Multilevel modelling for decision support in hypertrophic cardiomyopathy in the SMASH-HCM project

Hypertrophic cardiomyopathy (HCM) is the most common inherited genetic heart disease, and its most feared outcome is a sudden death even in a young otherwise healthy adult. The EU-funded project SMASH-HCM aims at dramatically improving HCM stratification and disease management, both for clinicians and patients. The project combines data from the patients at multiple levels, from genetic and molecular data to in-silico physiological and family history data and creates in-vitro and computational models of the disease at these various levels. A digital twin of the patient will be formed based on these data modelling tasks. Modelling approaches, data-driven artificial intelligence and knowledge existing in literature will complement each other to provide decision support for the clinicians to optimize interventions, and actionable information about the disease status and development will be offered to the patient

The Influence of Age and Skull Conductivity on Surface and Subdermal Bipolar EEG Leads

Bioelectric source measurements are influenced by the measurement location as well as the conductive properties of the tissues. Volume conductor effects such as the poorly conducting bones or the moderately conducting skin are known to affect the measurement precision and accuracy of the surface electroencephalography (EEG) measurements. This paper investigates the influence of age via skull conductivity upon surface and subdermal bipolar EEG measurement sensitivity conducted on two realistic head models from the Visible Human Project. Subdermal electrodes (a.k.a. subcutaneous electrodes) are implanted on the skull beneath the skin, fat, and muscles. We studied the effect of age upon these two electrode types according to the scalp-to-skull conductivity ratios of 5, 8, 15, and 30 : 1. The effects on the measurement sensitivity were studied by means of the half-sensitivity volume (HSV) and the region of interest sensitivity ratio (ROISR). The results indicate that the subdermal implantation notably enhances the precision and accuracy of EEG measurements by a factor of eight compared to the scalp surface measurements. In summary, the evidence indicates that both surface and subdermal EEG measurements benefit better recordings in terms of precision and accuracy on younger patients

INFLUENCE OF EXERCISE HISTORY ON FALL-INDUCED HIP FRACTURE RISK

Hip fracture is a major public health problem. Thin superolateral cortex of the femoral neck experiences unusually high stress in a sideway fall, contributing to hip fracture risk. The aim of this study is to examine how exercise based loading history, known to affect the femoral neck cortical structure, influences fall-induced fracture risk. For this purpose, finite element models were created from the proximal femur MRI of 91 young athletic and 20 control females. Fall-induced superolateral cortical safety factors (SF) were estimated in the distal volume of femoral neck. Significantly higher (p \u3c 0.05) SFs were observed from femoral necks with high impact (H-I), odd impact (O-I), and repetitive impact (R-I) exercise history, indicating lower fracture risk. The results indicate that it is advisable to include some impact exercise in a fracture preventive exercise progra

Causal coupling inference from multivariate time series based on ordinal partition transition networks

Identifying causal relationships is a challenging yet crucial problem in many fields of science like epidemiology, climatology, ecology, genomics, economics and neuroscience, to mention only a few. Recent studies have demonstrated that ordinal partition transition networks (OPTNs) allow inferring the coupling direction between two dynamical systems. In this work, we generalize this concept to the study of the interactions among multiple dynamical systems and we propose a new method to detect causality in multivariate observational data. By applying this method to numerical simulations of coupled linear stochastic processes as well as two examples of interacting nonlinear dynamical systems (coupled Lorenz systems and a network of neural mass models), we demonstrate that our approach can reliably identify the direction of interactions and the associated coupling delays. Finally, we study real-world observational microelectrode array electrophysiology data from rodent brain slices to identify the causal coupling structures underlying epileptiform activity. Our results, both from simulations and real-world data, suggest that OPTNs can provide a complementary and robust approach to infer causal effect networks from multivariate observational data

Multifocal optical projection microscopy enables label-free 3D measurement of cardiomyocyte cluster contractility

Human induced pluripotent stem cell (hiPSC)-derived cardiomyocyte (CM) models have become an attractive tool for in vitro cardiac disease modeling and drug studies. These models are moving towards more complex three-dimensional microphysiological organ-on-chip systems. Label-free imaging-based techniques capable of quantifying contractility in 3D are needed, as traditional two-dimensional methods are ill-suited for 3D applications. Here, we developed multifocal (MF) optical projection microscopy (OPM) by integrating an electrically tunable lens to our in-house built optical projection tomography setup for extended depth of field brightfield imaging in CM clusters. We quantified cluster biomechanics by implementing our previously developed optical flow-based CM video analysis for MF-OPM. To demonstrate, we acquired and analyzed multiangle and multifocal projection videos of beating hiPSC-CM clusters in 3D hydrogel. We further quantified cluster contractility response to temperature and adrenaline and observed changes to beating rate and relaxation. Challenges emerge from light penetration and overlaying textures in larger clusters. However, our findings indicate that MF-OPM is suitable for contractility studies of 3D clusters. Thus, for the first time, MF-OPM is used in CM studies and hiPSC-CM 3D cluster contraction is quantified in multiple orientations and imaging planes.Peer reviewe

Label-free Estimation of Sarcomere Orientation from Brightfield Microscopy Images of Induced Pluripotent Stem Cell Derived Cardiomyocyte Nuclei

Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) provide a platform for studying disease models and physiological conditions. Sarcomere structure orientation can be used to determine hiPSC-CM culture maturity. However, novel methods are needed for assessing their structure and cellular function. Brightfield microscopy enables continuous label-free measurement of cell cultures in vitro. Here, we propose evaluating sarcomere organization from the morphology and orientation of nuclei in brightfield images. We used publicly available image dataset consisting of brightfield complemented with stained nuclei and α- actinin. We trained a U-Net-based network for segmenting nuclei from brightfield images (IOU of 0.72) and extracted the orientation and aspect ratio of the predicted and stained nuclei. We quantified myofibrillar orientation from α-actinin and determined how it related to nuclei. The analysis revealed correlation between elongated nuclei and the orientation of the surrounding myofibrils. Our results indicate that brightfield data alone can provide estimates of cellular structures without staining. This provides the means to assess structure and maturity from repeated measurements of unstained cells, enabling high-throughput quantification of the in-vitro cardiomyocyte mechanobiology.Peer reviewe