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

Grazing Management Decision Making in the Pastoral Zone of Western Australia: An Application Using Control Theory

Rangeland degradation within the arid zone of Western Australia has occurred as a consequence of sheep overstocking. Optimum grazing management strategies and rangeland rehabilitation techniques are needed to maintain the resource base for future use. In this paper an optimal control framework is developed for the derivation of grazing management decisions. " An integrated model of an arid grazing ecological system (IMAGES)" is used to derive the rangeland dynamics. The state of the grazing ecological system is summarized into four variables: the population of mature desirable perennial plants, young desirable perennial seedlings, old desirable perennial seedlings and total forage biomass. The controls are a set of different seasonal stocking rates within the year. Optimal decision rules are derived for both a deterministic and stochastic case study. Generally, the optimum stocking rate increase with increasing value for the 4 state variables. In deterministic case it combines both uniform and varied stocking rates while in the stochastic case only the uniform stocking rates prevails. Compared to the stochastic case, the net present value is higher for most cases under deterministic climate sequences, although there are some exceptions. The differences in the deterministic and stochastic cases can be dramatic. The reason appears to be highly variable rainfall combined with nonlinear production functions and adjustment costs. An over-optimistic expectation about the weather can be very expensive. Work to verify the stochastic results is continuing

The Ahuachapan geothermal field, El Salvador: Exploitation model, performance predictions, economic analysis

The Earth Sciences Division of Lawrence Berkeley Laboratory (LBL) is conducting a reservoir evaluation study of the Ahuachapan geothermal field in El Salvador. This work is being performed in cooperation with the Comision Ejecutiva Hidroelectrica del Rio Lempa (CEL) and the Los Alamos National Laboratory (LANL) with funding from the US Agency for International Development (USAID). This appendix to the report describes the work done during the second year of the study (FY89--90). The first year's report included (1) the development of geological and conceptual models of the field, (2) the evaluation of the reservoir's initial thermodynamic and chemical conditions and their changes during exploitation, (3) the evaluation of interference test data and the observed reservoir pressure decline and (4) the development of a natural state model for the field. In these appendices the results of reservoir engineering studies to evaluate different production-injection scenarios for the Ahuachapan geothermal field are discussed. The purpose of the work was to evaluate possible reservoir management options to enhance as well as to maintain the productivity of the field during a 30-year period (1990--2020). The ultimate objective was to determine the feasibility of increasing the electrical power output at Ahuachapan from the current level of about 50 MW{sub e} to the total installed capacity of 95 MW{sub e}. the flow rate and flowing enthalpy are shown for 1975--1990 and extrapolated out to 2015. Future temperature distributions are predicted