25 research outputs found
Platelet Serotonin Aggravates Myocardial Ischemia/Reperfusion Injury via Neutrophil Degranulation
Background: Platelets store large amounts of serotonin that they release during thrombus formation or acute inflammation. This facilitates hemostasis and modulates the inflammatory response. Methods: Infarct size, heart function, and inflammatory cell composition were analyzed in mouse models of myocardial reperfusion injury with genetic and pharmacological depletion of platelet serotonin. These studies were complemented by in vitro serotonin stimulation assays of platelets and leukocytes in mice and men, and by measuring plasma serotonin levels and leukocyte activation in patients with acute coronary syndrome. Results: Platelet-derived serotonin induced neutrophil degranulation with release of myeloperoxidase and hydrogen peroxide (H2O2) and increased expression of membrane-bound leukocyte adhesion molecule CD11b, leading to enhanced inflammation in the infarct area and reduced myocardial salvage. In patients hospitalized with acute coronary syndrome, plasmatic serotonin levels correlated with CD11b expression on neutrophils and myeloperoxidase plasma levels. Long-term serotonin reuptake inhibition - reported to protect patients with depression from cardiovascular events - resulted in the depletion of platelet serotonin stores in mice. These mice displayed a reduction in neutrophil degranulation and preserved cardiac function. In line, patients with depression using serotonin reuptake inhibition, presented with suppressed levels of CD11b surface expression on neutrophils and lower myeloperoxidase levels in blood. Conclusions: Taken together, we identify serotonin as a potent therapeutic target in neutrophil-dependent thromboinflammation during myocardial reperfusion injury.Fil: Mauler, Maximilian. No especifĂca;Fil: Herr, Nadine. No especifĂca;Fil: Schoenichen, Claudia. No especifĂca;Fil: Witsch, Thilo. No especifĂca;Fil: Marchini, Timoteo Oscar. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Houssay. Instituto de BioquĂmica y Medicina Molecular. Universidad de Buenos Aires. Facultad Medicina. Instituto de BioquĂmica y Medicina Molecular; ArgentinaFil: HĂ€rdtner, Carmen. No especifĂca;Fil: Koentges, Christoph. No especifĂca;Fil: Kienle, Korbinian. Max Planck Institute Of Immunobiology And Epigenetics; AlemaniaFil: Ollivier, VĂ©ronique. Inserm; FranciaFil: Schell, Maximilian. No especifĂca;Fil: Dorner, Ludwig. No especifĂca;Fil: Wippel, Christopher. No especifĂca;Fil: Stallmann, Daniela. No especifĂca;Fil: Normann, Claus. No especifĂca;Fil: Bugger, Heiko. No especifĂca;Fil: Walther, Paul. Universitat Ulm; AlemaniaFil: Wolf, Dennis. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Ahrens, Ingo. No especifĂca;Fil: LĂ€mmermann, Tim. Max Planck Institute Of Immunobiology And Epigenetics; AlemaniaFil: Ho-Tin-NoĂ©, BenoĂźt. Inserm; FranciaFil: Ley, Klaus. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Bode, Christoph. No especifĂca;Fil: Hilgendorf, Ingo. No especifĂca;Fil: Duerschmied, Daniel. No especifĂca
ReSurveyGermany: Vegetation-plot time-series over the past hundred years in Germany
Vegetation-plot resurvey data are a main source of information on terrestrial biodiversity change, with records reaching back more than one century. Although more and more data from re-sampled plots have been published, there is not yet a comprehensive open-access dataset available for analysis. Here, we compiled and harmonised vegetation-plot resurvey data from Germany covering almost 100 years. We show the distribution of the plot data in space, time and across habitat types of the European Nature Information System (EUNIS). In addition, we include metadata on geographic location, plot size and vegetation structure. The data allow temporal biodiversity change to be assessed at the community scale, reaching back further into the past than most comparable data yet available. They also enable tracking changes in the incidence and distribution of individual species across Germany. In summary, the data come at a level of detail that holds promise for broadening our understanding of the mechanisms and drivers behind plant diversity change over the last century
Discourse and Regulation Failures: The Ambivalent Influence of NGOs on Political Organizations
<scp>ReSurveyEurope</scp>: A database of resurveyed vegetation plots in Europe
AbstractAimsWe introduce ReSurveyEurope â a new data source of resurveyed vegetation plots in Europe, compiled by a collaborative network of vegetation scientists. We describe the scope of this initiative, provide an overview of currently available data, governance, data contribution rules, and accessibility. In addition, we outline further steps, including potential research questions.ResultsReSurveyEurope includes resurveyed vegetation plots from all habitats. Version 1.0 of ReSurveyEurope contains 283,135 observations (i.e., individual surveys of each plot) from 79,190 plots sampled in 449 independent resurvey projects. Of these, 62,139 (78%) are permanent plots, that is, marked in situ, or located with GPS, which allow for high spatial accuracy in resurvey. The remaining 17,051 (22%) plots are from studies in which plots from the initial survey could not be exactly relocated. Four data sets, which together account for 28,470 (36%) plots, provide only presence/absence information on plant species, while the remaining 50,720 (64%) plots contain abundance information (e.g., percentage cover or coverâabundance classes such as variants of the BraunâBlanquet scale). The oldest plots were sampled in 1911 in the Swiss Alps, while most plots were sampled between 1950 and 2020.ConclusionsReSurveyEurope is a new resource to address a wide range of research questions on fineâscale changes in European vegetation. The initiative is devoted to an inclusive and transparent governance and data usage approach, based on slightly adapted rules of the wellâestablished European Vegetation Archive (EVA). ReSurveyEurope data are ready for use, and proposals for analyses of the data set can be submitted at any time to the coordinators. Still, further data contributions are highly welcome.</jats:sec
Unsupervised pattern and outlier detection for pedestrian trajectories using diffusion maps
The movement of pedestrian crowds is studied both for real-world applications and to gain fundamental scientific insights into systems of self-driven particles. Trajectory data describes the dynamics of pedestrian crowds at the level of individual movement paths. Analysing such data is a central challenge in pedestrian dynamics research, coupled with increasing data availability this implies a need for efficient methods to identify key features of the captured crowd dynamics. In this paper, we show that diffusion maps, an unsupervised manifold learning method, can be used for this purpose. We show how to build an informative feature space by defining a set of observables from trajectories. We use our diffusion map approach to analyse pedestrian movement on a stadium-shaped track, and during egress from a room, considering hundreds of trajectories for each scenario. We first verify that our diffusion map analysis can recover known leading variables that determine the system dynamics. Then, we show how our analysis facilitates a qualitative comparison of the dynamics inherent in entire data sets, by contrasting experimental with numerically simulated data. Finally, we establish how our approach can be used to automatically detect outliers that show behaviour distinct to others. These results indicate that our work can contribute a computationally efficient and unsupervised approach to analyse pedestrian dynamics without needing much prior knowledge of the data. We suggest this could be useful for automatically monitoring live data, or as an initial step to inform a subsequent analysis
Acute fluoxetine treatment induces slow rolling of leukocytes on endothelium in mice.
Activated platelets release serotonin at sites of inflammation where it acts as inflammatory mediator and enhances recruitment of neutrophils. Chronic treatment with selective serotonin reuptake inhibitors (SSRI) depletes the serotonin storage pool in platelets, leading to reduced leukocyte recruitment in murine experiments. Here, we examined the direct and acute effects of SSRI on leukocyte recruitment in murine peritonitis.C57Bl/6 and Tph1-/- (Tryptophan hydroxylase1) mice underwent acute treatment with the SSRI fluoxetine or vehicle. Serotonin concentrations were measured by ELISA. Leukocyte rolling and adhesion on endothelium was analyzed by intravital microscopy in mesentery venules with and without lipopolysaccharide challenge. Leukocyte extravasation in sterile peritonitis was measured by flow cytometry of abdominal lavage fluid.Plasma serotonin levels were elevated 2 hours after fluoxetine treatment (0.70 ± 0.1 ”g/ml versus 0.27 ± 0.1, p = 0.03, n = 14), while serum serotonin did not change. Without further stimulation, acute fluoxetine treatment increased the number of rolling leukocytes (63 ± 8 versus 165 ± 17/0.04 mm(2) min(-1)) and decreased their velocity (61 ± 6 versus 28 ± 1 ”m/s, both p<0.0001, n = 10). In Tph1-/- mice leukocyte rolling was not significantly influenced by acute fluoxetine treatment. Stimulation with lipopolysaccharide decreased rolling velocity and induced leukocyte adhesion, which was enhanced after fluoxetine pretreatment (27 ± 3 versus 36 ± 2/0.04 mm(2), p = 0.008, n = 10). Leukocyte extravasation in sterile peritonitis, however, was not affected by acute fluoxetine treatment.Acute fluoxetine treatment increased plasma serotonin concentrations and promoted leukocyte-endothelial interactions in-vivo, suggesting that serotonin is a promoter of acute inflammation. E-selectin was upregulated on endothelial cells in the presence of serotonin, possibly explaining the observed increase in leukocyte-endothelial interactions. However transmigration of neutrophils in sterile peritonitis was not affected by higher serotonin concentrations, indicating that the effect of fluoxetine was restricted to early steps in the leukocyte recruitment. Whether SSRI use in humans alters leukocyte recruitment remains to be investigated