Simulating the growth of articular cartilage explants in a permeation bioreactor to aid in experimental protocol design

Depth and strain rate-dependent mechanical response of chondrocytes in reserve zone cartilage subjected to compressive loading

The role of the growth plate reserve zone is not well understood. It has been proposed to serve as a source of stem cells and to produce morphogens that control the alignment of clones in preparation for the transition into the proliferative zone. We hypothesized that if such a role exists, there are likely to be mechanoregulatory stimuli in cellular response through the depth of the reserve zone. A poroelastic multiscale finite element model of bone/growth-plate/bone was developed for examining the reserve zone cell transient response when compressed to 5% of the cartilage thickness at strain rates of 0.18%/s, 5%/s, 50%/s, and 200%/s. Chondrocyte maximum principal strains, height-, width-, and membrane-strains were found to be highly dependent on reserve zone tissue depth and strain rate. Cell-level strains and fluid transmembrane outflow from the cell were influenced by the permeability of the calcified cartilage between subchondral bone plate and reserve zone and by the applied strain rate. Cell strain levels in the lower reserve zone were less sensitive to epiphyseal permeability than in the upper reserve zone. In contrast, the intracellular fluid pressures were relatively uniform with reserve zone tissue depth and less sensitive to epiphyseal permeability. Fluid shear stress, induced by fluid flow over the cell surface, provided mechanoregulatory signals potentially sufficient to stimulate reserve zone chondrocytes near the subchondral bone plate interface. These results suggest that the strain rate and tissue depth dependence of cell-level strains and cell surface fluid shear stress may provide mechanoregulatory cues in the reserve zone.

The effects of dynamic compressive loading on human mesenchymal stem cell osteogenesis in the stiff layer of a bilayer hydrogel

Bilayer hydrogels with a soft cartilage-like layer and a stiff bone-like layer embedded with human mesenchymal stem cells (hMSCs) are promising for osteochondral tissue engineering. The goals of this work were to evaluate the effects of dynamic compressive loading (2.5% applied strain, 1 Hz) on osteogenesis in the stiff layer and spatially map local mechanical responses (strain, stress, hydrostatic pressure, and fluid velocity). A bilayer hydrogel was fabricated from soft (24 kPa) and stiff (124 kPa) poly (ethylene glycol) hydrogels. With hMSCs embedded in the stiff layer, osteogenesis was delayed under loading evident by lower OSX and OPN expressions, alkaline phosphatase activity, and collagen content. At Day 28, mineral deposits were present throughout the stiff layer without loading but localized centrally and near the interface under loading. Local strains mapped by particle tracking showed substantial equivalent strain (~1.5%) transferring to the stiff layer. When hMSCs were cultured in stiff single-layer hydrogels subjected to similar strains, mineralization was inhibited. Finite element analysis revealed that hydrostatic pressures ≥~600 Pa correlated to regions lacking mineralization in both hydrogels. Fluid velocities were low (~1-10 nm/s) in the hydrogels with no apparent correlation to mineralization. Mineralization was recovered by inhibiting ERK1/2, indicating cell-mediated inhibition. These findings suggest that high strains (~1.5%) combined with higher hydrostatic pressures negatively impact osteogenesis, but in a manner that depends on the magnitude of each mechanical response. This work highlights the importance of local mechanical responses in mediating osteogenesis of hMSCs in bilayer hydrogels being studied for osteochondral tissue engineering.

Simulation of Subject-Specific Progression of Knee Osteoarthritis and Comparison to Experimental Follow-up Data: Data from the Osteoarthritis Initiative

Economic costs of osteoarthritis (OA) are considerable. However, there are no clinical tools to predict the progression of OA or guide patients to a correct treatment for preventing OA. We tested the ability of our cartilage degeneration algorithm to predict the subject-specific development of OA and separate groups with different OA levels. The algorithm was able to predict OA progression similarly with the experimental follow-up data and separate subjects with radiographical OA (Kellgren-Lawrence (KL) grade 2 and 3) from healthy subjects (KL0). Maximum degeneration and degenerated volumes within cartilage were significantly higher (p < 0.05) in OA compared to healthy subjects, KL3 group showing the highest degeneration values. Presented algorithm shows a great potential to predict subject-specific progression of knee OA and has a clinical potential by simulating the effect of interventions on the progression of OA, thus helping decision making in an attempt to delay or prevent further OA symptoms.

A Novel Method to Simulate the Progression of Collagen Degeneration of Cartilage in the Knee: Data from the Osteoarthritis Initiative

We present a novel algorithm combined with computational modeling to simulate the development of knee osteoarthritis. The degeneration algorithm was based on excessive and cumulatively accumulated stresses within knee joint cartilage during physiological gait loading. In the algorithm, the collagen network stiffness of cartilage was reduced iteratively if excessive maximum principal stresses were observed. The developed algorithm was tested and validated against experimental baseline and 4-year follow-up Kellgren-Lawrence grades, indicating different levels of cartilage degeneration at the tibiofemoral contact region. Test groups consisted of normal weight and obese subjects with the same gender and similar age and height without osteoarthritic changes. The algorithm accurately simulated cartilage degeneration as compared to the Kellgren-Lawrence findings in the subject group with excess weight, while the healthy subject group’s joint remained intact. Furthermore, the developed algorithm followed the experimentally found trend of cartilage degeneration in the obese group (R² = 0.95, p < 0.05; experiments vs. model), in which the rapid degeneration immediately after initiation of osteoarthritis (0–2 years, p < 0.001) was followed by a slow or negligible degeneration (2–4 years, p > 0.05). The proposed algorithm revealed a great potential to objectively simulate the progression of knee osteoarthritis.