The Milky Way Bulge: Observed properties and a comparison to external galaxies

The Milky Way bulge offers a unique opportunity to investigate in detail the role that different processes such as dynamical instabilities, hierarchical merging, and dissipational collapse may have played in the history of the Galaxy formation and evolution based on its resolved stellar population properties. Large observation programmes and surveys of the bulge are providing for the first time a look into the global view of the Milky Way bulge that can be compared with the bulges of other galaxies, and be used as a template for detailed comparison with models. The Milky Way has been shown to have a box/peanut (B/P) bulge and recent evidence seems to suggest the presence of an additional spheroidal component. In this review we summarise the global chemical abundances, kinematics and structural properties that allow us to disentangle these multiple components and provide constraints to understand their origin. The investigation of both detailed and global properties of the bulge now provide us with the opportunity to characterise the bulge as observed in models, and to place the mixed component bulge scenario in the general context of external galaxies. When writing this review, we considered the perspectives of researchers working with the Milky Way and researchers working with external galaxies. It is an attempt to approach both communities for a fruitful exchange of ideas.Comment: Review article to appear in "Galactic Bulges", Editors: Laurikainen E., Peletier R., Gadotti D., Springer Publishing. 36 pages, 10 figure

Preparing nurses for COVID-19 response efforts through involvement in antimicrobial stewardship programmes

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to spread internationally with 5 593 631 cases reported globally including 353 334 deaths [ 1 ] . Its rapid emergence and dissemination have highlighted multiple areas in which competencies in antimicrobial stewardship (AMS) (the safe and effective use of antimicrobials), specifically by nurses, can support response efforts. There have been calls for nurses to be recognised as legitimate contributors to AMS team efforts [ 2 , 3 , 4 , 5 ].Unfortunately, nurse’s role in these efforts, have received minimal mention in international and national policy [ 4 , 6 , 7 , 8 , 9 , 10 ]. It is reported that nurses’ knowledge of antibiotics is poor [ 11 , 12 ], and that AMS taught in nurse undergraduate programmes is disparate or lacking [ 13 ]. To address this gap, AMS consensus based international competency statements have been developed, focussed on six domains (Infection prevention and control, antimicrobials and antimicrobial resistance, the diagnosis of infection and use of antibiotics, antimicrobial prescribing practice, person centred care, interprofessional collaborative practice), which are (seen as) priorities/minimum requirements for nurses [ 14 , 15 ]

Common variants near MC4R are associated with fat mass, weight and risk of obesity.

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits