Modeling the collagen fibril network of biological tissues as a nonlinearly elastic material using a continuous volume fraction distribution function

Despite distinct mechanical functions, biological soft tissues have a common microstructure in which a ground matrix is reinforced by a collagen fibril network. The microstructural properties of the collagen network contribute to continuum mechanical tissue properties that are strongly anisotropic with tensile-compressive asymmetry. In this study, a novel approach based on a continuous distribution of collagen fibril volume fractions is developed to model fibril reinforced soft tissues as nonlinearly elastic and anisotropic material. Compared with other approaches that use a normalized number of fibrils for the definition of the distribution function, this representation is based on a distribution parameter (i.e. volume fraction) that is commonly measured experimentally while also incorporating pre-stress of the collagen fibril network in a tissue natural configuration. After motivating the form of the collagen strain energy function, examples are provided for two volume fraction distribution functions. Consequently, collagen second-Piola Kirchhoff stress and elasticity tensors are derived, first in general form and then specifically for a model that may be used for immature bovine articular cartilage. It is shown that the proposed strain energy is a convex function of the deformation gradient tensor and, thus, is suitable for the formation of a polyconvex tissue strain energy function

RF and THz Identification Using a New Generation of Chipless RFID Tags

This article presents two chipless RFID approaches where data are reading using electromagnetic waves and where the medium encoding the data is completely passive. The former approach rests on the use of RF waves (more precisely the ultra-wide band UWB). The tags developed for this application are comparable with very specific, planar, conductive, radar targets where the relation between the tag geometry and its electromagnetic signature is perfectly known and is used to encode the data. The principle of operation as well as the realization process of the RF tags presented in this paper is similar to those already reported in the literature. However, contrary to the majority of chipless RFID tags, these labels do not present an antenna function dissociated from the circuit part where the data are stored. Here, functions such as the receiver, the treatment and the emitter of the signal are closely dependent. The data storage capacity of the RF chipless tags is proportional to of the used frequency bandwidth. As radio spectrum is regulated, the number of possible encoding bits is thus strongly limited with this technology. This is the reason why we introduce a new family of tags radically different from the preceding one, where data is encoded in volume thanks to a multilayer structure operating in the THz domain. These two approaches although different are complementary and allow to increase significantly the data storage capacity of the chipless tags. Simulation and experimental results are reported in this paper for both configurations. We demonstrate a coding capacity of 3.3 bit/cm2 for RFID chipless tags and a potential 10 bits coding capacity in the THz domain

Mechanical Properties of Robocast Glass Scaffolds Assessed through Micro-CT-Based Finite Element Models

In this study, the mechanical properties of two classes of robocast glass scaffolds are obtained through Computed micro-Tomography (micro-CT) based Finite Element Modeling (FEM) with the specific purpose to explicitly account for the geometrical defects introduced during manufacturing. Both classes demonstrate a fiber distribution along two perpendicular directions on parallel layers with a (Formula presented.) tilting between two adjacent layers. The crack pattern identified upon compression loading is consistent with that found in experimental studies available in literature. The finite element models have demonstrated that the effect of imperfections on elastic and strength properties may be substantial, depending on the specific type of defect identified in the scaffolds. In particular, micro-porosity, fiber length interruption and fiber detaching were found as key factors. The micro-pores act as stress concentrators promoting fracture initiation and propagation, while fiber detachment reduces the scaffold properties substantially along the direction perpendicular to the fiber plane

Computational models for the simulation of the elastic and fracture properties of highly porous 3D-printed hydroxyapatite scaffolds

Bone scaffolding is a promising approach for the treatment of critical-size bone defects. Hydroxyapatite can be used to produce highly porous scaffolds as it mimics the mineralized part of bone tissue, but its intrinsic brittleness limits its usage. Among 3D printing techniques, vat photopolymerization allows for the best printing resolution for ceramic materials. In this study, we implemented a Computed micro-Tomography based Finite Element Model of a hydroxyapatite porous scaffold fabricated by vat photopolymerization. We used the model in order to predict the elastic and fracture properties of the scaffold. From the stress–strain diagram of a simulated compression test, we computed the stiffness and the strength of the scaffolds. We found that three morphometric features substantially affect the crack pattern. In particular, the crack propagation is not only dependent on the trabecular thickness but also depends on the slenderness and orientation of the trabeculae with respect to the load. The results found in this study can be used for the design of ceramic scaffolds with heterogeneous pore distribution in order to tailor and predict the compressive strength

Ultrasonographic diagnosis of placenta accreta spectrum (PAS) disorder: Ideation of an ultrasonographic score and correlation with surgical and neonatal outcomes

The objective of this study was to evaluate a novel ultrasonographic scoring system for the diagnosis of PAS and the prediction of maternal and neonatal outcomes. In this retrospective study, 138 patients with at least one previous caesarean section (CS) and placenta previa were included. They were divided into four groups ranging from Group 0 (Non PAS) to Group 3 (Placenta Percreta) according to the histological or surgical confirmation. Their ultrasound examinations during pregnancy were reviewed according to the nine different ultrasound signs reported by the European Working Group on Abnormally Invasive Placenta. For each parameter, 0 to 2 points were assigned. The sum of the points reflects the severity of PAS with a maximum score of 20. The scoring system revealed good performances in evaluation metrics, with an overall accuracy of 94%. In addition to this, patients’ characteristics and surgical and neonatal outcomes were analyzed with an evidence of higher incidence of complications in severe forms. Our study suggests that antenatal ultrasonographic diagnosis of PAS is feasible with sufficient level of accuracy. This will be important in identifying high-risk patients and implementing preventive strategy

Spatial Environmental Modeling of Autoantibody Outcomes among an African American Population

In this study of autoimmunity among a population of Gullah African Americans in South Carolina, the links between environmental exposures and autoimmunity (presence of antinuclear antibodies (ANA)) have been assessed. The study population included patients with systemic lupus erythematosus (n = 10), their first degree relatives (n = 61), and unrelated controls (n = 9) where 47.5% (n = 38) were ANA positive. This paper presents the methodology used to model ANA status as a function of individual environmental influences, both self-reported and measured, while controlling for known autoimmunity risk factors. We have examined variable dimension reduction and selection methods in our approach. Following the dimension reduction and selection methods, we fit logistic spatial Bayesian models to explore the relationship between our outcome of interest and environmental exposures adjusting for personal variables. Our analysis also includes a validation “strip” where we have interpolated information from a specific geographic area for a subset of the study population that lives in that vicinity. Our results demonstrate that residential proximity to exposure site is important in this form of analysis. The use of a validation strip network demonstrated that even with small sample numbers some significant exposure-outcome relationships can be detected