Cytokine Expression by Inflammatory Cells Obtained from the Spinal Cords of Lewis Rats with Experimental Autoimmune Encephalomyelitis Induced by Inoculation with Myelin Basic Protein and Adjuvants

Inflammatory cells were obtained from the spinal cords of rats with acute experimental autoimmune encephalomyelitis EAE induced by inoculation with myelin basic protein MBP and adjuvants. Reverse transcriptase-polymerase chain reaction RT-PCR was used to investigate the expression of mRNA for interleukin-2 IL-2 , IL-4, IL-10 and interferon-gamma (IFN-gamma) by cells from groups of rats studied 10-21 days after inoculation. On all days of study, the inflammatory cells, which were predominantly lymphocytes, expressed mRNA for IL-2, IL-4, IL-10 and IFN-gamma. In the mRNA from normal rat spinal cord tissue, there was little expression of cytokine mRNA. Cells from a short-term MBP-reactive T cell line expressed all the cytokines. Densitometry was used to measure the products of PCR, to assess the expression of each cytokine relative to that of beta-actin. IL-2 mRNA was expressed throughout the course of disease and reached a peak on day 18, during late clinical recovery. IFN-gamma was expressed throughout the course of the disease and was also high during late recovery. IL-4 mRNA was present in the spinal cord throughout the course of the disease, with a slight rise during late recovery. Relative expression of IL-10 rose to a peak on days 17-19, during late recovery from clinical disease. This study indicates that IL-2, IL-4, IL-10 and IFN-gamma are expressed by inflammatory cells in the spinal cord in EAE, with the relative expression of all cytokines being high during late clinical recovery

Planck 2015 results. XXVII. The Second Planck Catalogue of Sunyaev-Zeldovich Sources

We present the all-sky Planck catalogue of Sunyaev-Zeldovich (SZ) sources detected from the 29 month full-mission data. The catalogue (PSZ2) is the largest SZ-selected sample of galaxy clusters yet produced and the deepest all-sky catalogue of galaxy clusters. It contains 1653 detections, of which 1203 are confirmed clusters with identified counterparts in external data-sets, and is the first SZ-selected cluster survey containing > $10^3$ confirmed clusters. We present a detailed analysis of the survey selection function in terms of its completeness and statistical reliability, placing a lower limit of 83% on the purity. Using simulations, we find that the Y5R500 estimates are robust to pressure-profile variation and beam systematics, but accurate conversion to Y500 requires. the use of prior information on the cluster extent. We describe the multi-wavelength search for counterparts in ancillary data, which makes use of radio, microwave, infra-red, optical and X-ray data-sets, and which places emphasis on the robustness of the counterpart match. We discuss the physical properties of the new sample and identify a population of low-redshift X-ray under- luminous clusters revealed by SZ selection. These objects appear in optical and SZ surveys with consistent properties for their mass, but are almost absent from ROSAT X-ray selected samples

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease