Mei-p26 cooperates with Bam, Bgcn and Sxl to promote early germline development in the Drosophila ovary.

In the Drosophila female germline, spatially and temporally specific translation of mRNAs governs both stem cell maintenance and the differentiation of their progeny. However, the mechanisms that control and coordinate different modes of translational repression within this lineage remain incompletely understood. Here we present data showing that Mei-P26 associates with Bam, Bgcn and Sxl and nanos mRNA during early cyst development, suggesting that this protein helps to repress the translation of nanos mRNA. Together with recently published studies, these data suggest that Mei-P26 mediates both GSC self-renewal and germline differentiation through distinct modes of translational repression depending on the presence of Bam

Germline cells within germaria co-express Mei-P26, Bgcn, Sxl and Bam.

<p>(A) A wild-type germarium stained for Mei-P26 (red), GFP-Bgcn (green) and DNA (blue). (B) A wild-type germarium stained for Mei-P26 (red), Sxl (green) and DNA (blue). (C) A wild-type germarium stained for Mei-P26 (red), Bam (green) and DNA (blue). Scale bars represent 10 µm.</p

Sxl and Bam associate with Mei-P26.

<p>(A) Sxl immunoprecipitates with Mei-P26 in ovarian extracts from newly eclosed females. (B) Heat-shock induced Bam::HA and Sxl co-immunoprecipitate with Mei-P26. The levels of Sxl that associate with Mei-P26 do not appear to change in the presence of Bam::HA. (C) Extracts from whole ovaries were fractionated and the resulting eluents were probed for the presence of various proteins using western blot analysis. Mei-P26, GFP-tagged Bgcn, Sxl and HA-Bam were observed over a range of fractions but co-peaked in fraction 30. The control proteins Ter94 and Actin peaked in fractions 34 and 37 respectively.</p

Mei-P26 physically interacts with Bgcn.

<p>(A) V5-tagged Mei-P26 co-immunoprecipitates Myc tagged Bgcn from S2 cell extracts. GFP-Bgcn immunoprecipitates with Mei-P26 in (B) wild-type whole ovary extracts and (C) <i>bam^▵86</i> mutant ovary extracts. (D) Various combinations of Bam, Bgcn, Mei-P26, Ago1 bait and prey constructs were tested in a LexA based yeast-2-hybrid β-galactosidase assay.</p

Outcomes and Their State-level Variation in Patients Undergoing Surgery With Perioperative SARS-CoV-2 Infection in the USA. A Prospective Multicenter Study

Objective: To report the 30-day outcomes of patients with perioperative SARS-CoV-2 infection undergoing surgery in the USA. Background: Uncertainty regarding the postoperative risks of patients with SARS-CoV-2 exists. Methods: As part of the COVIDSurg multicenter study, all patients aged ≥17 years undergoing surgery between January 1 and June 30, 2020 with perioperative SARS-CoV-2 infection in 70 hospitals across 27 states were included. The primary outcomes were 30-day mortality and pulmonary complications. Multivariable analyses (adjusting for demographics, comorbidities, and procedure characteristics) were performed to identify predictors of mortality. Results: A total of 1581 patients were included; more than half of them were males (n = 822, 52.0%) and older than 50 years (n = 835, 52.8%). Most procedures (n = 1261, 79.8%) were emergent, and laparotomies (n = 538, 34.1%). The mortality and pulmonary complication rates were 11.0 and 39.5%, respectively. Independent predictors of mortality included age ≥70 years (odds ratio 2.46, 95% confidence interval [1.65-3.69]), male sex (2.26 [1.53-3.35]), ASA grades 3-5 (3.08 [1.60-5.95]), emergent surgery (2.44 [1.31-4.54]), malignancy (2.97 [1.58-5.57]), respiratory comorbidities (2.08 [1.30-3.32]), and higher Revised Cardiac Risk Index (1.20 [1.02-1.41]). While statewide elective cancelation orders were not associated with a lower mortality, a sub-analysis showed it to be associated with lower mortality in those who underwent elective surgery (0.14 [0.03-0.61]). Conclusions: Patients with perioperative SARS-CoV-2 infection have a significantly high risk for postoperative complications, especially elderly males. Postponing elective surgery and adopting non-operative management, when reasonable, should be considered in the USA during the pandemic peaks

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization 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