EczemaNet: automating detection and severity assessment of atopic dermatitis

Atopic dermatitis (AD), also known as eczema, is one of themost common chronic skin diseases. AD severity is primarily evaluatedbased on visual inspections by clinicians, but is subjective and has largeinter- and intra-observer variability in many clinical study settings. Toaid the standardisation and automating the evaluation of AD severity,this paper introduces a CNN computer vision pipeline, EczemaNet, thatfirst detects areas of AD from photographs and then makes probabilisticpredictions on the severity of the disease. EczemaNet combines trans-fer and multitask learning, ordinal classification, and ensembling overcrops to make its final predictions. We test EczemaNet using a set of im-ages acquired in a published clinical trial, and demonstrate low RMSEwith well-calibrated prediction intervals. We show the effectiveness of us-ing CNNs for non-neoplastic dermatological diseases with a medium-sizedataset, and their potential for more efficiently and objectively evaluatingAD severity, which has greater clinical relevance than mere classification

State Transition Algorithm

In terms of the concepts of state and state transition, a new heuristic random search algorithm named state transition algorithm is proposed. For continuous function optimization problems, four special transformation operators called rotation, translation, expansion and axesion are designed. Adjusting measures of the transformations are mainly studied to keep the balance of exploration and exploitation. Convergence analysis is also discussed about the algorithm based on random search theory. In the meanwhile, to strengthen the search ability in high dimensional space, communication strategy is introduced into the basic algorithm and intermittent exchange is presented to prevent premature convergence. Finally, experiments are carried out for the algorithms. With 10 common benchmark unconstrained continuous functions used to test the performance, the results show that state transition algorithms are promising algorithms due to their good global search capability and convergence property when compared with some popular algorithms.Comment: 18 pages, 28 figure

A new method for 2D gel spot alignment: application to the analysis of large sample sets in clinical proteomics

<p>Abstract</p> <p>Background</p> <p>In current comparative proteomics studies, the large number of images generated by 2D gels is currently compared using spot matching algorithms. Unfortunately, differences in gel migration and sample variability make efficient spot alignment very difficult to obtain, and, as consequence most of the software alignments return noisy gel matching which needs to be manually adjusted by the user.</p> <p>Results</p> <p>We present Sili2DGel an algorithm for automatic spot alignment that uses data from recursive gel matching and returns meaningful Spot Alignment Positions (SAP) for a given set of gels. In the algorithm, the data are represented by a graph and SAP by specific subgraphs. The results are returned under various forms (clickable synthetic gel, text file, etc.). We have applied Sili2DGel to study the variability of the urinary proteome from 20 healthy subjects.</p> <p>Conclusion</p> <p>Sili2DGel performs noiseless automatic spot alignment for variability studies (as well as classical differential expression studies) of biological samples. It is very useful for typical clinical proteomic studies with large number of experiments.</p

Comparing nuclear power trajectories in Germany and the UK: from ‘regimes' to ‘democracies’ in sociotechnical transitions and Discontinuities

This paper focuses on arguably the single most striking contrast in contemporary major energy politics in Europe (and even the developed world as a whole): the starkly differing civil nuclear policies of Germany and the UK. Germany is seeking entirely to phase out nuclear power by 2022. Yet the UK advocates a ‘nuclear renaissance’, promoting the most ambitious new nuclear construction programme in Western Europe.Here,this paper poses a simple yet quite fundamental question: what are the particular divergent conditions most strongly implicated in the contrasting developments in these two countries. With nuclear playing such an iconic role in historical discussions over technological continuity and transformation, answering this may assist in wider understandings of sociotechnical incumbency and discontinuity in the burgeoning field of‘sustainability transitions’. To this end, an ‘abductive’ approach is taken: deploying nine potentially relevant criteria for understanding the different directions pursued in Germany and the UK. Together constituted by 30 parameters spanning literatures related to socio-technical regimes in general as well as nuclear technology in particular, the criteria are divided into those that are ‘internal’ and ‘external’ to the ‘focal regime configuration’ of nuclear power and associated ‘challenger technologies’ like renewables. It is ‘internal’ criteria that are emphasised in conventional sociotechnical regime theory, with ‘external’ criteria relatively less well explored. Asking under each criterion whether attempted discontinuation of nuclear power would be more likely in Germany or the UK, a clear picture emerges. ‘Internal’ criteria suggest attempted nuclear discontinuation should be more likely in the UK than in Germany– the reverse of what is occurring. ‘External’ criteria are more aligned with observed dynamics –especially those relating to military nuclear commitments and broader ‘qualities of democracy’. Despite many differences of framing concerning exactly what constitutes ‘democracy’, a rich political science literature on this point is unanimous in characterising Germany more positively than the UK. Although based only on a single case,a potentially important question is nonetheless raised as to whether sociotechnical regime theory might usefully give greater attention to the general importance of various aspects of democracy in constituting conditions for significant technological discontinuities and transformations. If so, the policy implications are significant. A number of important areas are identified for future research, including the roles of diverse understandings and specific aspects of democracy and the particular relevance of military nuclear commitments– whose under-discussion in civil nuclear policy literatures raises its own questions of democratic accountability

Massive rotator cuff tears: functional outcome after debridement or arthroscopic partial repair

Background The surgical treatment of massive rotator cuff tears (RCT) is still controversial and can be based on a variety of different surgical repair methods. This study investigated the effectiveness of arthroscopic debridement or arthroscopic partial repair in patients with massive RCT. Materials and methods This prospective, randomized study involved forty-two patients with massive RCT (fatty infiltration stage 3 or 4) treated with either arthroscopic partial repair or arthroscopic debridement were selected to detect possible differences in functional outcome. Both groups were matched according to age and gender. Patients were examined before, and 16 ± 3 and 24 ± 2 months after surgery. The status of the rotator cuff repair was determined using ultrasonographic evaluation. Results Regardless of the treatment group, postoperative results demonstrated highly significant improvements compared with preoperative values in most parameters. The overall Constant score in the partial repair group was superior to the outcome in the debridement group (P \ 0.01, F = 8.561), according to better results in abductio

2′-O Methylation of the Viral mRNA Cap by West Nile Virus Evades Ifit1-Dependent and -Independent Mechanisms of Host Restriction In Vivo

Prior studies have shown that 2′-O methyltransferase activity of flaviviruses, coronaviruses, and poxviruses promotes viral evasion of Ifit1, an interferon-stimulated innate immune effector protein. Viruses lacking 2′-O methyltransferase activity exhibited attenuation in primary macrophages that was rescued in cells lacking Ifit1 gene expression. Here, we examined the role of Ifit1 in restricting pathogenesis in vivo of wild type WNV (WNV-WT) and a mutant in the NS5 gene (WNV-E218A) lacking 2′-O methylation of the 5′ viral RNA cap. While deletion of Ifit1 had marginal effects on WNV-WT pathogenesis, WNV-E218A showed increased replication in peripheral tissues of Ifit1−/− mice after subcutaneous infection, yet this failed to correlate with enhanced infection in the brain or lethality. In comparison, WNV-E218A was virulent after intracranial infection as judged by increased infection in different regions of the central nervous system (CNS) and a greater than 16,000-fold decrease in LD50 values in Ifit1−/− compared to wild type mice. Ex vivo infection experiments revealed cell-type specific differences in the ability of an Ifit1 deficiency to complement the replication defect of WNV-E218A. In particular, WNV-E218A infection was impaired in both wild type and Ifit1−/− brain microvascular endothelial cells, which are believed to participate in blood-brain barrier (BBB) regulation of virus entry into the CNS. A deficiency of Ifit1 also was associated with increased neuronal death in vivo, which was both cell-intrinsic and mediated by immunopathogenic CD8+ T cells. Our results suggest that virulent strains of WNV have largely evaded the antiviral effects of Ifit1, and viral mutants lacking 2′-O methylation are controlled in vivo by Ifit1-dependent and -independent mechanisms in different cell types

The state of the art in the analysis of two-dimensional gel electrophoresis images

Software-based image analysis is a crucial step in the biological interpretation of two-dimensional gel electrophoresis experiments. Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments. We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results. Challenges for analysis software as well as good practices are highlighted. We emphasize image warping and related methods that are able to overcome the difficulties that are due to varying migration positions of spots between gels. Spot detection, quantitation, normalization, and the creation of expression profiles are described in detail. The recent development of consensus spot patterns and complete expression profiles enables one to take full advantage of statistical methods for expression analysis that are well established for the analysis of DNA microarray experiments. We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field