Fatigue of textiles used in vascular surgery: Application to carotid endarterectomy.

Fatigue is a material-based phenomenon playing a significant role in the mechanical behavior of components and structures. Although fatigue has been well studied for traditional materials, such as metals, its underlying mechanisms are not thoroughly understood in novel applications such as the case of textiles used as patches to close the arteriotomy in carotid endarterectomy. The latter is a type of vascular surgery for the treatment of carotid artery disease in which after an arteriotomy and removal of atherosclerotic plaque closure is made with a patch sutured on the artery. Completion of the operation signals the initiation of complex mechanical and hemodynamic phenomena. Fatigue performance of the patch eventually determines the successful outcome of carotid endarterectomy. In this study, we evaluate with a two-fold approach the mechanics of patch angioplasty in carotid endarterectomy. First, an analytical model for the fatigue behavior of textiles is developed, considering the microstructure and geometry of the fabric. Then, the surgical procedure is simulated and a finite element analysis of the endarterectomized and patched carotid artery is employed. Stress fields are calculated, while deformation at the site of patch angioplasty indicates a potential cause for the formation of aneurismal degeneration after the surgery. Such analysis can provide a better understanding in the establishment of follow-up protocols.

Rheological properties of synovial fluid due to viscosupplements: A review for osteoarthritis remedy.

The synovial fluid is a transparent electrolyte solution included in joints to provide lubrication helping the proper movement. It exhibits complex rheological properties due to the interaction among its constituents i.e. hyaluronic acid, albumin, lubricin and phospholipids. In degenerative osteoarthritis and inflammatory rheumatoid arthritis diseases, the quantity of synovial fluid and lubrication efficiency significantly deteriorates. In that case, viscosupplementation with intra-articular hyaluronic acid may be prescribed to replenish the concentration, the molecular weight and the rheological properties of natural synovial fluid. The present review concentrates on the recent advancements in viscosupplementation with emphasis into their rheological properties, its effects on the rheological behavior of synovial fluid, and finally its clinical effectiveness. Initially, the properties of synovial fluid are summarized, and then a discussion on commercial viscosupplements, the role of polymeric properties and their rheological properties are reviewed. Moreover, a detailed discussion on the clinical effectiveness and challenges of viscosupplements are provided.

Tensor decomposition of TMS-induced EEG oscillations reveals data-driven profiles of antiepileptic drug effects.

Transcranial magnetic stimulation combined with electroencephalography is a powerful tool to probe human cortical excitability. The EEG response to TMS stimulation is altered by drugs active in the brain, with characteristic "fingerprints" obtained for drugs of known mechanisms of action. However, the extraction of specific features related to drug effects is not always straightforward as the complex TMS-EEG induced response profile is multi-dimensional. Analytical approaches can rely on a-priori assumptions within each dimension or on the implementation of cluster-based permutations which do not require preselection of specific limits but may be problematic when several experimental conditions are tested. We here propose an alternative data-driven approach based on PARAFAC tensor decomposition, which provides a parsimonious description of the main profiles underlying the multidimensional data. We validated reliability of PARAFAC on TMS-induced oscillations before extracting the features of two common anti-epileptic drugs (levetiracetam and lamotrigine) in an integrated manner. PARAFAC revealed an effect of both drugs, significantly suppressing oscillations in the alpha range in the occipital region. Further, this effect was stronger under the intake of levetiracetam. This study demonstrates, for the first time, that PARAFAC can easily disentangle the effects of subject, drug condition, frequency, time and space in TMS-induced oscillations.

Development of a new theoretical model for blood-CNTs effective thermal conductivity pertaining to hyperthermia therapy of glioblastoma multiform.

BACKGROUND AND OBJECTIVE: The present study deals with the hyperthermia therapy, which is the type of treatment in which tissues are exposed to high temperatures in order to destroy cancer cells with minimal injury to healthy tissues. In particular, it focuses on glioblastoma multiform, which is the most aggressive cancer that begins within the brain. Conventional treatments display limitations that can be overcome by using nanoparticles for targeted heating. Out of the proposed nanoparticles, this investigation focuses on a new field that utilizes carbon nanotubes (CNTs) which are able to selectively heat the cancer cells since they can convert near infrared light into heat. In the absence of any experiment or theoretical model for the estimation of an effective thermal conductivity of blood and CNTs, a first principle model is developed in this study which takes into account the blood micro-structure. Besides, a number of factors are included, namely the shape and the size of the nanoparticles, the interfacial layer formed around them and their volume fraction. METHODS: Firstly, assuming that the blood consists of blood cells and plasma, the thermal conductivity of the former is estimated. Then, the effective thermal conductivity of plasma/CNTs is calculated for various parameters. Finally, the resulting "bio-nanofluid" consisting of plasma/CNTs and blood cells is formed. RESULTS: It is ascertained that thin and elongated CNTs with relatively large nanolayer thickness as well as large concentrations of CNTs contribute to the increase of the thermal conductivity and, thus, in the enhancement of the heat transfer. CONCLUSIONS: Investigating of how design parameters pertaining to CNTs, such as their size and shape, affect the effective thermal conductivity of blood-CNTs, possible regulating ways are suggested regarding the hyperthermic treatment. Finally, the present simple estimation of the effective thermal conductivity can be used as an effective property of the nanofluid when it comes to numerical investigations regarding heat transfer occurring during hyperthermia or other potential clinical uses (for example targeted heat of living tissues).

Multiscale modeling of skeletal muscle tissues based on analytical and numerical homogenization.

A novel multiscale modeling framework for skeletal muscles based on analytical and numerical homogenization methods is presented to study the mechanical muscle response at finite strains under three-dimensional loading conditions. First an analytical microstructure-based constitutive model is developed and numerically implemented in a general purpose finite element program. The analytical model takes into account explicitly the volume fractions, the material properties, and the spatial distribution of muscle's constituents by using homogenization techniques to bridge the different length scales of the muscle structure. Next, a numerical homogenization model is developed using periodic eroded Voronoi tessellation to virtually represent skeletal muscle microstructures. The eroded Voronoi unit cells are then resolved by finite element simulations and are used to assess the analytical homogenization model. The material parameters of the analytical model are identified successfully by use of available experimental data. The analytical model is found to be in very good agreement with the numerical model for the full range of loadings, and a wide range of different volume fractions and heterogeneity contrasts between muscle's constituents. A qualitative application of the model on fusiform and pennate muscle structures shows its efficiency to examine the effect of muscle fiber concentration variations in an organ-scale model simulation.

Tensor-driven extraction of developmental features from varying paediatric EEG datasets.

OBJECTIVE: Constant changes in developing children's brains can pose a challenge in EEG dependant technologies. Advancing signal processing methods to identify developmental differences in paediatric populations could help improve function and usability of such technologies. Taking advantage of the multi-dimensional structure of EEG data through tensor analysis may offer a framework for extracting relevant developmental features of paediatric datasets. A proof of concept is demonstrated through identifying latent developmental features in resting-state EEG. APPROACH: Three paediatric datasets ([Formula: see text]) were analyzed using a two-step constrained parallel factor (PARAFAC) tensor decomposition. Subject age was used as a proxy measure of development. Classification used support vector machines (SVM) to test if PARAFAC identified features could predict subject age. The results were cross-validated within each dataset. Classification analysis was complemented by visualization of the high-dimensional feature structures using t-distributed stochastic neighbour embedding (t-SNE) maps. MAIN RESULTS: Development-related features were successfully identified for the developmental conditions of each dataset. SVM classification showed the identified features could accurately predict subject at a significant level above chance for both healthy and impaired populations. t-SNE maps revealed suitable tensor factorization was key in extracting the developmental features. SIGNIFICANCE: The described methods are a promising tool for identifying latent developmental features occurring throughout childhood EEG.

Elucidating age-specific patterns from background electroencephalogram pediatric datasets via PARAFAC.

Brain-computer interfaces (BCI) have the potential to provide non-muscular rehabilitation options for children. However, progressive changes in electrophysiology throughout development may pose a potential barrier in the translation of BCI rehabilitation schemes to children. Tensors and multiway analysis could provide tools which help characterize subtle developmental changes in electroencephalogram (EEG) profiles of children, thus supporting translation of BCI paradigms. Spatial, spectral and subject information of age-matched pediatric subjects in two EEG datasets were used to form 3-dimensional tensors for use in parallel factor analysis (PARAFAC) and direct projection comparison. Within dataset cross-validation results indicate PARAFAC can extract age-sensitive factors which accurately predict subject age in 90% of cases. Cross-dataset validation revealed extracted age-dependent factors correctly identified age in 3 of 4 test subjects. These findings demonstrate that tensor analysis can be applied to characterize the age-specific subtleties in EEG, which provide a means for tracking developmental changes in pediatric rehabilitation BCIs.

A homogenization model of the Voigt type for skeletal muscle.

A three-dimensional constitutive model for skeletal muscle incorporating microstructural characteristics is developed and numerically implemented in a general purpose finite element program. The proposed model takes into account explicitly the volume fractions of muscle fibers and connective tissue by using the Voigt homogenization approach to bridge the different length scales of the muscle structure. The model is used to estimate the active and passive homogenized muscle response. Next, the model is validated by experimental data and periodic three-dimensional unit cell calculations comprising various fiber volume fractions and mechanical properties of the constituents. The model is found to be in very good agreement with both the experimental data and the finite element results for all the examined cases. The influence of fiber volume fraction and material properties of constituents on effective muscle response under several loading conditions is examined.

Material modeling of biofilm mechanical properties.

A biofilm material model and a procedure for numerical integration are developed in this article. They enable calculation of a composite Young's modulus that varies in the biofilm and evolves with deformation. The biofilm-material model makes it possible to introduce a modeling example, produced by the Unified Multi-Component Cellular Automaton model, into the general-purpose finite-element code ABAQUS. Compressive, tensile, and shear loads are imposed, and the way the biofilm mechanical properties evolve is assessed. Results show that the local values of Young's modulus increase under compressive loading, since compression results in the voids "closing," thus making the material stiffer. For the opposite reason, biofilm stiffness decreases when tensile loads are imposed. Furthermore, the biofilm is more compliant in shear than in compression or tension due to the how the elastic shear modulus relates to Young's modulus.

Muscle-driven finite element simulation of human foot movements.

This paper describes a finite element scheme for realistic muscle-driven simulation of human foot movements. The scheme is used to simulate human ankle plantar flexion. A three-dimensional anatomically detailed finite element model of human foot and lower leg is developed and the idea of generating natural foot movement based entirely on the contraction of the plantar flexor muscles is used. The bones, ligaments, articular cartilage, muscles, tendons, as well as the rest soft tissues of human foot and lower leg are included in the model. A realistic three-dimensional continuum constitutive model that describes the biomechanical behaviour of muscles and tendons is used. Both the active and passive properties of muscle tissue are accounted for. The materials for bones and ligaments are considered as homogeneous, isotropic and linearly elastic, whereas the articular cartilage and the rest soft tissues (mainly fat) are defined as hyperelastic materials. The model is used to estimate muscle tissue deformations as well as stresses and strains that develop in the lower leg muscles during plantar flexion of the ankle. Stresses and strains that develop in Achilles tendon during such a movement are also investigated.

Lingual arch appliance fabrication in the dental office.

Lingual arch is a mandibular fixed bilateral space maintaining appliance. It prevents the first permanent molar from drifting forward and preserves the available space, especially the leeway space in mixed dentition cases. The purpose of the present article is to present a simplified way of lingual arch appliance fabrication in the dental office, which will result in effective space maintenance and time savings for both the patient and the dentist.