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- Mesenchymal stem cells (2)
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Controlling mesenchymal stem cells (MSCs) behavior is necessary to fully exploit their therapeutic potential. Various approaches are employed to effectively influence the migration capacity of MSCs. Here, topographic microstructures with different microscale roughness were created on polystyrene (PS) culture vessel surfaces as a feasible physical preconditioning strategy to modulate MSC migration. By analyzing trajectories of cells migrating after reseeding, we demonstrated that the mobilization velocity of human adipose derived mesenchymal stem cells (hADSCs) could be promoted by and persisted after brief preconditioning with the appropriate microtopography. Moreover, the elevated activation levels of focal adhesion kinase (FAK) and mitogen-activated protein kinase (MAPK) in hADSCs were also observed during and after the preconditioning process. These findings underline the potential enhancement of in vivo therapeutic efficacy in regenerative medicine via transplantation of topographic microstructure preconditioned stem cells.
Polymeric matrices mimicking multiple functions of the ECM are expected to enable a material induced regeneration of tissues. Here, we investigated the adipogenic differentiation of human adipose derived mesenchymal stem cells (hADSCs) in a 3D architectured gelatin based hydrogel (ArcGel) prepared from gelatin and L-lysine diisocyanate ethyl ester (LDI) in an one-step process, in which the formation of an open porous morphology and the chemical network formation were integrated. The ArcGel was designed to support adipose tissue regeneration with its 3D porous structure, high cell biocompatibility, and mechanical properties compatible with human subcutaneous adipose tissue. The ArcGel could support initial cell adhesion and survival of hADSCs. Under static culture condition, the cells could migrate into the inner part of the scaffold with a depth of 840 +/- 120 mu m after 4 days, and distributed in the whole scaffold (2mm in thickness) within 14 days. The cells proliferated in the scaffold and the fold increase of cell number after 7 days of culture was 2.55 +/- 0.08. The apoptotic rate of hADSCs in the scaffold was similar to that of cells maintained on tissue culture plates. When cultured in adipogenic induction medium, the hADSCs in the scaffold differentiated into adipocytes with a high efficiency (93 +/- 1%). Conclusively, this gelatin based 3D scaffold presented high cell compatibility for hADSC cultivation and differentiation, which could serve as a potential implant material in clinical applications for adipose tissue reparation and regeneration.
The link between streamflow extremes and climatology has been widely studied in recent decades. However, a study investigating the effect of large-scale circulation variations on the distribution of seasonal discharge extremes at the European level is missing. Here we fit a climate-informed generalized extreme value (GEV) distribution to about 600 streamflow records in Europe for each of the standard seasons, i.e., to winter, spring, summer and autumn maxima, and compare it with the classical GEV distribution with parameters invariant in time. The study adopts a Bayesian framework and covers the period 1950 to 2016. Five indices with proven influence on the European climate are examined independently as covariates, namely the North Atlantic Oscillation (NAO), the east Atlantic pattern (EA), the east Atlantic-western Russian pattern (EA/WR), the Scandinavia pattern (SCA) and the polar-Eurasian pattern (POL). It is found that for a high percentage of stations the climate-informed model is preferred to the classical model. Particularly for NAO during winter, a strong influence on streamflow extremes is detected for large parts of Europe (preferred to the classical GEV distribution for 46% of the stations). Climate-informed fits are characterized by spatial coherence and form patterns that resemble relations between the climate indices and seasonal precipitation, suggesting a prominent role of the considered circulation modes for flood generation. For certain regions, such as northwestern Scandinavia and the British Isles, yearly variations of the mean seasonal climate indices result in considerably different extreme value distributions and thus in highly different flood estimates for individual years that can also persist for longer time periods.
Especially for extreme precipitation or floods, there is considerable spatial and temporal variability in long term trends or in the response of station time series to large-scale climate indices. Consequently, identifying trends or sensitivity of these extremes to climate parameters can be marked by high uncertainty. When one develops a nonstationary frequency analysis model, a key step is the identification of potential trends or effects of climate indices on the station series. An automatic clustering procedure that effectively pools stations where there are similar responses is desirable to reduce the estimation variance, thus improving the identification of trends or responses, and accounting for spatial dependence. This paper presents a new hierarchical Bayesian approach for exploring homogeneity of response in large area data sets, through a multicomponent mixture model. The approach allows the reduction of uncertainties through both full pooling and partial pooling of stations across automatically chosen subsets of the data. We apply the model to study the trends in annual maximum daily stream flow at 68 gauges over Germany. The effects of changing the number of clusters and the parameters used for clustering are demonstrated. The results show that there are large, mainly upward trends in the gauges of the River Rhine Basin in Western Germany and along the main stream of the Danube River in the south, while there are also some small upward trends at gauges in Central and Northern Germany.