The cost-effectiveness of quality improvement projects: a conceptual framework, checklist and online tool for considering the costs and consequences of implementation based quality improvement

In resource constrained systems, decision makers should be concerned with the efficiency of implementing improvement techniques and technologies. Accordingly, they should consider both the costs and effectiveness of implementation as well as the cost-effectiveness of the innovation to be implemented. An approach to doing this effectively is encapsulated in the ‘policy cost-effectiveness’ approach. This paper outlines some of the theoretical and practical challenges to assessing policy cost-effectiveness (the cost-effectiveness of implementation projects). A checklist and associated (freely available) online application are also presented to help services develop more cost-effective implementation strategies

GPCR-OKB: the G protein coupled receptor oligomer knowledge base

Rapid expansion of available data about G Protein Coupled Receptor (GPCR) dimers/oligomers over the past few years requires an effective system to organize this information electronically. Based on an ontology derived from a community dialog involving colleagues using experimental and computational methodologies, we developed the GPCR-Oligomerization Knowledge Base (GPCR-OKB). GPCR-OKB is a system that supports browsing and searching for GPCR oligomer data. Such data were manually derived from the literature. While focused on GPCR oligomers, GPCR-OKB is seamlessly connected to GPCRDB, facilitating the correlation of information about GPCR protomers and oligomers

Compression of Structured High-Throughput Sequencing Data

Large biological datasets are being produced at a rapid pace and create substantial storage challenges, particularly in the domain of high-throughput sequencing (HTS). Most approaches currently used to store HTS data are either unable to quickly adapt to the requirements of new sequencing or analysis methods (because they do not support schema evolution), or fail to provide state of the art compression of the datasets. We have devised new approaches to store HTS data that support seamless data schema evolution and compress datasets substantially better than existing approaches. Building on these new approaches, we discuss and demonstrate how a multi-tier data organization can dramatically reduce the storage, computational and network burden of collecting, analyzing, and archiving large sequencing datasets. For instance, we show that spliced RNA-Seq alignments can be stored in less than 4% the size of a BAM file with perfect data fidelity. Compared to the previous compression state of the art, these methods reduce dataset size more than 40% when storing exome, gene expression or DNA methylation datasets. The approaches have been integrated in a comprehensive suite of software tools (http://goby.campagnelab.org) that support common analyses for a range of high-throughput sequencing assays.National Center for Research Resources (U.S.) (Grant UL1 RR024996)Leukemia & Lymphoma Society of America (Translational Research Program Grant LLS 6304-11)National Institute of Mental Health (U.S.) (R01 MH086883

Molecular evolutionary characterization of a V1R subfamily unique to strepsirrhine primates.

Vomeronasal receptor genes have frequently been invoked as integral to the establishment and maintenance of species boundaries among mammals due to the elaborate one-to-one correspondence between semiochemical signals and neuronal sensory inputs. Here, we report the most extensive sample of vomeronasal receptor class 1 (V1R) sequences ever generated for a diverse yet phylogenetically coherent group of mammals, the tooth-combed primates (suborder Strepsirrhini). Phylogenetic analysis confirms our intensive sampling from a single V1R subfamily, apparently unique to the strepsirrhine primates. We designate this subfamily as V1Rstrep. The subfamily retains extensive repertoires of gene copies that descend from an ancestral gene duplication that appears to have occurred prior to the diversification of all lemuriform primates excluding the basal genus Daubentonia (the aye-aye). We refer to the descendent clades as V1Rstrep-α and V1Rstrep-β. Comparison of the two clades reveals different amino acid compositions corresponding to the predicted ligand-binding site and thus potentially to altered functional profiles between the two. In agreement with previous studies of the mouse lemur (genus, Microcebus), the majority of V1Rstrep gene copies appear to be intact and under strong positive selection, particularly within transmembrane regions. Finally, despite the surprisingly high number of gene copies identified in this study, it is nonetheless probable that V1R diversity remains underestimated in these nonmodel primates and that complete characterization will be limited until high-coverage assembled genomes are available

Trees on networks: resolving statistical patterns of phylogenetic similarities among interacting proteins

<p>Abstract</p> <p>Background</p> <p>Phylogenies capture the evolutionary ancestry linking extant species. Correlations and similarities among a set of species are mediated by and need to be understood in terms of the phylogenic tree. In a similar way it has been argued that biological networks also induce correlations among sets of interacting genes or their protein products.</p> <p>Results</p> <p>We develop suitable statistical resampling schemes that can incorporate these two potential sources of correlation into a single inferential framework. To illustrate our approach we apply it to protein interaction data in yeast and investigate whether the phylogenetic trees of interacting proteins in a panel of yeast species are more similar than would be expected by chance.</p> <p>Conclusions</p> <p>While we find only negligible evidence for such increased levels of similarities, our statistical approach allows us to resolve the previously reported contradictory results on the levels of co-evolution induced by protein-protein interactions. We conclude with a discussion as to how we may employ the statistical framework developed here in further functional and evolutionary analyses of biological networks and systems.</p

Prevalence of human papillomavirus cervical infection in an Italian asymptomatic population

BACKGROUND: In the last decade many studies have definitely shown that human papillomaviruses (HPVs) are the major cause of cervical carcinogenesis and, in the last few years, HPV testing has been proposed as a new and more powerful tool for cervical cancer screening. This issue is now receiving considerable attention in scientific and non scientific press and HPV testing could be considered the most important change in this field since the introduction of cervical cytology. This paper reports our prevalence data of HPV infection collected in the '90s, while a follow up of these patients is ongoing. METHODS: For this study we used polymerase chain reaction (PCR) to search HPV DNA sequences in cervical cell scrapings obtained from 503 asymptomatic women attending regular cervical cancer screening program in the city of Genova, Italy. All patients were also submitted to a self-administered, standardized, questionnaire regarding their life style and sexual activity. On the basis of the presence of HPV DNA sequences women were separated into two groups: "infected" and "non infected" and a statistical analysis of the factors potentially associated with the infection group membership was carried out. RESULTS: The infection rate was 15.9% and the most frequent viral type was HPV 16. CONCLUSION: Our HPV positivity rate (15.9%) was consistent to that reported by other studies on European populations

Studying Public Health Law::Principles, Politics, and Populations as Patients

Public health law is firmly establishing itself as a crucial area of scholarly inquiry. Its vital importance has been sharply underscored following the outbreak of COVID-19, in response to which we have seen the institution of extreme legal measures—suchas the UK’s Coronavirus Act 2020—in efforts to control and contain the spread ofthe disease. The pandemic has also starkly exposed the complex nature of the regulatory challenges, nationally, internationally, and globally, to which such public health problems give rise. In approaching these, and other questions concerning the public’s health, such as non-communicable disease, public health law, as a field, brings notable distinctive features: these include a practical focus on populations, institutions, the prevention of ill health, protection of good health, and thepromotion of positive states of well-being; and concomitant critical approaches rooted in theories of social justice as contrasted with more narrow biomedical ethics. Such features make it in some senses atypical territory within the field of health law. Furthermore, the inherent role of political institutions places law conceptually within public health in a way that may be seen as distinguishable from law’s relationship with clinical medicine. This chapter explains how the broad reach and distinct features of public health require a commensurately broad approach to conceptualising public health law, and how distinct practical and theoretical features may be integrated into academic public health law. It also shows how public health law, with its distinct conceptualisations concerning ‘the body’ of medical jurisprudence, can both challenge and enrich medico-legal studies, and bring important perspectives within the broader field of health law

Methodologies used to estimate tobacco-attributable mortality: a review

<p>Abstract</p> <p>Background</p> <p>One of the most important measures for ascertaining the impact of tobacco on a population is the estimation of the mortality attributable to its use. To measure this, a number of indirect methods of quantification are available, yet there is no consensus as to which furnishes the best information. This study sought to provide a critical overview of the different methods of attribution of mortality due to tobacco consumption.</p> <p>Method</p> <p>A search was made in the Medline database until March 2005 in order to obtain papers that addressed the methodology employed for attributing mortality to tobacco use.</p> <p>Results</p> <p>Of the total of 7 methods obtained, the most widely used were the prevalence methods, followed by the approach proposed by Peto et al, with the remainder being used in a minority of studies.</p> <p>Conclusion</p> <p>Different methodologies are used to estimate tobacco attributable mortality, but their methodological foundations are quite similar in all. Mainly, they are based on the calculation of proportional attributable fractions. All methods show limitations of one type or another, sometimes common to all methods and sometimes specific.</p

Theorising lifestyle drift in health promotion: explaining community and voluntary sector engagement practices in disadvantaged areas

The past two decades have seen an increasing role for the UK community and voluntary sector (CVS) in health promotion in disadvantaged areas, largely based on assumptions on the part of funders that CVS providers are better able to engage ‘hard-to-reach’ population groups in services than statutory providers. However, there is limited empirical research exploring CVS provider practices in this field. Using ethnographic data, this paper examines the experiences of a network of CVS providers seeking to engage residents in health-promoting community services in a disadvantaged region in the North of England. The paper shows how CVS providers engaged in apparently contradictory practices, fluctuating between an empathically informed response to complex resident circumstances and (in the context of meeting externally set targets) behavioural lifestyle approaches to health promotion. Drawing on concepts from figurational sociology, the paper explains how lifestyle drift occurs in health promotion as a result of the complex web of relations (with funders, commissioners and residents) in which CVS providers are embedded. Despite the fact that research has revealed the impact of targets on the work of the CVS before, this paper demonstrates more specifically the way in which monitoring processes within CVS contracts can draw providers into the neoliberal lifestyle discourse so prevalent in health promotion

Congruence of tissue expression profiles from Gene Expression Atlas, SAGEmap and TissueInfo databases

BACKGROUND: Extracting biological knowledge from large amounts of gene expression information deposited in public databases is a major challenge of the postgenomic era. Additional insights may be derived by data integration and cross-platform comparisons of expression profiles. However, database meta-analysis is complicated by differences in experimental technologies, data post-processing, database formats, and inconsistent gene and sample annotation. RESULTS: We have analysed expression profiles from three public databases: Gene Expression Atlas, SAGEmap and TissueInfo. These are repositories of oligonucleotide microarray, Serial Analysis of Gene Expression and Expressed Sequence Tag human gene expression data respectively. We devised a method, Preferential Expression Measure, to identify genes that are significantly over- or under-expressed in any given tissue. We examined intra- and inter-database consistency of Preferential Expression Measures. There was good correlation between replicate experiments of oligonucleotide microarray data, but there was less coherence in expression profiles as measured by Serial Analysis of Gene Expression and Expressed Sequence Tag counts. We investigated inter-database correlations for six tissue categories, for which data were present in the three databases. Significant positive correlations were found for brain, prostate and vascular endothelium but not for ovary, kidney, and pancreas. CONCLUSION: We show that data from Gene Expression Atlas, SAGEmap and TissueInfo can be integrated using the UniGene gene index, and that expression profiles correlate relatively well when large numbers of tags are available or when tissue cellular composition is simple. Finally, in the case of brain, we demonstrate that when PEM values show good correlation, predictions of tissue-specific expression based on integrated data are very accurate