicates that the substrate binds with carboxyl-terminal residues (65-74) extended through the active site and core residues (1-64) forming exosite-type interactions with the Fn2 domain. This is reminiscent of the two-site mechanism proposed for C5a binding to its receptor. In the nonprime region of the active site, interactions with the substrate backbone are predicted to be more similar to those observed in kexins, involving a single beta-strand in the peptidase. However, in contrast to kexins, there would be diminished emphasis on side-chain interactions, with little charged character in the S3-S1 and S6-S4 subsites occupied by the side chains of residues in vr7 and vr9. Substrate binding is anticipated to be dominated by ionic interactions in two distinct regions of ScpA. On the prime side of the active site, salt bridges are predicted between P1', P2', and P7' residues, and residues in the catalytic and PA domains. Remote to the active site, a larger number of ionic interactions between residues in the C5a core and the Fn2 domain are observed in the model. Thus, both PA and Fn2 domains are expected to play significant roles in substrate recognition.