Solar Magnetic Carpet I: Simulation of Synthetic Magnetograms

This paper describes a new 2D model for the photospheric evolution of the magnetic carpet. It is the first in a series of papers working towards constructing a realistic 3D non-potential model for the interaction of small-scale solar magnetic fields. In the model, the basic evolution of the magnetic elements is governed by a supergranular flow profile. In addition, magnetic elements may evolve through the processes of emergence, cancellation, coalescence and fragmentation. Model parameters for the emergence of bipoles are based upon the results of observational studies. Using this model, several simulations are considered, where the range of flux with which bipoles may emerge is varied. In all cases the model quickly reaches a steady state where the rates of emergence and cancellation balance. Analysis of the resulting magnetic field shows that we reproduce observed quantities such as the flux distribution, mean field, cancellation rates, photospheric recycle time and a magnetic network. As expected, the simulation matches observations more closely when a larger, and consequently more realistic, range of emerging flux values is allowed (4e16 - 1e19 Mx). The model best reproduces the current observed properties of the magnetic carpet when we take the minimum absolute flux for emerging bipoles to be 4e16 Mx. In future, this 2D model will be used as an evolving photospheric boundary condition for 3D non-potential modeling.Comment: 33 pages, 16 figures, 5 gif movies included: movies may be viewed at http://www-solar.mcs.st-and.ac.uk/~karen/movies_paper1

A distinct influenza infection signature in the blood transcriptome of patients with severe community-acquired pneumonia

Introduction Diagnosis of severe influenza pneumonia remains challenging because of a lack of correlation between the presence of influenza virus and clinical status. We conducted gene-expression profiling in the whole blood of critically ill patients to identify a gene signature that would allow clinicians to distinguish influenza infection from other causes of severe respiratory failure, such as bacterial pneumonia, and noninfective systemic inflammatory response syndrome. Methods Whole-blood samples were collected from critically ill individuals and assayed on Illumina HT-12 gene-expression beadarrays. Differentially expressed genes were determined by linear mixed-model analysis and overrepresented biological pathways determined by using GeneGo MetaCore. Results The gene-expression profile of H1N1 influenza A pneumonia was distinctly different from those of bacterial pneumonia and systemic inflammatory response syndrome. The influenza gene-expression profile is characterized by upregulation of genes from cell-cycle regulation, apoptosis, and DNA-damage-response pathways. In contrast, no distinctive gene-expression signature was found in patients with bacterial pneumonia or systemic inflammatory response syndrome. The gene-expression profile of influenza infection persisted through 5 days of follow-up. Furthermore, in patients with primary H1N1 influenza A infection in whom bacterial co-infection subsequently developed, the influenza gene-expression signature remained unaltered, despite the presence of a superimposed bacterial infection. Conclusions The whole-blood expression-profiling data indicate that the host response to influenza pneumonia is distinctly different from that caused by bacterial pathogens. This information may speed the identification of the cause of infection in patients presenting with severe respiratory failure, allowing appropriate patient care to be undertaken more rapidly

Identifying key regulatory genes in the whole blood of septic patients to monitor underlying immune dysfunctions

There is currently no reliable tool available to measure immune dysfunction in septic patients in the clinical setting. This proof-of-concept study assesses the potential of gene expression profiling of whole blood as a tool to monitor immune dysfunction in critically ill septic patients. Whole-blood samples were collected daily for up to 5 days from patients admitted to the intensive care unit with sepsis. RNA isolated from whole-blood samples was assayed on Illumina HT-12 gene expression microarrays consisting of 48,804 probes. Microarray analysis identified 3,677 genes as differentially expressed across 5 days between septic patients and healthy controls. Of the 3,677 genes, biological pathway analysis identified 86 genes significantly downregulated in the sepsis patients were present in pathways relating to immune response. These 86 genes correspond to known immune pathways implicated in sepsis, including lymphocyte depletion, reduced T-lymphocyte activation, and deficient antigen presentation. Furthermore, expression levels of these genes correlated with clinical severity, with a significantly greater degree of downregulation found in nonsurvivors compared with survivors. The results show that whole-blood gene expression analysis can capture systemic immune dysfunctions in septic patients. Our study provides an experimental basis to support further study on the use of a gene expression–based assay, to assess immunosuppression, and to guide immunotherapy in future clinical trials

The low EOMES/TBX21 molecular phenotype in multiple sclerosis reflects CD56+ cell dysregulation and is affected by immunomodulatory therapies

Multiple Sclerosis (MS) is an autoimmune disease treated by therapies targeting peripheral blood cells. We previously identified that expression of two MS-risk genes, the transcription factors EOMES and TBX21 (ET), was low in blood from MS and stable over time. Here we replicated the low ET expression in a new MS cohort (p < 0.0007 for EOMES, p < 0.028 for TBX21) and demonstrate longitudinal stability (p < 10− 4) and high heritability (h2 = 0.48 for EOMES) for this molecular phenotype. Genes whose expression correlated with ET, especially those controlling cell migration, further defined the phenotype. CD56 + cells and other subsets expressed lower levels of Eomes or T-bet protein and/or were under-represented in MS. EOMES and TBX21 risk SNP genotypes, and serum EBNA-1 titres were not correlated with ET expression, but HLA-DRB1*1501 genotype was. ET expression was normalised to healthy control levels with natalizumab, and was highly variable for glatiramer acetate, fingolimod, interferon-beta, dimethyl fumarate

Solar magnetic carpet III : coronal modelling of synthetic magnetograms

PostprintPeer reviewe

The autoimmune risk gene ZMIZ1 is a vitamin D responsive marker of a molecular phenotype of multiple sclerosis

Multiple Sclerosis (MS) is a neurological condition driven in part by immune cells from the peripheral circulation, the targets for current successful therapies. The autoimmune and MS risk gene ZMIZ1 is underexpressed in blood in people with MS. We show that, from three independent sets of transcriptomic data, expression of ZMIZ1 is tightly correlated with that of hundreds of other genes. Further we show expression is partially heritable (heritability 0.26), relatively stable over time, predominantly in plasmacytoid dendritic cells and non-classical monocytes, and that levels of ZMIZ1 protein expression are reduced in MS. ZMIZ1 gene expression is increased in response to calcipotriol (1,25 Vitamin D3) (p < 0.0003) and associated with Epstein Barr Virus (EBV) EBNA-1 antibody titre (p < 0.004). MS therapies fingolimod and dimethyl fumarate altered blood ZMIZ1 gene expression compared to untreated MS. The phenotype indicates susceptibility to MS, and may correspond with clinical response and represent a novel clinical target