How Machines are Serviced - Design of a Virtual Reality-based Training System for Technical Customer Services

Training service provider is a crucial factor for high-quality service delivery. Due to the rise of new devices, reviving Virtual Reality (VR) offer great opportunities to overcome current training challenges. As various new interaction and visualization systems push into market, guidance on how to design VR-based training systems is necessary. The presented use case is based on technicians in technical customer services (TCS) who tackle increasing complexity of machines. We fill the research gap of design knowledge by (1) analyzing the domain in a multi-method approach to elicit meta-requirements, (2) proposing design principles, and (3) instantiating them in a prototype. The interaction of the user with the training system was identified as key aspect to foster learning. We follow a design science research approach (DSR) combing the build-phase with agile evaluation cycles obtaining focus groups and demonstration with a prototype

Expression of the Phosphatase Ppef2 Controls Survival and Function of CD8+ Dendritic Cells

Apoptotic cell death of Dendritic cells (DCs) is critical for immune homeostasis. Although intrinsic mechanisms controlling DC death have not been fully characterized up to now, experimentally enforced inhibition of DC-death causes various autoimmune diseases in model systems. We have generated mice deficient for Protein Phosphatase with EF-Hands 2 (Ppef2), which is selectively expressed in CD8+ DCs, but not in other related DC subtypes such as tissue CD103+ DCs. Ppef2 is down-regulated rapidly upon maturation of DCs by toll-like receptor stimuli, but not upon triggering of CD40. Ppef2-deficient CD8+ DCs accumulate the pro-apoptotic Bcl-2-like protein 11 (Bim) and show increased apoptosis and reduced competitve repopulation capacities. Furthermore, Ppef2−/− CD8+ DCs have strongly diminished antigen presentation capacities in vivo, as CD8+ T cells primed by Ppef2−/− CD8+ DCs undergo reduced expansion. In conclusion, our data suggests that Ppef2 is crucial to support survival of immature CD8+ DCs, while Ppef2 down-regulation during DC-maturation limits T cell responses

Biomarkers of Neurodegeneration in Autoimmune-Mediated Encephalitis.

Progranulin (PGRN), Total-Tau (t-tau), and Neurofilament light chain (NfL) are well known biomarkers of neurodegeneration. The objective of the present study was to investigate whether these parameters represent also biomarkers in autoimmune-mediated Encephalitis (AE) and may give us insights into the pathomechanisms of AE. We retrospectively examined the concentration of PGRN in the cerebrospinal fluid (CSF) and serum of 38 patients suffering from AE in acute phase and/or under treatment. This AE cohort comprises patients with autoantibodies against: NMDAR (n = 18 patients), Caspr2 (n = 8), Lgi-1 (n = 10), GABAB(R) (n = 1), and AMPAR (n = 1). Additionally, the concentrations of NfL (n = 25) and t-tau (n = 13) in CSF were measured when possible. Follow up data including MRI were available in 13 patients. Several age-matched cohorts with neurological diseases besides neuroinflammation or neurodegeneration served as control groups. We observed that PGRN was significantly elevated in the CSF of patients with NMDAR-AE in the acute phase, but normalized at follow up under treatment (p < 0.01). In the CSF of other patients with AE PGRN was in the range of the CSF levels of control groups. T-tau was highly elevated in the CSF of patients with temporal FLAIR-signal in the MRI and in patients developing a hippocampal sclerosis. NfL was exceptionally high initially in Patients with AE with a paraneoplastic or parainfectious cause and also normalized under treatment. The normalizations of all biomarkers were mirrored in an improvement on the modified Rankin scale. The data suggest that the concentration of PGRN in CSF might be a biomarker for acute NMDAR-AE. Pathological high t-tau levels may indicate a risk for hippocampal sclerosis. The biomarker properties of NfL remain unclear since the levels decrease under treatment, but it could not predict severity of disease in this small cohort. According to our results, we recommend to measure in clinical practice PGRN and t-tau in the CSF of patients with AE

Biomarkers of Neurodegeneration in Autoimmune-Mediated Encephalitis

Progranulin (PGRN), Total-Tau (t-tau), and Neurofilament light chain (NfL) are well known biomarkers of neurodegeneration. The objective of the present study was to investigate whether these parameters represent also biomarkers in autoimmune-mediated Encephalitis (AE) and may give us insights into the pathomechanisms of AE. We retrospectively examined the concentration of PGRN in the cerebrospinal fluid (CSF) and serum of 38 patients suffering from AE in acute phase and/or under treatment. This AE cohort comprises patients with autoantibodies against: NMDAR (n = 18 patients), Caspr2 (n = 8), Lgi-1 (n = 10), GABAB(R) (n = 1), and AMPAR (n = 1). Additionally, the concentrations of NfL (n = 25) and t-tau (n = 13) in CSF were measured when possible. Follow up data including MRI were available in 13 patients. Several age-matched cohorts with neurological diseases besides neuroinflammation or neurodegeneration served as control groups. We observed that PGRN was significantly elevated in the CSF of patients with NMDAR-AE in the acute phase, but normalized at follow up under treatment (p &lt; 0.01). In the CSF of other patients with AE PGRN was in the range of the CSF levels of control groups. T-tau was highly elevated in the CSF of patients with temporal FLAIR-signal in the MRI and in patients developing a hippocampal sclerosis. NfL was exceptionally high initially in Patients with AE with a paraneoplastic or parainfectious cause and also normalized under treatment. The normalizations of all biomarkers were mirrored in an improvement on the modified Rankin scale. The data suggest that the concentration of PGRN in CSF might be a biomarker for acute NMDAR-AE. Pathological high t-tau levels may indicate a risk for hippocampal sclerosis. The biomarker properties of NfL remain unclear since the levels decrease under treatment, but it could not predict severity of disease in this small cohort. According to our results, we recommend to measure in clinical practice PGRN and t-tau in the CSF of patients with AE

Swarm Learning for decentralized and confidential clinical machine learning

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine

Panel: Digital Work Futures: Preserving Human Distinctiveness and Value?

This panel took place during ECIS 2021 on June 14, 2021. The topic of the panel is Digital Work Futures: Preserving Human Distinctiveness and Value?

Combination of alcohol and fructose exacerbates metabolic imbalance in terms of hepatic damage, dyslipidemia, and insulin resistance in rats.

Although both alcohol and fructose are particularly steatogenic, their long-term effect in the development of a metabolic syndrome has not been studied in vivo. Consumption of fructose generally leads to obesity, whereas ethanol can induce liver damage in the absence of overweight. Here, Sprague-Dawley rats were fed ad libitum for 28 days on five diets: chow (control), liquid Lieber-DeCarli (LDC) diet, LDC +30%J of ethanol (L-Et) or fructose (L-Fr), and LDC combined with 30%J ethanol and 30%J fructose (L-EF). Body weight (BW) and liver weight (LW) were measured. Blood and liver samples were harvested and subjected to biochemical tests, histopathological examinations, and RT-PCR. Alcohol-containing diets substantially reduced the food intake and BW (≤3rd week), whereas fructose-fed animals had higher LW than controls (P<0.05). Additionally, leukocytes, plasma AST and leptin levels were the highest in the fructose-administered rats. Compared to the chow and LDC diets, the L-EF diet significantly elevated blood glucose, insulin, and total-cholesterol levels (also vs. the L-Et group). The albumin and Quick-test levels were the lowest, whereas ALT activity was the highest in the L-EF group. Moreover, the L-EF diet aggravated plasma triglyceride and reduced HDL-cholesterol levels more than 2.7-fold compared to the sum of the effects of the L-Et and L-Fr diets. The decreased hepatic insulin clearance in the L-EF group vs. control and LDC groups was reflected by a significantly decreased C-peptide:insulin ratio. All diets except the control caused hepatosteatosis, as evidenced by Nile red and H&E staining. Hepatic transcription of insulin receptor substrate-1/2 was mainly suppressed by the L-Fr and L-EF diets. The L-EF diet did not enhance the mitochondrial β-oxidation of fatty acids (Cpt1α and Ppar-α expressions) compared to the L-Et or L-Fr diet. Together, our data provide evidence for the coaction of ethanol and fructose with a high-fat-diet on dyslipidemia and insulin resistance-accompanied liver damage

Multimodal image registration by edge attraction and regularization using a B-spline grid

Multi modal image registration enables images from different modalities to be analyzed in the same coordinate system. The class of B-spline-based methods that maximize the Mutual Information between images produce satisfactory result in general, but are often complex and can converge slowly. The popular Demons algorithm, while being fast and easy to implement, produces unrealistic deformation fields and is sensitive to illumination differences between the two images, which makes it unsuitable for multi-modal registration in its original form. We propose a registration algorithm that combines a B-spline grid with deformations driven by image forces. The algorithm is easy to implement and is robust against large differences in the appearance between the images to register. The deformation is driven by attraction-forces between the edges in both images, and a B-spline grid is used to regularize the sparse deformation field. The grid is updated using an original approach by weighting the deformation forces for each pixel individually with the edge strengths. This approach makes the algorithm perform well even if not all corresponding edges are present. We report preliminary results by applying the proposed algorithm to a set of (multi-modal) test images. The results show that the proposed method performs well, but is less accurate than state of the art registration methods based on Mutual Information. In addition, the algorithm is used to register test images to manually drawn line images in order to demonstrate the algorithm's robustness