A biphasic visco-hyperelastic damage model for articular cartilage: application to micromechanical modelling of the osteoarthritis-induced degradation behaviour

Surrogate modeling of articular cartilage degradation to understand the synergistic role of MMP-1 and MMP-9: a case study

A characteristic feature of arthritic diseases is cartilage extracellular matrix (ECM) degradation, often orchestrated by the overexpression of matrix metalloproteinases (MMPs) and other proteases. The interplay between fibril level degradation and the tissue-level aggregate response to biomechanical loading was explored in this work by a computational multiscale cartilaginous model. We considered the relative abundance of collagenases (MMP-1) and gelatinases (MMP-9) in surrogate models, where the diffusion (spatial distribution) of these enzymes and the subsequent, co-localized fibrillar damage were spatially randomized with Latin Hypercube Sampling. The computational model was constructed by incorporating the results from prior molecular dynamics simulations (tensile test) of microfibril degradation into a hyper-elastoplastic fibril-reinforced cartilage model. Including MMPs-mediated collagen fibril-level degradation in computational models may help understand the ECM pathomechanics at the tissue level. The mechanics of cartilage tissue and fibril show variations in mechanical integrity depending on the different combinations of MMPs-1 and 9 with a concentration ratio of 1:1, 3:1, and 1:3 in simulated indentation tests. The fibril yield (local failure) was initiated at 20.2 ± 3.0 (%) and at 23.0 ± 2.8 (%) of bulk strain for col 1:gel 3 and col 3: gel 1, respectively. The reduction in failure stress (global response) was 39.8% for col 1:gel 3, 37.5% for col 1:gel 1, and 36.7% for col 3:gel 1 compared with the failure stress of the degradation free tissue. These findings indicate that cartilage's global and local mechanisms of failure largely depend on the relative abundance of the two key enzymes-collagenase (MMP-1) and gelatinase (MMP-9) and the spatial characteristics of diffusion across the layers of the cartilage ECM.

The molecular mechanism research of cartilage calcification induced by osteoarthritis

To explore the molecular mechanism of cartilage calcification induced by osteoarthritis (OA) based on distal-less homeobox gene 5 – alkaline phosphatase – integrin-binding sialoprotein – ecto-nucleotide pyrophosphatase 1 (DLX5-ALPL-IBSP-ENPP1) signal axis. Twenty-four rabbits were selected to build models of cartilage calcification induced by OA and randomly divided into 3 groups. The first group was the normal group whose rabbits were injected into 0.9% saline (0.3 mL), and the second group was model group. The third group was model group whose rabbits were injected into DLX5 antibody by caudal vein. Alizarin red calcium staining was used to analyze calcium deposition of cartilage matrix. Immunohistochemical staining was used to analyze the relative expression levels of proteins DLX5 and ENPP1, and western blot was used to analyze the DLX5, ALPL, IBSP, and ENPP1 expression. Calcium salt precipitation was the most serious, and the calcification area increased in the model group. Although calcified nodules appeared in the anti-DLX5 group, they were relatively few. Immunohistochemical staining analysis showed that the protein DLX5 located in the nucleus and the protein ENPP1 located in the extracellular matrix. Western blot analysis showed that the expressions of proteins DLX5, ALPL, IBSP, and ENPP1 were the highest in OA Model group than that of NC group, followed by anti-DLX5 group. The proteins DLX5, ALPL, IBSP, and ENPP1 can promote cartilage calcification induced by OA based on DLX5-ALPL-IBSP-ENPP1 signal axis.

Osteoarthritis year in review 2021: mechanics

Osteoarthritis (OA) has a complex, heterogeneous and only partly understood etiology. There is a definite role of joint cartilage pathomechanics in originating and progressing of the disease. Although it is still not identified precisely enough to design or select targeted treatments, the progress of this year's research demonstrates that this goal became much closer. On multiple scales - tissue, joint and whole body - an increasing number of studies were done, with impressive results. (1) Technology based instrument innovations, especially when combined with machine learning models, have broadened the applicability of biomechanics. (2) Combinations with imaging make biomechanics much more precise & personalized. (3) The combination of Musculoskeletal & Finite Element Models yield valid personalized cartilage loads. (4) Mechanical outcomes are becoming increasingly meaningful to inform and evaluate treatments, including predictive power from biomechanical models. Since most recent advancements in the field of biomechanics in OA are at the level of a proof op principle, future research should not only continue on this successful path of innovation, but also aim to develop clinical workflows that would facilitate including precision biomechanics in large scale studies. Eventually this will yield clinical tools for decision making and a rationale for new therapies in OA.

Icariin accelerates cartilage defect repair by promoting chondrogenic differentiation of BMSCs under conditions of oxygen-glucose deprivation

This study explored the role played by combined ICA and bone mesenchymal stem cells (BMSCs) in repairing rabbit knee cartilage defects. Firstly, rabbit BMSCs were isolated and used to construct an in vitro cellular model of oxygen‐glucose deprivation/reoxygenation (OGD/R). Subsequently, ICA processing, Alcian blue staining, immunofluorescence and Western blot studies were performed to evaluate the ability of BMSCs to display signs of chondrogenic differentiation. Furthermore, a rabbit knee cartilage injury model was established in vivo. International Cartilage Repair Society (ICRS) macroscopic evaluations, H&E, Alcian blue and EdU staining, as well as immunohistochemistry, were analysed cartilage repair and pathological condition of the knee cartilage tissue. Our in vitro results showed that ICA promoted the chondrogenic differentiation of BMSCs, as well as aggrecan (AGR), bone morphogenetic protein 2 (BMP2) and COL2A1 protein expression in BMSCs. In vivo experiments showed that rabbits in the BMSCs or ICA treatment group had higher ICRS scores and displayed a better restoration of cartilage‐like tissue and chondrocyte expression on the surface of their cartilage defects. In conclusion, ICA or BMSCs alone could repair rabbit knee cartilage damage, and combined treatment with ICA and BMSCs showed a better ability to repair rabbit knee cartilage damage.

A backward pre-stressing algorithm for efficient finite element implementation of in vivo material and geometrical parameters into fibril-reinforced mixture models of articular cartilage

Classical continuum mechanics has been widely used for implementation of the material models of articular cartilage (AC) mainly with the aid of the finite element (FE) method, which, in many cases, considers the stress-free configuration as the initial configuration. On the contrary, the AC experimental tests typically begin with the pre-stressed state of both material and geometrical properties. Indeed, imposing the initial pre-stress onto AC models with the in vivo values as the initial state would result in nonphysiologically expansion of the FE mesh due to the soft nature of AC. This change in the model configuration can also affect the material behavior kinematically in the mixture models of cartilage due to the intrinsic compressibility of the tissue. Although several different fixed-point backward algorithms, as the most straightforward pre-stressing methods, have already been developed to incorporate these initial conditions into FE models iteratively, such methods focused merely on the geometrical parameters, and they omitted the material variations of the anisotropic mixture models of AC. To address this issue, we propose an efficient algorithm generalizing the backward schemes to restore stress-free conditions by optimizing both the involving variables, and we hypothesize that it can affect the results considerably. To this end, a comparative simulation was implemented on an advanced and validated multiphasic model by the new and conventional algorithms. The results are in support of the hypothesis, as in our illustrative general AC model, the material parameters experienced a maximum error of 16% comparing to the initial in vivo data when the older algorithm was employed, and it led to a maximum variation of 44% in the recorded stresses comparing to the results of the new method. We conclude that our methodology enhanced the model fidelity, and it is applicable in most of the existing FE solvers for future mixture studies with accurate stress distributions.