Clinicians should consider early repair of rotator cuff cable tears, which may need surgical intervention to address their biomechanical pathology. In contrast, surgical treatment may be more safely delayed for rotator cuff crescent tears.

Sarcomere lengths have been a crucial outcome measure for understanding and explaining basic muscle properties and muscle function. Sarcomere lengths for a given muscle are typically measured at a single spot, often in the mid-belly of the muscle, and at a given muscle length. It is then assumed implicitly that the sarcomere length measured at this single spot represents the sarcomere lengths at other locations within the muscle, and force-length, force-velocity, and power-velocity properties of muscles are often implied based on these single sarcomere length measurements. Although, intuitively appealing, this assumption is yet to be supported by systematic evidence. The objective of this study was to measure sarcomere lengths at defined locations along and across an intact muscle, at different muscle lengths. Using second harmonic generation (SHG) imaging technique, sarcomere patterns in passive mouse tibialis anterior (TA) were imaged in a non-contact manner at five selected locations (“proximal,” “distal,” “middle,” “medial,” and “lateral” TA sites) and at three different lengths encompassing the anatomical range of motion of the TA. We showed that sarcomere lengths varied substantially within small regions of the muscle and also for different sites across the entire TA. Also, sarcomere elongations with muscle lengthening were non-uniform across the muscle, with the highest sarcomere stretches occurring near the myotendinous junction. We conclude that muscle mechanics derived from sarcomere length measured from a small region of a muscle may not well-represent the sarcomere length and associated functional properties of the entire muscle.

Articular cartilage experiences significant mechanical loads during daily activities. Healthy cartilage provides the capacity for load bearing and regulates the mechanobiological processes for tissue development, maintenance, and repair. Experimental studies at multiple scales have provided a fundamental understanding of macroscopic mechanical function, evaluation of the micromechanical environment of chondrocytes, and the foundations for mechanobiological response. In addition, computational models of cartilage have offered a concise description of experimental data at many spatial levels under healthy and diseased conditions, and have served to generate hypotheses for the mechanical and biological function. Further, modeling and simulation provides a platform for predictive risk assessment, management of dysfunction, as well as a means to relate multiple spatial scales. Simulation-based investigation of cartilage comes with many challenges including both the computational burden and often insufficient availability of data for model development and validation. This review outlines recent modeling and simulation approaches to understand cartilage function from a mechanical systems perspective, and illustrates pathways to associate mechanics with biological function. Computational representations at single scales are provided from the body down to the microstructure, along with attempts to explore multiscale mechanisms of load sharing that dictate the mechanical environment of the cartilage and chondrocytes.

Cells of the musculoskeletal system are known to respond to mechanical loading and chondrocytes within the cartilage are not an exception. However, understanding how joint level loads relate to cell level deformations, e.g. in the cartilage, is not a straightforward task. In this study, a multi-scale analysis pipeline was implemented to post-process the results of a macro-scale finite element (FE) tibiofemoral joint model to provide joint mechanics based displacement boundary conditions to micro-scale cellular FE models of the cartilage, for the purpose of characterizing chondrocyte deformations in relation to tibiofemoral joint loading. It was possible to identify the load distribution within the knee among its tissue structures and ultimately within the cartilage among its extracellular matrix, pericellular environment and resident chondrocytes. Various cellular deformation metrics (aspect ratio change, volumetric strain, cellular effective strain and maximum shear strain) were calculated. To illustrate further utility of this multi-scale modeling pipeline, two micro-scale cartilage constructs were considered: an idealized single cell at the centroid of a 100×100×100 μm block commonly used in past research studies, and an anatomically based (11 cell model of the same volume) representation of the middle zone of tibiofemoral cartilage. In both cases, chondrocytes experienced amplified deformations compared to those at the macro-scale, predicted by simulating one body weight compressive loading on the tibiofemoral joint. In the 11 cell case, all cells experienced less deformation than the single cell case, and also exhibited a larger variance in deformation compared to other cells residing in the same block. The coupling method proved to be highly scalable due to micro-scale model independence that allowed for exploitation of distributed memory computing architecture. The method’s generalized nature also allows for substitution of any macro-scale and/or micro-scale model providing application for other multi-scale continuum mechanics problems.

The influence of obesity on muscle integrity is not well understood. The purpose of this study was to quantify structural and molecular changes in the rat vastus lateralis (VL) muscle as a function of a 12-week obesity induction period and a subsequent adaptation period (additional 16-weeks). Male Sprague-Dawley rats consumed a high-fat, high-sucrose (DIO, n = 40) diet, or a chow control-diet (n = 14). At 12-weeks, DIO rats were grouped as prone (DIO-P, top 33% of weight change) or resistant (DIO-R, bottom 33%). Animals were euthanized at 12- or 28-weeks on the diet. At sacrifice, body composition was determined and VL muscles were collected. Intramuscular fat, fibrosis, and CD68+ cells were quantified histologically and relevant molecular markers were evaluated using RT-qPCR. At 12- and 28-weeks post-obesity induction, DIO-P rats had more mass and body fat than DIO-R and chow rats (p < 0.05). DIO-P and DIO-R rats had similar losses in muscle mass, which were greater than those in chow rats (p < 0.05). mRNA levels for MAFbx/atrogin-1 were reduced in DIO-P and DIO-R rats at 12- and 28-weeks compared to chow rats (p < 0.05), while expression of MuRF1 was similar to chow values. DIO-P rats demonstrated increased mRNA levels for pro-inflammatory mediators, inflammatory cells, and fibrosis compared to DIO-R and chow animals, despite having similar levels of intramuscular fat. The down-regulation of MAFbx/atrogin-1 may suggest onset of degenerative changes in VL muscle integrity of obese rats. DIO-R animals exhibited fewer inflammatory changes compared to DIO-P animals, suggesting a protective effect of obesity resistance on local inflammation. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 34:2069-2078, 2016.

Recent interest in the process of vascularization within the biomedical community has motivated numerous new research efforts focusing on the process of angiogenesis. Although the role of chemical factors during angiogenesis has been well documented, the role of mechanical factors, such as the interaction between angiogenic vessels and the extracellular matrix, remain poorly understood. In vitro methods for studying angiogenesis exist, however measurements available using such techniques often suffer from limited spatial and temporal resolution. For this reason, computational models have been extensively employed to investigate various aspects of angiogenesis. This manuscript outlines the formulation and validation of a simple and robust computational model developed to accurately simulate angiogenesis based on length, branching, and orientation morphometrics collected from vascularized tissue constructs. Excellent agreement was observed between computational and experimental morphometric data over time. Computational predictions of microvessel orientation within an anisotropic matrix correlated well with experimental data. The accuracy of this modeling approach makes it a valuable platform for investigating the role of mechanical interactions during angiogenesis.

Understanding the mechanical behavior of chondrocytes as a result of cartilage tissue mechanics has significant implications for both evaluation of mechanobiological function and to elaborate on damage mechanisms. A common procedure for prediction of chondrocyte mechanics (and of cell mechanics in general) relies on a computational post-processing approach where tissue level deformations drive cell level models. Potential loss of information in this numerical coupling approach may cause erroneous cellular scale results, particularly during multiphysics analysis of cartilage. The goal of this study was to evaluate the capacity of 1st and 2nd order data passing to predict chondrocyte mechanics by analyzing cartilage deformations obtained for varying complexity of loading scenarios. A tissue scale model with a sub-region incorporating representation of chondron size and distribution served as control. The postprocessing approach first required solution of a homogeneous tissue level model, results of which were used to drive a separate cell level model (same characteristics as the subregion of control model). The 1st data passing appeared to be adequate for simplified loading of the cartilage and for a subset of cell deformation metrics, e.g., change in aspect ratio. The 2nd order data passing scheme was more accurate, particularly when asymmetric permeability of the tissue boundaries were considered. Yet, the method exhibited limitations for predictions of instantaneous metrics related to the fluid phase, e.g., mass exchange rate. Nonetheless, employing higher-order data exchange schemes may be necessary to understand the biphasic mechanics of cells under lifelike tissue loading states for the whole time history of the simulation.

One contribution of 11 to a theme issue 'Multiscale modelling in biomechanics: theoretical, computational and translational challenges'.