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Percorrer CDRsp - Artigos em revistas internacionais por Domínios Científicos e Tecnológicos (FOS) "Ciências Médicas::Outras Ciências Médicas"
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- Bioactive Electrospun Fibers of Poly(ε-Caprolactone) Incorporating α-Tocopherol for Food Packaging ApplicationsPublication . Dumitriu, Raluca P.; Stoleru, Elena; Mitchell, Geoffrey R.; Vasile, Cornelia; Brebu, MihaiAntioxidant activity is an important feature for food contact materials such as packaging, aiming to preserve freshness and retard food spoilage. Common bioactive agents are highly susceptible to various forms of degradation; therefore, protection is required to maintain functionality and bioavailability. Poly(ε-caprolactone) (PCL), a biodegradable GRAS labeled polymer, was used in this study for encapsulation of α-tocopherol antioxidant, a major component of vitamin E, in the form of electrospun fibers. Rheological properties of the fiber forming solutions, which determine the electrospinning behavior, were correlated with the properties of electrospun fibers, e.g., morphology and surface properties. Interactions through hydrogen bonds were evidenced between the two components. These have strong effect on structuration of macromolecular chains, especially at low α-tocopherol amounts, decreasing viscosity and elastic modulus. Intra-molecular interactions in PCL strengthen at high α-tocopherol amounts due to decreased solvation, allowing good structural recovery after cease of mechanical stress. Morphologically homogeneous electrospun fibers were obtained, with ~6 µm average diameter. The obtained fibers were highly hydrophobic, with fast release in 95% ethanol as alternative simulant for fatty foods. This induced good in vitro antioxidant activity and significant in vivo reduction of microbial growth on cheese, as determined by respirometry. Therefore, the electrospun fibers from PCL entrapping α-tocopherol as bioactive agent showed potential use in food packaging materials.
- Improving the process of making rapid prototyping models from medical ultrasound imagesPublication . Vaezi, Mohammad; Chua, Chee Kai; Chou, Siaw MengPurpose – Today, medical models can be made by the use of medical imaging systems through modern image processing methods and rapid prototyping (RP) technology. In ultrasound imaging systems, as images are not layered and are of lower quality as compared to those of computerized tomography (CT) and magnetic resonance imaging (MRI), the process for making physical models requires a series of intermediate processes and it is a challenge to fabricate a model using ultrasound images due to the inherent limitations of the ultrasound imaging process. The purpose of this paper is to make high quality, physical models from medical ultrasound images by combining modern image processing methods and RP technology. Design/methodology/approach – A novel and effective semi-automatic method was developed to improve the quality of 2D image segmentation process. In this new method, a partial histogram of 2D images was used and ideal boundaries were obtained. A 3D model was achieved using the exact boundaries and then the 3D model was converted into the stereolithography (STL) format, suitable for RP fabrication. As a case study, the foetus was chosen for this application since ultrasonic imaging is commonly used for foetus imaging so as not to harm the baby. Finally, the 3D Printing (3DP) and PolyJet processes, two types of RP technique, were used to fabricate the 3D physical models. Findings – The physical models made in this way proved to have sufficient quality and shortened the process time considerably. Originality/value – It is still a challenge to fabricate an exact physical model using ultrasound images. Current commercial histogram-based segmentation method is time-consuming and results in a less than optimum 3D model quality. In this research work, a novel and effective semi-automatic method was developed to select the threshold optimum value easily.
- Statistical Modeling of Lower Limb Kinetics During Deep Squat and Forward LungePublication . Roeck, Joris De; Houcke, J. Van; Almeida, D.; Galibarov, P.; Roeck, L. De; Audenaert, Emmanuel A.Purpose: Modern statistics and higher computational power have opened novel possibilities to complex data analysis. While gait has been the utmost described motion in quantitative human motion analysis, descriptions of more challenging movements like the squat or lunge are currently lacking in the literature. The hip and knee joints are exposed to high forces and cause high morbidity and costs. Pre-surgical kinetic data acquisition on a patient-specific anatomy is also scarce in the literature. Studying the normal inter-patient kinetic variability may lead to other comparable studies to initiate more personalized therapies within the orthopedics. Methods: Trials are performed by 50 healthy young males who were not overweight and approximately of the same age and activity level. Spatial marker trajectories and ground reaction force registrations are imported into the Anybody Modeling System based on subject-specific geometry and the state-of-the-art TLEM 2.0 dataset. Hip and knee joint reaction forces were obtained by a simulation with an inverse dynamics approach. With these forces, a statistical model that accounts for inter-subject variability was created. For this, we applied a principal component analysis in order to enable variance decomposition. This way, noise can be rejected and we still contemplate all waveform data, instead of using deduced spatiotemporal parameters like peak flexion or stride length as done in many gait analyses. In addition, this current paper is, to the authors’ knowledge, the first to investigate the generalization of a kinetic model data toward the population. Results: Average knee reaction forces range up to 7.16 times body weight for the forwarded leg during lunge. Conversely, during squat, the load is evenly distributed. For both motions, a reliable and compact statistical model was created. In the lunge model, the first 12 modes accounts for 95.26% of inter-individual population variance. For the maximal-depth squat, this was 95.69% for the first 14 modes. Model accuracies will increase when including more principal components. Conclusion: Our model design was proved to be compact, accurate, and reliable. For models aimed at populations covering descriptive studies, the sample size must be at least 50.