473 research outputs found

    Many-to-One Boundary Labeling with Backbones

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    In this paper we study \emph{many-to-one boundary labeling with backbone leaders}. In this new many-to-one model, a horizontal backbone reaches out of each label into the feature-enclosing rectangle. Feature points that need to be connected to this label are linked via vertical line segments to the backbone. We present dynamic programming algorithms for label number and total leader length minimization of crossing-free backbone labelings. When crossings are allowed, we aim to obtain solutions with the minimum number of crossings. This can be achieved efficiently in the case of fixed label order, however, in the case of flexible label order we show that minimizing the number of leader crossings is NP-hard.Comment: 23 pages, 10 figures, this is the full version of a paper that is about to appear in GD'1

    CO2 laser supraglottic resurfacing for non-granulomatous chronic supraglottitis in two children

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    Chronic epiglottitis and supraglottitis are clinical entities that present with respiratory distress and are primarily associated with autoimmune disorders, gastroesophageal reflux disease, or angioedema. First described in adults with sarcoidosis in 2010, CO2 laser epiglottis resurfacing has been effective in reducing epiglottic edema. We present two cases of adolescent males with non-granulomatous chronic supraglottitis who were successfully treated with CO2 laser supraglottic resurfacing.Peer reviewe

    The Relationship Between Low Family Income and Psychological Disturbance in Young Children: An Australian Longitudinal Study

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    Objective This study examines the relationship between low family income (LFI) experienced at different points in time, chronic low income status and its impact on child behaviour measured at 5 years of age. Method Longitudinal data from the Mater University Study of Pregnancy were used to measure LFI in families at three points in time (the antenatal period, 6 months post birth and at 5 years of age). Outcome variables were three independent groups of behaviour problems labelled as externalising, social, attentional and thought (SAT) problems, and internalising problems. These groups were developed from the Child Behaviour Checklist. An analysis based on logistic regression modelling was carried out examining the relationship between LFI and a range of intermediate variables known to be associated with child behaviour problems. Results The more often families experienced low income, the higher the rate of child behaviour problems at age 5. Low family income was still independently associated with SAT behaviour problems after controlling for smoking in the first trimester, parenting styles, maternal depression and marital disharmony at age 5. The association between LFI and internalising and externalising behaviour problems was largely mediated by maternal depression. Conclusion Low family income is a significant factor in the aetiology of a variety of child behaviour problems. The mechanisms involved in the link between LFI and childhood internalising and externalising behaviours involve the exposure of the children to maternal depression. However, the relationship between LFI and SAT behaviour problems remains to be elucidated

    School achievement as a predictor of depression and self-harm in adolescence: linked education and health record study

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    BackgroundMental disorders in children and adolescents have an impact on educational attainment.AimsTo examine the temporal association between attainment in education and subsequent diagnosis of depression or self-harm in the teenage years.MethodGeneral practitioner, hospital and education records of young people in Wales between 1999 and 2014 were linked and analysed using Cox regression.ResultsLinked records were available for 652 903 young people and of these 33 498 (5.1%) developed depression and 15 946 (2.4%) self-harmed after the age of 12 but before the age of 20. Young people who developed depression over the study period were more likely to have achieved key stage 1 (age 7 years) but not key stage 2 (age 11) (hazard ratio (HR) = 0.79, 95% CI 0.74–0.84) milestones, indicating that they were declining in academic attainment during primary school. Conversely, those who self-harmed were achieving as well as those who did not self-harm in primary school, but showed a severe decline in their attainment during secondary school (HR = 0.72, 95% CI 0.68–0.78).ConclusionsLong-term declining educational attainment in primary and secondary school was associated with development of depression in the teenage years. Self-harm was associated with declining educational attainment during secondary school only. Incorporating information on academic decline with other known risk factors for depression/self-harm (for example stressful life events, parental mental health problems) may improve risk profiling methods.Declaration of interestNone

    Multi-omics subgroups associated with glycaemic deterioration in type 2 diabetes:an IMI-RHAPSODY Study

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    Introduction: Type 2 diabetes (T2D) onset, progression and outcomes differ substantially between individuals. Multi-omics analyses may allow a deeper understanding of these differences and ultimately facilitate personalised treatments. Here, in an unsupervised “bottom-up” approach, we attempt to group T2D patients based solely on -omics data generated from plasma. Methods: Circulating plasma lipidomic and proteomic data from two independent clinical cohorts, Hoorn Diabetes Care System (DCS) and Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS), were analysed using Similarity Network Fusion. The resulting patient network was analysed with Logistic and Cox regression modelling to explore relationships between plasma -omic profiles and clinical characteristics. Results: From a total of 1,134 subjects in the two cohorts, levels of 180 circulating plasma lipids and 1195 proteins were used to separate patients into two subgroups. These differed in terms of glycaemic deterioration (Hazard Ratio=0.56;0.73), insulin sensitivity and secretion (C-peptide, p=3.7e-11;2.5e-06, DCS and GoDARTS, respectively; Homeostatic model assessment 2 (HOMA2)-B; -IR; -S, p=0.0008;4.2e-11;1.1e-09, only in DCS). The main molecular signatures separating the two groups included triacylglycerols, sphingomyelin, testican-1 and interleukin 18 receptor. Conclusions: Using an unsupervised network-based fusion method on plasma lipidomics and proteomics data from two independent cohorts, we were able to identify two subgroups of T2D patients differing in terms of disease severity. The molecular signatures identified within these subgroups provide insights into disease mechanisms and possibly new prognostic markers for T2D.</p

    Moving beyond size and phosphatidylserine exposure: evidence for a diversity of apoptotic cell-derived extracellular vesicles in vitro

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    Apoptosis is a form of programmed cell death that occurs throughout life as part of normal development as well as pathologic processes including chronic inflammation and infection. Although the death of a cell is often considered as the only biological outcome of a cell committed to apoptosis, it is becoming increasingly clear that the dying cell can actively communicate with other cells via soluble factors as well as membrane-bound extracellular vesicles (EVs) to regulate processes including cell clearance, immunity and tissue repair. Compared to EVs generated from viable cells such as exosomes and microvesicles, apoptotic cell-derived EVs (ApoEVs) are less well defined and the basic criteria for ApoEV characterization have not been established in the field. In this study, we will examine the current understanding of ApoEVs, in particular, the ApoEV subtype called apoptotic bodies (ApoBDs). We described that a subset of ApoBDs can be larger than 5 μm and smaller than 1 μm based on flow cytometry and live time-lapse microscopy analysis, respectively. We also described that a subset of ApoBDs can expose a relatively low level of phosphatidylserine on its surface based on annexin A5 staining. Furthermore, we characterized the presence of caspase-cleaved proteins (in particular plasma membrane-associated or cytoplasmic proteins) in samples enriched in ApoBDs. Lastly, using a combination of biochemical-, live imaging- and flow cytometry-based approaches, we characterized the progressive lysis of ApoBDs. Taken together, these results extended our understanding of ApoBDs

    Multi-omics subgroups associated with glycaemic deterioration in type 2 diabetes:an IMI-RHAPSODY Study

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    Introduction: Type 2 diabetes (T2D) onset, progression and outcomes differ substantially between individuals. Multi-omics analyses may allow a deeper understanding of these differences and ultimately facilitate personalised treatments. Here, in an unsupervised “bottom-up” approach, we attempt to group T2D patients based solely on -omics data generated from plasma. Methods: Circulating plasma lipidomic and proteomic data from two independent clinical cohorts, Hoorn Diabetes Care System (DCS) and Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS), were analysed using Similarity Network Fusion. The resulting patient network was analysed with Logistic and Cox regression modelling to explore relationships between plasma -omic profiles and clinical characteristics. Results: From a total of 1,134 subjects in the two cohorts, levels of 180 circulating plasma lipids and 1195 proteins were used to separate patients into two subgroups. These differed in terms of glycaemic deterioration (Hazard Ratio=0.56;0.73), insulin sensitivity and secretion (C-peptide, p=3.7e-11;2.5e-06, DCS and GoDARTS, respectively; Homeostatic model assessment 2 (HOMA2)-B; -IR; -S, p=0.0008;4.2e-11;1.1e-09, only in DCS). The main molecular signatures separating the two groups included triacylglycerols, sphingomyelin, testican-1 and interleukin 18 receptor. Conclusions: Using an unsupervised network-based fusion method on plasma lipidomics and proteomics data from two independent cohorts, we were able to identify two subgroups of T2D patients differing in terms of disease severity. The molecular signatures identified within these subgroups provide insights into disease mechanisms and possibly new prognostic markers for T2D.</p
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