Optimal filtering of the LISA data

The LISA time-delay-interferometry responses to a gravitational-wave signal are rewritten in a form that accounts for the motion of the LISA constellation around the Sun; the responses are given in closed analytic forms valid for any frequency in the band accessible to LISA. We then present a complete procedure, based on the principle of maximum likelihood, to search for stellar-mass binary systems in the LISA data. We define the required optimal filters, the amplitude-maximized detection statistic (analogous to the F statistic used in pulsar searches with ground-based interferometers), and discuss the false-alarm and detection probabilities. We test the procedure in numerical simulations of gravitational-wave detection.Comment: RevTeX4, 28 pages, 9 EPS figures. Minus signs fixed in Eq. (46) and Table II. Corrected discussion of F-statistic distribution in Sec. IV

The chemical compound 'Heatin' stimulates hypocotyl elongation and interferes with the Arabidopsis NIT1-subfamily of nitrilases

Temperature passively affects biological processes involved in plant growth. Therefore, it is challenging to study the dedicated temperature signalling pathways that orchestrate thermomorphogenesis, a suite of elongation growth-based adaptations that enhance leaf-cooling capacity. We screened a chemical library for compounds that restored hypocotyl elongation in the pif4-2-deficient mutant background at warm temperature conditions in Arabidopsis thaliana to identify modulators of thermomorphogenesis. The small aromatic compound 'Heatin', containing 1-iminomethyl-2-naphthol as a pharmacophore, was selected as an enhancer of elongation growth. We show that ARABIDOPSIS ALDEHYDE OXIDASES redundantly contribute to Heatin-mediated hypocotyl elongation. Following a chemical proteomics approach, the members of the NITRILASE1-subfamily of auxin biosynthesis enzymes were identified among the molecular targets of Heatin. Our data reveal that nitrilases are involved in promotion of hypocotyl elongation in response to high temperature and Heatin-mediated hypocotyl elongation requires the NITRILASE1-subfamily members, NIT1 and NIT2. Heatin inhibits NIT1-subfamily enzymatic activity in vitro and the application of Heatin accordingly results in the accumulation of NIT1-subfamily substrate indole-3-acetonitrile in vivo. However, levels of the NIT1-subfamily product, bioactive auxin (indole-3-acetic acid), were also significantly increased. It is likely that the stimulation of hypocotyl elongation by Heatin might be independent of its observed interaction with NITRILASE1-subfamily members. However, nitrilases may contribute to the Heatin response by stimulating indole-3-acetic acid biosynthesis in an indirect way. Heatin and its functional analogues present novel chemical entities for studying auxin biology

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

Finding Prototypes Through a Two-Step Fuzzy Approach

Usually, the aim of cluster analysis is to build prototypes, i.e., typologies of units that present similar characteristics. In this paper, an alternative approach based on consensus clustering between two different clustering methods is proposed to obtain homogeneous prototypes. The clustering methods used are fuzzy c-means (that minimizes the objective function with respect to centers of the groups) and archetypal analysis (that minimizes the objective function with respect to extremes of the groups). The consensus clustering is used to assess the correspondence between the clustering solutions obtained and to find the prototypes as a compromise between the two clustering methods