Ascending thoracic aorta dimension and outcomes in acute type B dissection (from the International Registry of Acute Aortic Dissection [IRAD])

It is not well known if the size of the ascending thoracic aorta at presentation predicts features of presentation, management, and outcomes in patients with acute type B aortic dissection. The International Registry of Acute Aortic Dissection (IRAD) database was queried for all patients with acute type B dissection who had documentation of ascending thoracic aortic size at time of presentation. Patients were categorized according to ascending thoracic aortic diameters ≤4.0, 4.1 to 4.5, and ≥4.6 cm. Four hundred eighteen patients met inclusion criteria; 291 patients (69.6%) were men with a mean age of 63.2 ± 13.5 years. Ascending thoracic aortic diameter ≤4.0 cm was noted in 250 patients (59.8%), 4.1 to 4.5 cm in 105 patients (25.1%), and ≥4.6 cm in 63 patients (15.1%). Patients with an ascending thoracic aortic diameter ≥4.6 cm were more likely to be men (p = 0.01) and have Marfan syndrome (p <0.001) and known bicuspid aortic valve disease (p = 0.003). In patients with an ascending thoracic aorta ≥4.1 cm, there was an increased incidence of surgical intervention (p = 0.013). In those with an ascending thoracic aorta ≥4.6 cm, the root, ascending aorta, arch, and aortic valve were more often involved in surgical repair. Patients with an ascending thoracic aorta ≤4.0 were more likely to have endovascular therapy than those with larger ascending thoracic aortas (p = 0.009). There was no difference in overall mortality or cause of death. In conclusion, ascending thoracic aortic enlargement in patients with acute type B aortic dissection is common. Although its presence does not appear to predict an increased risk of mortality, it is associated with more frequent open surgical intervention that often involves replacement of the proximal aorta. Those with smaller proximal aortas are more likely to receive endovascular therapy.

Simultaneous Multiscale Polyaffine Registration by Incorporating Deformation Statistics

Locally affine (polyaffine) image registration methods capture intersubject non-linear deformations with a low number of parameters, while providing an intuitive interpretation for clinicians. Considering the mandible bone, anatomical shape differences can be found at different scales, e.g. left or right side, teeth, etc. Classically, sequential coarse to fine registration are used to handle multiscale deformations, instead we propose a simultaneous optimization of all scales. To avoid local minima we incorporate a prior on the polyaffine transformations. This kind of groupwise registration approach is natural in a polyaffine context, if we assume one configuration of regions that describes an entire group of images, with varying transformations for each region. In this paper, we reformulate polyaffine deformations in a generative statistical model, which enables us to incorporate deformation statistics as a prior in a Bayesian setting. We find optimal transformations by optimizing the maximum a posteriori probability. We assume that the polyaffine transformations follow a normal distribution with mean and concentration matrix. Parameters of the prior are estimated from an initial coarse to fine registration. Knowing the region structure, we develop a blockwise pseudoinverse to obtain the concentration matrix. To our knowledge, we are the first to introduce simultaneous multiscale optimization through groupwise polyaffine registration. We show results on 42 mandible CT images.

Multiscale Characterization of Acrylic Bone Cement Modified with Functionalized Mesoporous Silica Nanoparticles

Acrylic bone cement is widely used to anchor orthopedic implants to bone and mechanical failure of the cement mantle surrounding an implant can contribute to aseptic loosening. In an effort to enhance the mechanical properties of bone cement, a variety of nanoparticles and fibers can be incorporated into the cement matrix. Mesoporous silica nanoparticles (MSNs) are a class of particles that display high potential for use as reinforcement within bone cement. Therefore, the purpose of this study was to quantify the impact of modifying an acrylic cement with various low-loadings of mesoporous silica. Three types of MSNs (one plain variety and two modified with functional groups) at two loading ratios (0.1 and 0.2 wt/wt) were incorporated into a commercially available bone cement. The mechanical properties were characterized using four-point bending, microindentation and nanoindentation (static, stress relaxation, and creep) while material properties were assessed through dynamic mechanical analysis, differential scanning calorimetry, thermogravimetric analysis, FTIR spectroscopy, and scanning electron microscopy. Four-point flexural testing and nanoindentation revealed minimal impact on the properties of the cements, except for several changes in the nano-level static mechanical properties. Conversely, microindentation testing demonstrated that the addition of MSNs significantly increased the microhardness. The stress relaxation and creep properties of the cements measured with nanoindentation displayed no effect resulting from the addition of MSNs. The measured material properties were consistent among all cements. Analysis of scanning electron micrographs images revealed that surface functionalization enhanced particle dispersion within the cement matrix and resulted in fewer particle agglomerates. These results suggest that the loading ratios of mesoporous silica used in this study were not an effective reinforcement material. Future work should be conducted to determine the impact of higher MSN loading ratios and alternative functional groups. (C) 2014 Elsevier Ltd. All rights reserved.

A novel computer simulation method for simulating the multiscale transduction dynamics of signal proteins

Signal proteins are able to adapt their response to a change in the environment, governing in this way a broad variety of important cellular processes in living systems. While conventional molecular-dynamics (MD) techniques can be used to explore the early signaling pathway of these protein systems at atomistic resolution, the high computational costs limit their usefulness for the elucidation of the multiscale transduction dynamics of most signaling processes, occurring on experimental timescales. To cope with the problem, we present in this paper a novel multiscale-modeling method, based on a combination of the kinetic Monte-Carlo- and MD-technique, and demonstrate its suitability for investigating the signaling behavior of the photoswitch light-oxygen-voltage-2-Jα domain from Avena Sativa (AsLOV2-Jα) and an AsLOV2-Jα-regulated photoactivable Rac1-GTPase (PA-Rac1), recently employed to control the motility of cancer cells through light stimulus. More specifically, we show that their signaling pathways begin with a residual re-arrangement and subsequent H-bond formation of amino acids near to the flavin-mononucleotide chromophore, causing a coupling between β-strands and subsequent detachment of a peripheral α-helix from the AsLOV2-domain. In the case of the PA-Rac1 system we find that this latter process induces the release of the AsLOV2-inhibitor from the switchII-activation site of the GTPase, enabling signal activation through effector-protein binding. These applications demonstrate that our approach reliably reproduces the signaling pathways of complex signal proteins, ranging from nanoseconds up to seconds at affordable computational costs.