Study of KS KL Coupled Decays and KL -Be Interactions with the CMD-2 Detector at VEPP-2M Collider

The integrated luminosity about 4000 inverse nanobarn of around phi meson mass ( 5 millions of phi mesons) has been collected with the CMD-2 detector at the VEPP-2M collider. A latest analysis of the KS KL coupled decays based on 30 % of available data is presented in this paper. The KS KL pairs from phi meson decays were reconstructed in the drift chamber when both kaons decayed into two charged particles. From a sample of 1423 coupled decays a selection of candidates to the CP violating KL into pi+ pi- decay was performed. CP violating decays were not identified because of the domination of events with a KL regenerating at the Be beam pipe into KS and a background from KL semileptonic decays. The regeneration cross section of 110 MeV/c KL mesons was found to be 53 +- 17 mb in agreement with theoretical expectations. The angular distribution of KS mesons after regeneration and the total cross section of KL for Be have been measured.Comment: 14 pages, 8 figure

Search for rare Phi decays in pi+ pi_ gamma final state

A search for phi radiative decays has been performed using a data sample of about 2.0 million phi decays collected by the CMD-2 detector at VEPP-2M collider in Novosibirsk. From the selected e+ e- -> pi+ pi- gamma events the following results were obtained: B(phi -> f0(980) gamma) < 1x10-4 for destructive and B(phi -> f0(980) gamma) < 7x10-4 for constructive interference with the Bremsstrahlung process respectively, B(phi -> gamma -> pi+ pi- gamma) 20 MeV, B(phi -> rho gamma) < 7x10-4. From the selected e+ e- -> mu+ mu- gamma events B(phi -> mu+ mu- gamma) = (2.3+-1.0)x10-5 has been obtained for E of gamma> 20 MeV. The upper limit on the P,CP-violating decay eta -> pi+ pi- has also been placed: B(eta -> pi+ pi-) < 9x10-4 . All upper limits are at 90 % C.L.Comment: 18 pages, 7 figure

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

Plant virology in subSaharan Africa: proceedings of a conference organized by IITA, 48 June 2001

The rice yellow mottle diseases is the main virus disease found on rice in Africa. It has been reported in all major rice producing zone of sub-saharan Africa (East,West,Central and Southern Africa and Madagascar). The disease incidence and accompanying yield losses could be high depending on the rice cultivars grown, the date of infection and type of rice