Biology subjects

Grodzinsky, A.

Publications and source records attributed to Grodzinsky, A..

3 recordsLinked to original sources

bioRxiv2026

A computational framework to model cartilage degeneration induced by mechanoinflammation and cytokine-driven inflammation in post-traumatic osteoarthritis

Knee joint injury is a major risk factor for post-traumatic osteoarthritis (PTOA), often associated with early cartilage degeneration. Mechanical overloading and cytokine-driven inflammation are key drivers of this process, yet the underlying mechanisms and their distinct temporal and spatial contributions to cartilage degradation remain unclear. Here, we present a mechanobiological finite element framework that simulates cartilage degradation through cell-mediated proteolytic activity triggered by mechanoinflammation and cytokine-driven inflammation. The model reproduces experimentally observed depth-dependent loss of collagen and aggrecan, with mechanoinflammation inducing a transient response and cytokine-driven inflammation sustaining prolonged matrix degradation. Sensitivity analysis further shows that mechanoinflammation-driven degradation is governed mainly by protease production per cell, whereas cytokine-driven degradation is more sensitive to the rate of cellular stimulation. Together, this framework provides a mechanistic basis to study proteolytic cartilage degeneration and supports future in silico evaluation of therapeutic strategies aimed at mitigating cartilage degradation in PTOA.

biophysics↗

bioRxiv2025

MMP release following cartilage injury leads to collagen loss in intact tissue - a computational study

Damage of collagen fibril network in articular cartilage plays a key role in post-traumatic osteoarthritis but the main underlying mechanobiological mechanisms of fibrils degeneration early after injury are not fully understood. This study explores the hypothesis that injurious loading leads to cellular damage that triggers the release of matrix metalloproteinases (MMPs), resulting in loss of collagen content in cartilage. To investigate this, we developed a computational mechano-signaling model simulating spatial collagen loss in bovine cartilage. In the model, the injurious loading causes excessive shear strains in tissue matrix, leading to cell damage and subsequent release of MMPs. The model was compared to ex vivo cartilage explant experiments over 12 days post-injury where collagen content was assessed via Fourier-transform infrared microspectroscpy. By day 12, the simulated collagen loss aligned with our experimental findings along most of tissue depth ([~]30% bulk average loss in the model vs. [~]35% in the experiment). The results suggest that injury-related cell damage and the downstream MMP activity could partly explain the depth-wise collagen content loss in early days after ex vivo cartilage injury. Ultimately, combining the current approach with joint-level computational models could enhance the prediction of the onset and progression of cartilage degeneration. Author SummaryKnee injuries can initiate an irreversible degeneration of articular cartilage which can later lead to the development of post-traumatic osteoarthritis over the years. Currently, there is no cure or effective intervention to repair degenerated cartilage or halt disease progression. Yet, opportunities for intervention depend on a thorough understanding of mechanisms that govern the very early changes in cartilage tissue composition such as the collagen fibrils. In this work, we developed a finite element computational modeling framework to simulate cartilage following injurious loading, focusing on the early loss of collagen content. The model aims to capture the role of injury-induced cellular damage in elevating proteolytic activity within the tissue, which could rapidly degrade collagen fibrils and result in significant collagen loss. This model framework offers a tool for studying the degradation of the collagen fibril network, testing hypotheses involving cell-driven mechano-signalling pathways and evaluating potential treatment interventions aimed at preventing collagen loss.

biophysics↗

bioRxiv2022

Injury-related cell death and proteoglycan loss in articular cartilage: Numerical model combining necrosis, reactive oxygen species, and inflammatory cytokines

Osteoarthritis (OA) is a common musculoskeletal disease that leads to deterioration of articular cartilage, joint pain, and decreased quality of life. When OA develops after a joint injury, it is designated as post-traumatic OA (PTOA). The etiology of PTOA remains poorly understood, but it is known that proteoglycan (PG) loss, cell dysfunction, and cell death in cartilage are among the first signs of the disease. These processes, influenced by biomechanical and inflammatory stimuli, disturb the normal cell-regulated balance between tissue synthesis and degeneration. Previous computational mechanobiological models have not explicitly incorporated the cell-mediated degradation mechanisms triggered by an injury that eventually can lead to tissue-level compositional changes. Here, we developed a 2-D mechanobiological finite element model to predict necrosis, apoptosis following excessive production of reactive oxygen species (ROS), and inflammatory cytokine (interleukin-1)-driven apoptosis in cartilage explant. The resulting PG loss over 30 days was simulated. Biomechanically triggered PG degeneration, associated with cell necrosis, excessive ROS production, and cell apoptosis, was predicted to be localized near a lesion, while interleukin-1 diffusion-driven PG degeneration was manifested more globally. The numerical predictions were supported by several previous experimental findings. Furthermore, the ROS and inflammation mechanisms had longer-lasting effects (over 3 days) on the PG content than localized necrosis. Interestingly, the model also showed proteolytic activity and PG biosynthesis closer to the levels of healthy tissue when pro-inflammatory cytokines were rapidly inhibited or cleared from the culture medium, leading to partial recovery of PG content. The mechanobiological model presented here may serve as a numerical tool for assessing early cartilage degeneration mechanisms and the efficacy of interventions to mitigate PTOA progression. Author summaryOsteoarthritis is one of the most common musculoskeletal diseases. When osteoarthritis develops after a joint injury, it is designated as post-traumatic osteoarthritis. A defining feature of osteoarthritis is degeneration of articular cartilage, which is partly driven by cartilage cells after joint injury, and further accelerated by inflammation. The degeneration triggered by these biomechanical and biochemical mechanisms is currently irreversible. Thus, early prevention/mitigation of disease progression is a key to avoiding PTOA. Prior computational models have been developed to provide insights into the complex mechanisms of cartilage degradation, but they rarely include cell-level cartilage degeneration mechanisms. Here, we present a novel approach to simulate how the early post-traumatic biomechanical and inflammatory effects on cartilage cells eventually influence tissue composition. Our model includes the key regulators of early post-traumatic osteoarthritis: chondral lesions, cell death, reactive oxygen species, and inflammatory cytokines. The model is supported by several experimental explant culture findings. Interestingly, we found that when post-injury inflammation is mitigated, cartilage composition can partially recover. We suggest that mechanobiological models including cell-tissue-level mechanisms can serve as future tools for evaluating high-risk lesions and developing new intervention strategies.

biophysics↗