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In this paper, we present the abilities of an in silico platform used to simulate the effects of different drugs on heartbeat cycle performance. The platform is based on a finite element modelling approach with the fluid–solid interaction implemented using a loose coupling procedure. Active mechanical stresses are calculated using the Hunter excitation model while the passive mechanical stresses are calculated using a recently introduced experiment-based material model for the heart tissue. The applicability of the platform is illustrated using a simple parametric model of the left ventricle. The simulations are performed using parameters that are specific to drugs such as digoxin, mavacamten, 2-deoxy adenosine triphosphate, and disopyramide, with the concentration of calcium in the cardiac cells affected by these drugs given as an input function. The results are obtained for two geometries mimicking patients with hypertrophic and dilated cardiomyopathy, and also for different inlet/outlet boundary conditions simulating different drug effects at the macroscopic level. Using in silico simulations with virtual patients, it is possible to evaluate the influence of different drugs on cardiac output and ejection fraction. This approach can significantly reduce computational costs with an acceptable solution accuracy compared to approaches coupling finite element and biophysical muscle model methods that are used to calculate drug effects at the micro level.

Vibrations while driving, regardless of their intensity and shape, have the most obvious effect of reducing driving comfort. Seat-to-head frequency response function (STHT) is a complex relationship resulting from the movement of the head due to the action of excitation on the seat in the form of vibrations in the seat/head interface. In this research, an artificial neural network model was developed, which aims to simulate the STHT function through the body of the subjects based on the data obtained experimentally. The experiments were conducted with twenty healthy male volunteers, who were exposed to single-axis fore-and-aft random broadband vibration. All the results of the experiment were recorded on the basis of which the artificial neural network (ANN) was trained. The developed ANN model has the ability to predict STHT values in the range of trained values both when changing the anthropometric measures of the subjects and changes in the input characteristics of vibrations. The mathematical models based on recurrent neural networks (RNN) used in this paper show with high accuracy STHT values in case there exists prior information about the anthropometric measures of the subjects and the input characteristics of vibrations. The results show that the expensive real-time simulations could be avoided by using reliable neural network models.

For many decades, the clinical unmet needs of primary Sjögren’s Syndrome (pSS) have been left unresolved due to the rareness of the disease and the complexity of the underlying pathogenic mechanisms, including the pSS-associated lymphomagenesis process. Here, we present the HarmonicSS cloud-computing exemplar which offers beyond the state-of-the-art data analytics services to address the pSS clinical unmet needs, including the development of lymphoma classification models and the identification of biomarkers for lymphomagenesis. The users of the platform have been able to successfully interlink, curate, and harmonize 21 regional, national, and international European cohorts of 7,551 pSS patients with respect to the ethical and legal issues for data sharing. Federated AI algorithms were trained across the harmonized databases, with reduced execution time complexity, yielding robust lymphoma classification models with 85% accuracy, 81.25% sensitivity, 85.4% specificity along with 5 biomarkers for lymphoma development. To our knowledge, this is the first GDPR compliant platform that provides federated AI services to address the pSS clinical unmet needs.

We evaluated the influence of an antioxidant-rich extract of Filipendula ulmaria L. on anxiety levels induced by nano-sized particles of different calcium phosphates. Rats in experimental groups were administered with either nano-sized hydroxyapatite, tricalcium phosphate, or amorphous calcium phosphate in the presence of Filipendula ulmaria extract. Appropriate behavioral tests were performed to assess anxiety levels, while oxidative status and apoptosis parameters were determined in the hippocampus samples. The applied calcium phosphates increased oxidative stress markers in hippocampal tissue, accompanied by an enhanced pro-apoptotic mechanism. Moreover, the hippocampal immunoreactivity for brain-derived neurotrophic factor and GABAergic-A receptors was significantly lower following calcium phosphate nanoparticles intake. The observed functional and morphological alterations in the rat hippocampus occurred simultaneously with the anxiogenic response estimated in behavioral testing. The neuroprotective effect of Filipendula ulmaria was markedly manifested by the attenuation of oxidative damage induced by amorphous calcium phosphate and enhanced anti-apoptotic action in the rat hippocampus. The increased hippocampal immunoreactivity for brain-derived neurotrophic factor, GABAergic-A receptors and significant anxiolytic-like effects of Filipendula ulmaria may suggest a beneficial role of antioxidant supplementation in preventing anxiogenic response to nano-sized calcium phosphates.

Cardiomyopathy is associated with structural and functional abnormalities of the ventricular myocardium and can be classified in two major groups: hypertrophic (HCM) and dilated (DCM) cardiomyopathy. Computational modeling and drug design approaches can speed up the drug discovery and significantly reduce expenses aiming to improve the treatment of cardiomyopathy. In the SILICOFCM project, a multiscale platform is developed using coupled macro- and microsimulation through finite element (FE) modeling of fluid–structure interactions (FSI) and molecular drug interactions with the cardiac cells. FSI was used for modeling the left ventricle (LV) with a nonlinear material model of the heart wall. Simulations of the drugs’ influence on the electro-mechanics LV coupling were separated in two scenarios, defined by the principal action of specific drugs. We examined the effects of Disopyramide and Dygoxin which modulate Ca2+ transients (first scenario), and Mavacamten and 2-deoxy adenosine triphosphate (dATP) which affect changes of kinetic parameters (second scenario). Changes of pressures, displacements, and velocity distributions, as well as pressure–volume (P-V) loops in the LV models of HCM and DCM patients were presented. Additionally, the results obtained from the SILICOFCM Risk Stratification Tool and PAK software for high-risk HCM patients closely followed the clinical observations. This approach can give much more information on risk prediction of cardiac disease to specific patients and better insight into estimated effects of drug therapy, leading to improved patient monitoring and treatment.

Abstract Background Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular disease that affects approximately one in 500 people. HCM is a recognized genetic disorder most often caused by mutations involving myosin-binding protein C (MYBPC3) and β-myosin heavy chain (MYH7) which are responsible for approximately three-quarters of the identified mutations. Methods As a part of the international multidisciplinary SILICOFCM project ( www.silicofcm.eu ) the present study evaluated the association between underlying genetic mutations and clinical phenotype in patients with HCM. Only patients with confirmed single pathogenic mutations in either MYBPC3 or MYH7 genes were included in the study and divided into two groups accordingly. The MYBPC3 group was comprised of 48 patients (76%), while the MYH7 group included 15 patients (24%). Each patient underwent clinical examination and echocardiography. Results The most prevalent symptom in patients with MYBPC3 was dyspnea (44%), whereas in patients with MYH7 it was palpitations (33%). The MYBPC3 group had a significantly higher number of patients with a positive family history of HCM (46% vs. 7%; p = 0.014). There was a numerically higher prevalence of atrial fibrillation in the MYH7 group (60% vs. 35%, p = 0.085). Laboratory analyses revealed normal levels of creatinine (85.5 ± 18.3 vs. 81.3 ± 16.4 µmol/l; p = 0.487) and blood urea nitrogen (10.2 ± 15.6 vs. 6.9 ± 3.9 mmol/l; p = 0.472) which were similar in both groups. The systolic anterior motion presence was significantly more frequent in patients carrying MYH7 mutation (33% vs. 10%; p = 0.025), as well as mitral leaflet abnormalities (40% vs. 19%; p = 0.039). Calcifications of mitral annulus were registered only in MYH7 patients (20% vs. 0%; p = 0.001). The difference in diastolic function, i.e. E/e′ ratio between the two groups was also noted (MYBPC3 8.8 ± 3.3, MYH7 13.9 ± 6.9, p = 0.079). Conclusions Major findings of the present study corroborate the notion that MYH7 gene mutation patients are presented with more pronounced disease severity than those with MYBPC3.

Bioresorbable vascular scaffolds (BVS), made either from polymers or from metals, are promising materials for treating coronary artery disease through the processes of percutaneous transluminal coronary angioplasty. Despite the opinion that bioresorbable polymers are more promising for coronary stents, their long-term advantages over metallic alloys have not yet been demonstrated. The development of new polymer-based BVS or optimization of the existing ones requires engineers to perform many very expensive mechanical tests to identify optimal structural geometry and material characteristics. in silico mechanical testing opens the possibility for a fast and low-cost process of analysis of all the mechanical characteristics and also provides the possibility to compare two or more competing designs. In this study, we used a recently introduced material model of poly-l-lactic acid (PLLA) fully bioresorbable vascular scaffold and recently empowered numerical InSilc platform to perform in silico mechanicals tests of two different stent designs with different material and geometrical characteristics. The result of inflation, radial compression, three-point bending, and two-plate crush tests shows that numerical procedures with true experimental constitutive relationships could provide reliable conclusions and a significant contribution to the optimization and design of bioresorbable polymer-based stents.

The release of metal particles and ions due to wear and corrosion is one of the main underlying reasons for the long-term complications of implantable metallic implants. The rather short-term focus of the established in-vitro biocompatibility tests cannot take into account such effects. Corrosion behavior of metallic implants mostly investigated in in-vitro body-like environments for long time periods and their coupling with long-term in-vitro experiments are not practical. Mathematical modeling and modeling the corrosion mechanisms of metals and alloys is receiving a considerable attention to make predictions in particular for long term applications by decreasing the required experimental duration. By using such in-silico approaches, the corrosion conditions for later stages can be mimicked immediately in in-vitro experiments. For this end, we have developed a mathematical model for multi-pit corrosion based on Cellular Automata (CA). The model consists of two sub-models, corrosion initialization and corrosion progression, each driven by a set of rules. The model takes into account several environmental factors (pH, temperature, potential difference, etc.), as well as stochastic component, present in phenomena such as corrosion. The selection of NiTi was based on the risk of Ni release from the implant surface as it leads to immune reactions. We have also performed experiments with Nickel Titanium (NiTi) shape memory alloys. The images both from simulation and experiments can be analyzed using a set of statistical methods, also investigated in this paper (mean corrosion, standard deviation, entropy etc.). For more widespread implementation, both simulation model, as well as analysis of output images are implemented as a web tool. Described methodology could be applied to any metal provided that the parameters for the model are available. Such tool can help biomedical researchers to test their new metallic implant systems at different time points with respect to ion release and corrosion and couple the obtained information directly with in-vitro tests.

Nonprofit, nongovernmental organizations (NGOs) are important development actors that operate in ecosystems of multi and cross-sector stakeholders in order to reach the most vulnerable social groups of people. Having this in mind, our goal was to explore to what extent their social capital influences their knowledge in order to propose a model that could optimize their knowledge management maturity through social resources embedded into their structure. Therefore, we focused on NGOs from the European Union and the Western Balkans operating in the international development and cooperation sector. We first conducted a survey among 215 NGOs and then cross-checked the received data through desk research and in-depth interviews. We utilized collected structured data and devised a binary classification model capable of discriminating high level from the low level of knowledge management maturity in NGOs, and multi-class classification model for estimating the actual category of knowledge management maturity which can simulate the real connection among social capital and existing knowledge management maturity. Our findings provide valuable data to the NGO management, regardless of where the NGO comes from, of the number of employees it has, and the number of projects it runs. The mathematical models based on neural networks used in this paper show with high accuracy what the knowledge management maturity level (for each output) is in case there exists prior information about social capital (inputs).

Objectives: Salivary gland ultrasonography (SGUS) is increasingly applied for the management of primary Sjögren's syndrome (pSS). This study aims to: (i) compare the reliability between two SGUS scores; (ii) test the reliability among sonographers with different levels of experience.Methods: In the reliability exercise, two four-grade semi-quantitative SGUS scoring systems, namely De Vita et al. and OMERACT, were tested. The sonographers involved in work-package 7 of the HarmonicSS project from nine countries in Europe were invited to participate. Different levels of sonographers were identified on the basis of their SGUS experience and of the knowledge of the tested scores. A dedicated atlas was used as support for SGUS scoring.Results: Twenty sonographers participated in the two rounds of the reliability exercise. The intra-rater reliability for both scores was almost perfect, with a Light's kappa of 0.86 for the De Vita et al. score and 0.87 for the OMERACT score. The inter-rater reliability for the De Vita et al. and the OMERACT score was substantial with Light's Kappa of 0.75 and 0.77, respectively. Furthermore, no significant difference was noticed among sonographers with different levels of experience.Conclusion: The two tested SGUS scores are reliable for the evaluation of major salivary glands in pSS, and even less-expert sonographers could be reliable if adequately instructed.

Background and Objectives: Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac disease that affects approximately 1 in 500 people. Due to an incomplete disease penetrance associated with numerous factors, HCM is not manifested in all carriers of genetic mutation. Although about two-thirds of patients are male, it seems that female gender is associated with more severe disease phenotype and worse prognosis. The objective of this study was to evaluate the gender related differences in HCM presentation. Materials and Methods: This study was conducted as a part of the international multidisciplinary SILICOFCM project. Clinical information, laboratory analyses, electrocardiography, echocardiography, and genetic testing data were collected for 362 HCM patients from four clinical centers (Florence, Newcastle, Novi Sad, and Regensburg). There were 33% female patients, and 67% male patients. Results: Female patients were older than males (64.5 vs. 53.5 years, p < 0.0005). The male predominance was present across all age groups until the age of 70, when gender distribution became comparable. Females had higher number of symptomatic individuals then males (69% vs. 52%, p = 0.003), most frequently complaining of dyspnea (50% vs. 30%), followed by chest pain (30% vs. 17%), fatigue (26% vs. 13%), palpitations (22% vs. 13%), and syncope (13% vs. 8%). The most common rhythm disorder was atrial fibrillation which was present in a similar number of females and males (19% vs. 13%, p = 0.218). Levels of N-terminal pro-brain natriuretic peptide were comparable between the genders (571 vs. 794 ng/L, p = 0.244). Echocardiography showed similar thickness of interventricular septum (18 vs. 16 mm, p = 0.121) and posterolateral wall (13 vs. 12 mm, p = 0.656), however, females had a lower number of systolic anterior motion (8% vs. 16%, p = 0.020) and other mitral valve abnormalities. Conclusions: Female patients are underrepresented but seem to have a more pronounced clinical presentation of HCM. Therefore, establishing gender specific diagnostic criteria for HCM should be considered.

Mass transport represents the most fundamental process in living organisms. It includes delivery of nutrients, oxygen, drugs, and other substances from the vascular system to tissue and transport of waste and other products from cells back to vascular and lymphatic network and organs. Furthermore, movement is achieved by mechanical forces generated by muscles in coordination with the nervous system. The signals coming from the brain, which have the character of electrical waves, produce activation within muscle cells. Therefore, from a physics perspective, there exist a number of physical fields within the body, such as velocities of transport, pressures, concentrations of substances, and electrical potential, which is directly coupled to biochemical processes of transforming the chemical into mechanical energy and further internal forces for motion. The overall problems of mass transport and electrophysiology coupled to mechanics can be investigated theoretically by developing appropriate computational models. Due to the enormous complexity of the biological system, it would be almost impossible to establish a detailed computational model for the physical fields related to mass transport, electrophysiology, and coupled fields. To make computational models feasible for applications, we here summarize a concept of smeared physical fields, with coupling among them, and muscle mechanics, which includes dependence on the electrical potential. Accuracy of the smeared computational models, also with coupling to muscle mechanics, is illustrated with simple example, while their applicability is demonstrated on a liver model with tumors present. The last example shows that the introduced methodology is applicable to large biological systems.

Benign Paroxysmal Positional Vertigo (BPPV) is the most common vestibular disorder. In this paper we tried to investigate a model of the semi-circular canal (SCC) with parametrically defined dimension and full 3D three SCC from patient-specific 3D reconstruction. Full Navier-Stokes equations and continuity equations are used for fluid domain with Arbitrary-Lagrangian Eulerian (ALE) formulation for mesh motion. Fluid-structure interaction for fluid coupling with cupula deformation is used. Particle tracking algorithm has been used for particle motion. Velocity distribution, shear stress and force from endolymph side are presented for one parametric SCC and three patient-specific SCC. All models are used for correlation with the same experimental protocols with head moving and nystagmus eye tracking.

In this study we investigated gait measurement with wearable sensor for subjects with and without multiple sclerosis (MS) and evaluation gait function.The gait function was measured with Avatar sensors system in 3 patients with MS and in 3 healthy subjects without MS. The system consists of a main sensor node and three additional fixtures. Each sensor node is wearing three-axial accelerometer and two-axis gyroscope. Cross-correlation analysis with the walk signal was applied.Coefficient values from cross-correlation are determined for all 6 subjects. Then for a new unknown subject the cross-correlation was applied and the mean value cross-correlation for healthy subjects was 0.0477, while in MS subjects this value was 0.0207. A proven validation for this small training system has shown the evidence for different gait analysis for MS and healthy subjects.This small study opens a new avenue for clinical diagnosis of potential MS subjects while wearable sensor can provide an objective framework for assessing gait abnormality. The measured data can provide better understanding on the progression of the disease and response to treatment.

Benign Paroxysmal Positional Vertigo (BPPV) is one of the most common vestibular disorders occuring due to the presence of basophilic particles in the semicircular canals (SCC). Three-dimensional biomechanical model of the SCC is described with full 3D fluid-structure interaction of particles, wall, cupula deformation and endolymph fluid flow. The model of the SCC with parametric defined dimension and fully 3D three SCC from patient specific 3D reconstruction is presented. Navier-Stokes equations with continuity equations described fluid flow while Arbitrary-Lagrangian Eulerian (ALE) formulation is used for mesh motion. Fluid-structure interaction for fluid coupling with cupula deformation is used. Particle tracking algorithm has been used for particle motion. Different size and number of particles with their full interaction between themselves, wall and cupula deformation are used. Velocity distribution, shear stress and force from endolymph side are presented for parametric one SCC and patient specific three SCC. All the models are used for correlation with the same experimental protocols with head moving and nystagmus eye tracking. Full fluid-structure interaction of otoconia particles, wall, cupula deflection and endolymph flow in three-dimension give more details and understanding of the pathology of the specific patient in standard clinical diagnostic and therapy procedure for BPPV.

Plants have been used for centuries to treat several illnesses. The Plectranthus genus has a vast variety of species that has allowed the isolation of cytotoxic compounds with notable activities. The abietane diterpenes 6,7-dehydroroyleanone (DeRoy, 1), 7α-acetoxy-6β-hydroxyroyleanone (Roy, 2), and Parvifloron D (ParvD, 3) were obtained from Plectranthus spp. and showed promising biological activities, such as cytotoxicity. The inhibitory effects of the different natural abietanes (1-3) were compared in MFC7, SkBr3, and SUM159 cell lines, as well as SUM159 grown in cancer stem cell-inducing conditions. Based on the royleanones’ bioactivity, the derivatives RoyBz (4), RoyBzCl (5), RoyPr2 (6), and DihydroxyRoy (7), previously obtained from 2, were selected for further studies. Protein kinases C (PKCs) are involved in several carcinogenic processes. Thus, PKCs are potential targets for cancer therapy. To date, the portfolio of available PKC modulators remains very limited due to the difficulty of designing isozyme-selective PKC modulators. As such, molecular docking was used to evaluate royleanones 1-6 as predicted isozyme-selective PKC binders. Subtle changes in the binding site of each PKC isoform change the predicted interaction profiles of the ligands. Subtle changes in royleanone substitution patterns, such as a double substitution only with non-substituted phenyls, or hydroxybenzoate at position four that flips the binding mode of ParvD (3), can increase the predicted interactions in certain PKC subtypes.

In vitro models are very important in medicine and biology, because they provide an insight into cells' and microorganisms' behavior. Since these cells and microorganisms are isolated from their natural environment, these models may not completely or precisely predict the effects on the entire organism. Improvement in this area is secured by organ-on-a-chip development. The organ-on-a-chip assumes cells cultured in a microfluidic chip. The chip simulates bioactivities, mechanics and physiological behavior of organs or organ systems, generating artificial organs in that way. There are several cell lines used so far for each tested artificial organ. For lungs, mostly used cell lines are 16HBE, A549, Calu-3, NHBE, while mostly used cell lines for liver are HepG2, Hep 3B, TPH1, etc. In this paper, state of the art for lung and liver organ-on-a-chip is presented, together with the established in vitro testing on lung and liver cell lines, with the emphasis on Calu-3 (for lung cell lines) and Hep-G2 (for liver cell lines). Primary focus in this review is to discuss different researches on the topics of lung and liver cell line models, approaches in determining fate and transport, cell partitioning, cell growth and division, as well as cell dynamics, meaning toxicity and effects. The review is finalized with current research gaps and problems, stating potential future developments in the field.

The aim of this work was to investigate effects of the formulation factors on tablet printability as well as to optimize and predict extended drug release from cross-linked polymeric ibuprofen printlets using an artificial neural network (ANN). Printlets were printed using digital light processing (DLP) technology from formulations containing polyethylene glycol diacrylate, polyethylene glycol, and water in concentrations according to D-optimal mixture design and 0.1% w/w riboflavin and 5% w/w ibuprofen. It was observed that with higher water content longer exposure time was required for successful printing. For understanding the effects of excipients and printing parameters on drug dissolution rate in DLP printlets two different neural networks were developed with using two commercially available softwares. After comparison of experimental and predicted values of in vitro dissolution at the corresponding time points for optimized formulation, the R2 experimental vs. predicted value was 0.9811 (neural network 1) and 0.9960 (neural network 2). According to difference f1 and similarity factor f2 (f1 = 14.30 and f2 = 52.15) neural network 1 with supervised multilayer perceptron, backpropagation algorithm, and linear activation function gave a similar dissolution profile to obtained experimental results, indicating that adequate ANN is able to set out an input−output relationship in DLP printing of pharmaceutics.

Lung cancer is the major cancer killer in the Western world, with the small cell lung cancer (SCLC) representing around 15–20% of all lung cancers. Extensive disease small cell lung cancer (ED SCLC) is found in approximately two-thirds of all cases, composed of both metastatic (M1) and non-metastatic (but presumably with tumor burden too large for locoregional-only approach) variant. Standard treatment options involve chemotherapy (CHT) over the past several decades. Radiation therapy (RT) had mostly been used in palliation of locoregional and/or metastatic disease. In contrast to its established role in treating metastatic disease, thoracic RT (TRT) had never been established as important part of the treatment aspects in this setting. In the past two decades, thoracic oncologists have witnessed wide introduction of modern RT and CHT aspects in ED SCLC, which led to more frequent use of RT and rise in the number of clinical studies. Since the pivotal study of Jeremic et al., who were the first to show importance of TRT in ED SCLC, a number of single-institutional studies have reconfirmed this observation, while recent prospective randomized trials (CREST and RTOG 0937) brought more substance to this issue. Similarly, the issue of prophylactic cranial irradiation was investigated in EORTC and the Japanese study, respectively, bringing somewhat conflicting results and calling for additional research in this setting. Future studies in ED SCLC could incorporate questions of RT dose and fractionation as well as the number of CHT cycles and type of combined Rt-CHT (sequential vs concurrent).

Anatomy of frontal sinuses varies individually, from differences in volume and shape to a rare case when the sinuses are absent. However, there are scarce data related to influence of these variations on impact generated fracture pattern. Therefore, the aim of this study was to analyse the influence of frontal sinus volume on the stress distribution and fracture pattern in the frontal region. The study included four representative Finite Element models of the skull. Reference model was built on the basis of computed tomography scans of a human head with normally developed frontal sinuses. By modifying the reference model, three additional models were generated: a model without sinuses, with hypoplasic, and with hyperplasic sinuses. A 7.7 kN force was applied perpendicularly to the forehead of each model, in order to simulate a frontal impact. The results demonstrated that the distribution of impact stress in frontal region depends on the frontal sinus volume. The anterior sinus wall showed the highest fragility in case with hyperplasic sinuses, whereas posterior wall/inner plate showed more fragility in cases with hypoplasic and undeveloped sinuses. Well-developed frontal sinuses might, through absorption of the impact energy by anterior wall, protect the posterior wall and intracranial contents.

Due to the important biological role of red blood cells (RBCs) in vertebrates, the analysis of reshaping and dynamics of RBCs motion is a critical issue in physiology and biomechanics. In this paper the behavior of RBCs within the immature capillary plexus during embryonic development of zebrafish has been analyzed. Relying on the fact that zebrafish embryos are small and optically transparent, it is possible to image the blood flow.. In this way the anatomy of blood vessels is monitored along with the circulation throughout their development. Numerical simulations were performed using a specific numerical model that combines fluid flow simulation, modeling of interaction of individual red blood cells immersed in blood plasma with the surrounding fluid and modeling the deformation of individual cells. The results of numerical simulations are in accordance with the in vivo observed region of interest within the caudal vein plexus of the zebrafish embryo. Good agreement of results demonstrates the capabilities of the developed numerical model to predict and analyze the motion and deformation of RBCs in complex geometries. The proposed model (methodology) will help to elucidate different rheological and hematological related pathologies and finally to design better treatment strategies.

INTRODUCTION:Hemodynamic parameters in zebrafish receive increasing attention because of their important role in cardiovascular processes such as atherosclerosis, hematopoiesis, sprouting and intussusceptive angiogenesis. To study underlying mechanisms, the precise modulation of parameters like blood flow velocity or shear stress is centrally important. Questions related to blood flow have been addressed in the past in either embryonic or ex vivo-zebrafish models but little information is available for adult animals. Here we describe a pharmacological approach to modulate cardiac and hemodynamic parameters in adult zebrafish in vivo. MATERIALS AND METHODS:Adult zebrafish were paralyzed and orally perfused with salt water. The drugs isoprenaline and sodium nitroprusside were directly applied with the perfusate, thus closely resembling the preferred method for drug delivery in zebrafish, namely within the water. Drug effects on the heart and on blood flow in the submental vein were studied using electrocardiograms, in vivo-microscopy and mathematical flow simulations. RESULTS:Under control conditions, heart rate, blood flow velocity and shear stress varied less than ± 5%. Maximal chronotropic effects of isoprenaline were achieved at a concentration of 50 μmol/L, where it increased the heart rate by 22.6 ± 1.3% (n = 4; p < 0.0001). Blood flow velocity and shear stress in the submental vein were not significantly increased. Sodium nitroprusside at 1 mmol/L did not alter the heart rate but increased blood flow velocity by 110.46 ± 19.64% (p = 0.01) and shear stress by 117.96 ± 23.65% (n = 9; p = 0.03). DISCUSSION:In this study, we demonstrate that cardiac and hemodynamic parameters in adult zebrafish can be efficiently modulated by isoprenaline and sodium nitroprusside. Together with the suitability of the zebrafish for in vivo-microscopy and genetic modifications, the methodology described permits studying biological processes that are dependent on hemodynamic alterations.

PURPOSE: The relationship between low endothelial shear stress (ESS) and coronary atherosclerosis is well established. ESS assessment so far depended on invasive procedures. The aim of this study was to demonstrate the relationship between ESS and coronary atherosclerosis by using non-invasive coronary computed tomography angiography (CTA) for computational fluid dynamics (CFD) simulations. METHODS: A total number of 7 consecutive patients with suspected coronary artery disease who received CTA and invasive angiography with IVUS analysis were included in this study. CTA examinations were performed using a dual-source scanner. These datasets were used to build a 3D mesh model. CFD calculations were performed using a validated CFD solver. The presence of plaque was assumed if the thickness of the intima-media complex exceeded 0.3 mm in IVUS. Plaque composition was derived by IVUS radiofrequency data analysis. RESULTS: Plaque was present in 32.1% of all analyzed cross-sections. Plaque prevalence was highest in areas of low ESS (49.6%) and high ESS (34.8%). In parts exposed to intermediate-low and intermediate-high ESS few plaques were found (20.0% and 24.0%) (p