Oral health awareness and care preferences in patients with diabetes : a qualitative study

Background People with type 2 diabetes have an increased risk of oral health problems; however, oral health is currently not included in structured diabetes reviews and education in the UK. Aim and Objectives This study explores the patient experience related to oral health and diabetes, especially in relation to: • Awareness of the link between oral health and diabetes and oral self care needs • Interaction with health professionals in dental and general practice • Preferences for receiving oral health information and education Methods This nested qualitative study involved semi-structured telephone interviews with a purposive sample of 20 participants from a questionnaire study on oral health awareness in patients with diabetes. Interview transcripts were analysed using a thematic framework approach. Results Participants were mostly unaware of the link between oral health and diabetes. Those that had been made aware by a health professional were not given concrete self care advice. Interactions with dental professionals were often limited to informing the dental practice of their diagnosis and current medication. Most participants were in favour of dentists screening for diabetes, but as their general practice was the hub for diabetes care, they felt GPs or nurses should provide oral health information and discuss oral health with patients. Conclusions Written information regarding diabetes and its possible effects on oral health needs to be more readily available to people with diabetes, especially at diagnosis. There may be a place for introducing a structured oral health question in routine diabetes reviews

BiofilmQuant: A Computer-Assisted Tool for Dental Biofilm Quantification

Dental biofilm is the deposition of microbial material over a tooth substratum. Several methods have recently been reported in the literature for biofilm quantification; however, at best they provide a barely automated solution requiring significant input needed from the human expert. On the contrary, state-of-the-art automatic biofilm methods fail to make their way into clinical practice because of the lack of effective mechanism to incorporate human input to handle praxis or misclassified regions. Manual delineation, the current gold standard, is time consuming and subject to expert bias. In this paper, we introduce a new semi-automated software tool, BiofilmQuant, for dental biofilm quantification in quantitative light-induced fluorescence (QLF) images. The software uses a robust statistical modeling approach to automatically segment the QLF image into three classes (background, biofilm, and tooth substratum) based on the training data. This initial segmentation has shown a high degree of consistency and precision on more than 200 test QLF dental scans. Further, the proposed software provides the clinicians full control to fix any misclassified areas using a single click. In addition, BiofilmQuant also provides a complete solution for the longitudinal quantitative analysis of biofilm of the full set of teeth, providing greater ease of usability.Comment: 4 pages, 4 figures, 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014

A Statistical Modeling Approach to Computer-Aided Quantification of Dental Biofilm

Biofilm is a formation of microbial material on tooth substrata. Several methods to quantify dental biofilm coverage have recently been reported in the literature, but at best they provide a semi-automated approach to quantification with significant input from a human grader that comes with the graders bias of what are foreground, background, biofilm, and tooth. Additionally, human assessment indices limit the resolution of the quantification scale; most commercial scales use five levels of quantification for biofilm coverage (0%, 25%, 50%, 75%, and 100%). On the other hand, current state-of-the-art techniques in automatic plaque quantification fail to make their way into practical applications owing to their inability to incorporate human input to handle misclassifications. This paper proposes a new interactive method for biofilm quantification in Quantitative light-induced fluorescence (QLF) images of canine teeth that is independent of the perceptual bias of the grader. The method partitions a QLF image into segments of uniform texture and intensity called superpixels; every superpixel is statistically modeled as a realization of a single 2D Gaussian Markov random field (GMRF) whose parameters are estimated; the superpixel is then assigned to one of three classes (background, biofilm, tooth substratum) based on the training set of data. The quantification results show a high degree of consistency and precision. At the same time, the proposed method gives pathologists full control to post-process the automatic quantification by flipping misclassified superpixels to a different state (background, tooth, biofilm) with a single click, providing greater usability than simply marking the boundaries of biofilm and tooth as done by current state-of-the-art methods.Comment: 10 pages, 7 figures, Journal of Biomedical and Health Informatics 2014. keywords: {Biomedical imaging;Calibration;Dentistry;Estimation;Image segmentation;Manuals;Teeth}, http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6758338&isnumber=636350

What Does the Minimum Wage Do?

This book attempts to make sense of the research on the minimum wage that began in the early 1990s. The authors look at who is affected by the minimum wage, both directly and indirectly; which observable, measurable variables (e.g., wages, employment, school enrollment) the minimum wage influences; how long it takes for the variables to respond to the minimum wage and the size and desirability of the effect; why the minimum wage has the results it does (and not others); and the workers most likely to be affected by changes to the minimum wage.https://research.upjohn.org/up_press/1245/thumbnail.jp

Variable-delay Polarization Modulators for Cryogenic Millimeter-wave Applications

We describe the design, construction, and initial validation of the variable-delay polarization modulator (VPM) designed for the PIPER cosmic microwave background polarimeter. The VPM modulates between linear and circular polarization by introducing a variable phase delay between orthogonal linear polarizations. Each VPM has a diameter of 39 cm and is engineered to operate in a cryogenic environment (1.5 K). We describe the mechanical design and performance of the kinematic double-blade flexure and drive mechanism along with the construction of the high precision wire grid polarizers.Comment: 8 pages, 10 Figures, Submitted to Review of Scientific Instrument

Mutational Analysis of the Active Site and Antibody Epitopes of the Complement-inhibitory Glycoprotein, CD59

The Ly-6 superfamily of cell surface molecules includes CD59, a potent regulator of the complement system that protects host cells from the cytolytic action of the membrane attack complex (MAC). Although its mechanism of action is not well understood, CD59 is thought to prevent assembly of the MAC by binding to the C8 and/or C9 proteins of the nascent complex. Here a systematic, structure-based mutational approach has been used to determine the region(s) of CD59 required for its protective activity. Analysis of 16 CD59 mutants with single, highly nonconservative substitutions suggests that CD59 has a single active site that includes Trp-40, Arg-53, and Glu-56 of the glycosylated, membrane-distal face of the disk-like extracellular domain and, possibly, Asp-24 positioned at the edge of the domain. The putative active site includes residues conserved across species, consistent with the lack of strict homologous restriction previously observed in studies of CD59 function. Competition and mutational analyses of the epitopes of eight CD59-blocking and non-blocking monoclonal antibodies confirmed the location of the active site. Additional experiments showed that the expression and function of CD59 are both glycosylation independent

Is it possible to predict improved diabetes outcomes following diabetes self-management education : a mixed-methods longitudinal design

Objective: To predict the diabetes-related outcomes of people undertaking a type 2 Diabetes Self-Management Education (DSME) programme from their baseline data. Design: A mixed-methods longitudinal experimental study. 6 practice nurses and 2 clinical academics undertook blind assessments of all baseline and process data to predict clinical, behavioural and psychological outcomes at 6 months post-DSME programme. Setting Primary care. Participants: –31 people with type 2 diabetes who had not previously undertaken DSME. Intervention: All participants undertook the Diabetes Manual 1:1 self-directed learning 12-week DSME programme supported by practice nurses trained as Diabetes Manual facilitators. Outcome variables: Glycated haemoglobin (HbA1c), diabetes knowledge, physical activity, waist circumference, self-efficacy, diabetes distress, anxiety, depression, demographics, change talk and treatment satisfaction. These variables were chosen because they are known to influence self-management behaviour or to have been influenced by a DSME programme in empirical evidence. Results: Baseline and 6-month follow-up data were available for 27 participants of which 13 (48%) were male, 22 (82%) white British, mean age 59 years and mean duration of type 2 diabetes 9.1 years. Significant reductions were found in HbA1c t(26)=2.35, p=0.03, and diabetes distress t(26)=2.30, p=0.03, and a significant increase in knowledge t(26)=−2.06, p=0.05 between baseline and 6 months. No significant changes were found in waist circumference, physical activity, anxiety, depression or self-efficacy. Accuracy of predictions varied little between clinical academics and practice nurses but greatly between outcome (0–100%). The median and mode accuracy of predicted outcome was 66.67%. Accuracy of prediction for the key outcome of HbA1c was 44.44%. Diabetes distress had the highest prediction accuracy (81.48%). Conclusions: Clinicians in this small study were unable to identify individuals likely to achieve improvement in outcomes from DSME. DSME should be promoted to all patients with diabetes according to guidelines

The effect of a livelihoods intervention in an urban slum in India: Do vocational counseling and training alter the attitudes and behavior of adolescent girls?

This Population Council working paper examines whether an experimental intervention for girls aged 14–19 that provided reproductive health information, vocational counseling and training, and assistance with opening savings accounts in slum areas of Allahabad in Uttar Pradesh, India had an effect on their attitudes and behaviors. Although the livelihoods program was acceptable to parents and feasible to implement, the project had only a minimal impact on the behavior and attitudes of adolescent girls in the experimental slums. The greatest changes between the baseline and the endline surveys were found in those outcomes that most closely reflected the content of the intervention. Girls exposed to the intervention were significantly more likely to have knowledge of safe spaces, be a member of a group, score higher on the social skills index, be informed about reproductive health, and spend time on leisure activities than were the matched control respondents. No effect was found on gender-role attitudes, mobility, self-esteem, work expectations, or on number of hours visiting friends, performing domestic chores, or engaging in labor-market work

Polyploidy breaks speciation barriers in Australian burrowing frogs Neobatrachus

Polyploidy has played an important role in evolution across the tree of life but it is still unclear how polyploid lineages may persist after their initial formation. While both common and well-studied in plants, polyploidy is rare in animals and generally less understood. The Australian burrowing frog genus Neobatrachus is comprised of six diploid and three polyploid species and offers a powerful animal polyploid model system. We generated exome-capture sequence data from 87 individuals representing all nine species of Neobatrachus to investigate species-level relationships, the origin and inheritance mode of polyploid species, and the population genomic effects of polyploidy on genus-wide demography. We describe rapid speciation of diploid Neobatrachus species and show that the three independently originated polyploid species have tetrasomic or mixed inheritance. We document higher genetic diversity in tetraploids, resulting from widespread gene flow between the tetraploids, asymmetric inter-ploidy gene flow directed from sympatric diploids to tetraploids, and isolation of diploid species from each other. We also constructed models of ecologically suitable areas for each species to investigate the impact of climate on differing ploidy levels. These models suggest substantial change in suitable areas compared to past climate, which correspond to population genomic estimates of demographic histories. We propose that Neobatrachus diploids may be suffering the early genomic impacts of climate-induced habitat loss, while tetraploids appear to be avoiding this fate, possibly due to widespread gene flow. Finally, we demonstrate that Neobatrachus is an attractive model to study the effects of ploidy on the evolution of adaptation in animals