A Population-Based Ultra-Widefield Digital Image Grading Study for Age-Related Macular Degeneration-Like Lesions at the Peripheral Retina.

Our understanding of the relevance of peripheral retinal abnormalities to disease in general and in age-related macular degeneration (AMD) in particular is limited by the lack of detailed peripheral imaging studies. The purpose of this study was to develop image grading protocols suited to ultra-widefield imaging (UWFI) in an aged population

Initial experience with the Oncotype DX assay in decision-making for adjuvant therapy of early oestrogen receptor-positive breast cancer in Hong Kong

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Methods for estimating the case fatality ratio for a novel, emerging infectious disease.

During the course of an epidemic of a potentially fatal disease, it is important that the case fatality ratio be well estimated. The authors propose a novel method for doing so based on the Kaplan-Meier survival procedure, jointly considering two outcomes (death and recovery), and evaluate its performance by using data from the 2003 epidemic of severe acute respiratory syndrome in Hong Kong, People's Republic of China. They compare this estimate obtained at various points in the epidemic with the case fatality ratio eventually observed; with two commonly quoted, naïve estimates derived from cumulative incidence and mortality statistics at single time points; and with estimates in which a parametric mixture model is used. They demonstrate the importance of patient characteristics regarding outcome by analyzing subgroups defined by age at admission to the hospital

Macular Telangiectasia Type 2: A Classification System Using MultiModal Imaging MacTel Project Report Number 10

Purpose: To develop a severity classification for macular telangiectasia type 2 (MacTel) disease using multimodal imaging. Design: An algorithm was used on data from a prospective natural history study of MacTel for classification development. Subjects: A total of 1733 participants enrolled in an international natural history study of MacTel. Methods: The Classification and Regression Trees (CART), a predictive nonparametric algorithm used in machine learning, analyzed the features of the multimodal imaging important for the development of a classification, including reading center gradings of the following digital images: stereoscopic color and red-free fundus photographs, fluorescein angiographic images, fundus autofluorescence images, and spectral-domain (SD)-OCT images. Regression models that used least square method created a decision tree using features of the ocular images into different categories of disease severity. Main Outcome Measures: The primary target of interest for the algorithm development by CART was the change in best-corrected visual acuity (BCVA) at baseline for the right and left eyes. These analyses using the algorithm were repeated for the BCVA obtained at the last study visit of the natural history study for the right and left eyes. Results: The CART analyses demonstrated 3 important features from the multimodal imaging for the classification: OCT hyper-reflectivity, pigment, and ellipsoid zone loss. By combining these 3 features (as absent, present, noncentral involvement, and central involvement of the macula), a 7-step scale was created, ranging from excellent to poor visual acuity. At grade 0, 3 features are not present. At the most severe grade, pigment and exudative neovascularization are present. To further validate the classification, using the Generalized Estimating Equation regression models, analyses for the annual relative risk of progression over a period of 5 years for vision loss and for progression along the scale were performed. Conclusions: This analysis using the data from current imaging modalities in participants followed in the MacTel natural history study informed a classification for MacTel disease severity featuring variables from SD-OCT. This classification is designed to provide better communications to other clinicians, researchers, and patients. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references

MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

Abstract Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw.http://deepblue.lib.umich.edu/bitstream/2027.42/78256/1/1471-2105-11-504.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/2/1471-2105-11-504-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/3/1471-2105-11-504-S2.ZIPhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/4/1471-2105-11-504.pdfPeer Reviewe

Evidence-based practice educational intervention studies: A systematic review of what is taught and how it is measured

Abstract Background Despite the established interest in evidence-based practice (EBP) as a core competence for clinicians, evidence for how best to teach and evaluate EBP remains weak. We sought to systematically assess coverage of the five EBP steps, review the outcome domains measured, and assess the properties of the instruments used in studies evaluating EBP educational interventions. Methods We conducted a systematic review of controlled studies (i.e. studies with a separate control group) which had investigated the effect of EBP educational interventions. We used citation analysis technique and tracked the forward and backward citations of the index articles (i.e. the systematic reviews and primary studies included in an overview of the effect of EBP teaching) using Web of Science until May 2017. We extracted information on intervention content (grouped into the five EBP steps), and the outcome domains assessed. We also searched the literature for published reliability and validity data of the EBP instruments used. Results Of 1831 records identified, 302 full-text articles were screened, and 85 included. Of these, 46 (54%) studies were randomised trials, 51 (60%) included postgraduate level participants, and 63 (75%) taught medical professionals. EBP Step 3 (critical appraisal) was the most frequently taught step (63 studies; 74%). Only 10 (12%) of the studies taught content which addressed all five EBP steps. Of the 85 studies, 52 (61%) evaluated EBP skills, 39 (46%) knowledge, 35 (41%) attitudes, 19 (22%) behaviours, 15 (18%) self-efficacy, and 7 (8%) measured reactions to EBP teaching delivery. Of the 24 instruments used in the included studies, 6 were high-quality (achieved ≥3 types of established validity evidence) and these were used in 14 (29%) of the 52 studies that measured EBP skills; 14 (41%) of the 39 studies that measured EBP knowledge; and 8 (26%) of the 35 studies that measured EBP attitude. Conclusions Most EBP educational interventions which have been evaluated in controlled studies focus on teaching only some of the EBP steps (predominantly critically appraisal of evidence) and did not use high-quality instruments to measure outcomes. Educational packages and instruments which address all EBP steps are needed to improve EBP teaching

Acute Kawasaki Disease: Not Just for Kids

Kawasaki Disease is a small-to-medium-vessel vasculitis that preferentially affects children. Kawasaki Disease can occur in adults, but the presentation may differ from that observed in children. Typical findings in both adults and children include fever, conjunctivitis, pharyngitis, and skin erythema progressing to a desquamating rash on the palms and soles. Adults more frequently present with cervical adenopathy (93% of adults vs. 15% of children), hepatitis (65% vs. 10%), and arthralgia (61% vs. 24–38%). In contrast, adults are less frequently affected by meningitis (10% vs. 34%), thrombocytosis (55% vs. 100%), and coronary artery aneurysms (5% vs. 18–25%). We report a case of acute Kawasaki Disease in a 24-year-old man who presented with rash, fever, and arthritis. He was successfully treated with high-dose aspirin and intravenous immunoglobulin (IVIG). Our case highlights the importance of considering Kawasaki Disease in adults presenting with symptoms commonly encountered in a general medical practice

Inflammatory cytokines and biofilm production sustain Staphylococcus aureus outgrowth and persistence: A pivotal interplay in the pathogenesis of Atopic Dermatitis

Individuals with Atopic dermatitis (AD) are highly susceptible to Staphylococcus aureus colonization. However, the mechanisms driving this process as well as the impact of S. aureus in AD pathogenesis are still incompletely understood. In this study, we analysed the role of biofilm in sustaining S. aureus chronic persistence and its impact on AD severity. Further we explored whether key inflammatory cytokines overexpressed in AD might provide a selective advantage to S. aureus. Results show that the strength of biofilm production by S. aureus correlated with the severity of the skin lesion, being significantly higher (P < 0.01) in patients with a more severe form of the disease as compared to those individuals with mild AD. Additionally, interleukin (IL)-β and interferon γ (IFN-γ), but not interleukin (IL)-6, induced a concentration-dependent increase of S. aureus growth. This effect was not observed with coagulase-negative staphylococci isolated from the skin of AD patients. These findings indicate that inflammatory cytokines such as IL1-β and IFN-γ, can selectively promote S. aureus outgrowth, thus subverting the composition of the healthy skin microbiome. Moreover, biofilm production by S. aureus plays a relevant role in further supporting chronic colonization and disease severity, while providing an increased tolerance to antimicrobials

Teaching Robust Argumentation Informed by the Nature of Science to Support Social Justice. Experiences from Two Projects in Lower Secondary Schools in Norway

Under embargo until: 2022-09-09This chapter suggests a set of design principles for science curricula that will enable students to produce evidence-based arguments expressing views related to their own interests. It is based on the assumption that the ability to construct evidence-based arguments strengthens students’ ability to promote their own views in the interest of social justice. This is of special importance for students not enculturated into such argumentation through their upbringing. To promote one’s own views in a debate means to critique others’ arguments, and especially to ensure one’s own arguments are resistent to criticism. Insight into the nature of science includes insights in how to construct sound arguments based on facts and research results. The discussion of design principles is based on an analysis of two science projects in two lower secondary schools in Norway (Grade 8). In the first project, students produced scientific claims based on evidence from their own practical experiments. In the second project, the students developed and applied a method for estimating energy use and carbon dioxide (CO2) emissions. The students used their findings to construct arguments related to local transport plans. The analysis focuses on challenges and successes in scaffolding students at different competence levels to successfully produce evidence-based arguments.acceptedVersio