The Potentials and Caveats of Mesenchymal Stromal Cell-Based Therapies in the Preterm Infant

Preponderance of proinflammatory signals is a characteristic feature of all acute and resulting long-term morbidities of the preterm infant. The proinflammatory actions are best characterized for bronchopulmonary dysplasia (BPD) which is the chronic lung disease of the preterm infant with lifelong restrictions of pulmonary function and severe consequences for psychomotor development and quality of life. Besides BPD, the immature brain, eye, and gut are also exposed to inflammatory injuries provoked by infection, mechanical ventilation, and oxygen toxicity. Despite the tremendous progress in the understanding of disease pathologies, therapeutic interventions with proven efficiency remain restricted to a few drug therapies with restricted therapeutic benefit, partially considerable side effects, and missing option of applicability to the inflamed brain. The therapeutic potential of mesenchymal stromal cells (MSCs)-also known as mesenchymal stem cells-has attracted much attention during the recent years due to their anti-inflammatory activities and their secretion of growth and development-promoting factors. Based on a molecular understanding, this review summarizes the positive actions of exogenous umbilical cord-derived MSCs on the immature lung and brain and the therapeutic potential of reprogramming resident MSCs. The pathomechanistic understanding of MSC actions from the animal model is complemented by the promising results from the first phase I clinical trials testing allogenic MSC transplantation from umbilical cord blood. Despite all the enthusiasm towards this new therapeutic option, the caveats and outstanding issues have to be critically evaluated before a broad introduction of MSC-based therapies

Almost sure stability of the Euler-Maruyama method with random variable stepsize for stochastic differential equations

In this paper, the Euler–Maruyama (EM) method with random variable stepsize is studied to reproduce the almost sure stability of the true solutions of stochastic differential equations. Since the choice of the time step is based on the current state of the solution, the time variable is proved to be a stopping time. Then the semimartingale convergence theory is employed to obtain the almost sure stability of the random variable stepsize EM solution. To our best knowledge, this is the first paper to apply the random variable stepsize (with clear proof of the stopping time) to the analysis of the almost sure stability of the EM method

Multilevel Monte Carlo methods

The author's presentation of multilevel Monte Carlo path simulation at the MCQMC 2006 conference stimulated a lot of research into multilevel Monte Carlo methods. This paper reviews the progress since then, emphasising the simplicity, flexibility and generality of the multilevel Monte Carlo approach. It also offers a few original ideas and suggests areas for future research

A Dual Fluorescence–Spin Label Probe for Visualization and Quantification of Target Molecules in Tissue by Multiplexed FLIM–EPR Spectroscopy

Simultaneous visualization and concentration quantification of molecules in biological tissue is an important though challenging goal. The advantages of fluorescence lifetime imaging microscopy (FLIM) for visualization, and electron paramagnetic resonance (EPR) spectroscopy for quantification are complementary. Their combination in a multiplexed approach promises a successful but ambitious strategy because of spin label-mediated fluorescence quenching. Here, we solved this problem and present the molecular design of a dual label (DL) compound comprising a highly fluorescent dye together with an EPR spin probe, which also renders the fluorescence lifetime to be concentration sensitive. The DL can easily be coupled to the biomolecule of choice, enabling in vivo and in vitro applications. This novel approach paves the way for elegant studies ranging from fundamental biological investigations to preclinical drug research, as shown in proof-of-principle penetration experiments in human skin ex vivo

Host preferences and differential contributions of deciduous tree species shape mycorrhizal species richness in a mixed Central European forest

Mycorrhizal species richness and host ranges were investigated in mixed deciduous stands composed of Fagus sylvatica, Tilia spp., Carpinus betulus, Acer spp., and Fraxinus excelsior. Acer and Fraxinus were colonized by arbuscular mycorrhizas and contributed 5% to total stand mycorrhizal fungal species richness. Tilia hosted similar and Carpinus half the number of ectomycorrhizal (EM) fungal taxa compared with Fagus (75 putative taxa). The relative abundance of the host tree the EM fungal richness decreased in the order Fagus > Tilia >> Carpinus. After correction for similar sampling intensities, EM fungal species richness of Carpinus was still about 30–40% lower than that of Fagus and Tilia. About 10% of the mycorrhizal species were shared among the EM forming trees; 29% were associated with two host tree species and 61% with only one of the hosts. The latter group consisted mainly of rare EM fungal species colonizing about 20% of the root tips and included known specialists but also putative non-host associations such as conifer or shrub mycorrhizas. Our data indicate that EM fungal species richness was associated with tree identity and suggest that Fagus secures EM fungal diversity in an ecosystem since it shared more common EM fungi with Tilia and Carpinus than the latter two among each other

Fully-discrete finite element approximations for a fourth-order linear stochastic parabolic equation with additive space-time white noise

We consider an initial and Dirichlet boundary value problem for a fourth-order linear stochastic parabolic equation, in one space dimension, forced by an additive space-time white noise. Discretizing the space-time white noise a modelling error is introduced and a regularized fourth-order linear stochastic parabolic problem is obtained. Fully-discrete approximations to the solution of the regularized problem are constructed by using, for discretization in space, a Galerkin finite element method based on C0 or C1 piecewise polynomials, and, for time-stepping, the Backward Euler method. We derive strong a priori estimates for the modelling error and for the approximation error to the solution of the regularized problem