Spatial distribution of bivalves in relation to environmental conditions (middle Danube catchment, Hungary)

The spatial distribution of bivalves in relation to environmental conditions was studied along a second- and third order stream – medium-sized river (River Ipoly) – large river (River Danube) continuum in the Hungarian Danube River system. Quantitative samples were collected four times in 2007 and a total of 1662 specimens, belonging to 22 bivalve species were identified. Among these species, two are endangered (Pseudanodonta complanata, Unio crassus) and five are invasive (Dreissena polymorpha, D. rostriformis bugensis, Corbicula fluminea, C. fluminalis, Anodonta woodiana) in Hungary. The higher density presented by Pisidium subtruncatum, P. supinum, P. henslowanum and C. fluminea suggests that these species may have a key role in this ecosystem. Three different faunal groups were distinguished but no significant temporal change was detected. The lowest density and diversity with two species (P. casertanum and P. personatum) occurred in streams. The highest density and diversity was found in the River Ipoly, in the side arms of the Danube and in the main arm of the Danube with sand and silt substrate, being dominated by P. subtruncatum and P. henslowanum. Moderate density and species richness were observed in the main arm of the Danube with pebble and stone substrate, being dominated by C. fluminea and S. rivicola. Ten environmental variables were found to have significant influence on the distribution of bivalves, the strongest explanatory factors being substrate types, current velocity and sedimentological characteristics.The project was financially supported by the Hungarian Scientific Research Fund under the contract No. OTKA T/046180. Special thanks to the DanubeIpoly National Park for the help in field work.info:eu-repo/semantics/publishedVersio

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