P-wave excited baryons from pion- and photo-induced hyperon production

We report evidence for $N(1710)P_{11}$, $N(1875)P_{11}$, $N(1900)P_{13}$, $\Delta(1600)P_{33}$, $\Delta(1910)P_{31}$, and $\Delta(1920)P_{33}$, and find indications that $N(1900)P_{13}$ might have a companion state at 1970\,MeV. The controversial $\Delta(1750)P_{31}$ is not seen. The evidence is derived from a study of data on pion- and photo-induced hyperon production, but other data are included as well. Most of the resonances reported here were found in the Karlsruhe-Helsinki (KH84) and the Carnegie-Mellon (CM) analyses but were challenged recently by the Data Analysis Center at GWU. Our analysis is constrained by the energy independent $\pi N$ scattering amplitudes from either KH84 or GWU. The two $\pi N$ amplitudes from KH84 or GWU, respectively, lead to slightly different $\pi N$ branching ratios of contributing resonances but the debated resonances are required in both series of fits.Comment: 22 pages, 28 figures. Some additional sets of data are adde

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

Recruitment variability in Baltic Sea sprat (Sprattus sprattus)is tightly coupled to temperature and transport patterns affecting the larval and early juvenile stages

Recruitment patterns of Baltic Sea sprat (Sprattus sprattus) were correlated to time series of (i) month- and depth-specific temperature conditions and (ii) larval drift patterns inferred from long-term Lagrangian particle simulations. From the latter, we derived an index that likely reflected the variable degree of annual larval transport from the central, deep spawning basins to the shallow coastal areas of the Baltic Sea. The drift index was significantly (P < 0.001) correlated to sprat recruitment success and explained, together with sprat spawning stock biomass, 82% of the overall variability between 1979 and 2003. Years of strong larval displacement towards southern and eastern Baltic coasts corresponded to relative recruitment failure, while years of retention within the deep basins were associated with relative recruitment success. The strongest correlation between temperature and recruitment occurred during August in surface waters, explaining 73% of the overall variability. Together, the two approaches advocate that new year classes of Baltic sprat are predominantly composed of individuals born late in the season and are determined in strength mainly by processes acting during the late larval and early juvenile stages. However, prior to be included in recruitment predictions, the biological mechanisms underlying these strong correlations may need to be better resolve