Osteoarthritis (OA) affects a large number of the population, and its incidence is showing a growing trend with the increasing life span. OA is the most prevalent joint condition worldwide, and currently, there is no functional cure for it. This review seeks to briefly overview the management of knee OA concerning standardized pharmaceutical and clinical approaches, as well as the new biotechnological horizons of OA treatment. The potential of biomaterials and state of the art of advanced therapeutic approaches, such as cell and gene therapy focused primarily on cartilage regeneration are the main subjects of this review. Biotechnol. Bioeng. 2017;114: 717-739. © 2016 Wiley Periodicals, Inc.

BackgroundPathogenesis of inflammatory diseases can be tracked by studying the causality relationships among the factors contributing to its development. We could, for instance, hypothesize on the connections of the pathogenesis outcomes to the observed conditions. And to prove such causal hypotheses we would need to have the full understanding of the causal relationships, and we would have to provide all the necessary evidences to support our claims. In practice, however, we might not possess all the background knowledge on the causality relationships, and we might be unable to collect all the evidence to prove our hypotheses.ResultsIn this work we propose a methodology for the translation of biological knowledge on causality relationships of biological processes and their effects on conditions to a computational framework for hypothesis testing. The methodology consists of two main points: hypothesis graph construction from the formalization of the background knowledge on causality relationships, and confidence measurement in a causality hypothesis as a normalized weighted path computation in the hypothesis graph. In this framework, we can simulate collection of evidences and assess confidence in a causality hypothesis by measuring it proportionally to the amount of available knowledge and collected evidences.ConclusionsWe evaluate our methodology on a hypothesis graph that represents both contributing factors which may cause cartilage degradation and the factors which might be caused by the cartilage degradation during osteoarthritis. Hypothesis graph construction has proven to be robust to the addition of potentially contradictory information on the simultaneously positive and negative effects. The obtained confidence measures for the specific causality hypotheses have been validated by our domain experts, and, correspond closely to their subjective assessments of confidences in investigated hypotheses. Overall, our methodology for a shared hypothesis testing framework exhibits important properties that researchers will find useful in literature review for their experimental studies, planning and prioritizing evidence collection acquisition procedures, and testing their hypotheses with different depths of knowledge on causal dependencies of biological processes and their effects on the observed conditions.

Osteochondral (OC) defects are prevalent among young adults and are notorious for being unable to heal. Although they are traumatic in nature, they often develop silently. Detection of many OC defects is challenging, despite the criticality of early care. Current repair approaches face limitations and cannot provide regenerative or long-standing solution. Clinicians and researchers are working together in order to develop approaches that can regenerate the damaged tissues and protect the joint from developing osteoarthritis. The current concepts of tissue engineering and regenerative medicine, which have brought many promising applications to OC management, are overviewed herein. We will also review the types of stem cells that aim to provide sustainable cell sources overcoming the limitation of autologous chondrocyte-based applications. The various scaffolding materials that can be used as extracellular matrix mimetic and having functional properties similar to the OC unit are also discussed.

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