Vitamin C as a Potential Prophylactic Measure Against Frozen Shoulder in an In Vivo Shoulder Contracture Animal Model

BACKGROUND Frozen shoulder is a common, painful, and movement-restricting condition. Although primary frozen shoulder is idiopathic, secondary frozen shoulder can occur after trauma or surgery. Prophylactic and therapeutic options are often unsatisfactory. Vitamin C (ascorbic acid) is a potent physiological antioxidant and likely inhibits the activation of nuclear factor κB, which plays a decisive role in inflammatory reactions. HYPOTHESIS Because of its anti-inflammatory effects, vitamin C may be valuable in the prevention of secondary frozen shoulder. STUDY DESIGN Controlled laboratory study. METHODS An in vivo shoulder contracture model was conducted by fixation of the right proximal limb of Sprague-Dawley rats. A treatment group (n = 8) receiving vitamin C orally was compared with a control group (n = 9) without vitamin C. The primary outcome was capsular thickness at the shoulder joint measured on magnetic resonance imaging (MRI) examination. Further histological examination was performed but was not statistically analyzed because of variability of the cutting plane through the glenoid. RESULTS Vitamin C treatment resulted in less thickening of the axillary fold of the operated shoulder at 2 of the 3 locations measured on MRI compared with untreated controls (insertion to the glenoid, P = .074; insertion to the humerus, P = .006; middle of the axillary recess, P = .008). The observed structural changes in histological examination corroborated the significant changes obtained from the MRI measurements. CONCLUSION Prophylactic vitamin C seemed to reduce the thickening of the axillary recess in secondary frozen shoulder in this preclinical study. CLINICAL RELEVANCE Vitamin C may be helpful as a noninvasive therapeutic measure to prevent secondary frozen shoulder (eg, within the context of surgery in the shoulder region or immobilization) or to treat primary frozen shoulder at an early stage. Further studies are required to evaluate the effect of this treatment in humans and the necessary dosage in humans

An artificial intelligence algorithm is highly accurate for detecting endoscopic features of eosinophilic esophagitis

The endoscopic features associated with eosinophilic esophagitis (EoE) may be missed during routine endoscopy. We aimed to develop and evaluate an Artificial Intelligence (AI) algorithm for detecting and quantifying the endoscopic features of EoE in white light images, supplemented by the EoE Endoscopic Reference Score (EREFS). An AI algorithm (AI-EoE) was constructed and trained to differentiate between EoE and normal esophagus using endoscopic white light images extracted from the database of the University Hospital Augsburg. In addition to binary classification, a second algorithm was trained with specific auxiliary branches for each EREFS feature (AI-EoE-EREFS). The AI algorithms were evaluated on an external data set from the University of North Carolina, Chapel Hill (UNC), and compared with the performance of human endoscopists with varying levels of experience. The overall sensitivity, specificity, and accuracy of AI-EoE were 0.93 for all measures, while the AUC was 0.986. With additional auxiliary branches for the EREFS categories, the AI algorithm (AI-EoE-EREFS) performance improved to 0.96, 0.94, 0.95, and 0.992 for sensitivity, specificity, accuracy, and AUC, respectively. AI-EoE and AI-EoE-EREFS performed significantly better than endoscopy beginners and senior fellows on the same set of images. An AI algorithm can be trained to detect and quantify endoscopic features of EoE with excellent performance scores. The addition of the EREFS criteria improved the performance of the AI algorithm, which performed significantly better than endoscopists with a lower or medium experience level

Detection of duodenal villous atrophy on endoscopic images using a deep learning algorithm

Background and aims Celiac disease with its endoscopic manifestation of villous atrophy is underdiagnosed worldwide. The application of artificial intelligence (AI) for the macroscopic detection of villous atrophy at routine esophagogastroduodenoscopy may improve diagnostic performance. Methods A dataset of 858 endoscopic images of 182 patients with villous atrophy and 846 images from 323 patients with normal duodenal mucosa was collected and used to train a ResNet 18 deep learning model to detect villous atrophy. An external data set was used to test the algorithm, in addition to six fellows and four board certified gastroenterologists. Fellows could consult the AI algorithm’s result during the test. From their consultation distribution, a stratification of test images into “easy” and “difficult” was performed and used for classified performance measurement. Results External validation of the AI algorithm yielded values of 90 %, 76 %, and 84 % for sensitivity, specificity, and accuracy, respectively. Fellows scored values of 63 %, 72 % and 67 %, while the corresponding values in experts were 72 %, 69 % and 71 %, respectively. AI consultation significantly improved all trainee performance statistics. While fellows and experts showed significantly lower performance for “difficult” images, the performance of the AI algorithm was stable. Conclusion In this study, an AI algorithm outperformed endoscopy fellows and experts in the detection of villous atrophy on endoscopic still images. AI decision support significantly improved the performance of non-expert endoscopists. The stable performance on “difficult” images suggests a further positive add-on effect in challenging cases

Exploitation of the Timing Capabilities of Metallic Magnetic Calorimeters for a Coincidence Measurement Scheme

In this report, we compare two filter algorithms for extracting timing information using novel metallic magnetic calorimeter detectors, applied to the precision X-ray spectroscopy of highly charged ions in a storage ring. Accurate timing information is crucial when exploiting coincidence conditions for background suppression to obtain clean spectra. For X-rays emitted by charge-changing interactions between ions and a target, this is a well-established technique when relying on conventional semiconductor detectors that offer a good temporal resolution. However, until recently, such a coincidence scheme had never been realized with metallic magnetic calorimeters, which typically feature much longer signal rise times. In this report, we present optimized timing filter algorithms for this type of detector. Their application to experimental data recently obtained at the electron cooler of CRYRING@ESR at GSI, Darmstadt is discussed

ICT for Sustainability — Current and future research directions

This workshop brings together researchers from the entire iSchools community to propose, share and discuss their current research and future research agendas and foster collaborations on ICT for Sustainability. ICT plays a major role in sustainability. It threatens sustainability as ICT devices cause carbon emissions, produce e-waste, but it can also be an enabler of sustainability, in form of systems that support the protection of natural resources, and that foster social sustainability, in the form of systems that foster communities and participation. These supporting systems come from many intellectual traditions within and beyond the information field and design. The iSchools community provides an excellent place to discuss this crucial topic at the intersection of information, society, and technology. This workshop will bring together scholars from across the information field studying ICT for sustainability, to foster new interdisciplinary and multidisciplinary collaborations.ye

Major flaws in conflict prevention policies towards Africa : the conceptual deficits of international actors’ approaches and how to overcome them

Current thinking on African conflicts suffers from misinterpretations oversimplification, lack of focus, lack of conceptual clarity, state-centrism and lack of vision). The paper analyses a variety of the dominant explanations of major international actors and donors, showing how these frequently do not distinguish with sufficient clarity between the ‘root causes’ of a conflict, its aggravating factors and its triggers. Specifically, a correct assessment of conflict prolonging (or sustaining) factors is of vital importance in Africa’s lingering confrontations. Broader approaches (e.g. “structural stability”) offer a better analytical framework than familiar one-dimensional explanations. Moreover, for explaining and dealing with violent conflicts a shift of attention from the nation-state towards the local and sub-regional level is needed.Aktuelle Analysen afrikanischer Gewaltkonflikte sind häufig voller Fehlinterpretationen (Mangel an Differenzierung, Genauigkeit und konzeptioneller Klarheit, Staatszentriertheit, fehlende mittelfristige Zielvorstellungen). Breitere Ansätze (z. B. das Modell der Strukturellen Stabilität) könnten die Grundlage für bessere Analyseraster und Politiken sein als eindimensionale Erklärungen. häufig differenzieren Erklärungsansätze nicht mit ausreichender Klarheit zwischen Ursachen, verschärfenden und auslösenden Faktoren. Insbesondere die richtige Einordnung konfliktverlängernder Faktoren ist in den jahrzehntelangen gewaltsamen Auseinandersetzungen in Afrika von zentraler Bedeutung. Das Diskussionspapier stellt die große Variationsbreite dominanter Erklärungsmuster der wichtigsten internationalen Geber und Akteure gegenüber und fordert einen Perspektivenwechsel zum Einbezug der lokalen und der subregionalen Ebene für die Erklärung und Bearbeitung gewaltsamer Konflikte

Rhea—a manually curated resource of biochemical reactions

Rhea (http://www.ebi.ac.uk/rhea) is a comprehensive resource of expert-curated biochemical reactions. Rhea provides a non-redundant set of chemical transformations for use in a broad spectrum of applications, including metabolic network reconstruction and pathway inference. Rhea includes enzyme-catalyzed reactions (covering the IUBMB Enzyme Nomenclature list), transport reactions and spontaneously occurring reactions. Rhea reactions are described using chemical species from the Chemical Entities of Biological Interest ontology (ChEBI) and are stoichiometrically balanced for mass and charge. They are extensively manually curated with links to source literature and other public resources on metabolism including enzyme and pathway databases. This cross-referencing facilitates the mapping and reconciliation of common reactions and compounds between distinct resources, which is a common first step in the reconstruction of genome scale metabolic networks and models

The Electron Capture in 163^{163} Ho Experiment - a Short Update

The definition of the absolute neutrino mass scale is one of the main goals of the Particle Physics today. The study of the end-point regions of the β- and electron capture (EC) spectrum offers a possibility to determine the effective electron (anti-)neutrino mass in a completely model independent way, as it only relies on the energy and momentum conservation. The ECHo (Electron Capture in 163Ho) experiment has been designed in the attempt to measure the effective mass of the electron neutrino by performing high statistics and high energy resolution measurements of the 163 Ho electron capture spectrum. To achieve this goal, large arrays of low temperature metallic magnetic calorimeters (MMCs) implanted with with 163Ho are used. Here we report on the structure and the status of the experiment