99 research outputs found

    Studies of the dose-effect relation

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    Dose-effect relations and, specifically, cell survival curves are surveyed with emphasis on the interplay of the random factors — biological variability, stochastic reaction of the cell, and the statistics of energy deposition —that co-determine their shape. The global parameters mean inactivation dose, , and coefficient of variance, V, represent this interplay better than conventional parameters. Mechanisms such as lesion interaction, misrepair, repair overload, or repair depletion have been invoked to explain sigmoid dose dependencies, but these notions are partly synonymous and are largely undistinguishable on the basis of observed dose dependencies. All dose dependencies reflect, to varying degree, the microdosimetric fluctuations of energy deposition, and these have certain implications, e.g. the linearity of the dose dependence at small doses, that apply regardless of unresolved molecular mechanisms of cellular radiation action

    Successful desensitization with human insulin in a patient with an insulin allergy and hypersensitivity to protamine: a case report

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    <p>Abstract</p> <p>Introduction</p> <p>Insulin allergy may occur in patients treated with subcutaneous applications of insulin preparations. Besides additives in the insulin preparation such as protamine, cresol, and phenol, the insulin molecule itself may be the cause of the allergy. In the latter case, therapeutic options are rare.</p> <p>Case presentation</p> <p>A 68-year-old man with poorly controlled type 2 diabetes mellitus received different insulin preparations subcutaneously while on oral medication. Six to eight hours after each subcutaneous application, he developed pruritic plaques with a diameter of >15 cm at the injection sites that persisted for several days. Allergologic testing revealed positive reactions against every insulin preparation and against protamine. Investigation of serum samples demonstrated IgG antibodies against human and porcine insulin. We treated the patient with human insulin using an ultra-rush protocol beginning with 0.004 IU and a rapid augmentation in dose up to 5 IU. Therapy was accompanied by antihistamine therapy. Subsequent conversion to therapy with glargine insulin (6 IE twice daily) was well-tolerated.</p> <p>Conclusion</p> <p>As reported in this case, desensitization with subcutaneously administered human insulin using an ultra-rush protocol in patients with an insulin allergy may present an easy form of therapy that is successful within a few days.</p

    SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

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    Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

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

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    Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 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

    A first update on mapping the human genetic architecture of COVID-19

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