Biology subjects

Kaiser, E.

Publications and source records attributed to Kaiser, E..

3 recordsLinked to original sources

bioRxiv2025

Changes in peripheral blood leukocyte composition precede development of heart-reactive autoantibodies in patients hospitalised for acute heart failure

In a retrospective pilot study, we showed that the induction of heart-reactive autoantibodies (HRA) in the wake of acutely decompensated heart failure predicts worse outcomes. To gain deeper insights into the immunological mechanisms causing induction of HRA after heart failure decompensation we initiated the prospective Acute Heart Failure-Immunomonitoring Cohort Study (AHF-ImmunoCS). For this study, 380 patients were enrolled and will be followed up, including serial collection of biomaterials, for a period of 18 months after the index hospitalisation for AHF. Analysis of AHF-ImmunoCS samples obtained at baseline and at 6-month follow-up from 110 patients showed de novo induction of HRA - as detected by indirect immunofluorescence (IFT) - in 21% of patients (previously published percentage: 32%). The IFT results did not reflect induction of broad anti-heart autoimmunity as autoantibodies against other cardiac antigens like Troponin I3 or Myosin Light Chain 7 were not induced in parallel. To understand what drives HRA induction in these patients we longitudinally immunophenotyped peripheral blood leukocytes at baseline, 6-week and 6-month follow-up by high-resolution spectral flow cytometry. Among lymphocytes, induction of HRA in the wake of acute decompensation of heart failure was associated with a higher proportion of CD4+ T cells among lymphocytes, more CD45RA+ CCR7+ naive conventional, i.e. non-regulatory, and more CXCR3+ CCR4- Th1 cells among CD4+ T cells at baseline. Among myeloid cells, there were no differences at baseline between patients going on to develop HRA and those that did not. However, patients developing HRA had higher proportions of eosinophils (six-month follow-up) and lower proportions of Arginase+ HLA-DR- polymorphnuclear myeloid-derived suppressor cells among myeloid cells (six-week and six-month follow-up). Our data, thus, implicate that alterations in the composition of both the lymphoid and the myeloid compartments might drive HRA induction which impacts disease progression and prognosis in AHF.

immunology↗

bioRxiv2024

Viewing stomata in action: Autonomous in planta imaging of individual stomatal movement links morphology and kinetics

Stomata regulate plant gas exchange under changing environments, but observations of the dynamics of single stomata in planta are sparse. We developed a compact microscope system that can measure the kinetics of tens of stomata in planta simultaneously, with sub-minute time resolution. Dark field imaging with green light was used to create 3D stacks from which 2D surface projection were constructed to resolve stomatal apertures within the field of view. Stomatal dynamics of Chrysanthemum morifolium (Chrysanthemum) and Zea Mays (Maize) under dynamically changing light intensity were categorized, and a kinetic model was fitted to the data for quantitative comparison. In addition, we also resolved dynamics of the surface position of the leaf, related to dynamics of leaf thickness or bending. Maize stomata oscillated frequently between open and closed states under constant growth light and these oscillating stomata responded faster to changes in light than non-oscillating stomata at the same aperture. The slow closure of Chrysanthemum stomata reduced water use efficiency (WUE). Over 50% showed delayed or partial closure, leading to unnecessarily large apertures after reduced light. Stomata with larger apertures had more lag and similar closure speeds compared to those with smaller apertures and lag, further reducing WUE. In contrast, maize stomata with larger apertures closed faster, with no lag. In conclusion, our new system enables fine mapping of the heterogeneity of movement in neighboring stomata, providing new insights on the relations between stomatal dimensions, relative position and aperture changes under fluctuating light intensity.

plant biology↗

bioRxiv2022

A small dynamic leaf-level model predicting photosynthesis in greenhouse tomatoes

The conversion of supplemental greenhouse light energy into biomass is not always optimal. Recent trends in global energy prices and discussions on climate change highlight the need to reduce our energy footprint associated with the use of supplemental light in greenhouse crop production. This can be achieved by implementing "smart" lighting regimens which in turn rely on a good understanding of how fluctuating light influences photosynthetic physiology. Here, a simple fit-for-purpose dynamic model is presented. It accurately predicts net leaf photosynthesis under natural fluctuating light. It comprises two ordinary differential equations predicting: 1) the total stomatal conductance to CO2 diffusion and 2) the CO2 concentration inside a leaf. It contains elements of the Farquhar-von Caemmerer-Berry model and the successful incorporation of this model suggests that for tomato (Solanum lycopersicum L.), it is sufficient to assume that Rubisco remains activated despite rapid fluctuations in irradiance. Furthermore, predictions of the net photosynthetic rate under both 400ppm and enriched 800ppm ambient CO2 concentrations indicate a strong correlation between the dynamic rate of photosynthesis and the rate of electron transport. Finally, we are able to indicate whether dynamic photosynthesis is Rubisco or electron transport rate limited. Author summaryThe cultivation of greenhouse crops under optimised conditions will become increasingly important, with supplemental lighting playing a vital role. However, converting light energy into plant photosynthesis is not always optimal. A potential venue that may lead to the efficient conversion of light energy involves a model-based implementation of "smart" lighting control strategy. This approach does however necessitate a good understanding of how plants harness light energy under natural fluctuating irradiance. Accordingly, as a first step, we have developed a small leaf-level model that predicts dynamic photosynthesis in natural fluctuating light. It may potentially be used in future supplemental light control applications.

plant biology↗