Improving model quality through foundational ontologies: Two contrasting approaches to the representation of roles

Several foundational ontologies have been developed recently. We examine two of these from the point of view of their quality in representing temporal changes, focusing on the example of roles. We discuss how these are modelled in two foundational ontologies: the Unified Foundational Ontology and the BORO foundational ontology. These exhibit two different approaches, endurantist and perdurantist respectively. We illustrate the differences using a running example in the university student domain, wherein one individual is not only a registered student but also, for part of this period, was elected the President of the Student Union. The metaphysical choices made by UFO and BORO lead to different representations of roles. Two key differences which affect the way roles are modelled are exemplified in this paper: (1) different criteria of identity and (2) differences in the way individual objects extend over time and possible worlds. These differences impact upon the quality of the models produced in terms of their respective explanatory power. The UFO model concentrates on the notion of validity in “all possible worlds” and is unable to accurately represent the way particulars are extended in time. The perdurantist approach is best able to describe temporal changes wherein roles are spatio-temporal extents of individuals

Australian utility weights for the EORTC QLU-C10D, a multi-attribute utility instrument derived from the cancer-specific quality of life questionnaire, EORTC QLQ-C30

Background: The EORTC QLU-C10D is a new multi-attribute utility instrument derived from the widely-used cancer-specific quality of life questionnaire, EORTC QLQ-C30. The QLU-C10D contains ten dimensions (Physical, Role, Social and Emotional Functioning; Pain, Fatigue, Sleep, Appetite, Nausea, Bowel Problems), each with 4 levels. To be used in cost-utility analysis, country-specific valuation sets are required. Objective: To provide Australian utility weights for the QLU-C10D. Methods: An Australian online panel was quota sampled to ensure population representativeness by sex and age (≥18y). Participants completed a discrete choice experiment (DCE) consisting of 16 choice-pairs. Each pair comprised two QLU-C10D health states plus life expectancy. Data were analysed using conditional logistic regression, parameterised to fit the quality-adjusted life-year framework. Utility weights were calculated as the ratio of each QOL dimension-level coefficient to the coefficient on life expectancy. Results: 1979 panel members opted-in, 1904 (96%) completed at least one choice-pair, and 1846 (93%) completed all 16 choice-pairs. Dimension weights were generally monotonic: poorer levels within each dimension were generally associated with greater utility decrements. The dimensions that impacted most on choice were, in order, Physical Functioning, Pain, Role Functioning and Emotional Functioning. Oncology-relevant dimensions with moderate impact were Nausea and Bowel Problems. Fatigue, Trouble Sleeping and Appetite had relatively small impact. The value of the worst health state was -0.096, somewhat worse than death. Conclusions: This study provides the first country-specific value set for the QLU-C10D, which can facilitate cost-utility analyses when applied to data collected with the EORTC QLQ-C30, prospectively and retrospectively

FTO Is Expressed in Neurones throughout the Brain and Its Expression Is Unaltered by Fasting

Single-nucleotide polymorphisms in the first intron of the ubiquitously expressed FTO gene are associated with obesity. Although the physiological functions of FTO remain unclear, food intake is often altered when Fto expression levels are manipulated. Furthermore, deletion of FTO from neurones alone has a similar effect on food intake to deletion of FTO in all tissues. These results indicate that FTO expression in the brain is particularly important. Considerable focus has been placed on the dynamic regulation of Fto mRNA expression in the hypothalamus after short-term (16–48 hour) fasting, but results have been controversial. There are no studies that quantify FTO protein levels across the brain, and assess its alteration following short-term fasting. Using immunohistochemistry, we found that FTO protein is widely expressed in mouse brain, and present in the majority of neurones. Using quantitative Western blotting and RT-qPCR we show that FTO protein and mRNA levels in the hypothalamus, cerebellum and rostral brain are relatively uniform, and levels in the brain are higher than in skeletal muscles of the lower limbs. Fasting for 18 hours does not alter the expression pattern, or levels, of FTO protein and mRNA. We further show that the majority of POMC neurones, which are critically involved in food intake regulation, also express FTO, but that the percentage of FTO-positive POMC neurones is not altered by fasting. In summary, we find no evidence that Fto/FTO expression is regulated by short-term (18-hour) fasting. Thus, it is unlikely that the hunger and increased post-fasting food intake caused by such food deprivation is driven by alterations in Fto/FTO expression. The widespread expression of FTO in neurones also suggests that physiological studies of this protein should not be limited to the hypothalamus

Measuring patient-reported outcomes: moving beyond misplaced common sense to hard science

Interest in the patient's views of his or her illness and treatment has increased dramatically. However, our ability to appropriately measure such issues lags far behind the level of interest and need. Too often such measurement is considered to be a simple and trivial activity that merely requires the application of common sense. However, good quality measurement of patient-reported outcomes is a complex activity requiring considerable expertise and experience. This review considers the most important issues related to such measurement in the context of chronic disease and details how instruments should be developed, validated and adapted for use in additional languages. While there is often consensus on how best to undertake these activities, there is generally little evidence to support such accord. The present article questions these orthodox views and suggests alternative approaches that have been shown to be effective

Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data

International audienceBACKGROUND: The intra- and inter-species genetic diversity of bacteria and the absence of 'reference', or the most representative, sequences of individual species present a significant challenge for sequence-based identification. The aims of this study were to determine the utility, and compare the performance of several clustering and classification algorithms to identify the species of 364 sequences of 16S rRNA gene with a defined species in GenBank, and 110 sequences of 16S rRNA gene with no defined species, all within the genus Nocardia. METHODS: A total of 364 16S rRNA gene sequences of Nocardia species were studied. In addition, 110 16S rRNA gene sequences assigned only to the Nocardia genus level at the time of submission to GenBank were used for machine learning classification experiments. Different clustering algorithms were compared with a novel algorithm or the linear mapping (LM) of the distance matrix. Principal Components Analysis was used for the dimensionality reduction and visualization. RESULTS: The LM algorithm achieved the highest performance and classified the set of 364 16S rRNA sequences into 80 clusters, the majority of which (83.52%) corresponded with the original species. The most representative 16S rRNA sequences for individual Nocardia species have been identified as 'centroids' in respective clusters from which the distances to all other sequences were minimized; 110 16S rRNA gene sequences with identifications recorded only at the genus level were classified using machine learning methods. Simple kNN machine learning demonstrated the highest performance and classified Nocardia species sequences with an accuracy of 92.7% and a mean frequency of 0.578. CONCLUSION: The identification of centroids of 16S rRNA gene sequence clusters using novel distance matrix clustering enables the identification of the most representative sequences for each individual species of Nocardia and allows the quantitation of inter- and intra-species variability

Evolving the theory and praxis of knowledge translation through social interaction: a social phenomenological study

Background: As an inherently human process fraught with subjectivity, dynamic interaction, and change, social interaction knowledge translation (KT) invites implementation scientists to explore what might be learned from adopting the academic tradition of social constructivism and an interpretive research approach. This paper presents phenomenological investigation of the second cycle of a participatory action KT intervention in the home care sector to answer the question: What is the nature of the process of implementing KT through social interaction? Methods: Social phenomenology was selected to capture how the social processes of the KT intervention were experienced, with the aim of representing these as typical socially-constituted patterns. Participants (n = 203), including service providers, case managers, administrators, and researchers organized into nine geographically-determined multi-disciplinary action groups, purposefully selected and audiotaped three meetings per group to capture their enactment of the KT process at early, middle, and end-of-cycle timeframes. Data, comprised of 36 hours of transcribed audiotapes augmented by researchers\u27 field notes, were analyzed using social phenomenology strategies and authenticated through member checking and peer review. Results: Four patterns of social interaction representing organization, team, and individual interests were identified: overcoming barriers and optimizing facilitators; integrating \u27science push\u27 and \u27demand pull\u27 approaches within the social interaction process; synthesizing the research evidence with tacit professional craft and experiential knowledge; and integrating knowledge creation, transfer, and uptake throughout everyday work. Achieved through relational transformative leadership constituted simultaneously by both structure and agency, in keeping with social phenomenology analysis approaches, these four patterns are represented holistically in a typical construction, specifically, a participatory action KT (PAKT) model. Conclusion: Study findings suggest the relevance of principles and foci from the field of process evaluation related to intervention implementation, further illuminating KT as a structuration process facilitated by evolving transformative leadership in an active and integrated context. The model provides guidance for proactively constructing a \u27fit\u27 between content, context, and facilitation in the translation of evidence informing professional craft knowledge

The Role Of Condition-Specific Preference-Based Measures In Health Technology Assessment

A condition-specific preference-based measure (CSPBM) is a measure of health related quality of life (HRQoL) that is specific to a certain condition or disease and that can be used to obtain the quality adjustment weight of the quality adjusted life year (QALY) for use in economic models. This article provides an overview of the role of CSPBMs, the development of CSPBMs, and presents a description of existing CSPBMs in the literature. The article also provides an overview of the psychometric properties of CSPBMs in comparison to generic preference-based measures (generic PBMs), and considers the advantages and disadvantages of CSPBMs in comparison to generic PBMs. CSPBMs typically include dimensions that are important for that condition but may not be important across all patient groups. There are a large number of CSPBMs across a wide range of conditions, and these vary from covering a wide range of dimensions to more symptomatic or uni-dimensional measures. Psychometric evidence is limited but suggests that CSPBMs offer an advantage in more accurate measurement of milder health states. The mean change and standard deviation can differ for CSPBMs and generic PBMs, and this may impact on incremental cost-effectiveness ratios. CSPBMs have a useful role in HTA where a generic PBM is not appropriate, sensitive or responsive. However due to issues of comparability across different patient groups and interventions, their usage in health technology assessment is often limited to conditions where it is inappropriate to use a generic PBM or sensitivity analyses