Osteoarthritis (OA) is a major cause of disability in the adult population. As a progressive degenerative joint disorder, OA is characterized by cartilage damage, changes in the subchondral bone, osteophyte formation, muscle weakness, and inflammation of the synovium tissue and tendon. Although OA has long been viewed as a primary disorder of articular cartilage, subchondral bone is attracting increasing attention. It is commonly reported to play a vital role in the pathogenesis of OA. Subchondral bone sclerosis, together with progressive cartilage degradation, is widely considered as a hallmark of OA. Despite the increase in bone volume fraction, subchondral bone is hypomineralized, due to abnormal bone remodeling. Some histopathological changes in the subchondral bone have also been detected, including microdamage, bone marrow edema-like lesions and bone cysts. This review summarizes basic features of the osteochondral junction, which comprises subchondral bone and articular cartilage. Importantly, we discuss risk factors influencing subchondral bone integrity. We also focus on the microarchitectural and histopathological changes of subchondral bone in OA, and provide an overview of their potential contribution to the progression of OA. A hypothetical model for the pathogenesis of OA is proposed.

Atomic scale computer simulations, validated with experimental data, are used to uncover the factors responsible for defect‐induced chemical expansion observed in non‐stoichiometric oxides, exemplified by CeO2 and ZrO2. It is found that chemical expansion is the result of two competing processes: the formation of a vacancy (leading to a lattice contraction primarily due to electrostatic interactions) and the cation radius change (leading to a lattice expansion primarily due to steric effects). The chemical expansion coefficient is modeled as the summation of two terms that are proportional to the cation and oxygen radius change. This model introduces an empirical parameter, the vacancy radius, which can be reliably predicted from computer simulations, as well as from experimental data. This model is used to predict material compositions that minimize chemical expansion in fluorite structured solid oxide fuel cell electrolyte materials under typical operating conditions.