Adolescent valuation of CARIES-QC-U: a child-centred preference-based measure of dental caries

Objectives: This study develops an adolescent value set for a child-centred dental caries-specific measure of oral health-related quality of life (OHRQoL) based upon CARIES-QC (Caries Impacts and Experiences Questionnaire for Children). This study develops a new approach to valuing child health by eliciting adolescent preferences and anchoring these onto the 1-0 full health-dead QALY (quality adjusted life year) scale using ordinal adult preferences.Methods: Two online surveys were created to elicit preferences for the CARIES-QC classification system. The first comprised best-worst scaling (BWS) tasks for completion by adolescents aged 11-16 years. The second comprised discrete choice experiment tasks with a duration attribute (DCETTO) for completion by adults aged over 18 years. Preferences were modelled using the conditional logit model. Mapping regressions anchored the adolescent BWS data onto the QALY scale using adult DCETTO values, since the BWS survey data alone cannot generate anchored values.Results: 723 adolescents completed the BWS survey and 626 adults completed the DCE(TTO )survey. The samples were representative of UK adolescent and adult populations. Fully consistent and robust models were produced for both BWS and DCETTO data. BWS preferences were mapped onto DCETTO values, resulting utility estimates for each health state defined by the classification system.Conclusion: This is the first measure with predetermined scoring based on preferences to be developed specifically for use in child oral health research, and uses a novel technique to generate a value set using adolescent preferences. The estimates can be used to generate QALYs in economic evaluations of interventions to improve children's oral health

Discrete choice experiments or best-worst scaling? A qualitative study to determine the suitability of preference elicitation tasks in research with children and young people

Background Ordinal tasks are increasingly used to explore preferences for health states. This study aimed to determine the suitability of two ordinal preference elicitation tasks (discrete choice experiments (DCE) and best-worst scaling (BWS)) for use with children and young people to generate health state utility values. The study explored children’s understanding, the relationship between their age and level of understanding, and how many tasks they felt they could complete. Methods Children aged 11–16 years were recruited from a secondary school in South Yorkshire, UK. Participants were asked to ‘think aloud’ as they completed a computer-based survey that contained both DCE and BWS tasks relating to dental caries (tooth decay) health states. Health states involved descriptions of the impact of tooth decay on children’s daily lives. One-to-one semi-structured interviews were then held with participants, with use of a topic guide. Qualitative data were transcribed verbatim and analysed thematically. Results A total of 33 children (12 male, 21 female) participated, comprising 5–6 children from each school year group. Children expressed a preference for BWS and demonstrated a better understanding of these tasks than DCE. There was no clear relationship between children’s level of understanding and age. Children felt they could manage between 8 and 10 BWS tasks comfortably. Conclusion This study suggests that BWS tasks are the most appropriate type of preference elicitation task to value health states for children and young people aged 11–16 years to complete

Simulations of extensional flow in microrheometric devices

We present a detailed numerical study of the flow of a Newtonian fluid through microrheometric devices featuring a sudden contraction–expansion. This flow configuration is typically used to generate extensional deformations and high strain rates. The excess pressure drop resulting from the converging and diverging flow is an important dynamic measure to quantify if the device is intended to be used as a microfluidic extensional rheometer. To explore this idea, we examine the effect of the contraction length, aspect ratio and Reynolds number on the flow kinematics and resulting pressure field. Analysis of the computed velocity and pressure fields show that, for typical experimental conditions used in microfluidic devices, the steady flow is highly three-dimensional with open spiraling vortical structures in the stagnant corner regions. The numerical simulations of the local kinematics and global pressure drop are in good agreement with experimental results. The device aspect ratio is shown to have a strong impact on the flow and consequently on the excess pressure drop, which is quantified in terms of the dimensionless Couette and Bagley correction factors. We suggest an approach for calculating the Bagley correction which may be especially appropriate for planar microchannels

Microfluidic systems for the analysis of the viscoelastic fluid flow phenomena in porous media

In this study, two microfluidic devices are proposed as simplified 1-D microfluidic analogues of a porous medium. The objectives are twofold: firstly to assess the usefulness of the microchannels to mimic the porous medium in a controlled and simplified manner, and secondly to obtain a better insight about the flow characteristics of viscoelastic fluids flowing through a packed bed. For these purposes, flow visualizations and pressure drop measurements are conducted with Newtonian and viscoelastic fluids. The 1-D microfluidic analogues of porous medium consisted of microchannels with a sequence of contractions/ expansions disposed in symmetric and asymmetric arrangements. The real porous medium is in reality, a complex combination of the two arrangements of particles simulated with the microchannels, which can be considered as limiting ideal configurations. The results show that both configurations are able to mimic well the pressure drop variation with flow rate for Newtonian fluids. However, due to the intrinsic differences in the deformation rate profiles associated with each microgeometry, the symmetric configuration is more suitable for studying the flow of viscoelastic fluids at low De values, while the asymmetric configuration provides better results at high De values. In this way, both microgeometries seem to be complementary and could be interesting tools to obtain a better insight about the flow of viscoelastic fluids through a porous medium. Such model systems could be very interesting to use in polymer-flood processes for enhanced oil recovery, for instance, as a tool for selecting the most suitable viscoelastic fluid to be used in a specific formation. The selection of the fluid properties of a detergent for cleaning oil contaminated soil, sand, and in general, any porous material, is another possible application

Genetic risk prediction and neurobiological understanding of alcoholism

We have used a translational Convergent Functional Genomics (CFG) approach to discover genes involved in alcoholism, by gene-level integration of genome-wide association study (GWAS) data from a German alcohol dependence cohort with other genetic and gene expression data, from human and animal model studies, similar to our previous work in bipolar disorder and schizophrenia. A panel of all the nominally significant P-value single-nucleotide length polymorphisms (SNPs) in the top candidate genes discovered by CFG (n = 135 genes, 713 SNPs) was used to generate a genetic risk prediction score (GRPS), which showed a trend towards significance (P = 0.053) in separating alcohol dependent individuals from controls in an independent German test cohort. We then validated and prioritized our top findings from this discovery work, and subsequently tested them in three independent cohorts, from two continents. In order to validate and prioritize the key genes that drive behavior without some of the pleiotropic environmental confounds present in humans, we used a stress-reactive animal model of alcoholism developed by our group, the D-box binding protein (DBP) knockout mouse, consistent with the surfeit of stress theory of addiction proposed by Koob and colleagues. A much smaller panel (n = 11 genes, 66 SNPs) of the top CFG-discovered genes for alcoholism, cross-validated and prioritized by this stress-reactive animal model showed better predictive ability in the independent German test cohort (P = 0.041). The top CFG scoring gene for alcoholism from the initial discovery step, synuclein alpha (SNCA) remained the top gene after the stress-reactive animal model cross-validation. We also tested this small panel of genes in two other independent test cohorts from the United States, one with alcohol dependence (P = 0.00012) and one with alcohol abuse (a less severe form of alcoholism; P = 0.0094). SNCA by itself was able to separate alcoholics from controls in the alcohol-dependent cohort (P = 0.000013) and the alcohol abuse cohort (P = 0.023). So did eight other genes from the panel of 11 genes taken individually, albeit to a lesser extent and/or less broadly across cohorts. SNCA, GRM3 and MBP survived strict Bonferroni correction for multiple comparisons. Taken together, these results suggest that our stress-reactive DBP animal model helped to validate and prioritize from the CFG-discovered genes some of the key behaviorally relevant genes for alcoholism. These genes fall into a series of biological pathways involved in signal transduction, transmission of nerve impulse (including myelination) and cocaine addiction. Overall, our work provides leads towards a better understanding of illness, diagnostics and therapeutics, including treatment with omega-3 fatty acids. We also examined the overlap between the top candidate genes for alcoholism from this work and the top candidate genes for bipolar disorder, schizophrenia, anxiety from previous CFG analyses conducted by us, as well as cross-tested genetic risk predictions. This revealed the significant genetic overlap with other major psychiatric disorder domains, providing a basis for comorbidity and dual diagnosis, and placing alcohol use in the broader context of modulating the mental landscape

Root canal morphology of primary maxillary second molars:a micro-computed tomography analysis

Aim Successful endodontic treatment of primary teeth requires comprehensive knowledge and understanding of root canal morphology. The purpose of this study was to investigate the root canal configurations of primary maxillary second molars using micro-computed tomography. Methods Extracted human primary maxillary second molars (n = 57) were scanned using micro-computed tomography and reconstructed to produce three-dimensional models. Each root canal system was analysed qualitatively according to Vertucci's classification. Results 22.8% (n = 13) of the sample presented with the fusion of the disto-buccal and palatal roots; of these, Type V was the most prevalent classification. For teeth with three separate roots (n = 44), the most common root canal type was Type 1 for the palatal canal (100%) and disto-buccal canal (77.3%) and Type V for the mesio-buccal canal (36.4%). Overall, 7% (n = 4) of mesio-buccal canals were 'unclassifiable'. Conclusion The root canal systems of primary maxillary second molars were not only complex but had a range of configurations that may contribute to unfavourable clinical outcomes after endodontic treatment

Reappraising Sexual Coevolution and the Sex Roles

Over recent decades, new ideas have radically altered how we see sex and reproduction. The implications of these ideas are still being explored, yielding intriguing discoveries