How do patients with end-stage ankle arthritis decide between two surgical treatments?:A qualitative study

To examine how patients decide between ankle fusion and ankle replacement in end-stage ankle arthritis

Diagnosis of periarticular osteoporosis in rheumatoid arthritis using digital X-ray radiogrammetry

Osteoporosis can manifest in two ways in rheumatoid arthritis: generalized bone loss, which may result from immobility, the inflammatory process per se and/or treatments such as steroids; and periarticular demineralization, which is probably due to local release of inflammatory agents. Digital X-ray radiogrammetry (DXR) is an effective and sensitive modality for monitoring periarticular osteoporosis, which is among the earliest features of rheumatoid arthritis, preceding bone erosions. DXR is a promising technique, which can provide quantitative data that allow early diagnosis. During the course of rheumatoid arthritis it can be deployed in combination with established X-ray scoring methods to inform decisions regarding the optimal therapy to prevent joint destruction

Mammary Tumor Microenvironment Reprogramming in Response to Pyruvate Carboxylase Modulation

Breast cancer is the deadliest cancer amongst women globally, with metastatic breast cancer being particularly deadly. Pyruvate carboxylase (PC) catalyzes the conversion of pyruvate to oxaloacetate for anaplerotic refilling of TCA cycle intermediates, feeding numerous energetic and biosynthetic pathways. Upregulation of PC is an important contributor to metabolic reprogramming and aggressiveness in metastatic breast cancer. Less understood, however, is the effects of PC expression on metabolic reprogramming and the TME in primary tumors. In this study, we investigate whether suppression of PC alters metabolism and drives microenvironmental adaptation in a primary tumor model of breast cancer. PC knockdown resulted in increased lactate production with a decrease in mitochondrial respiration, suggesting that diminished PC-mediated anaplerosis alters carbon utilization and contributes to metabolic reprogramming. Suppression of PC also resulted in tumors with distinct transcriptomic profiles versus control, with signatures of immune responses diminished in response to loss of PC. As lactate is a profound immunosuppressive signaling molecule in the TME, it may be a driver of TME immunosuppression in response to PC suppression. We conclude that PC knockdown promotes a metabolically altered tumor microenvironment associated with immunosuppression and tumor growth.Bachelor of Scienc

OPENSENSEMAP - A Citizen Science Platform For Publishing And Exploring Sensor Data as Open Data

A plethora of citizen science sensor platforms for dierent use-cases already exist. They provide cheap, precongured, plug and playable hardware and software solutions. Using data from multiple platforms and resources can be a challenging task in respect of discovering, exploring, downloading and converting. This work aims to implement a one-stop-shop for sensor data that tries to tackle these problems. Therefore a basic data schema capable of metadata is established that allows publishing generic sensor platforms and sensor data. For exploration a web platform is implemented based on common web standards. This work describes the requirements, design and implementation of the OpenSenseMap. OpenSenseMap is following the clientserver model and its complete application stack is implemented in JavaScript. It describes the basic components and the underlying data model. All components are using open-source technology and are published under an opensource license too. The RESTful service is the heart of OpenSenseMap and implements the data publish and data retrieval functions. Developers may use it to build custom applications around OpenSenseMap or integrate OpenSenseMap into existing projects. The NodeJS application runs its own web server and implements the different HTTP request types. The OpenSenseMap concept is being evaluated with a technical and a user survey

Pyruvate Carboxylase Expression Modulates Primary Mammary Tumor Growth and Central Carbon Metabolism

Metabolic reprogramming is a fundamental requirement for triple-negative breast cancer’s (TNBC) growth and progression, with pyruvate carboxylase (PC) identified as a key mediator of breast cancer metastasis to the lung. Less is known, however, of PC’s role at the primary site. This study thus aimed to investigate the impact of PC suppression on primary tumor growth and if PC expression could inform the use of targeted metabolic therapies to augment currently used treatments for TNBC. Two separate PC knockdown cell lines revealed PC suppression to drive both a pro-tumor and anti-tumor effect, revealing a complex relationship between PC expression and tumor growth. PC suppressed M-Wnt cells in culture produced more lactate and had reduced rates of oxidative phosphorylation, rendering them more sensitive to lactate metabolism inhibition. This study highlights a dichotomous role for PC at the primary site that warrants additional investigation into utilizing PC to inform metabolic-based therapies.Master of Scienc

Efficient Processing of Spatio-Temporal Data Streams With Spiking Neural Networks

Kugele A, Pfeil T, Pfeiffer M, Chicca E. Efficient Processing of Spatio-Temporal Data Streams With Spiking Neural Networks. Frontiers in Neuroscience. 2020;14: 439.Spiking neural networks (SNNs) are potentially highly efficient models for inference on fully parallel neuromorphic hardware, but existing training methods that convert conventional artificial neural networks (ANNs) into SNNs are unable to exploit these advantages. Although ANN-to-SNN conversion has achieved state-of-the-art accuracy for static image classification tasks, the following subtle but important difference in the way SNNs and ANNs integrate information over time makes the direct application of conversion techniques for sequence processing tasks challenging. Whereas all connections in SNNs have a certain propagation delay larger than zero, ANNs assign different roles to feed-forward connections, which immediately update all neurons within the same time step, and recurrent connections, which have to be rolled out in time and are typically assigned a delay of one time step. Here, we present a novel method to obtain highly accurate SNNs for sequence processing by modifying the ANN training before conversion, such that delays induced by ANN rollouts match the propagation delays in the targeted SNN implementation. Our method builds on the recently introduced framework of streaming rollouts, which aims for fully parallel model execution of ANNs and inherently allows for temporal integration by merging paths of different delays between input and output of the network. The resulting networks achieve state-of-the-art accuracy for multiple event-based benchmark datasets, including N-MNIST, CIFAR10-DVS, N-CARS, and DvsGesture, and through the use of spatio-temporal shortcut connections yield low-latency approximate network responses that improve over time as more of the input sequence is processed. In addition, our converted SNNs are consistently more energy-efficient than their corresponding ANNs

The Treatment of Giant Cell Arteritis in Different Clinical Settings

This paper aims to raise awareness of the different disease courses, comorbidities, and therapy situations in patients with giant cell arteritis (GCA), which require a differentiated approach and often a deviation from current treatment guidelines. With the approval of tocilizumab (TOC), which specifically binds to both soluble and membrane-bound IL-6 receptor and inhibits IL-6 receptor-mediated signaling, the spectrum of available effective treatment options has been significantly broadened. TOC yields an extensive range of possible applications that go beyond a glucocorticoid-saving effect. In this context, the treatment of GCA is dependent on the disease course as well as the associated comorbidities. The different stages of GCA in association to co-morbidities require a detailed treatment strategy

Reliability of a risk-factor questionnaire for osteoporosis: a primary care survey study with dual energy x-ray absorptiometry ground truth

(1) Purpose: Predisposing factors to osteoporosis (OP) as well as dual-source x-ray densitometry (DXA) steer therapeutic decisions by determining the FRAX index. This study examines the reliability of a standard risk factor questionnaire in OP-screening. (2) Methods: n = 553 eligible questionnaires encompassed 24 OP-predisposing factors. Reliability was assessed using DXA as a gold standard. Multiple logistic regression and Spearman’s correlations, as well as the confounding influence of age and body mass index, were analyzed in SPSS (IBM Corporation, Armonk, NY, USA). (3) Results: Our study revealed low patient self-awareness regarding OP and its risk factors. One out of every four patients reported a positive history for osteoporosis not confirmed by DXA. The extraordinarily high incidence of rheumatoid arthritis and thyroid disorders likely reflect confusion with other diseases or health anxiety. FRAX-determining risk factors such as malnutrition, liver insufficiency, prior fracture without trauma, and glucocorticoid therapy did not correlate with increased OP incidence, altogether demonstrating how inaccurate survey information could influence therapeutic decisions on osteoporosis. (4) Conclusions: Contradictive results and a low level of patient self-awareness suggest a high degree of uncertainty and low reliability of the current OP risk factor survey

Diagnosing lung involvement in inflammatory rheumatic diseases—Where do we currently stand?

Lung involvement is the most common and serious organ manifestation in patients with inflammatory rheumatic disease (IRD). The type of pulmonary involvement can differ, but the most frequent is interstitial lung disease (ILD). The clinical manifestations of IRD-ILD and severity can vary from subclinical abnormality to dyspnea, respiratory failure, and death. Consequently, early detection is of significant importance. Pulmonary function test (PFT) including diffusing capacity of the lungs for carbon monoxide (DLCO), and forced vital capacity (FVC) as well as high-resolution computed tomography (HRCT) are the standard tools for screening and monitoring of ILD in IRD-patients. Especially, the diagnostic accuracy of HRCT is considered to be high. Magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) allow both morphological and functional assessment of the lungs. In addition, biomarkers (e.g., KL-6, CCL2 , or MUC5B) are being currently evaluated for the detection and prognostic assessment of ILD. Despite the accuracy of HRCT, invasive diagnostic methods such as bronchoalveolar lavage (BAL) and lung biopsy are still important in clinical practice. However, their therapeutic and prognostic relevance remains unclear. The aim of this review is to give an overview of the individual methods and to present their respective advantages and disadvantages in detecting and monitoring ILD in IRD-patients in the clinical routine