Dilated cardiomyopathy (DCM) is a condition characterized by impaired cardiac contractility and enlargement of the heart chambers, leading to systolic dysfunction. Danicamtiv, a novel myosin activator, shows potential in restoring cardiac function by modulating crossbridge cycling affecting positively on increasing force and calcium sensitivity. While promising results have been observed in mouse and porcine models, the translational gap to human cardiac function remains. To address this, we used the MUSICO computational platform, which models sarcomere dynamics and crossbridge behavior, to simulate the effects of Danicamtiv on human trabeculae affected by DCM. MUSICO simulations were performed using experimental data from mouse and porcine cardiac tissues, incorporating physiological differences such as heart rates and myosin isoforms. The simulations demonstrated that Danicamtiv enhances tension at high calcium concentrations (pCa=4), increases calcium sensitivity, and prolongs muscle relaxation during twitch contractions. These effects are achieved by increasing [Ca2+] sensitivity of the transition rate from the crossbridge “OFF” state to “ON” state and by decreasing ADP release rate, leading to prolonged tension development. Our findings suggest that Danicamtiv has the potential to improve cardiac function in human DCM, providing a valuable tool for predicting drug efficacy in silico. Further validation using human cardiac tissue is needed to confirm its therapeutic impact.

Heart failure is recognized as a modern epidemic and despite advances in therapy and research, heart failure still carries an ominous prognosis and a significant socioeconomic burden. The main aim of this paper is to demonstrate how novel Decision Support System (DSS) and computational platform like INTELHEART can transform the future of healthcare and early diagnosis of heart failure. The main idea is integration of patient-specific data (i.e. demographic and physical characteristics, medical history, symptoms and signs) and results obtained using existing and novel diagnostic technologies into the cloud environment. Data will be used by different tools for machine learning and computational modelling, developing virtual patient population. Moreover, voice as a biomarker will be collected among participating patients, in order to create a VoiceHeart mobile app. INTELHEART represents a transformative advancement in heart failure care, aiming to make treatment more personalized, and proactive. This initiative centers on precision medicine, using AI-driven analysis and a powerful DSS alongside the cloud-based platform and VoiceHeart mobile app to assist both clinicians and patients. Additionally, it incorporates assessments of psychological resilience and emotional well-being, addressing the oftenoverlooked mental health factors essential to comprehensive heart failure management.

This paper presents a short review of the piezoelectric materials in energy harvesting. Energy harvesting principle, as the method for obtaining energy from environment has been described. Materials and material combinations for creating an energy harvesting composites are discussed, such as ceramic- and polymer-based composites and their mechanical properties. The list of the mostly used piezoelectric materials is presented and elaborated. Possible applications of the energy harvesting materials are discussed, including nanogenerators, biosensors and biomedical applications.

Continuous degeneration of muscle tissue, inflammatory processes and fibrosis characterized by a loss of muscle mass, formation of micro-scars, adipose tissue in the muscles and eventual muscle punctures are often signs of muscular dystrophies (dystrophinopathies). These neuromuscular diseases result from genetic mutations of a structural protein called dystrophin. The absence of functional dystrophin leads to the most common and severe form of muscular dystrophy, Duchenne muscular dystrophy (DMD). Typically, within one muscle bundle there are so-called fast and slow muscle fibers that shorten and lengthen at different speeds during muscle contraction. Using the multiscale muscle platform Mexie we evaluated how the lack of dystrophin affects the connective tissue deformation between these two types of muscle fibers. By adjusting the elasticity of extracellular matrix layer, we estimated the magnitude of the shear strain under unloaded and lightly loaded fiber contractions caused by differences in shortening velocities between fast and slow fibers. The simulations showed that without dystrophin large shear strains are generated causing local micro injury and inflammation leading to further muscle degeneration. The multiscale muscle modeling approach presented here could help accelerate understanding of DMD and lead to faster development of new drugs and treatments of patients.

Hypertrophic and Dilated Cardiomyopathies are caused by inherited mutations in sarcomeric proteins: Myosin (M), Troponin (Tn), Tropomyosin (Tm) and Myosin Binding Protein-C (MyBP-C). A quantitative understanding of how mutations change protein behaviour, and hence cardiac muscle contraction, and how adaptations to these changes result in disease, could accelerate the design of novel personalized treatments and therapeutics. Newly developed multiscale computational tools, tightly interlaced with multiple experiments, can enhance efforts to correct the problems associated with cardiomyopathies and prevent or more effectively manage the disease. Using these computational tools, we examined the effects of mutations in myosin and troponin on cardiac muscle contractility and overall heart functional behaviour. We also examined the effects of potential therapeutics that modulate protein interactions and cardiac muscle contractility.