Overview of the MOSAiC expedition - Atmosphere

With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic

Food insecurity in relation to changes in hemoglobin A1c, self-efficacy, and fruit/vegetable intake during a diabetes educational intervention.

ObjectiveFood insecurity is hypothesized to make diabetes self-management more difficult. We conducted a longitudinal assessment of food insecurity with several diabetes self-care measures.Research design and methodsWe conducted a secondary, observational analysis of 665 low-income patients with diabetes, all of whom received self-management support as part of a larger diabetes educational intervention. We analyzed baseline food insecurity (measured by the U.S. Department of Agriculture Food Security module) in relation to changes in hemoglobin A1c (HbA1c) as well as self-reported diabetes self-efficacy and daily fruit and vegetable intake. We examined longitudinal differences using generalized estimating equation linear regression models, controlling for time, age, sex, race, income, and intervention arm.ResultsOverall, 57% of the sample had an income <$15,000. Participants who were food insecure (33%) were younger, had less income, and were more likely to be unemployed compared with participants who were food secure. At baseline, those who were food insecure had higher mean HbA1c values (8.4% vs. 8.0%) and lower self-efficacy and fruit and vegetable intake than those who were food secure (all P < 0.05). Compared with food-secure individuals, participants who were food insecure had significantly greater improvements in HbA1c over time (0.38% decrease compared with 0.01% decrease; P value for interaction <0.05) as well as in self-efficacy (P value for interaction <0.01). There was no significant difference in HbA1c by food security status at follow-up.ConclusionsParticipants experiencing food insecurity had poorer diabetes-related measures at baseline but made significant improvements in HbA1c and self-efficacy. Low-income patients who were food insecure may be particularly receptive to diabetes self-management support, even if interventions are not explicitly structured to address finances or food security challenges

Overview of the MOSAiC expedition:atmosphere

Abstract With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore crosscutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic

Tales of diversity: Genomic and morphological characteristics of forty-six <i>Arthrobacter</i> phages

<div><p>The vast bacteriophage population harbors an immense reservoir of genetic information. Almost 2000 phage genomes have been sequenced from phages infecting hosts in the phylum Actinobacteria, and analysis of these genomes reveals substantial diversity, pervasive mosaicism, and novel mechanisms for phage replication and lysogeny. Here, we describe the isolation and genomic characterization of 46 phages from environmental samples at various geographic locations in the U.S. infecting a single <i>Arthrobacter</i> sp. strain. These phages include representatives of all three virion morphologies, and Jasmine is the first sequenced podovirus of an actinobacterial host. The phages also span considerable sequence diversity, and can be grouped into 10 clusters according to their nucleotide diversity, and two singletons each with no close relatives. However, the clusters/singletons appear to be genomically well separated from each other, and relatively few genes are shared between clusters. Genome size varies from among the smallest of siphoviral phages (15,319 bp) to over 70 kbp, and G+C contents range from 45–68%, compared to 63.4% for the host genome. Although temperate phages are common among other actinobacterial hosts, these <i>Arthrobacter</i> phages are primarily lytic, and only the singleton Galaxy is likely temperate.</p></div

Genome organization of <i>Arthrobacter</i> phage Amigo, Cluster AQ.

<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0180517#pone.0180517.g005" target="_blank">Fig 5</a> for details.</p

Genome organization of <i>Arthrobacter</i> phage Maggie, Cluster AN.

<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0180517#pone.0180517.g005" target="_blank">Fig 5</a> for details.</p