Explore the vast range of titles available.

Chaste - Cancer, Heart And Soft Tissue Environment - is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high-performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs). Re-use of these components avoids the need for researchers to 're-invent the wheel' with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD) licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials.

Mitochondrial Ca 2+ homoeostasis regulates aerobic metabolism and cell survival. Ca 2+ flux into mitochondria is mediated by the mitochondrial calcium uniporter (MCU) channel whereas Ca 2+ export is often through an electrogenic Na + –Ca 2+ exchanger. Here, we report remarkable functional versatility in mitochondrial Na + –Ca 2+ exchange under conditions where mitochondria are depolarised. Following physiological stimulation of cell-surface receptors, mitochondrial Na + –Ca 2+ exchange initially operates in reverse mode, transporting cytosolic Ca 2+ into the matrix. As matrix Ca 2+ rises, the exchanger reverts to its forward mode state, extruding Ca 2+ . Transitions between reverse and forward modes generate repetitive oscillations in matrix Ca 2+ . We further show that reverse mode Na + –Ca 2+ activity is regulated by the mitochondrial fusion protein mitofusin 2. Our results demonstrate that reversible switching between transport modes of an ion exchanger molecule generates functionally relevant oscillations in the levels of the universal Ca 2+ messenger within an organelle. Mitochondrial Ca 2+ homoeostasis is tightly regulated and export of Ca 2+ is mediated by an Na + Ca 2+ exchanger. Here authors show that in depolarised mitochondria the exchanger initially operates in reverse mode, transporting cytosolic Ca 2+ into the matrix before it reverts to its forward mode state.

Ion channel models present many challenging optimisation problems. These include unidentifiable parameters, noisy data, unobserved states, and a combination of both fast and slow timescales. This can make it difficult to choose a suitable optimisation routine a priori . Nevertheless, many attempts have been made to design optimisation routines specifically for ion channel models, however, little work has been done to compare these optimisation approaches. We have developed ionBench, an open-source optimisation benchmarking framework, to evaluate and compare these approaches against a standard set of ion channel optimisation problems. We included implementations of thirty-four unique optimisation approaches that have been previously applied to ion channel models and evaluated them against the ionBench test suite, consisting of five parameter optimisation problems derived from the cardiac ion channel literature. Each optimisation approach was initiated from multiple starting parameters and tasked with reproducing a problem-specific simulated dataset. Through ionBench, we tracked and evaluated the performance of these optimisations, identifying the expected run time until a successful optimisation for each approach, which was used for comparisons. Finally, we used these results, in addition to other literature results, to identify a new efficient approach. Its use could reduce computation time by multiple orders of magnitude, while also improving the reliability of ion channel parameter optimisation.

During drug development, candidate compounds are extensively tested for proarrhythmic risk and in particular risk of Torsade de Pointes (TdP), as indicated by prolongation of the QT interval. Drugs that inhibit the rapid delayed rectifier K + current ( I Kr ) can prolong the action potential duration (APD) and thereby the QT interval, and so are routinely rejected. However, simultaneous inhibition of the L-type Ca 2 + current ( I CaL ) can mitigate the effect of I Kr inhibition, so that including both effects can improve test specificity. Mathematical models of the action potential (AP) can be used to predict the APD prolongation resulting from a given level of I Kr and I CaL inhibition, but for use in safety-testing their predictive capabilities should first be carefully verified. We present the first systematic comparison between experimental drug-induced APD and predictions by AP models. New experimental data were obtained ex vivo for APD response to I Kr and/or I CaL inhibition by applying 9 compounds at different concentrations to adult human ventricular trabeculae at physiological temperature. Compounds with similar effects on I Kr and I CaL exhibited less APD prolongation compared to selective I Kr inhibitors. We then integrated in vitro IC 50 patch-clamp data for I Kr and I CaL inhibition by the tested compounds into simulations with AP models. Models were assessed against the ex vivo data on their ability to recapitulate drug-induced APD changes observed experimentally. None of the tested AP models reproduced the APD changes observed experimentally across all combinations and degrees of I Kr and/or I CaL inhibition: they matched the data either for selective I Kr inhibitors or for compounds with comparable effects on I Kr and I CaL . This work introduces a new benchmarking framework to assess the predictivity of current and future AP models for APD response to I Kr and/or I CaL inhibition. This is an essential primary step towards an in silico framework that integrates in vitro data for translational clinical cardiac safety.

Computer models of the human ventricular cardiomyocyte action potential (AP) have reached a level of detail and maturity that has led to an increasing number of applications in the pharmaceutical sector. However, interfacing the models with experimental data can become a significant computational burden. To mitigate the computational burden, the present study introduces a neural network (NN) that emulates the AP for given maximum conductances of selected ion channels, pumps, and exchangers. Its applicability in pharmacological studies was tested on synthetic and experimental data. The NN emulator potentially enables massive speed-ups compared to regular simulations and the forward problem (find drugged AP for pharmacological parameters defined as scaling factors of control maximum conductances) on synthetic data could be solved with average root-mean-square errors (RMSE) of 0.47 mV in normal APs and of 14.5 mV in abnormal APs exhibiting early afterdepolarizations (72.5% of the emulated APs were alining with the abnormality, and the substantial majority of the remaining APs demonstrated pronounced proximity). This demonstrates not only very fast and mostly very accurate AP emulations but also the capability of accounting for discontinuities, a major advantage over existing emulation strategies. Furthermore, the inverse problem (find pharmacological parameters for control and drugged APs through optimization) on synthetic data could be solved with high accuracy shown by a maximum RMSE of 0.22 in the estimated pharmacological parameters. However, notable mismatches were observed between pharmacological parameters estimated from experimental data and distributions obtained from the Comprehensive in vitro Proarrhythmia Assay initiative. This reveals larger inaccuracies which can be attributed particularly to the fact that small tissue preparations were studied while the emulator was trained on single cardiomyocyte data. Overall, our study highlights the potential of NN emulators as powerful tool for an increased efficiency in future quantitative systems pharmacology studies.

Studies have demonstrated non-myocytes, including fibroblasts, can electrically couple to myocytes in culture. However, evidence demonstrating current can passively spread across scar tissue in the intact heart remains elusive. We hypothesize electrotonic conduction occurs across non-myocyte gaps in the heart and is partly mediated by Connexin43 (Cx43). We investigated whether non-myocytes in ventricular scar tissue are electrically connected to surrounding myocardial tissue in wild type and fibroblast-specific protein-1 driven conditional Cx43 knock-out mice (Cx43fsp1KO). Electrical coupling between the scar and uninjured myocardium was demonstrated by injecting current into the myocardium and recording depolarization in the scar through optical mapping. Coupling was significantly reduced in Cx43fsp1KO hearts. Voltage signals were recorded using microelectrodes from control scars but no signals were obtained from Cx43fsp1KO hearts. Recordings showed significantly decreased amplitude, depolarized resting membrane potential, increased duration and reduced upstroke velocity compared to surrounding myocytes, suggesting that the non-excitable cells in the scar closely follow myocyte action potentials. These results were further validated by mathematical simulations. Optical mapping demonstrated that current delivered within the scar could induce activation of the surrounding myocardium. These data demonstrate non-myocytes in the scar are electrically coupled to myocytes and coupling depends on Cx43 expression.

Differences in mRNA expression levels have been observed in failing versus non-failing human hearts for several membrane channel proteins and accessory subunits. These differences may play a causal role in electrophysiological changes observed in human heart failure and atrial fibrillation, such as action potential (AP) prolongation, increased AP triangulation, decreased intracellular calcium transient (CaT) magnitude and decreased CaT triangulation. Our goal is to investigate whether the information contained in mRNA measurements can be used to predict cardiac electrophysiological remodeling in heart failure using computational modeling. Using mRNA data recently obtained from failing and non-failing human hearts, we construct failing and non-failing cell populations incorporating natural variability and up/down regulation of channel conductivities. Six biomarkers are calculated for each cell in each population, at cycle lengths between 1500 ms and 300 ms. Regression analysis is performed to determine which ion channels drive biomarker variability in failing versus non-failing cardiomyocytes. Our models suggest that reported mRNA expression changes are consistent with AP prolongation, increased AP triangulation, increased CaT duration, decreased CaT triangulation and amplitude, and increased delay between AP and CaT upstrokes in the failing population. Regression analysis reveals that changes in AP biomarkers are driven primarily by reduction in I[Formula: see text], and changes in CaT biomarkers are driven predominantly by reduction in I(Kr) and SERCA. In particular, the role of I(CaL) is pacing rate dependent. Additionally, alternans developed at fast pacing rates for both failing and non-failing cardiomyocytes, but the underlying mechanisms are different in control and heart failure.

Cellular electrophysiology underpins fields from basic science in neurology, cardiology, and oncology to safety critical applications for drug safety testing, risk assessment of rare mutations, and models based on cellular electrophysiology data even guide clinical interventions. Patch‐clamp voltage clamp is the gold standard for measuring ionic current dynamics that explain cellular electrophysiology, but recordings can be influenced by artifacts introduced by the measurement process. A computational approach is developed, validated through electrical model cell experiments, to explain and predict intricate artifacts in voltage‐clamp experiments. Applied to various cardiac fast sodium current measurements, the model resolved artifacts in the experiments by coupling observed current with simulated membrane voltage, explaining some typically observed shifts and delays in recorded currents. It is shown that averaging data for current‐voltage relationships can introduce biases comparable to effect sizes reported for disease‐causing mutations. The computational pipeline provides improved assessment and interpretation of voltage‐clamp experiments, correcting, and enhancing understanding of ion channel behavior. Patch‐clamp experiments are fundamental to the measurement and understanding of ion currents that underlie physiological functions from neural activity to muscle contraction. Via a mathematical model of the experimental apparatus, this article highlights how artifact effects can be as large as some reported mutation and drug effects, and enables computational models to allow for artifacts when calibrating to experimental data.

Store-operated Ca 2+ entry, involving endoplasmic reticulum Ca 2+ sensing STIM proteins and plasma membrane Orai1 channels, is a widespread and evolutionary conserved Ca 2+ influx pathway. This form of Ca 2+ influx occurs at discrete loci where peripheral endoplasmic reticulum juxtaposes the plasma membrane. Stimulation evokes numerous STIM1-Orai1 clusters but whether distinct signal transduction pathways require different cluster numbers is unknown. Here, we show that two Ca 2+ -dependent transcription factors, NFAT1 and c-fos, have different requirements for the number of STIM1-Orai1 clusters and on the Ca 2+ flux through them. NFAT activation requires fewer clusters and is more robustly activated than c-fos by low concentrations of agonist. For similar cluster numbers, transcription factor recruitment occurs sequentially, arising from intrinsic differences in Ca 2+ sensitivities. Variations in the number of STIM1-Orai1 clusters and Ca 2+ flux through them regulate the robustness of signalling to the nucleus whilst imparting a mechanism for selective recruitment of different Ca 2+ -dependent transcription factors. Endoplasmic reticulum Ca2+ sensing STIM proteins and plasma membrane Orai1 channels together regulate Ca2+ influx in eukaryotic cells. Here authors show that two Ca2+-dependent transcription factors, NFAT1 and c-fos, have different requirements for the number of STIM1-Orai1 clusters and on the Ca2+ flux through the clusters.