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On Modeling Bio-Scaffolds:Structural and Fluid Transport Characterization Based on 3-D Imaging Data

Tsinghua Science and Technology 2009年第S1期14卷 20-23页

作者： NOTARBERARDINO Bruno BAKER Matthew TABOR Gavin turner irene YANG Lincoln School of Engineering Computing and Mathematics University of Exeter Exeter EX4 4QF United Kingdom Department of Mechanical Engineering University of Bath Bath BA2 7AY United Kingdom Shanghai Gaitech Scientific Instruments Co. Ltd.

Bio-scaffolds which are most commonly open celled porous structures are increasingly used for tissue engineering and regenerative medicine. A number of studies have shown that the bulk properties of such irregular structures are poorly modeled using idealized unit cell approaches. The paper therefore uses novel image based meshing techniques to explore both fluid flow and bulk structural properties of a bone scaffold, as accurate modeling of bio-scaffolds with non-uniform cellular structures is very important for the development of optimal scaffolds for tissue engineering application. In this study, a porous hydroxyapatite/tricalcium phosphate (HA/TCP) bone scaffold has been scanned in a Micro-CT scanner, and converted into a volumetric mesh using image processing software developed by the authors. The resulting mesh was then exported to commercial FEA and CFD solvers for analysis. Initial FEA and CFD studies have shown promising results and have highlighted the importance of accurate modeling to understand how microstructures influence the mechanical property of the scaffold, and to analyze flow regimes through the sample. The work highlights the potential use of image based meshing for the ad hoc characterization of scaffolds as well as for assisting in the design of scaffolds with tailored strength, stiffness, and transport properties.

关键词： bio-scaffolds material characterization finite element computational fluid dynamics dynamics microstructures

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Motor adaptation and internal model formation in a robot-mediated forcefield

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Psychoradiology 2021年第2期1卷 73-87页

作者： Myriam Taga Annacarmen Curci Sara Pizzamigglio irene Lacal Duncan L.turner Cynthia H.Y.Fu 无 School of Health Sports and BioscienceUniversity of East LondonLondonUK Department of Computer Science School of ArchitectureComputing and EngineeringUniversity of East LondonLondonUK Department of Physiology and Pharmacology Sapienza UniversityRomeItaly School of Psychology University of East LondonLondonUK Centre for Affective Disorders Institute of PsychiatryPsychology and NeuroscienceKing’s College LondonLondonUK

Background:Motor adaptation relies on error-based learning for accurate movements in changing ***,the neurophysiological mechanisms driving individual differences in performance are *** magnetic stimulation(TMS)-evoked potential can provide a direct measure of cortical ***:To investigate cortical excitability as a predictor of motor learning and motor adaptation in a robot-mediated ***:A group of 15 right-handed healthy participants(mean age 23 years)performed a robot-mediated forcefield perturbation *** were two conditions:unperturbed non-adaptation and perturbed *** was applied in the resting state at baseline and following motor adaptation over the contralateral primary motor cortex(left M1).Electroencephalographic(EEG)activity was continuously recorded,and cortical excitability was measured by TMS-evoked potential(TEP).Motor learning was quantified by the motor learning ***:Larger error-related negativity(ERN)in fronto-central regions was associated with improved motor per-formance as measured by a reduction in trajectory *** TEP N100 peak amplitude predicted motor learning(P=0.005),which was significantly attenuated relative to baseline(P=0.0018)following motor ***:ERN reflected the formation of a predictive internal model adapted to the forcefield *** in TEP N100 amplitude reflected an increase in cortical excitability with motor adaptation reflecting neuroplastic changes in the sensorimotor *** N100 is a potential biomarker for predicting the outcome in robot-mediated therapy and a mechanism to investigate psychomotor abnormalities in depression.

关键词： EEG TMS motor adaptation robot-mediated forcefield N100 ERN

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