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

Formation of virtual organizations through negotiation

Abstract. In this paper negotiation is presented as a solution to the formation of virtual organization in domains with many parties having (partially) unknown constraints and profiles and in which the environment is dynamic by nature. The solution presented is based on the MAGNET negotiation system, for which an extension is presented, that allows for last minute changes and failure management. An efficient algorithm is presented for supplier agents, incorporating preferences, and other constraints related to existing individual plans). Combining the algorithms for supplier agents, with a simple customer agent specification, and the ability to iterate the bidding, MAGNET is extended to deal with domains as described above. A case study in logistics using real data from a logistics company shows the validity of the approach.

Designing and developing monitoring agents for ERP systems

This work discusses the case study of a bus company that needs to evolve its ERP system to enhance the managerial strategic control over the maintenance process of the bus fleet. This maintenance process was initially characterized by a poor performance that caused the low quality of the final service to the customer. The solution to the problem, we discuss in this article, is the integration of monitoring agents, called Probes, into the ERP system. Probes enable to control the process performance aligning it to the company\u2019s strategic goals. Probes offer a real time monitoring of the strategic goals achievement, also increasing the understanding of the maintenance activities. At the end, the use of Probes in the ERP system of the company has determined a significant change in the strategy of the company that obtained higher performances of the maintenance process and consequentially a higher quality of the offered service