Supersymmetric Distributions, Hilbert Spaces of Supersymmetric Functions and Quantum Fields

The recently investigated Hilbert-Krein and other positivity structures of the superspace are considered in the framework of superdistributions. These tools are applied to problems raised by the rigorous supersymmetric quantum field theory.Comment: 24 page

Extracellular Domain N-Glycosylation Controls Human Thrombopoietin Receptor Cell Surface Levels

The thrombopoietin receptor (TpoR) is a type I transmembrane protein that mediates the signaling functions of thrombopoietin (Tpo) in regulating megakaryocyte differentiation, platelet formation, and hematopoietic stem cell renewal. We probed the role of each of the four extracellular domain putative N-glycosylation sites for cell surface localization and function of the receptor. Single N-glycosylation mutants at any of the four sites were able to acquire the mature N-glycosylated pattern, but exhibited a decreased Tpo-dependent JAK2–STAT response in stably transduced Ba/F3 or Ba/F3-JAK2 cell lines. The ability of JAK2 to promote cell surface localization and stability of TpoR required the first N-glycosylation site (Asn117). In contrast, the third N-glycosylation site (Asn298) decreased receptor maturation and stability. TpoR mutants lacking three N-glycosylation sites were defective in maturation, but N-glycosylation on the single remaining site could be detected by sensitivity to PNGaseF. The TpoR mutant defective in all four N-glycosylation sites was severely impaired in plasma membrane localization and was degraded by the proteasome. N-glycosylation receptor mutants are not misfolded as, once localized on the cell surface in overexpression conditions, they can bind and respond to Tpo. Our data indicate that extracellular domain N-glycosylation sites regulate in a combinatorial manner cell surface localization of TpoR. We discuss how mutations around TpoR N-glycosylation sites might contribute to inefficient receptor traffic and disease

In-flight calibration of the Hot Ion Analyser on board Cluster

The Hot Ion Analyser (HIA), part of the Cluster Ion Spectrometry experiment, has the objective to measure the three-dimensional velocity distributions of ions. Due to a variety of factors (exposure to radiation, detector fatigue and aging, changes in the operating parameters, etc.), the particles' detection efficiency changes over time, prompting for continuous in-flight calibration. This is achieved by comparing the HIA data with the data provided by the WHISPER (Waves of HIgh frequency and Sounder for Probing of Electron density by Relaxation) experiment on magnetosheath intervals, for the high-sensitivity section of the instrument, or solar wind intervals, for the low-sensitivity section. The paper presents in detail the in-flight calibration methodology, reports on the work carried out for calibrating HIA and discusses plans to extend this activity in order to ensure the instrument's highest data accuracy

Magnetic Resonance Imaging as a Prognostic Disability Marker in Clinically Isolated Syndrome and Multiple Sclerosis:A Systematic Review and Meta-Analysis

To date, there are no definite imaging predictors for long-term disability in multiple sclerosis (MS). Magnetic resonance imaging (MRI) is the key prognostic tool for MS, primarily at the early stage of the disease. Recent findings showed that white matter lesion (WML) counts and volumes could predict long-term disability for MS. However, the prognostic value of MRI in the early stage of the disease and its link to long-term physical disability have not been assessed systematically and quantitatively. A meta-analysis was conducted using studies from four databases to assess whether MS lesion counts and volumes at baseline MRI scans could predict long-term disability, assessed by the expanded disability status scale (EDSS). Fifteen studies were eligible for the qualitative analysis and three studies for meta-analysis. T2 brain lesion counts and volumes after the disease onset were associated with disability progression after 10 years. Four or more lesions at baseline showed a highly significant association with EDSS 3 and EDSS 6, with a pooled OR of 4.10 and 4.3, respectively. The risk increased when more than 10 lesions were present. This review and meta-analysis confirmed that lesion counts and volumes could be associated with disability and might offer additional valid guidance in treatment decision making. Future work is essential to determine whether these prognostic markers have high predictive potential.</p

Magnetic Resonance Imaging as a Prognostic Disability Marker in Clinically Isolated Syndrome and Multiple Sclerosis:A Systematic Review and Meta-Analysis

To date, there are no definite imaging predictors for long-term disability in multiple sclerosis (MS). Magnetic resonance imaging (MRI) is the key prognostic tool for MS, primarily at the early stage of the disease. Recent findings showed that white matter lesion (WML) counts and volumes could predict long-term disability for MS. However, the prognostic value of MRI in the early stage of the disease and its link to long-term physical disability have not been assessed systematically and quantitatively. A meta-analysis was conducted using studies from four databases to assess whether MS lesion counts and volumes at baseline MRI scans could predict long-term disability, assessed by the expanded disability status scale (EDSS). Fifteen studies were eligible for the qualitative analysis and three studies for meta-analysis. T2 brain lesion counts and volumes after the disease onset were associated with disability progression after 10 years. Four or more lesions at baseline showed a highly significant association with EDSS 3 and EDSS 6, with a pooled OR of 4.10 and 4.3, respectively. The risk increased when more than 10 lesions were present. This review and meta-analysis confirmed that lesion counts and volumes could be associated with disability and might offer additional valid guidance in treatment decision making. Future work is essential to determine whether these prognostic markers have high predictive potential.</p