Macroscale mesenchymal condensation to study cytokine-driven cellular and matrix-related changes during cartilage degradation. (28th July 2020)

• Record Type: Journal Article
• Authors: Weber, Marie-Christin; Fischer, Lisa; Damerau, Alexandra; Ponomarev, Igor; Pfeiffenberger, Moritz; Gaber, Timo; Götschel, Sebastian; Lang, Jens; Röblitz, Susanna; Buttgereit, Frank; Ehrig, Rainald; Lang, Annemarie
• Is Part Of: Biofabrication. Volume 12:Number 4(2020)
• Publication Date: 2020-07-28
• Subjects: in vitro model -- tissue engineered cartilage -- cytokine-induced inflammation -- in silico model; Biomedical engineering -- Periodicals; Tissue engineering -- Periodicals; Biomedical materials -- Microstructure -- Periodicals; Bioengineering -- Periodicals; 610.28
• DOI: 10.1088/1758-5090/aba08f
• Languages: English
• ISSNs: 1758-5082

Abstract

Abstract: Understanding the pathophysiological processes of cartilage degradation requires adequate model systems to develop therapeutic strategies towards osteoarthritis (OA). Although different in vitro or in vivo models have been described, further comprehensive approaches are needed to study specific disease aspects. This study aimed to combine in vitro and in silico modeling based on a tissue-engineering approach using mesenchymal condensation to mimic cytokine-induced cellular and matrix-related changes during cartilage degradation. Thus, scaffold-free cartilage-like constructs (SFCCs) were produced based on self-organization of mesenchymal stromal cells (mesenchymal condensation) and (i) characterized regarding their cellular and matrix composition or secondly (ii) treated with interleukin-1β (IL–1β) and tumor necrosis factor α (TNFα) for 3 weeks to simulate OA-related matrix degradation. In addition, an existing mathematical model based on partial differential equations was optimized and transferred to the underlying settings to simulate the distribution of IL–1β, type II collagen degradation and cell number reduction. By combining in vitro and in silico methods, we aimed to develop a valid, efficient alternative approach to examine and predict disease progression and effects of new therapeutics.