Long-Distance Signals Are Required for Morphogenesis of the Regenerating Xenopus Tadpole Tail, as Shown by Femtosecond-Laser Ablation

tadpoles has recently emerged as an important model for these studies; we explored the role of the spinal cord during tadpole tail regeneration.Using ultrafast lasers to ablate cells, and Geometric Morphometrics to quantitatively analyze regenerate morphology, we explored the influence of different cell populations. For at least twenty-four hours after amputation (hpa), laser-induced damage to the dorsal midline affected the morphology of the regenerated tail; damage induced 48 hpa or later did not. Targeting different positions along the anterior-posterior (AP) axis caused different shape changes in the regenerate. Interestingly, damaging two positions affected regenerate morphology in a qualitatively different way than did damaging either position alone. Quantitative comparison of regenerate shapes provided strong evidence against a gradient and for the existence of position-specific morphogenetic information along the entire AP axis.We infer that there is a conduit of morphology-influencing information that requires a continuous dorsal midline, particularly an undamaged spinal cord. Contrary to expectation, this information is not in a gradient and it is not localized to the regeneration bud. We present a model of morphogenetic information flow from tissue undamaged by amputation and conclude that studies of information coming from far outside the amputation plane and regeneration bud will be critical for understanding regeneration and for translating fundamental understanding into biomedical approaches

Anisotropic nanomaterials: structure, growth, assembly, and functions

Comprehensive knowledge over the shape of nanomaterials is a critical factor in designing devices with desired functions. Due to this reason, systematic efforts have been made to synthesize materials of diverse shape in the nanoscale regime. Anisotropic nanomaterials are a class of materials in which their properties are direction-dependent and more than one structural parameter is needed to describe them. Their unique and fine-tuned physical and chemical properties make them ideal candidates for devising new applications. In addition, the assembly of ordered one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) arrays of anisotropic nanoparticles brings novel properties into the resulting system, which would be entirely different from the properties of individual nanoparticles. This review presents an overview of current research in the area of anisotropic nanomaterials in general and noble metal nanoparticles in particular. We begin with an introduction to the advancements in this area followed by general aspects of the growth of anisotropic nanoparticles. Then we describe several important synthetic protocols for making anisotropic nanomaterials, followed by a summary of their assemblies, and conclude with major applications

Data from: A convex formulation for magnetic particle imaging x-space reconstruction

Magnetic Particle Imaging (MPI) is an emerging imaging modality with exceptional promise for clinical applications in rapid angiography, cell therapy tracking, cancer imaging, and inflammation imaging. Recent publications have demonstrated quantitative mpi across rat sized fields of view with x-space reconstruction methods. Critical to any medical imaging technology is the reliability and accuracy of image reconstruction. Because the average value of the mpi signal is lost during direct-feedthrough signal filtering, mpi reconstruction algorithms must recover this zero-frequency value. Prior x-space mpi recovery techniques were limited to 1d approaches which could introduce artifacts when reconstructing a 3d image. In this paper, we formulate x-space reconstruction as a 3d convex optimization problem and apply robust a priori knowledge of image smoothness and non-negativity to reduce non-physical banding and haze artifacts. We conclude with a discussion of the powerful extensibility of the presented formulation for future applications

A Convex Formulation for Magnetic Particle Imaging X-Space Reconstruction.

Magnetic Particle Imaging (mpi) is an emerging imaging modality with exceptional promise for clinical applications in rapid angiography, cell therapy tracking, cancer imaging, and inflammation imaging. Recent publications have demonstrated quantitative mpi across rat sized fields of view with x-space reconstruction methods. Critical to any medical imaging technology is the reliability and accuracy of image reconstruction. Because the average value of the mpi signal is lost during direct-feedthrough signal filtering, mpi reconstruction algorithms must recover this zero-frequency value. Prior x-space mpi recovery techniques were limited to 1d approaches which could introduce artifacts when reconstructing a 3d image. In this paper, we formulate x-space reconstruction as a 3d convex optimization problem and apply robust a priori knowledge of image smoothness and non-negativity to reduce non-physical banding and haze artifacts. We conclude with a discussion of the powerful extensibility of the presented formulation for future applications

Experimental MPI Partial FOV Data

Experimental magnetic particle imaging partial field of view data of a coronary artery phantom and a double helix phantom

Partial field of view gridding detail.

<p>The received signal is interpolated to partial fov images using the ffr trajectory. Each <i>x</i>-axis traversal is broken into a separate partial fov image. Varying colors delimit each partial fov image. The sinusoidal pattern in the trajectory is formed due to the simultaneous <i>x</i>-axis shift field and the <i>z</i>-axis drive field.</p

Experimental MPI data from a coronary artery phantom.

<p>Images were reconstructed with the proposed reconstruction formulation and contrasted to the previous 1ddc recovery as well as no dc recovery. The imaging phantom was created by 3d printing an abs plastic coronary artery model. The reconstructed 3d dataset is shown as maximum intensity projection images. With no dc recovery, many image intensity dropouts are evident. These dropouts are corrected with dc recovery algorithms. The optimized 3d recovery contains fewer artifacts (solid arrow) and less background haze than the prior algorithm. Light deconvolution can be used to remove remaining background haze present in the reconstructed signal; however, deconvolution can lead to image dropouts (dashed arrow). The total imaging time was 10 min with a fov of 4.5 cm by 3.5 cm by 9.5 cm (<i>x</i>,<i>y</i>,<i>z</i>).</p

Experimental data illustrating proposed image reconstruction.

<p><b>(Left)</b> The measured signal is filtered and velocity compensated before gridding to partial fov images. The partial fov) images become the input to the optimization problem. <b>(Right)</b> The optimization problem formulation of dc recovery is illustrated. The forward model <b>A</b> consists of the <b>S</b> and <b>D</b> operators, where <b>S</b> is the segmentation operator and <b>D</b> is the dc removal operator. The initial estimated image is the zero vector, <i><b>ρ</b></i>₀ = <b>0</b>. The estimated image, <i><b>ρ</b></i>, is calculated and updated with each step of the iterative proximal gradient solver [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140137#pone.0140137.ref029" target="_blank">29</a>]. The optimization problem is formulated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140137#pone.0140137.e009" target="_blank">Eq 6</a>.</p

Singular values and right singular vectors, V, were calculated on A for a 1d problem where 15 pixels overlapped between adjacent partial fovs and the partial fov width was 20.

<p>The singular vectors represent the spatial <i>z</i>-axis and are shown in absolute value. The singular values demonstrate well-posed nature of the proposed reconstruction problem.</p

Field free point MPI system photo.

<p>This 7Tm^-1ffpmpi system was used to experimentally demonstrate the effectiveness of the 3d optimized reconstruction.</p