Simulation of ectopic pacemakers in the heart: multiple ectopic beats generated by reentry inside fibrotic regions

The inclusion of nonconducting media, mimicking cardiac fibrosis, in two models of cardiac tissue produces the formation of ectopic beats. The fraction of nonconducting media in comparison with the fraction of healthy myocytes and the topological distribution of cells determines the probability of ectopic beat generation. First, a detailed subcellular microscopic model that accounts for the microstructure of the cardiac tissue is constructed and employed for the numerical simulation of action potential propagation. Next, an equivalent discrete model is implemented, which permits a faster integration of the equations. This discrete model is a simplified version of the microscopic model that maintains the distribution of connections between cells. Both models produce similar results when describing action potential propagation in homogeneous tissue; however, they slightly differ in the generation of ectopic beats in heterogeneous tissue. Nevertheless, both models present the generation of reentry inside fibrotic tissues. This kind of reentry restricted to microfibrosis regions can result in the formation of ectopic pacemakers, that is, regions that will generate a series of ectopic stimulus at a fast pacing rate. In turn, such activity has been related to trigger fibrillation in the atria and in the ventricles in clinical and animal studies.Peer ReviewedPostprint (published version

Simulações computacionais de arritmias cardíacas em ambientes de computação de alto desempenho do tipo Multi-GPU

Computer models have become valuable tools for the study and comprehension of the complex phenomena of cardiac electrophysiology. However, the high complexity of the biophysical processes and the microscopic level of details demand complex mathematical and computational models. Key aspects of cardiac electrophysiology, such as slow conduction, conduction block and saltatory effects have been the research topic of many studies since they are strongly related to cardiac arrhythmia. However, to reproduce these phenomena the numerical models need to use sub-cellular discretization for the solution of the PDEs and nonuniform, heterogeneous tissue electric conductivity. Due to the high computational costs of simulations that reproduce the fine microstructure of cardiac tissue, previous studies have considered tissue experiments of small or moderate sizes and used simple cardiac cell models. In this work we develop a cardiac electrophysiology model (microscopic model) that captures the microstructure of cardiac tissue by using a very fine spatial discretization (8µm) and uses a very modern and complex cell model based on Markov Chains for the characterization of ion channel's structure and dynamics. To cope with the computational challenges, the model was parallelized using a hybrid approach: cluster computing and GPGPUs (General-purpose computing on graphics processing units). Our parallel implementation of this model using a Multi-GPU platform was able to reduce the execution times of the simulations from more than 6 days (on a single processor) to 21 minutes (on a small 8-node cluster equipped with 16 GPUs). Furthermore, in order to decrease further the computational cost we have developed a discrete model equivalent to the microscopic one. This new model was also parallelized using the same approach as the microscopic model and was able to perform simulations that took 21 minutes to be executed in just 65 seconds. We believe that this new parallel implementation paves the way for the investigation of many open questions associatedOs modelos computacionais tornaram-se ferramentas valiosas para o estudo e compreensão dos fenômenos da eletrofisiologia cardíaca. No entanto, a elevada complexidade dos processos biofísicos e o nível microscópico de detalhes exigem complexos modelos computacionais. Aspectos-chave da eletrofisiologia cardíaca, tais como condução lenta e bloqueio de condução tem sido tema de pesquisa de muitos estudos, uma vez que estão fortemente relacionados à arritmia cardíaca. No entanto, ao reproduzir estes fenômenos os modelos necessitam de uma discretização sub-celular para a solução das equações diferenciais e uma condutividade eléctrica do tecido não uniforme e heterogênea. Devido aos elevados custos computacionais de simulações que reproduzem a microestrutura fina do tecido cardíaco, estudos prévios têm considerado experimentos de tecido de pequenas dimensões e têm utilizados modelos simples de células cardíacas. Neste trabalho, desenvolvemos um modelo (modelo microscópico) da eletrofisiologia cardíaca que capta a microestrutura do tecido cardíaco usando uma discretização espacial muito fina (8µm) e utilizamos um modelo celular moderno e complexo baseado em Cadeias de Markov para a caracterização da estrutura e dinâmica dos canais iônicos. Para lidar com os desafios computacionais, o modelo foi paralelizado usando uma abordagem híbrida: a computação em cluster e GPGPUs (General-purpose computing on Graphics Processing Units). Nossa implementação paralela deste modelo, utilizando uma plataforma multi-GPU, foi capaz de reduzir os tempos de execução das simulações de mais de 6 dias (em um único processador) para 21 minutos (em um pequeno cluster de 8 nós equipado com 16 GPUs). Além disso, para diminuir ainda mais o custo computacional, foi desenvolvido um modelo discreto equivalente ao modelo microscópico. Este novo modelo foi paralelizado usando a mesma abordagem do modelo microscópico e foi capaz de executar simulações que demoravam 21 minutos em apenas 65 segundos. Acreditamos que esta nova implementação paralela abre caminho para a investigação de muitas questões em aberto associadas à natureza complexa e discreta da propagação dos potenciais de ação no tecido cardíaco.FAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerai

Simulation of ectopic pacemakers in the heart: multiple ectopic beats generated by reentry inside fibrotic regions

The inclusion of nonconducting media, mimicking cardiac fibrosis, in two models of cardiac tissue produces the formation of ectopic beats. The fraction of nonconducting media in comparison with the fraction of healthy myocytes and the topological distribution of cells determines the probability of ectopic beat generation. First, a detailed subcellular microscopic model that accounts for the microstructure of the cardiac tissue is constructed and employed for the numerical simulation of action potential propagation. Next, an equivalent discrete model is implemented, which permits a faster integration of the equations. This discrete model is a simplified version of the microscopic model that maintains the distribution of connections between cells. Both models produce similar results when describing action potential propagation in homogeneous tissue; however, they slightly differ in the generation of ectopic beats in heterogeneous tissue. Nevertheless, both models present the generation of reentry inside fibrotic tissues. This kind of reentry restricted to microfibrosis regions can result in the formation of ectopic pacemakers, that is, regions that will generate a series of ectopic stimulus at a fast pacing rate. In turn, such activity has been related to trigger fibrillation in the atria and in the ventricles in clinical and animal studies.Peer Reviewe

Simulations of Complex and Microscopic Models of Cardiac Electrophysiology Powered by Multi-GPU Platforms

Key aspects of cardiac electrophysiology, such as slow conduction, conduction block, and saltatory effects have been the research topic of many studies since they are strongly related to cardiac arrhythmia, reentry, fibrillation, or defibrillation. However, to reproduce these phenomena the numerical models need to use subcellular discretization for the solution of the PDEs and nonuniform, heterogeneous tissue electric conductivity. Due to the high computational costs of simulations that reproduce the fine microstructure of cardiac tissue, previous studies have considered tissue experiments of small or moderate sizes and used simple cardiac cell models. In this paper, we develop a cardiac electrophysiology model that captures the microstructure of cardiac tissue by using a very fine spatial discretization (8 μm) and uses a very modern and complex cell model based on Markov chains for the characterization of ion channel’s structure and dynamics. To cope with the computational challenges, the model was parallelized using a hybrid approach: cluster computing and GPGPUs (general-purpose computing on graphics processing units). Our parallel implementation of this model using a multi-GPU platform was able to reduce the execution times of the simulations from more than 6 days (on a single processor) to 21 minutes (on a small 8-node cluster equipped with 16 GPUs, i.e., 2 GPUs per node)

Reactive interstitial and reparative fibrosis as substrates for cardiac ectopic pacemakers and reentries

This book constitutes the refereed proceedings of the 4th International Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2016, held in Granada, Spain, in April 2016. The 69 papers presented were carefully reviewed and selected from 286 submissions. The scope of the conference spans the following areas: bioinformatics for healthcare and diseases; biomedical image analysis; biomedical signal analysis; computational systems for modeling biological processes; eHealth; tools for next generation sequencing data analysis; assistive technology for people with neuromotor disorders; fundamentals of biological dynamics and maximization of the information extraction from the experiments in the biological systems; high performance computing in bioinformatics, computational biology and computational chemistry; human behavior monitoring, analysis and understanding; pattern recognition and machine learning in the -omics sciences; and resources for bioinformatics.Dangerous cardiac arrhythmias have been frequently associated with focal sources of fast pulses, i.e. ectopic pacemakers. However, there is a lack of experimental evidences that could explain how ectopic pacemakers could be formed in cardiac tissue. In recent studies, we have proposed a new theory for the genesis of ectopic pacemakers in pathological cardiac tissues: reentry inside microfbrosis, i.e., a small region where excitable myocytes and non-conductive material coexist. In this work, we continue this investigation by comparing different types of fibrosis, reparative and reactive interstitial fibrosis. We use detailed and modern models of cardiac electrophysiology that account for the micro-structure of cardiac tissue. In addition, for the solution of our models we use, for the first time, a new numerical algorithm based on the Uniformization method. Our simulation results suggest that both types of fibrosis can support reentries, and therefore can generate in-silico ectopic pacemakers. However, the probability of reentries differs quantitatively for the different types of fibrosis. In addition, the new Uniformization method yields 20-fold increase in cardiac tissue simulation speed and, therefore, was an essential technique that allowed the execution of over a thousand of simulations.Peer Reviewe

Copaiba Oil Resin Exerts an Additive Effect to Babassu Oil on Behavioral Changes in Human Endometriotic Cell Cultures

Background: Current drugs for the treatment of endometriosis are not able to completely cure the condition, and significant side effects hinder the continuation of treatment. Therefore, it is necessary to search for new drug candidates. In the present paper, the use of plant extracts is highlighted. Babassu oil and Copaiba oil resin have several therapeutic properties. We investigated the in vitro effects of two nanoemulsions containing oil extracted from Babassu (Orbignya speciosa) nuts (called SNEDDS-18) and/or oil resin extracted from Copaiba trunk (Copaifera langsdorffii) (called SNEDDS-18/COPA) on cultured human eutopic endometrium stromal cells from endometrial biopsies of patients without (CESC) and with (EuESC) endometriosis as well as human stromal cells from biopsies of endometriotic lesions (EctESC). Methods: CESC, EuESC, and EctESC were taken and treated with SNEDDS-18 and SNEDDS-18/COPA to evaluate their effects on cytotoxicity, cell morphology, proliferation, and signaling pathways. Results: After 48 h of incubation with SNEDDS-18 and SNEDDS-18/COPA, cell viability and proliferation were inhibited, especially in EctESC. The lowest concentration of both nanoemulsions reduced cell viability and proliferation and broke down the cytoskeleton in EctESCs. After 24 h of treatment a decrease in IL-1, TNF-α, and MCP-1 was observed, as well as an increase in IL-10 production. Conclusions: Both nanoemulsions can affect endometriotic stromal cell behaviors, thus revealing two potential candidates for new phytotherapeutic agents for the management of endometriosis

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora