Acceptance of Enhanced Robotic Assistance Systems in People With Amyotrophic Lateral Sclerosis–Associated Motor Impairment: Observational Online Study

Background: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by a progressive paresis of the extremities and the loss of manual functioning. Due to the severe functional impairment that the disease entails, ALS requires the provision of comprehensive nursing care and a complex set of assistive technology devices. To relieve caregivers and promote autonomy of people with ALS, robotic assistance systems are being developed. This trial aims to evaluate the acceptance of technology, in general, and of robotic arm assistance among people with ALS in order to lay the groundwork for the development of a semiautomatic robotic arm that can be controlled by humans via a multimodal user interface and that will allow users to handle objects and attend to their own bodies. Objective: The aim of this study was to perform a systematic analysis of technology commitment and acceptance of robotic assistance systems from the perspective of physically limited people living with ALS. Methods: The investigation was conducted as a study of a prospective cohort. Participants were only included if they had received a medical diagnosis of ALS. Data collection took place via an online questionnaire on the Ambulanzpartner Soziotechnologie internet platform. Technological commitment was measured using the Neyer short scale. Furthermore, a multidimensional questionnaire was specially developed to analyze participant acceptance of robotic arm assistance: the Acceptance Measure of Robotic Arm Assistance (AMRAA). This questionnaire was accompanied by a video introducing the robot arm. ALS severity was ascertained using the ALS Functional Rating Scale–Extended (ALSFRS-EX). Results: A total of 268 people with ALS participated in the survey. Two-thirds of the participants were male. The overall mean ALS severity score was 42.9 (SD 11.7) points out of 60 on the ALSFRS-EX, with the most relevant restrictions on arms and legs (<60% of normal functioning). Technological commitment ranked high, with the top third scoring 47.2 points out of 60. Younger participants and males showed significantly higher values. The AMRAA score was, again, significantly higher among younger participants. However, the gender difference within the overall cohort was not significant. The more limited the arm functioning of participants according to the ALSFRS-EX subscale, the higher the acceptance rate of robotic assistance. This relationship proved significant. Conclusions: People with ALS display high technological commitment and feel positive about using technological assistance systems. In our study, younger participants were more open to technology use, in general, and robotic assistance, in particular. Self-appraisal of technology acceptance, competence, and control conviction were generally higher among men. However, any presumed gender difference vanished when users were asked to rate the anticipated usefulness of the technology, in particular the robotic arm. The acceptance was also reflected in users’ increased willingness to use a robotic arm as the functionality of their own arms decreased. From the perspective of people with ALS, robotic assistance systems are critical to promoting individual autonomy. Another key consideration in the development of future assistive technologies should be the reduction of caregiver burden. Trial Registration: German Clinical Trials Register DRKS00012803; https://tinyurl.com/w9yzduh

О сущности языковой компетенции

В статье даётся характеристика сущностных сторон языковой компетенции как био и социального и интеллектуального феномена.У статті подається характеристика сутнісних сторін мовної компетенції як біо та соціального та інтелектуального феномену.The characteristics of essential aspects of language competency as bio- and social and intellectual phenomenon is given in the article

Genome-Wide Scan on Total Serum IgE Levels Identifies FCER1A as Novel Susceptibility Locus

High levels of serum IgE are considered markers of parasite and helminth exposure. In addition, they are associated with allergic disorders, play a key role in anti-tumoral defence, and are crucial mediators of autoimmune diseases. Total IgE is a strongly heritable trait. In a genome-wide association study (GWAS), we tested 353,569 SNPs for association with serum IgE levels in 1,530 individuals from the population-based KORA S3/F3 study. Replication was performed in four independent population-based study samples (total n = 9,769 individuals). Functional variants in the gene encoding the alpha chain of the high affinity receptor for IgE (FCER1A) on chromosome 1q23 (rs2251746 and rs2427837) were strongly associated with total IgE levels in all cohorts with P values of 1.85×10−20 and 7.08×10−19 in a combined analysis, and in a post-hoc analysis showed additional associations with allergic sensitization (P = 7.78×10−4 and P = 1.95×10−3). The “top” SNP significantly influenced the cell surface expression of FCER1A on basophils, and genome-wide expression profiles indicated an interesting novel regulatory mechanism of FCER1A expression via GATA-2. Polymorphisms within the RAD50 gene on chromosome 5q31 were consistently associated with IgE levels (P values 6.28×10−7−4.46×10−8) and increased the risk for atopic eczema and asthma. Furthermore, STAT6 was confirmed as susceptibility locus modulating IgE levels. In this first GWAS on total IgE FCER1A was identified and replicated as new susceptibility locus at which common genetic variation influences serum IgE levels. In addition, variants within the RAD50 gene might represent additional factors within cytokine gene cluster on chromosome 5q31, emphasizing the need for further investigations in this intriguing region. Our data furthermore confirm association of STAT6 variation with serum IgE levels

Conditional Stat1 Ablation Reveals the Importance of Interferon Signaling for Immunity to Listeria monocytogenes Infection

Signal transducer and activator of transcription 1 (Stat1) is a key player in responses to interferons (IFN). Mutations of Stat1 cause severe immune deficiencies in humans and mice. Here we investigate the importance of Stat1 signaling for the innate and secondary immune response to the intracellular bacterial pathogen Listeria monocytogenes (Lm). Cell type-restricted ablation of the Stat1 gene in naïve animals revealed unique roles in three cell types: macrophage Stat1 signaling protected against lethal Lm infection, whereas Stat1 ablation in dendritic cells (DC) did not affect survival. T lymphocyte Stat1 reduced survival. Type I IFN (IFN-I) signaling in T lymphocytes reportedly weakens innate resistance to Lm. Surprisingly, the effect of Stat1 signaling was much more pronounced, indicating a contribution of Stat1 to pathways other than the IFN-I pathway. In stark contrast, Stat1 activity in both DC and T cells contributed positively to secondary immune responses against Lm in immunized animals, while macrophage Stat1 was dispensable. Our findings provide the first genetic evidence that Stat1 signaling in different cell types produces antagonistic effects on innate protection against Lm that are obscured in mice with complete Stat1 deficiency. They further demonstrate a drastic change in the cell type-dependent Stat1 requirement for memory responses to Lm infection

Recommendations for enterovirus diagnostics and characterisation within and beyond Europe.

Enteroviruses (EV) can cause severe neurological and respiratory infections, and occasionally lead to devastating outbreaks as previously demonstrated with EV-A71 and EV-D68 in Europe. However, these infections are still often underdiagnosed and EV typing data is not currently collected at European level. In order to improve EV diagnostics, collate data on severe EV infections and monitor the circulation of EV types, we have established European non-polio enterovirus network (ENPEN). First task of this cross-border network has been to ensure prompt and adequate diagnosis of these infections in Europe, and hence we present recommendations for non-polio EV detection and typing based on the consensus view of this multidisciplinary team including experts from over 20 European countries. We recommend that respiratory and stool samples in addition to cerebrospinal fluid (CSF) and blood samples are submitted for EV testing from patients with suspected neurological infections. This is vital since viruses like EV-D68 are rarely detectable in CSF or stool samples. Furthermore, reverse transcriptase PCR (RT-PCR) targeting the 5'noncoding regions (5'NCR) should be used for diagnosis of EVs due to their sensitivity, specificity and short turnaround time. Sequencing of the VP1 capsid protein gene is recommended for EV typing; EV typing cannot be based on the 5'NCR sequences due to frequent recombination events and should not rely on virus isolation. Effective and standardized laboratory diagnostics and characterisation of circulating virus strains are the first step towards effective and continuous surveillance activities, which in turn will be used to provide better estimation on EV disease burden

The cross-sectional GRAS sample: A comprehensive phenotypical data collection of schizophrenic patients

<p>Abstract</p> <p>Background</p> <p>Schizophrenia is the collective term for an exclusively clinically diagnosed, heterogeneous group of mental disorders with still obscure biological roots. Based on the assumption that valuable information about relevant genetic and environmental disease mechanisms can be obtained by association studies on patient cohorts of ≥ 1000 patients, if performed on detailed clinical datasets and quantifiable biological readouts, we generated a new schizophrenia data base, the GRAS (Göttingen Research Association for Schizophrenia) data collection. GRAS is the necessary ground to study genetic causes of the schizophrenic phenotype in a 'phenotype-based genetic association study' (PGAS). This approach is different from and complementary to the genome-wide association studies (GWAS) on schizophrenia.</p> <p>Methods</p> <p>For this purpose, 1085 patients were recruited between 2005 and 2010 by an invariable team of traveling investigators in a cross-sectional field study that comprised 23 German psychiatric hospitals. Additionally, chart records and discharge letters of all patients were collected.</p> <p>Results</p> <p>The corresponding dataset extracted and presented in form of an overview here, comprises biographic information, disease history, medication including side effects, and results of comprehensive cross-sectional psychopathological, neuropsychological, and neurological examinations. With >3000 data points per schizophrenic subject, this data base of living patients, who are also accessible for follow-up studies, provides a wide-ranging and standardized phenotype characterization of as yet unprecedented detail.</p> <p>Conclusions</p> <p>The GRAS data base will serve as prerequisite for PGAS, a novel approach to better understanding 'the schizophrenias' through exploring the contribution of genetic variation to the schizophrenic phenotypes.</p

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods - recursive partitioning and regression - to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; Pcombined = 2.01 × 10-19 and 2.35 × 10-13, respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes. ©2007 Nature Publishing Group