Personalised service? Changing the role of the government librarian

Investigates the feasibility of personalised information service in a government department. A qualitative methodology explored stakeholder opinions on the remit, marketing, resourcing and measurement of the service. A questionnaire and interviews gathered experiences of personalised provision across the government sector. Potential users were similarly surveyed to discuss how the service could meet their needs. Data were analysed using coding techniques to identify emerging theory. Lessons learned from government librarians centred on clarifying requirements, balancing workloads and selective marketing. The user survey showed low usage and awareness of existing specialist services, but high levels of need and interest in services repackaged as a tailored offering. Fieldwork confirmed findings from the literature on the scope for adding value through information management advice, information skills training and substantive research assistance and the need to understand business processes and develop effective partnerships. Concluding recommendations focus on service definition, strategic marketing, resource utilisation and performance measurement

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