Design and rationale of haemodynamic guidance with CardioMEMS in patients with a left ventricular assist device: the HEMO-VAD pilot study

AimsWe aim to study the feasibility and clinical value of pulmonary artery pressure monitoring with the CardioMEMS™device in order to optimize and guide treatment in patients with a HeartMate3left ventricular assist device (LVAD).Methods and resultsIn this single-centre, prospective pilot study, we will include10consecutive patients with New YorkHeart Association Class IIIb or IV with Interagency Registry for Mechanically Assisted Circulatory Support Classes2–5scheduledfor implantation of a HeartMate3LVAD. Prior to LVAD implantation, patients will receive a CardioMEMS sensor, for dailypulmonary pressure readings. The haemodynamic information provided by the CardioMEMS will be used to improvehaemodynamic status prior to LVAD surgery and optimize the timing of LVAD implantation. Post-LVAD implantation, thehaemodynamic changes will be assessed for additive value in detecting potential complications in an earlier stage (bleedingand tamponade). During the outpatient clinic phase, we will assess whether the haemodynamic feedback can optimize pumpsettings, detect potential complications, and further tailor the clinical management of these patients.ConclusionsThe HEMO-VAD study is thefirst prospective pilot study to explore the safety and feasibility of usingCardioMEMS for optimization of LVAD therapy with additional (remote) haemodynamic information

Neutrino oscillation studies with IceCube-DeepCore

AbstractIceCube, a gigaton-scale neutrino detector located at the South Pole, was primarily designed to search for astrophysical neutrinos with energies of PeV and higher. This goal has been achieved with the detection of the highest energy neutrinos to date. At the other end of the energy spectrum, the DeepCore extension lowers the energy threshold of the detector to approximately 10 GeV and opens the door for oscillation studies using atmospheric neutrinos. An analysis of the disappearance of these neutrinos has been completed, with the results produced being complementary with dedicated oscillation experiments. Following a review of the detector principle and performance, the method used to make these calculations, as well as the results, is detailed. Finally, the future prospects of IceCube-DeepCore and the next generation of neutrino experiments at the South Pole (IceCube-Gen2, specifically the PINGU sub-detector) are briefly discussed

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives