In the literature: March 2026 highlights

Folkmanaite, Milda, et al. “Electromechanical modelling and simulation of human‐induced pluripotent stem cell‐derived cardiomyocytes predict drug‐induced contractility effects.” The Journal of Physiology (2026).

Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) hold promise in personalized medicine, particularly for cardiac diseases and human-data-based pharmacology studies. Assessing hiPSC-CM mechanics and their changes in response to drug action in silico enables more efficient drug testing. For such investigations, hiPSC-CMs also provide a versatile alternative to adult human cardiac tissue which is limited in availability for research. To enable in silico investigations of hiPSC-CM electrophysiology and contraction, we developed and evaluated two versions of hiPSC-CM electromechanical models with different maturation states. The models were based solely on human cardiomyocyte and hiPSC-CM data. The evaluation process involved comparing simulation outcomes with an extensive dataset of experimental data to ensure the reliability of the model within the context of hiPSC-CM pharmacology studies. The models uniquely incorporated the mechanical properties of hiPSC-CMs, providing insights into the mechanisms underlying their contractile behaviour. In our in silico studies, we simulated the effects of 64 different drugs, including those with previously untested inotropic effects. We demonstrated agreement between the simulation and experimental datasets, correctly identifying the inotropic effects of 41 out of 48 drugs. We also compared the effect of pharmacological agents with unknown inotropic effects and conducted novel experiments demonstrating agreement with simulation outcomes. Finally, using the models, we demonstrated the mechanisms of previously unrecognized rate-dependent inotropic effects of paliperidone. Altogether this study presents an in vitro – in silico framework which is evaluated against experimental data and allows for simulating drug-dependent electromechanical effects with high accuracy and prediction of rate-dependent inotropic effects.

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Lai, Juntong, and Damien Lacroix. “A computational study of adiposity-associated factors in the inflammatory process of osteoarthritis.” Journal of Theoretical Biology (2026): 112429.

Chronic inflammation is a key factor in the degenerative changes of osteoarthritic joints. Obesity significantly raises the risk of osteoarthritis (OA), since excess body fat (adipose tissue) not only systemically increases the level of inflammation but also locally stimulates the inflammatory responses within osteoarthritic joints. In this context, physical activity is a practical approach in OA prevention and intervention, whereas current therapeutic strategies remain empirical and lack patient-specific tailoring. This makes it challenging to determine the appropriate dose and timing of physical activity therapy for diverse individuals. Building on our previous work of an adipokine-mediated inflammation model, this study aimed to analyse the effects of obesity and physical activity on OA inflammation by parameterising the inflammatory activities. In this model, five key mediator groups (pro- and anti-inflammatory cytokines, matrix metalloproteinases, adipokines and fibronectin fragments) were included. A global sensitivity analysis was conducted in the estimated parametric space and revealed the critical role of adiposity-associated factors in regulating inflammation. In addition, the inflammatory activities were simulated by tuning two adiposity-associated parameters, body mass index (BMI) and physical activity level (PAL), factoring in a simulated injury. The effectiveness of three physical activity intervention strategies was assessed by examining the inflammatory responses of the representative cases with four BMI profiles. A marked sensitivity to the timing (window period) of physical activity implementation was found. Results underscored the importance of accounting for both the adiposity level and the extent of tissue damage when designing intervention strategies of physical activity and optimising their timing for managing OA inflammation. This novel computational study analyses the adiposity-associated effects of physical activity on OA inflammation, illustrating that the effective window period of physical activity interventions varies from 0 to 15 months, depending on the level of adiposity and mechanical damage. Outcomes from the evaluation of the time window can strategically contribute to optimising physical activity interventions for the management of OA risk at an early stage.

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Soehnlen, Sophia, et al. “Predicted effects of hip distraction on knee ligament mechanics following total knee arthroplasty: A finite element analysis.” Clinical Biomechanics (2026): 106763.