Explicit Finite Element Models Accurately Predict Subject-Specific and Velocity-Dependent Kinetics of Sideways Fall Impact

The majority of hip fractures in the elderly are the result of a fall from standing or from a lower height. Current injury models focus mostly on femur strength while neglecting subject-specific loading. This article presents an injury modeling strategy for hip fractures related to sideways falls that takes subject-specific impact loading into account. Finite element models (FEMs) of the human body were used to predict the experienced load and the femoral strength in a single model. We validated these models for their predicted peak force, effective pelvic stiffness, and fracture status against matching ex vivo sideways fall impacts (n = 11) with a trochanter velocity of 3.1 m/s. Furthermore, they were compared to sideways impacts of volunteers with lower impact velocities that were previously conducted by other groups. Good agreement was found between the ex vivo experiments and the FEMs with respect to peak force (root mean square error [RMSE] = 10.7%, R² = 0.85) and effective pelvic stiffness (R² = 0.92, RMSE = 12.9%). The FEMs were predictive of the fracture status for 10 out of 11 specimens. Compared to the volunteer experiments from low height, the FEMs overestimated the peak force by 25% for low BMI subjects and 8% for high BMI subjects. The effective pelvic stiffness values that were derived from the FEMs were comparable to those derived from impacts with volunteers. The force attenuation from the impact surface to the femur ranged between 27% and 54% and was highly dependent on soft tissue thickness (R² = 0.86). The energy balance in the FEMS showed that at the time of peak force 79% to 93% of the total energy is either kinetic or was transformed to soft tissue deformation. The presented FEMs allow for direct discrimination between fracture and nonfracture outcome for sideways falls and bridge the gap between impact testing with volunteers and impact conditions representative of real life falls. © 2019 American Society for Bone and Mineral Research.     

The chondrocyte channelome: A narrative review

Chondrocytes are the main cells in the extracellular matrix (ECM) of articular cartilage and possess a highly differentiated phenotype that is the hallmark of the unique physiological functions of this specialised load-bearing connective tissue. The plasma membrane of articular chondrocytes contains a rich and diverse complement of membrane proteins, known as the membranome, which defines the cell surface phenotype of the cells. The membranome is a key target of pharmacological agents and is important for chondrocyte function. It includes channels, transporters, enzymes, receptors, and anchors for intracellular, cytoskeletal and ECM proteins and other macromolecular complexes. The chondrocyte channelome is a sub-compartment of the membranome and includes a complete set of ion channels and porins expressed in these cells. Many of these are multi-functional proteins with “moonlighting” roles, serving as channels, receptors and signalling components of larger molecular assemblies. The aim of this review is to summarise our current knowledge of the fundamental aspects of the chondrocyte channelome, discuss its relevance to cartilage biology and highlight its possible role in the pathogenesis of osteoarthritis (OA). Excessive and inappropriate mechanical loads, an inflammatory micro-environment, alternative splicing of channel components or accumulation of basic calcium phosphate crystals can result in an altered chondrocyte channelome impairing its function. Alterations in Ca²⁺ signalling may lead to defective synthesis of ECM macromolecules and aggravated catabolic responses in chondrocytes, which is an important and relatively unexplored aspect of the complex and poorly understood mechanism of OA development.     

Characterization of Benign Myocarditis Using Quantitative Delayed-Enhancement Imaging Based on Molli T1 Mapping

Delayed contrast enhancement after injection of a gadolinium-chelate (Gd-chelate) is a reference imaging method to detect myocardial tissue changes. Its localization within the thickness of the myocardial wall allows differentiating various pathological processes such as myocardial infarction (MI), inflammatory myocarditis, and cardiomyopathies. The aim of the study was first to characterize benign myocarditis using quantitative delayed-enhancement imaging and then to investigate whether the measure of the extracellular volume fraction (ECV) can be used to discriminate between MI and myocarditis.In 6 patients with acute benign myocarditis (32.2 ± 13.8 year-old, subepicardial late gadolinium enhancement [LGE]) and 18 patients with MI (52.3 ± 10.9 year-old, subendocardial/transmural LGE), myocardial T1 was determined using the Modified Look-Locker Imaging (MOLLI) sequence at 3 Tesla before and after Gd-chelate injection. T1 values were compared in LGE and normal regions of the myocardium. The myocardial T1 values were normalized to the T1 of blood, and the ECV was calculated from T1 values of myocardium and blood pre- and post-Gd injection.In both myocarditis and MI, the T1 was lower in LGE regions than in normal regions of the left ventricle. T1 of LGE areas was significantly higher in myocarditis than in MI (446.8 ± 45.8 vs 360.5 ± 66.9 ms, P = 0.003) and ECV was lower in myocarditis than in MI (34.5 ± 3.3 vs 53.8 ± 13.0 %, P = 0.004).Both inflammatory process and chronic fibrosis induce LGE (subepicardial in myocarditis and subendocardial in MI). The present study demonstrates that the determination of T1 and ECV is able to differentiate the 2 histological patterns.Further investigation will indicate whether the severity of ECV changes might help refine the predictive risk of LGE in myocarditis.     

Ebola Virus RNA Stability in Human Blood and Urine in West Africa’s Environmental Conditions

We evaluated RNA stability of Ebola virus in EDTA blood and urine samples collected from infected patients and stored in West Africa’s environmental conditions. In blood, RNA was stable for at least 18 days when initial cycle threshold values were <30, but in urine, RNA degradation occurred more quickly.