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Orthodontic treatments are concomitant with mechanical forces and thereby cause teeth movements. The applied forces are transmitted to the tooth root and the periodontal ligaments which is compressed on one side and tensed up on the other side. Indeed, strong forces can lead to tooth root resorption and the crown-to-tooth ratio is reduced with the potential for significant clinical impact. The cementum, which covers the tooth root, is a thin mineralized tissue of the periodontium that connects the periodontal ligament with the tooth and is build up by cementoblasts. The impact of tension and compression on these cells is investigated in several in vivo and in vitro studies demonstrating differences in protein expression and signaling pathways. In summary, osteogenic marker changes indicate that cyclic tensile forces support whereas static tension inhibits cementogenesis. Furthermore, cementogenesis experiences the same protein expression changes in static conditions as static tension, but cyclic compression leads to the exact opposite of cyclic tension. Consistent with marker expression changes, the singaling pathways of Wnt/ß-catenin and RANKL/OPG show that tissue compression leads to cementum degradation and tension forces to cementogenesis. However, the cementum, and in particular its cementoblasts, remain a research area which should be explored in more detail to understand the underlying mechanism of bone resorption and remodeling after orthodontic treatments.
Purpose
In vivo, a loss of mesh porosity triggers scar tissue formation and restricts functionality. The purpose of this study was to evaluate the properties and configuration changes as mesh deformation and mesh shrinkage of a soft mesh implant compared with a conventional stiff mesh implant in vitro and in a porcine model.
Material and Methods
Tensile tests and digital image correlation were used to determine the textile porosity for both mesh types in vitro. A group of three pigs each were treated with magnetic resonance imaging (MRI) visible conventional stiff polyvinylidene fluoride meshes (PVDF) or with soft thermoplastic polyurethane meshes (TPU) (FEG Textiltechnik mbH, Aachen, Germany), respectively. MRI was performed with a pneumoperitoneum at a pressure of 0 and 15 mmHg, which resulted in bulging of the abdomen. The mesh-induced signal voids were semiautomatically segmented and the mesh areas were determined. With the deformations assessed in both mesh types at both pressure conditions, the porosity change of the meshes after 8 weeks of ingrowth was calculated as an indicator of preserved elastic properties. The explanted specimens were examined histologically for the maturity of the scar (collagen I/III ratio).
Results
In TPU, the in vitro porosity increased constantly, in PVDF, a loss of porosity was observed under mild stresses. In vivo, the mean mesh areas of TPU were 206.8 cm2 (± 5.7 cm2) at 0 mmHg pneumoperitoneum and 274.6 cm2 (± 5.2 cm2) at 15 mmHg; for PVDF the mean areas were 205.5 cm2 (± 8.8 cm2) and 221.5 cm2 (± 11.8 cm2), respectively. The pneumoperitoneum-induced pressure increase resulted in a calculated porosity increase of 8.4% for TPU and of 1.2% for PVDF. The mean collagen I/III ratio was 8.7 (± 0.5) for TPU and 4.7 (± 0.7) for PVDF.
Conclusion
The elastic properties of TPU mesh implants result in improved tissue integration compared to conventional PVDF meshes, and they adapt more efficiently to the abdominal wall. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 827–833, 2018.
Edge-based and face-based smoothed finite element methods (ES-FEM and FS-FEM, respectively) are modified versions of the finite element method allowing to achieve more accurate results and to reduce sensitivity to mesh distortion, at least for linear elements. These properties make the two methods very attractive. However, their implementation in a standard finite element code is nontrivial because it requires heavy and extensive modifications to the code architecture. In this article, we present an element-based formulation of ES-FEM and FS-FEM methods allowing to implement the two methods in a standard finite element code with no modifications to its architecture. Moreover, the element-based formulation permits to easily manage any type of element, especially in 3D models where, to the best of the authors' knowledge, only tetrahedral elements are used in FS-FEM applications found in the literature. Shape functions for non-simplex 3D elements are proposed in order to apply FS-FEM to any standard finite element.
Impaired cerebral autoregulation and neurovascular coupling (NVC) contribute to delayed cerebral ischemia after subarachnoid hemorrhage (SAH). Retinal vessel analysis (RVA) allows non-invasive assessment of vessel dimension and NVC hereby demonstrating a predictive value in the context of various neurovascular diseases. Using RVA as a translational approach, we aimed to assess the retinal vessels in patients with SAH. RVA was performed prospectively in 24 patients with acute SAH (group A: day 5–14), in 11 patients 3 months after ictus (group B: day 90 ± 35), and in 35 age-matched healthy controls (group C). Data was acquired using a Retinal Vessel Analyzer (Imedos Systems UG, Jena) for examination of retinal vessel dimension and NVC using flicker-light excitation. Diameter of retinal vessels—central retinal arteriolar and venular equivalent—was significantly reduced in the acute phase (p < 0.001) with gradual improvement in group B (p < 0.05). Arterial NVC of group A was significantly impaired with diminished dilatation (p < 0.001) and reduced area under the curve (p < 0.01) when compared to group C. Group B showed persistent prolonged latency of arterial dilation (p < 0.05). Venous NVC was significantly delayed after SAH compared to group C (A p < 0.001; B p < 0.05). To our knowledge, this is the first clinical study to document retinal vasoconstriction and impairment of NVC in patients with SAH. Using non-invasive RVA as a translational approach, characteristic patterns of compromise were detected for the arterial and venous compartment of the neurovascular unit in a time-dependent fashion. Recruitment will continue to facilitate a correlation analysis with clinical course and outcome.
Searching optimal interplanetary trajectories for low-thrust spacecraft is usually a difficult and time-consuming task that involves much experience and expert knowledge in astrodynamics and optimal control theory. This is because the convergence behavior of traditional local optimizers, which are based on numerical optimal control methods, depends on an adequate initial guess, which is often hard to find, especially for very-low-thrust trajectories that necessitate many revolutions around the sun. The obtained solutions are typically close to the initial guess that is rarely close to the (unknown) global optimum. Within this paper, trajectory optimization problems are attacked from the perspective of artificial intelligence and machine learning. Inspired by natural archetypes, a smart global method for low-thrust trajectory optimization is proposed that fuses artificial neural networks and evolutionary algorithms into so-called evolutionary neurocontrollers. This novel method runs without an initial guess and does not require the attendance of an expert in astrodynamics and optimal control theory. This paper details how evolutionary neurocontrol works and how it could be implemented. The performance of the method is assessed for three different interplanetary missions with a thrust to mass ratio <0.15mN/kg (solar sail and nuclear electric).