Finite element (FE) modeling has emerged as a powerful computational approach in cardiovascular biomechanics, enabling detailed simulations of myocardial stress, strain, and hemodynamics, which are challenging to measure with conventional imaging techniques. This narrative review explores the progression of cardiac FE modeling from research-focused applications to its increasing integration into clinical practice. Specific attention is given to the mechanical effects of myocardial infarction, the limitations of conventional LV volume-reduction surgeries, and novel therapeutic approaches like passive myocardial reinforcement via hydrogel injections. Furthermore, the review highlights the critical role of patient-specific FE simulations in optimizing LV assist device parameters and guiding targeted device placements. Cutting-edge developments in artificial intelligence-enhanced FE modeling, including surrogate models and precomputed simulation databases, are examined for their potential to facilitate real-time, personalized therapeutic decision-making. Collectively, these advancements position FE modeling as an essential tool in precision medicine for structural heart disease.

Lineage plasticity underscores the resilience of cancer cells in the context of drug treatment. However, lineage fates can also be therapeutically directed. We demonstrate that the eukaryotic initiation factor 4E (eIF4E) cap-binding domain is a critical regulator of lineage plasticity in prostate cancer. Using a first-in-class cap-binding domain inhibitor, we found that plasticity is driven by translational repression of basal keratins through a shared cis-regulatory element enciphered in their 5' untranslated regions (UTRs). Simultaneously this stabilized the androgen receptor (AR) through translational upregulation of the deubiquitinases BAP1 and OTUD3. This lineage program is essential for cell survival and drives a druggable vulnerability. Notably, tumors resistant to AR blockade regained sensitivity upon eIF4E cap-binding domain inhibition, which reprogrammed them toward a luminal state. In castration-resistant prostate cancer (CRPC) patients, elevated eIF4E expression was associated with a basal phenotype, reduced luminal differentiation and accelerated resistance to AR pathway inhibitors (ARPIs). These discoveries uncover a role for the eIF4E cap-binding domain in lineage plasticity and highlight that targeting this domain offers a promising strategy to overcome treatment resistance in prostate cancer.

Mitral valve orifice area is a key functional metric that depends on complex geometric features, motivating a systematic assessment of the relative influence of these parameters. In this study, the mitral valve geometry is parameterized using twelve geometric variables, and a global sensitivity analysis based on Sobol indices is performed to quantify their relative importance. Because global sensitivity analysis requires many simulations, a Gaussian Process regressor is developed to efficiently predict the orifice area from the geometric inputs. Structural simulations of the mitral valve are carried out in Abaqus, focusing exclusively on the valve mechanics. The predicted distribution of orifice areas obtained from the Gaussian Process shows strong agreement with the ground-truth simulation results, and similar agreement is observed when only the most influential geometric parameters are varied. The analysis identifies a subset of geometric parameters that dominantly govern the mitral valve orifice area and can be reliably extracted from medical imaging modalities such as echocardiography. These findings establish a direct link between echocardiographic measurements and physics-based simulations and provide a framework for patient-specific assessment of mitral valve mechanics, with potential applications in guiding interventional strategies such as MitraClip placement.