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Abstract Articular joints facilitate motion and transfer loads to underlying bone through a combination of cartilage tissue and synovial fluid, which together generate a low‐friction contact surface. Traumatic injury delivered to cartilage and the surrounding joint capsule causes secretion of proinflammatory cytokines by chondrocytes and the synovium, triggering cartilage matrix breakdown and impairing the ability of synovial fluid to lubricate the joint. Once these inflammatory processes become chronic, posttraumatic osteoarthritis (PTOA) development begins. However, the exact mechanism by which negative alterations to synovial fluid leads to PTOA pathogenesis is not fully understood. We hypothesize that removing the lubricating macromolecules from synovial fluid alters the relationship between mechanical loads and subsequent chondrocyte behavior in injured cartilage. To test this hypothesis, we utilized an ex vivo model of PTOA that involves subjecting cartilage explants to a single rapid impact followed by continuous articulation within a lubricating bath of either healthy synovial fluid, phosphate‐buffered saline (PBS), synovial fluid treated with hyaluronidase, or synovial fluid treated with trypsin. These treatments degrade the main macromolecules attributed with providing synovial fluid with its lubricating properties; hyaluronic acid and lubricin. Explants were then bisected and fluorescently stained to assess global and depth‐dependent cell death, caspase activity, and mitochondrial depolarization. Explants were tested via confocal elastography to determine the local shear strain profile generated in each lubricant. These results show that degrading hyaluronic acid or lubricin in synovial fluid significantly increases middle zone chondrocyte damage and shear strain loading magnitudes, while also altering chondrocyte sensitivity to loading. 

In various biological systems, analyzing how cell behaviors are coordinated over time would enable a deeper understanding of tissue-scale response to physiologic or superphysiologic stimuli. Such data is necessary for establishing both normal tissue function and the sequence of events after injury that lead to chronic disease. However, collecting and analyzing these large datasets presents a challenge—such systems are time-consuming to process, and the overwhelming scale of data makes it difficult to parse overall behaviors. This problem calls for an analysis technique that can quickly provide an overview of the groups present in the entire system and also produce meaningful categorization of cell behaviors. Here, we demonstrate the application of an unsupervised method—the Variational Autoencoder (VAE)—to learn the features of cells in cartilage tissue after impact-induced injury and identify meaningful clusters of chondrocyte behavior. This technique quickly generated new insights into the spatial distribution of specific cell behavior phenotypes and connected specific peracute calcium signaling timeseries with long term cellular outcomes, demonstrating the value of the VAE technique. 

Cellular response to stimulation governs tissue scale processes ranging from growth and development to maintaining tissue health and initiating disease. To determine how cells coordinate their response to such stimuli, it is necessary to simultaneously track and measure the spatiotemporal distribution of their behaviors throughout the tissue. Here, we report on a novel SpatioTemporal Response AnalysisIN Situ(STRAINS) tool that uses fluorescent micrographs, cell tracking, and machine learning to measure such behavioral distributions. STRAINS is broadly applicable to any tissue where fluorescence can be used to indicate changes in cell behavior. For illustration, we use STRAINS to simultaneously analyze the mechanotransduction response of 5000 chondrocytes—over 20 million data points—in cartilage during the 50 ms to 4 hours after the tissue was subjected to local mechanical injury, known to initiate osteoarthritis. We find that chondrocytes exhibit a range of mechanobiological responses indicating activation of distinct biochemical pathways with clear spatial patterns related to the induced local strains during impact. These results illustrate the power of this approach.