Patiromer Facilitates Angiotensin Inhibitor and Mineralocorticoid Antagonist Therapies in Patients With Heart Failure and Hyperkalemia

Background: Hyperkalemia (HK) is associated with suboptimal renin–angiotensin system (RAS) inhibitor and mineralocorticoid receptor antagonist (MRA) use in heart failure with reduced ejection fraction (HFrEF). Objectives: This study sought to assess characteristics and RAS inhibitor/MRA use in patients receiving patiromer during the DIAMOND (Patiromer for the Management of Hyperkalemia in Subjects Receiving RAASi Medications for the Treatment of Heart Failure) run-in phase. Methods: Patients with HFrEF and HK or past HK entered a run-in phase of ≤12 weeks with patiromer-facilitated RAS inhibitor/MRA optimization to achieve ≥50% recommended RAS inhibitor dose, 50 mg/d MRA, and normokalemia. Patients achieving these criteria (randomized group) were compared with the run-in failure group (patients not meeting the randomization criteria). Results: Of 1,038 patients completing the run-in, 878 (84.6%) were randomized and 160 (15.4%) were run-in failures. Overall, 422 (40.7%) had HK entering run-in with a similar frequency in the randomized and run-in failure groups (40.3% vs 42.5%; P = 0.605). From start to the end of run-in, in the randomized group, an increase was observed in target RAS inhibitor and MRA use in patients with HK (RAS inhibitor: 76.8% to 98.6%; MRA: 35.9% to 98.6%) and past HK (RAS inhibitor: 60.5% to 98.1%; MRA: 15.6% to 98.7%). Despite not meeting the randomization criteria, an increase after run-in was observed in the run-in failure group in target RAS inhibitor (52.5% to 70.6%) and MRA use (15.0% to 48.1%). This increase was observed in patients with HK (RAS inhibitor: 51.5% to 64.7%; MRA: 19.1% to 39.7%) and past HK (RAS inhibitor: 53.3% to 75.0%; MRA: 12.0% to 54.3%). Conclusions: In patients with HFrEF and HK or past HK receiving suboptimal RAS inhibitor/MRA therapy, RAS inhibitor/MRA optimization increased during patiromer-facilitated run-in.</p

Risk Factors Associated With Severe Hypoglycemia in Older Adults With Type 1 Diabetes

OBJECTIVE Severe hypoglycemia is common in older adults with long-standing type 1 diabetes, but little is known about factors associated with its occurrence

The Near Infrared Imager and Slitless Spectrograph for the James Webb Space Telescope. IV. Aperture Masking Interferometry

The James Webb Space Telescope’s Near Infrared Imager and Slitless Spectrograph (JWST-NIRISS) flies a 7-hole non-redundant mask (NRM), the first such interferometer in space, operating at 3-5 μm wavelengths, and a bright limit of ≃4 mag in W2. We describe the NIRISS Aperture Masking Interferometry (AMI) mode to help potential observers understand its underlying principles, present some sample science cases, explain its operational observing strategies, indicate how AMI proposals can be developed with data simulations, and how AMI data can be analyzed. We also present key results from commissioning AMI. Since the allied Kernel Phase Imaging (KPI) technique benefits from AMI operational strategies, we also cover NIRISS KPI methods and analysis techniques, including a new user-friendly KPI pipeline. The NIRISS KPI bright limit is ≃8 W2 (4.6 μm) magnitudes. AMI NRM and KPI achieve an inner working angle of ∼70 mas, which is well inside the ∼400 mas NIRCam inner working angle for its circular occulter coronagraphs at comparable wavelengths

The Near Infrared Imager and Slitless Spectrograph for the James Webb Space Telescope. IV. Aperture Masking Interferometry

The James Webb Space Telescope’s Near Infrared Imager and Slitless Spectrograph (JWST-NIRISS) flies a 7-hole non-redundant mask (NRM), the first such interferometer in space, operating at 3-5 μm wavelengths, and a bright limit of ≃4 mag in W2. We describe the NIRISS Aperture Masking Interferometry (AMI) mode to help potential observers understand its underlying principles, present some sample science cases, explain its operational observing strategies, indicate how AMI proposals can be developed with data simulations, and how AMI data can be analyzed. We also present key results from commissioning AMI. Since the allied Kernel Phase Imaging (KPI) technique benefits from AMI operational strategies, we also cover NIRISS KPI methods and analysis techniques, including a new user-friendly KPI pipeline. The NIRISS KPI bright limit is ≃8 W2 (4.6 μm) magnitudes. AMI NRM and KPI achieve an inner working angle of ∼70 mas, which is well inside the ∼400 mas NIRCam inner working angle for its circular occulter coronagraphs at comparable wavelengths.</p

The Near Infrared Imager and Slitless Spectrograph for the James Webb Space Telescope. IV. Aperture Masking Interferometry

The James Webb Space Telescope’s Near Infrared Imager and Slitless Spectrograph (JWST-NIRISS) flies a 7-hole non-redundant mask (NRM), the first such interferometer in space, operating at 3-5 μm wavelengths, and a bright limit of ≃4 mag in W2. We describe the NIRISS Aperture Masking Interferometry (AMI) mode to help potential observers understand its underlying principles, present some sample science cases, explain its operational observing strategies, indicate how AMI proposals can be developed with data simulations, and how AMI data can be analyzed. We also present key results from commissioning AMI. Since the allied Kernel Phase Imaging (KPI) technique benefits from AMI operational strategies, we also cover NIRISS KPI methods and analysis techniques, including a new user-friendly KPI pipeline. The NIRISS KPI bright limit is ≃8 W2 (4.6 μm) magnitudes. AMI NRM and KPI achieve an inner working angle of ∼70 mas, which is well inside the ∼400 mas NIRCam inner working angle for its circular occulter coronagraphs at comparable wavelengths

The Near Infrared Imager and Slitless Spectrograph for the James Webb Space Telescope. IV. Aperture Masking Interferometry

The James Webb Space Telescope’s Near Infrared Imager and Slitless Spectrograph (JWST-NIRISS) flies a 7-hole non-redundant mask (NRM), the first such interferometer in space, operating at 3-5 μm wavelengths, and a bright limit of ≃4 mag in W2. We describe the NIRISS Aperture Masking Interferometry (AMI) mode to help potential observers understand its underlying principles, present some sample science cases, explain its operational observing strategies, indicate how AMI proposals can be developed with data simulations, and how AMI data can be analyzed. We also present key results from commissioning AMI. Since the allied Kernel Phase Imaging (KPI) technique benefits from AMI operational strategies, we also cover NIRISS KPI methods and analysis techniques, including a new user-friendly KPI pipeline. The NIRISS KPI bright limit is ≃8 W2 (4.6 μm) magnitudes. AMI NRM and KPI achieve an inner working angle of ∼70 mas, which is well inside the ∼400 mas NIRCam inner working angle for its circular occulter coronagraphs at comparable wavelengths.</p

The Near Infrared Imager and Slitless Spectrograph for the James Webb Space Telescope -- IV. Aperture Masking Interferometry

The James Webb Space Telescope's Near Infrared Imager and Slitless Spectrograph (JWST-NIRISS) flies a 7-hole non-redundant mask (NRM), the first such interferometer in space, operating at 3-5 \micron~wavelengths, and a bright limit of $\simeq 4$ magnitudes in W2. We describe the NIRISS Aperture Masking Interferometry (AMI) mode to help potential observers understand its underlying principles, present some sample science cases, explain its operational observing strategies, indicate how AMI proposals can be developed with data simulations, and how AMI data can be analyzed. We also present key results from commissioning AMI. Since the allied Kernel Phase Imaging (KPI) technique benefits from AMI operational strategies, we also cover NIRISS KPI methods and analysis techniques, including a new user-friendly KPI pipeline. The NIRISS KPI bright limit is $\simeq 8$ W2 magnitudes. AMI (and KPI) achieve an inner working angle of $\sim 70$ mas that is well inside the $\sim 400$ mas NIRCam inner working angle for its circular occulter coronagraphs at comparable wavelengths.Comment: 30 pages, 10 figure

Distribution maps of vegetation alliances in Europe

Aim The first comprehensive checklist of European phytosociological alliances, orders and classes (EuroVegChecklist) was published by Mucina et al. (2016, Applied Vegetation Science, 19 (Suppl. 1), 3–264). However, this checklist did not contain detailed information on the distribution of individual vegetation types. Here we provide the first maps of all alliances in Europe. Location Europe, Greenland, Canary Islands, Madeira, Azores, Cyprus and the Caucasus countries. Methods We collected data on the occurrence of phytosociological alliances in European countries and regions from literature and vegetation-plot databases. We interpreted and complemented these data using the expert knowledge of an international team of vegetation scientists and matched all the previously reported alliance names and concepts with those of the EuroVegChecklist. We then mapped the occurrence of the EuroVegChecklist alliances in 82 territorial units corresponding to countries, large islands, archipelagos and peninsulas. We subdivided the mainland parts of large or biogeographically heterogeneous countries based on the European biogeographical regions. Specialized alliances of coastal habitats were mapped only for the coastal section of each territorial unit. Results Distribution maps were prepared for 1,105 alliances of vascular-plant dominated vegetation reported in the EuroVegChecklist. For each territorial unit, three levels of occurrence probability were plotted on the maps: (a) verified occurrence; (b) uncertain occurrence; and (c) absence. The maps of individual alliances were complemented by summary maps of the number of alliances and the alliance–area relationship. Distribution data are also provided in a spreadsheet. Conclusions The new map series represents the first attempt to characterize the distribution of all vegetation types at the alliance level across Europe. There are still many knowledge gaps, partly due to a lack of data for some regions and partly due to uncertainties in the definition of some alliances. The maps presented here provide a basis for future research aimed at filling these gaps

Multiband GPI imaging of the HR 4796A debris disk

Stars and planetary system

Measurements of differential production cross sections for a Z boson in association with jets in pp collisions at root s=8 TeV

Peer reviewe