Hierarchical accumulation of RyR post-translational modifications drives disease progression in dystrophic cardiomyopathy

AIMS:Duchenne muscular dystrophy (DMD) is a muscle disease with serious cardiac complications. Changes in Ca(2+) homeostasis and oxidative stress were recently associated with cardiac deterioration, but the cellular pathophysiological mechanisms remain elusive. We investigated whether the activity of ryanodine receptor (RyR) Ca(2+) release channels is affected, whether changes in function are cause or consequence and which post-translational modifications drive disease progression. METHODS AND RESULTS:Electrophysiological, imaging, and biochemical techniques were used to study RyRs in cardiomyocytes from mdx mice, an animal model of DMD. Young mdx mice show no changes in cardiac performance, but do so after ∼8 months. Nevertheless, myocytes from mdx pups exhibited exaggerated Ca(2+) responses to mechanical stress and 'hypersensitive' excitation-contraction coupling, hallmarks of increased RyR Ca(2+) sensitivity. Both were normalized by antioxidants, inhibitors of NAD(P)H oxidase and CaMKII, but not by NO synthases and PKA antagonists. Sarcoplasmic reticulum Ca(2+) load and leak were unchanged in young mdx mice. However, by the age of 4-5 months and in senescence, leak was increased and load was reduced, indicating disease progression. By this age, all pharmacological interventions listed above normalized Ca(2+) signals and corrected changes in ECC, Ca(2+) load, and leak. CONCLUSION:Our findings suggest that increased RyR Ca(2+) sensitivity precedes and presumably drives the progression of dystrophic cardiomyopathy, with oxidative stress initiating its development. RyR oxidation followed by phosphorylation, first by CaMKII and later by PKA, synergistically contributes to cardiac deterioration.

Hierarchical segmentation-assisted multimodal registration for MR brain images

Information theory-based metric such as mutual information (MI) is widely used as similarity measurement for multimodal registration. Nevertheless, this metric may lead to matching ambiguity for non-rigid registration. Moreover, maximization of MI alone does not necessarily produce an optimal solution. In this paper, we propose a segmentation-assisted similarity metric based on point-wise mutual information (PMI). This similarity metric, termed SPMI, enhances the registration accuracy by considering tissue classification probabilities as prior information, which is generated from an expectation maximization (EM) algorithm. Diffeomorphic demons is then adopted as the registration model and is optimized in a hierarchical framework (H-SPMI) based on different levels of anatomical structure as prior knowledge. The proposed method is evaluated using Brainweb synthetic data and clinical fMRI images. Both qualitative and quantitative assessment were performed as well as a sensitivity analysis to the segmentation error. Compared to the pure intensity-based approaches which only maximize mutual information, we show that the proposed algorithm provides significantly better accuracy on both synthetic and clinical data.

Fully Automatic Segmentation of AP Pelvis X-rays via Random Forest Regression and Hierarchical Sparse Shape Composition

Knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic and robust approach for landmarking and segmentation of both pelvis and femur in a conventional AP X-ray. Our approach is based on random forest regression and hierarchical sparse shape composition. Experiments conducted on 436 clinical AP pelvis x-rays show that our approach achieves an average point-to-curve error around 1.3 mm for femur and 2.2 mm for pelvis, both with success rates around 98%. Compared to existing methods, our approach exhibits better performance in both the robustness and the accuracy.

Biodiversity effects on nitrate concentrations in soil solution: a Bayesian model

Ecosystems are faced with high rates of species loss which has consequences for their functions and services. To assess the effects of plant species diversity on the nitrogen (N) cycle, we developed a model for monthly mean nitrate (NO3-N) concentrations in soil solution in 0-30 cm mineral soil depth using plant species and functional group richness and functional composition as drivers and assessing the effects of conversion of arable land to grassland, spatially heterogeneous soil properties, and climate. We used monthly mean NO3-N concentrations from 62 plots of a grassland plant diversity experiment from 2003 to 2006. Plant species richness (1-60) and functional group composition (1-4 functional groups: legumes, grasses, non-leguminous tall herbs, non-leguminous small herbs) were manipulated in a factorial design. Plant community composition, time since conversion from arable land to grassland, soil texture, and climate data (precipitation, soil moisture, air and soil temperature) were used to develop one general Bayesian multiple regression model for the 62 plots to allow an in-depth evaluation using the experimental design. The model simulated NO3-N concentrations with an overall Bayesian coefficient of determination of 0.48. The temporal course of NO3-N concentrations was simulated differently well for the individual plots with a maximum plot-specific Nash-Sutcliffe Efficiency of 0.57. The model shows that NO3-N concentrations decrease with species richness, but this relation reverses if more than approx. 25 % of legume species are included in the mixture. Presence of legumes increases and presence of grasses decreases NO3-N concentrations compared to mixtures containing only small and tall herbs. Altogether, our model shows that there is a strong influence of plant community composition on NO3-N concentrations.

Hierarchical self-assembly of nucleotide-appended oligopyrenotides into defined supramolecular objects

Supramolecular DNA assembly blends DNA building blocks with synthetic organic and inorganic molecules giving structural and functional advantages both to the initial self-assembly process and to the final construct. Synthetic molecules can bring a number of additional interactions into DNA nanotechnology. Incorporating extended aromatic molecules as connectors of DNA strands allows folding of these strands through π-π stacking (DNA “foldamers”). In previous work it was shown that short oligopyrenotides (phosphodiester-linked pyrene oligomers) behave as staircase-like foldamers, which cooperatively self-assemble into two-dimensional supramolecular polymers in aqueous medium. Herein, we demonstrate that a 10-mer DNA-sequence modified with 7 pyrene units (see illustration) forms dimensionally-defined supramolecular polymers under thermodynamic conditions in water. We present the self-assembly behavior, morphological studies, and the spectroscopic properties of the investigated DNA-sequences (illustrative AFM picture shown below).

Hierarchical self-assembly of nucleotide-appended oligopyrenotides into defined supramolecular objects

Supramolecular DNA assembly blends DNA building blocks with synthetic organic molecules giving structural and functional advantages. Incorporating extended aromatic molecules as connectors of DNA strands allows folding of these strands through π-π stacking (DNA 'foldamers'). In previous work it was shown that short oligopyrenotides behave as staircase-like foldamers, which cooperatively self-assemble into 2D supramolecular polymers in aqueous medium. Herein, we demonstrate that 10-mer DNA-sequence conjugated with seven pyrene unites forms dimensionally-defined supramolecular polymers under thermodynamic conditions in water. We present the self-assembly behavior, morphologycal studies (AFM and TEM), and the spectroscopic properties (UV/vis, CD) of the investigated pyrene - conjugated DNA-sequence.