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RELA haploinsufficiency is a recently described autoinflammatory condition presenting with intermittent fevers and mucocutaneous ulcerations. The RELA gene encodes the p65 protein, one of five NF-κB family transcription factors. As RELA is an essential regulator of mucosal homeostasis, haploinsufficiency leads to decreased NF-κB signaling which promotes TNF-driven mucosal apoptosis with impaired epithelial recovery. Thus far, only eight cases have been reported in the literature. Here, we report four families with three novel and one previously described pathogenic variant in RELA. These four families included 23 affected individuals for which genetic testing was available in 16. Almost half of these patients had been previously diagnosed with more common rheumatologic entities (such as Behcet's Disease; BD) prior to the discovery of their pathogenic RELA variants. The most common clinical features were orogenital ulcers, rash, joint inflammation, and fever. The least common were conjunctivitis and recurrent infections. Clinical variability was remarkable even among familial cases, and incomplete penetrance was observed. Patients in our series were treated with a variety of medications, and benefit was observed with glucocorticoids, colchicine, and TNF inhibitors. Altogether, our work adds to the current literature and doubles the number of reported cases with RELA-Associated Inflammatory Disease (RAID). It reaffirms the central importance of the NF-κB pathway in immunity and inflammation, as well as the important regulatory role of RELA in mucosal homeostasis. RELA associated inflammatory disease should be considered in all patients with BD, particularly those with early onset and/or with a strong family history.
In recent years, the ability of intelligent systems to be understood by developers and users has received growing attention. This holds in particular for social robots, which are supposed to act autonomously in the vicinity of human users and are known to raise peculiar, often unrealistic attributions and expectations. However, explainable models that, on the one hand, allow a robot to generate lively and autonomous behavior and, on the other, enable it to provide human-compatible explanations for this behavior are missing. In order to develop such a self-explaining autonomous social robot, we have equipped a robot with own needs that autonomously trigger intentions and proactive behavior, and form the basis for understandable self-explanations. Previous research has shown that undesirable robot behavior is rated more positively after receiving an explanation. We thus aim to equip a social robot with the capability to automatically generate verbal explanations of its own behavior, by tracing its internal decision-making routes. The goal is to generate social robot behavior in a way that is generally interpretable, and therefore explainable on a socio-behavioral level increasing users' understanding of the robot's behavior. In this article, we present a social robot interaction architecture, designed to autonomously generate social behavior and self-explanations. We set out requirements for explainable behavior generation architectures and propose a socio-interactive framework for behavior explanations in social human-robot interactions that enables explaining and elaborating according to users' needs for explanation that emerge within an interaction. Consequently, we introduce an interactive explanation dialog flow concept that incorporates empirically validated explanation types. These concepts are realized within the interaction architecture of a social robot, and integrated with its dialog processing modules. We present the components of this interaction architecture and explain their integration to autonomously generate social behaviors as well as verbal self-explanations. Lastly, we report results from a qualitative evaluation of a working prototype in a laboratory setting, showing that (1) the robot is able to autonomously generate naturalistic social behavior, and (2) the robot is able to verbally self-explain its behavior to the user in line with users' requests.
Introduction. The experience of pain is regularly accompanied by facial expressions. The gold standard for analyzing these facial expressions is the Facial Action Coding System (FACS), which provides so-called action units (AUs) as parametrical indicators of facial muscular activity. Particular combinations of AUs have appeared to be pain-indicative. The manual coding of AUs is, however, too time- and labor-intensive in clinical practice. New developments in automatic facial expression analysis have promised to enable automatic detection of AUs, which might be used for pain detection. Objective. Our aim is to compare manual with automatic AU coding of facial expressions of pain. Methods. FaceReader7 was used for automatic AU detection. We compared the performance of FaceReader7 using videos of 40 participants (20 younger with a mean age of 25.7 years and 20 older with a mean age of 52.1 years) undergoing experimentally induced heat pain to manually coded AUs as gold standard labeling. Percentages of correctly and falsely classified AUs were calculated, and we computed as indicators of congruency, "sensitivity/recall," "precision," and "overall agreement (F1)." Results. The automatic coding of AUs only showed poor to moderate outcomes regarding sensitivity/recall, precision, and F1. The congruency was better for younger compared to older faces and was better for pain-indicative AUs compared to other AUs. Conclusion. At the moment, automatic analyses of genuine facial expressions of pain may qualify at best as semiautomatic systems, which require further validation by human observers before they can be used to validly assess facial expressions of pain.
The purpose of this study is to research the antecedents of the sustainable travel decision-making of European travelers and thereby identify important lessons for the transition towards sustainable travel and tourism. The study is based on data collected through a representative survey, conducted in five European countries, with a sample of n = 5024 respondents. The results of descriptive statistics, EFA (Exploratory Factor Analysis) and FA (Factor Analysis) are presented in order to explore sustainable travel decision-making through environmental (policy-related and personal) attitudes and travel mode decision priorities in the European context. Furthermore, the study provides new evidence regarding the under-researched phenomenon of the attitude–behavior gap by presenting a model for the sustainability-oriented decision-making of travelers, including attitudes and travel mode priorities as antecedents. The results confirm the existence of moral licensing in travel decision-making, thereby extending the relevance of this theory into travel and tourism, which has not been done before. The denial of environmental issues is also being researched as regards its interaction with positive environmental attitudes, environmental travel mode priorities and non-environmental travel priorities, thereby advancing our understanding of the interplay between these categories. The interplay between the four categories furthers our understanding of the perplexity of travelers in terms of sustainable travel decision-making.
The article improves understanding on leveraging new technology for DT (digital transformation) of grape harvest in SME wineries. It provides evidence on technologies used and workplace types deployed in grape harvesting, as well as strategic paths in deploying new technology, thereby contributing to the literature on networked sensing and seizing capabilities in the wine industry 4.0. The research approach is explorative and qualitative drawing on 31 interviews with wine industry 4.0 experts and managers, mostly owners of SMEs: wineries, wine software and wine machinery enterprises. Resulting findings serve as a roadmap for digital transformation of grape harvest process in SME wineries explaining technologies and work roles necessary for DWT (digital workplace transformation), as well as strategic paths of deployment of novel grape harvest technology. Previous research on the wine industry 4.0 has focused on BMI, while this research expands the focus to include a wider concept of technology adoption strategy as well as DWT. The research identifies two types of factors impacting the strategic deployment of grape harvest technology: pull factors, also termed servitization factors, as well as push factors, termed also digital transformation factors.
This study set out to uncover brand positioning configurations by presenting state-of-the-art brand management literature and applying a novel, mixed-methods approach to examine the under-researched wine industry transformation towards open innovation in branding. German winery brands were analyzed using a multimethod approach leaning on a novel netnographic methodology and multiple sources. The sample included 572 wineries from all 13 German wine regions with website text data and online review text data from each winery. The study identified nine prime words used to describe both brand identity as well as wine brand image. It revealed word–price clusters of brand identity and image. The results offer insights into communication and pricing opportunities for wine brand identity as well as image, thereby contributing to open brand innovation.
The purpose of this paper is to examine the impact that various types of business model extensions (hospitality and tourism, online sales platforms, and sustainability) have on the winery business. The research is based on company data and online observations of N = 886 German wineries and deploys a content analysis, netnography, and structural equation modeling (SEM) in order to test the hypothesis on business model extensions of wineries, which have been set forth in the previous literature. The findings indicate that business model extensions related to online sales platforms have a positive impact on winery business size. These results mean that developing online sales platforms enlarges the winery BM (business model) size and type (manager-run, state-owned, or cooperatives). The paper presents in detail the impact of winery BM extensions on winery BM model type and size, thereby contributing to the literature on business model innovation.
The article explores SME (Small and Medium Sized Enterprises) brand strategies as a means to position and successfully engage in competitive markets. A derived typology of brand strategy types deals with social profiling and sheds light on brand strategy internalization of two current managerial paradigms—sustainability and co-creation. N = 895 German SME wineries were examined, leaning on a netnographic analysis of predominantly websites and social media interactions. A two-step clustering method thereby identified eight winery SME brand strategy types. The importance of sustainability across the identified eight brand strategy types is significant. Co-creation turned out to be a key profiling trait characterizing one brand strategy type. The typology illustrates strategic richness, with brand strategies leaning predominantly on traditional values, on sustainability, on external reputation, or on more innovative customer centric concepts such as co-creation. Hereby, the typology and the identified brand levers invite to strategically design brand management, governance, and sustainability. Wineries which focus on traditional positioning and legitimacy were found to be cautious in deploying co-creation through social media. Winery brands that are characterized by engagement in digital co-creation apparently either tend to expand their scope or partially combine it with traditional values, making them the most diverse type identified. Sustainability obviously needs to be addressed by all brand strategies. Despite industry and country focus, the analyses illustrate the relevance of socially-oriented profiling and highlights that sustainability has reached a status of a fundamental business approach still allowing to differentiate thereon. Furthermore, the business models of the SMEs need to deliver communicated values.
This article provides insights into the modalities of business-model change and innovation. On the basis of an analysis of empirical data of small and medium enterprises, a transition from wine production centrism to its expanded use in hospitality and tourism is explored. Previous research on wine tourism and hospitality predominantly focuses on a destination perspective, neglecting the organizational winery perspective. The article deploys a mixed methods approach, combining netnography and a content analysis for data collection with grounded research and clustering for theory building. The sample size included 885 German wineries. Data stemmed from two distinct sources (websites and a secondary publication in form of a wine guide) and has been analyzed through a two-step clustering algorithm as well as a Principal Component Analysis (PCA). The two-step clustering algorithm resulted in nine different business models while the PCA analysis grouped the variables into the following two categories: basic winery business model (BM) and BM extension into hospitality and tourism, thereby validating the difference between the two constructs. The results point to the diverse nature of business model extensions of wineries in tourism and hospitality, depending on their organizational type and size. This study offers a classification of small and medium sized enterprise’s strategic business model expansion, and explores the expansion of the wine industry through wine hospitality and tourism services, starting with the winery organizational perspective, which has not been done before.
The reported research examines the impact of product portfolio labeling strategies on brand reputation and equity. A netnographic approach allowed to observe winery portfolio labeling approaches and create a typology of winery labeling strategies. Expert evaluation served to assess the dependent variable brand equity by deploying a regression analysis. For the observed wine industry, being part of the food industry, creating consistent and recognizable brands has a direct relevance for reducing (sustainability-related) food information overload and thereby building sustainable brand equity. The results uncover the relative importance of each of the six identified labeling strategies as well as their impact on reputation and brand equity creation. The results point to the need to establish a consistent, strategically founded product communication. Such an approach, with a positive effect on reputation building can serve to build sustainable brand equity. “Stuck in the middle”-type strategies apparently diminish winery brand equity exploitation. The findings contribute to the knowledge on food labels in product communication strategies and their impact on organizational brand equity, thereby having high relevance for the implementation of environmental certification initiatives in an organizational context. The article deploys a novel research approach in an under-researched area to provide new insights for further research as well as implications for practice.
The deficiency of adenosine deaminase 2 (DADA2) is an autosomal recessively inherited disease that has undergone extensive phenotypic expansion since being first described in patients with fevers, recurrent strokes, livedo racemosa, and polyarteritis nodosa in 2014. It is now recognized that patients may develop multisystem disease that spans multiple medical subspecialties. Here, we describe the findings from a large single center longitudinal cohort of 60 patients, the broad phenotypic presentation, as well as highlight the cohort's experience with hematopoietic cell transplantation and COVID-19. Disease manifestations could be separated into three major phenotypes: inflammatory/vascular, immune dysregulatory, and hematologic, however, most patients presented with significant overlap between these three phenotype groups. The cardinal features of the inflammatory/vascular group included cutaneous manifestations and stroke. Evidence of immune dysregulation was commonly observed, including hypogammaglobulinemia, absent to low class-switched memory B cells, and inadequate response to vaccination. Despite these findings, infectious complications were exceedingly rare in this cohort. Hematologic findings including pure red cell aplasia (PRCA), immune-mediated neutropenia, and pancytopenia were observed in half of patients. We significantly extended our experience using anti-TNF agents, with no strokes observed in 2026 patient months on TNF inhibitors. Meanwhile, hematologic and immune features had a more varied response to anti-TNF therapy. Six patients received a total of 10 allogeneic hematopoietic cell transplant (HCT) procedures, with secondary graft failure necessitating repeat HCTs in three patients, as well as unplanned donor cell infusions to avoid graft rejection. All transplanted patients had been on anti-TNF agents prior to HCT and received varying degrees of reduced-intensity or non-myeloablative conditioning. All transplanted patients are still alive and have discontinued anti-TNF therapy. The long-term follow up afforded by this large single-center study underscores the clinical heterogeneity of DADA2 and the potential for phenotypes to evolve in any individual patient.
BACKGROUND
Biallelic loss-of-function variants in NCF1 lead to reactive oxygen species deficiency and chronic granulomatous disease (CGD). Heterozygosity for the p.Arg90His variant in NCF1 has been associated with susceptibility to systemic lupus erythematosus, rheumatoid arthritis, and Sjögren's syndrome in adult patients. This study demonstrates the association of the homozygous p.Arg90His variant with interferonopathy with features of autoinflammation and autoimmunity in a pediatric patient.
CASE PRESENTATION
A 5-year old female of Indian ancestry with early-onset recurrent fever and headache, and persistently elevated antinuclear, anti-Ro, and anti-La antibodies was found to carry the homozygous p.Arg90His variant in NCF1 through exome sequencing. Her unaffected parents and three other siblings were carriers for the mutant allele. Because the presence of two NCF1 pseudogenes, this variant was confirmed by independent genotyping methods. Her intracellular neutrophil oxidative burst and NCF1 expression levels were normal, and no clinical features of CGD were apparent. Gene expression analysis in peripheral blood detected an interferon gene expression signature, which was further supported by cytokine analyses of supernatants of cultured patient's cells. These findings suggested that her inflammatory disease is at least in part mediated by type I interferons. While her fever episodes responded well to systemic steroids, treatment with the JAK inhibitor tofacitinib resulted in decreased serum ferritin levels and reduced frequency of fevers.
CONCLUSION
Homozygosity for p.Arg90His in NCF1 should be considered contributory in young patients with an atypical systemic inflammatory antecedent phenotype that may evolve into autoimmunity later in life. The complex genomic organization of NCF1 poses a difficulty for high-throughput genotyping techniques and variants in this gene should be carefully evaluated when using the next generation and Sanger sequencing technologies. The p.Arg90His variant is found at a variable allele frequency in different populations, and is higher in people of South East Asian ancestry. In complex genetic diseases such as SLE, other rare and common susceptibility alleles might be necessary for the full disease expressivity.
Somatic Mutations in UBA1 Define a Distinct Subset of Relapsing Polychondritis Patients With VEXAS
(2021)
Neurodevelopmental disorder with dysmorphic facies and distal limb anomalies (NEDDFL), defined primarily by developmental delay/intellectual disability, speech delay, postnatal microcephaly, and dysmorphic features, is a syndrome resulting from heterozygous variants in the dosage-sensitive bromodomain PHD finger chromatin remodeler transcription factor BPTF gene. To date, only 11 individuals with NEDDFL due to de novo BPTF variants have been described. To expand the NEDDFL phenotypic spectrum, we describe the clinical features in 25 novel individuals with 20 distinct, clinically relevant variants in BPTF, including four individuals with inherited changes in BPTF. In addition to the previously described features, individuals in this cohort exhibited mild brain abnormalities, seizures, scoliosis, and a variety of ophthalmologic complications. These results further support the broad and multi-faceted complications due to haploinsufficiency of BPTF.
It is only a matter of time until autonomous vehicles become ubiquitous; however, human driving supervision will remain a necessity for decades. To assess the drive's ability to take control over the vehicle in critical scenarios, driver distractions can be monitored using wearable sensors or sensors that are embedded in the vehicle, such as video cameras. The types of driving distractions that can be sensed with various sensors is an open research question that this study attempts to answer. This study compared data from physiological sensors (palm electrodermal activity (pEDA), heart rate and breathing rate) and visual sensors (eye tracking, pupil diameter, nasal EDA (nEDA), emotional activation and facial action units (AUs)) for the detection of four types of distractions. The dataset was collected in a previous driving simulation study. The statistical tests showed that the most informative feature/modality for detecting driver distraction depends on the type of distraction, with emotional activation and AUs being the most promising. The experimental comparison of seven classical machine learning (ML) and seven end-to-end deep learning (DL) methods, which were evaluated on a separate test set of 10 subjects, showed that when classifying windows into distracted or not distracted, the highest F1-score of 79%; was realized by the extreme gradient boosting (XGB) classifier using 60-second windows of AUs as input. When classifying complete driving sessions, XGB's F1-score was 94%. The best-performing DL model was a spectro-temporal ResNet, which realized an F1-score of 75%; when classifying segments and an F1-score of 87%; when classifying complete driving sessions. Finally, this study identified and discussed problems, such as label jitter, scenario overfitting and unsatisfactory generalization performance, that may adversely affect related ML approaches.
This study advances the research and methodological approach to measuring and understanding national-level destination competitiveness, sustainability and governance, by creating a model that could be of use for both developing and developed destinations. The study gives a detailed overview of the research field of measuring destination competitiveness and sustainability. It also identifies major predictors of destination competitiveness and sustainability and thereby presents destination researchers and practitioners with a useful list of priority areas, both from a global perspective and from the perspective of other similar destinations. Finally, the study identifies two major types of destination governance with implications for research, policy and practice across the destination life-cycle. The research deals with the analysis of the secondary data from the World Economic Forum Travel and Tourism Index (WEF T&T). Major types of destination governance and predictors of belonging to either one of the types, as well as inside cluster predictors have been extracted through a two-step cluster analysis. The results support the notion that a meaningful model of national-level destination governance needs to take into account different development levels of different destinations. The main limitation of the study is its typology creation approach, as it inevitably leads to simplifications.