The MEF2-class IIa histone deacetylase (HDAC) axis operates in several differentiation pathways and in numerous adaptive responses. We show here that nuclear active HDAC4 and HDAC7 display transforming capability. HDAC4 oncogenic potential depends on the repression of a limited set of genes, most of which are MEF2 targets. Genes verified as targets of the MEF2-HDAC axis are also under the influence of the phosphatidylinositol 3-kinase (PI3K)/Akt pathway that affects MEF2 protein stability. A signature of MEF2 target genes identified by this study is recurrently repressed in soft tissue sarcomas. Correlation studies depicted two distinct groups of soft tissue sarcomas: one in which MEF2 repression correlates with PTEN downregulation and a second group in which MEF2 repression correlates with HDAC4 levels. Finally, simultaneous pharmacological inhibition of the PI3K/Akt pathway and of MEF2-HDAC interaction shows additive effects on the transcription of MEF2 target genes and on sarcoma cells proliferation. Overall, our work pinpoints an important role of the MEF2-HDAC class IIa axis in tumorigenesis.

[1] The seeds of many aquatic plants are buoyant and thus transported at the water surface, where they are subject to surface tension that may enhance their retention within emergent vegetation. Specifically, seeds may be trapped by surface tension (i.e., by the Cheerios effect) at the surface-piercing interface of the vegetation. In this work we develop a physical model that predicts this mechanism of seed trapping, advancing the model proposed by Defina and Peruzzo (2010) that describes the propagation of floating particles through emergent vegetation. The emergent vegetation is simulated as an array of cylinders, randomly arranged, with the mean gap between cylinders far greater than the particle size, which prevents the trapping of particles between pairs of cylinders, referred to as net trapping. Laboratory experiments are used to guide and validate the model. The model also has good agreement with experimental data available in the literature for real seeds and more complex plant morphology.Citation: Peruzzo, P., A. Defina, and H. Nepf (2012), Capillary trapping of buoyant particles within regions of emergent vegetation, Water Resour. Res., 48, W07512,

[1] In this paper we present early results of laboratory experiments to investigate the transport and diffusion of floating particles (e.g., buoyant seeds) in open channel flow with emergent vegetation. The experiments are aimed at providing a better understanding of the relevant particle-vegetation interaction mechanisms responsible for the observed diffusion processes. Qualitative observational data are then used to set up a stochastic model for floating particle transport and diffusion. Quantitative observations, such as the distribution of distances travelled by a particle before it is permanently captured by a plant and the arrival-time distributions at prescribed cross sections along the vegetated test section, are instead used to calibrate and validate the model. The comparison between theoretical predictions and experimental results is quite satisfactory and suggests that the observed relevant aspects of the particle-vegetation interaction processes are properly described in the model.

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[1] In this paper we present the results of a new laboratory investigation aimed at providing a better understanding of the transport and diffusion processes of floating particles (e.g., buoyant seeds) in open channel flow with emergent vegetation. The experiments are designed primarily to study the influence of vegetation density and flow velocity on the relevant interaction mechanisms between particles and vegetation. The aim is also to ascertain the validity of a stochastic model recently proposed by Defina and Peruzzo (2010). We find that (1) the proper definition of plant spacing is given as 1/n p d p , with d p being the plant diameter and n p being the number of plants per unit area, (2) the particle retention time distribution can be satisfactorily approximated by a weighted combination of two exponential distributions, (3) flow velocity has a significant influence on the retention time and on the efficiency of the different trapping mechanisms, and (4) vegetation pattern and density have a minor influence on the probability of capture and on the retention time of particles. Indeed, the comparison between model predictions and experimental results is satisfactory and suggests that the observed relevant aspects of the particle-vegetation interaction processes are properly described by the model.