Ex situ bioengineering of the rat thyroid using as a scaffold the three-dimensional (3D) decellularized matrix of the glandular lobe: clues to the organomorphic principle

Recently, we designed a bioreactor system for bioengineering ex situ (i.e. on the laboratory bench) a bioartificial thyroid gland suitable for transplantation. It is based on the organomorphic principle, i.e. the bioreactor mimics the macro-microscopic architecture of the thyroid stromal-vascular scaffold (SVS). To prove the reliability of this approach, we have initiated a pilot study using as a model the rat thyroid, and its natural decellularized 3D matrix to be eventually recellularized up to formation of a viable 3D thyroid lobe ex situ. Sprague-Dawley male rats (220-240 g) were used as thyroid donors. After penthobarbital anesthesia, rats were thyroidectomised and thyroid matrixes obtained by decellularization of the native SVS. Initially, we applied a sequence of liquid N2 freezing at - 80°C / thawing at 4°C for a total of 72 h, various washings with 0.02% trypsin / 0.05% EDTA for 1 h at 37°C, 3% Triton X-100 for 72 h at 4°C, and 4% deoxycholic acid for 24 h at 4°C, followed by sterilization with 0.1% peracetic acid, and 1% penicillin / streptomycin / fungizone for 24 h. Test matrixes were made electrondense with uranium / bismuth / lead counterstaining, and analyzed by microtomography (microTC). Primary thyroid cultures were prepared using enzymatic breaking of the native thyroid tissue. Cells were seeded at 19.000 / cm 2, and grown 72 h in low-glucose DMEM supplemented with 10% FBS / 5% FCS. Following trypsinization, 450.000 cells were harvested to coat the inner surface of the matrix. After 7 and 14 days, colonized matrixes were fixed in aldheydes and processed for light (LM), transmission (TEM) and scanning electron (SEM) microscopy. Culture supernatants were collected every 48 h, and thyroid hormones assessed with chemiluminescent immunoassays. Complete decellularization and maintenance of the 3D architecture of the thyroid SVS were achieved. Thyroid-derived cells were found to aggregate, link and give rise to intracytoplasmic cavities up to follicular coating, whereas secretory de-differentiation occurred. These results show that the 3D matrix of the rat thyroid can be used as a natural scaffold to recellularize the thyroid lobe with progenitor-like elements, supporting the validity of the organomorphic principle for ex situ bioengineering of a bioartificial thyroid gland. Grants FIL09, PRIN082008ZCCJX4, FIRB2010RBAP10MLK

Symplectic methods for separable Hamiltonian systems

This paper focuses on the solution of separable Hamiltonian systems using explicit symplectic integration methods. Strategies for reducing the effect of cumulative rounding errors are outlined and advantages over a standard formulation are demonstrated. Procedures for automatically choosing appropriate methods are also described. © Springer-Verlag 2002

Approximation of a 3D Volume from one 2D Image. A Medical Application

We study the possibility for a tridimensional reconstruction of one lobe of the thyroid gland from a single bidimensional echographic or scintigraphic image. From a numerical point of view the scope is to provide an approximation to its volume, besides to a visualization of the gland in space, that is more accurate than the current way of estimating such a volume. We focus on a particular pathology of the thyroid, namely the Plummer nodule. Through the tridimensional information obtained, the aim is to perform both a functional and morphological analysis of the thyroid lobe affected by the Plummer pathology, in order to obtain therapeutic indication, to avoid the surgical extraction of the gland

Numerical Assessments in the Work of Vito Volterra

The modern developments in mathematical biology took place roughly between 1920 and 1940: the eminent Italian mathematician Vito Volterra played a decisive role in it. In this work a brief description is contained of the life and work of Volterra, within the frame of reference given by the Italian historic period in which he lived. The aim, in particular, is to outline the numerical assessments pervading the research achievements of the Italian scientist. To this aim, a class of the most famous problems are recalled, that were faced by Volterra in the field of mathematical biology. The solution to such a problem is numerically obtained, via both classic methods and a more recent geometric approach, and visualized, by exploiting the resources of an integrated, uniform and versatile framework for scientific calculus and graphics

Extrapolation Methods in Mathematica

This article outlines design and implementation details of the framework for one step methods for solving ordinary differential equations in Mathematica. The solver breaks up the solution into three main phases for equation processing and classification, numerical solution and processing of results. One of the distinguishing features of the framework is the hierarchical nature of the method invocation which allows for simple construction of composed integration schemes. A plug-in facility for user defined schemes is also provided. Highly accurate reference solutions can also be obtained by making use of arbitrary precision software arithmetic. Issues relating to appropriate formulation and efficient implementation will also be discussed, together with strategies for automatic method, order and parameter selection

Blind Restoration of Astronomical Images

Image restoration is of considerable interest in numerous scientific applications. When the image formation system is space invariant and linear, the blurred noise-free image can be expressed as the convolution of the original image with a blurring function: if the latter is known, then the Fast Fourier Transform can be used to efficiently compute convolutions. The algorithm presented here tries to remove the blur, using a priori constraints, without the knowledge of the blurring function. This approach is often referred to as Blind Deconvolution and finds useful applications, in particular, in astronomical imaging, in which the atmosphere of the Earth and the instruments of observation constitute sources of distortion and aberration that cannot be quantified in advance

Hybrid solvers for composition and splitting methods

AbstractComposition and splitting are useful techniques for constructing special purpose integration methods for numerically solving many types of differential equations. In this article we will review these methods and summarise the essential ingredients of an implementation that has recently been added to a framework for solving differential equations in Mathematica

Constrained Iterations for Blind Deconvolution and Convexity Issues

The need for image restoration arises in many applications of various scientific disciplines, such as medicine and astronomy and, in general, whenever an unknown image must be recovered from blurred and noisy data. The algorithm studied in this work restores the image without the knowledge of the blur, using little a priori information and a 'blind inverse filter' iteration. It represents a variation of the methods proposed by Kundur and Hatzinakos (1998) and by Ng, Plemmons and Qiao (2000). The problem of interest here is an 'inverse' one, that cannot be solved by simple filtering since it is ill--posed. The imaging system is assumed to be linear and space--invariant: this allows a simplified relationship between unknown and observed images, described by a 'point spread function' modeling the distortion. The blurring, though, makes the restoration ill--conditioned: 'regularization' is therefore also needed, obtained by adding constraints to the formulation of the estimated solution. The problem is modeled as a constrained minimization: particular attention is given here to the analysis of the objective function and on establishing whether or not it is a convex function, whose minima can be located by classic optimization techniques and descent methods. Numerical examples are applied to simulated data and to real data derived from various applications. Comparison with the behavior of the two other methods, mentioned above, show the effectiveness of our variant

Derivation of symmetric composition constants for symmetric integrators

This work focuses on the derivation of composition methods for the numerical integration of ordinary differential equations, which give rise to very challenging optimization problems. Composition is a useful technique for constructing high order approximations whilst conserving certain geometric properties. We survey existing composition methods and describe results of an intensive numerical search for new methods. Details of the search procedure are given along with numerical examples which indicate that the new methods perform better than previously known methods. Some insight into the location of global minima for these problems is obtained as a result