A comparative study of fractional step method in its quasi-implicit, semi-implicit and fully-explicit forms for incompressible flows

The present review describes and analyses a class of finite element fractional step methodsfor solving the incompressible Navier-Stokes equations. Our objective is not to reproduce the extensivecontributions on the subject, but to report on our long-term experience with and provide a unified overviewof a particular approach: the characteristic based split method. Three procedures, the semi-implicit, quasi-implicit and fully-explicit, are studied and compared. This work provides a thorough assessment of theaccuracy and efficiency of these schemes, both for a first and second order pressure split. In transientproblems, the quasi-implicit form significantly outperforms the fully-explicit approach. The second order(pressure) fractional step method displays significant convergence and accuracy benefits when the quasi-implicit projection method is employed. The fully-explicit method, utilising artificial compressibility and apseudo time stepping procedure, requires no second order fractional split to achieve second order or higheraccuracy. While the fully-explicit form is efficient for steady state problems, due to its ability to handle localtime stepping, the quasi-implicit is the best choice for transient flow calculations with time independent boundary conditions. The semi-implicit form, with its stability restrictions, is the least favoured of all the three forms for incompressible flow calculations

Modelling accidental hypothermia effects on a human body under different pathophysiological conditions

Accidental exposure to cold water environment is one of the most challenging situations in which hypothermia occurs. In the present work, we aim to characterise the energy balance of a human body subjected to such extreme environmental conditions. This study is carried out using a recently developed computational model and by setting boundary conditions needed to simulate the effect of cold surrounding environment. A major finding is the capacity of the body core regions to maintain their temperature high for a substantial amount of time, even under the most extreme environmental conditions. We also considered two disease states that highlight the spectrum of possible pathologies implicated in thermal regulation of the human body. These states are (i) cardiomyopathy, which affects the operating capacity of the heart, and (ii) malnutrition, which directly impairs the body’s ability to regulate heat exchange with the environment. We have found that cardiomyopathy has little influence on the thermal balance of the human body, whereas malnutrition has a profound negative effect on the thermal balance and leads to dramatic reduction in core temperature

An advanced computational bioheat transfer model for a human body with an embedded systemic circulation

In the present work, an elaborate one-dimensional thermofluid model for a human body is presented. By contrast to the existing pure conduction-/perfusion-based models, the proposed methodology couples the arterial fluid dynamics of a human body with a multi-segmental bioheat model of surrounding solid tissues. In the present configuration, arterial flow is included through a network of elastic vessels. More than a dozen solid segments are employed to represent the heat conduction in the surrounding tissues, and each segment is constituted by a multilayered circular cylinder. Such multi-layers allow flexible delineation of the geometry and incorporation of properties of different tissue types. The coupling of solid tissue and fluid models requires subdivision of the arterial circulation into large and small arteries. The heat exchange between tissues and arterial wall occurs by convection in large vessels and by perfusion in small arteries. The core region, including the heart, provides the inlet conditions for the fluid equations. In the proposed model, shivering, sweating, and perfusion changes constitute the basis of the thermoregulatory system. The equations governing flow and heat transfer in the circulatory system are solved using a locally conservative Galerkin approach, and the heat conduction in the surrounding tissues is solved using a standard implicit backward Euler method. To investigate the effectiveness of the proposed model, temperature field evolutions are monitored at different points of the arterial tree and in the surrounding tissue layers. To study the differences due to flow-induced convection effects on thermal balance, the results of the current model are compared against those of the widely used modelling methodologies. The results show that the convection significantly influences the temperature distribution of the solid tissues in the vicinity of the arteries. Thus, the inner convection has a more predominant role in the human body heat balance than previously thought. To demonstrate its capabilities, the proposed new model is used to study different scenarios, including thermoregulation inactivity and variation in surrounding atmospheric conditions

Synergy Between Intercellular Communication and Intracellular Ca2+ Handling in Arrhythmogenesis

Calcium is the primary signalling component of excitation-contraction coupling, the process linking electrical excitability of cardiac muscle cells to coordinated contraction of the heart. Understanding Ca2þ handling processes at the cellular level and the role of intercellular communication in the emergence of multicellular synchronization are key aspects in the study of arrhythmias. To probe these mechanisms, we have simulated cellular interactions on large scale arrays that mimic cardiac tissue, and where individual cells are represented by a mathematical model of intracellular Ca2þ dynamics. Theoretical predictions successfully reproduced experimental findings and provide novel insights on the action of two pharmacological agents (ionomycin and verapamil) that modulate Ca2þ signalling pathways via distinct mechanisms. Computational results have demonstrated how transitions between local synchronisation events and large scale wave formation are affected by these agents. Entrainment phenomena are shown to be linked to both ntracellular Ca2þ and coupling-specific dynamics in a synergistic manner. The intrinsic variability of the cellular matrix is also shown to affect emergent patterns of rhythmicity, providing insights into the origins of arrhythmogenic Ca2þ perturbations in cardiac tissue in situ

RNA Modification Level Estimation with pulseR

RNA modifications regulate the complex life of transcripts. An experimental approach called LAIC-seq was developed to characterize modification levels on a transcriptome-wide scale. In this method, the modified and unmodified molecules are separated using antibodies specific for a given RNA modification (e.g., m6A). In essence, the procedure of biochemical separation yields three fractions: Input, eluate, and supernatent, which are subjected to RNA-seq. In this work, we present a bioinformatics workflow, which starts from RNA-seq data to infer gene-specific modification levels by a statistical model on a transcriptome-wide scale. Our workflow centers around the pulseR package, which was originally developed for the analysis of metabolic labeling experiments. We demonstrate how to analyze data without external normalization (i.e., in the absence of spike-ins), given high efficiency of separation, and how, alternatively, scaling factors can be derived from unmodified spike-ins. Importantly, our workflow provides an estimate of uncertainty of modification levels in terms of confidence intervals for model parameters, such as gene expression and RNA modification levels. We also compare alternative model parametrizations, log-odds, or the proportion of the modified molecules and discuss the pros and cons of each representation. In summary, our workflow is a versatile approach to RNA modification level estimation, which is open to any read-count-based experimental approach

A comparison of metabolic labeling and statistical methods to infer genome-wide dynamics of RNA turnover

Metabolic labeling of newly transcribed RNAs coupled with RNA-seq is being increasingly used for genome-wide analysis of RNA dynamics. Methods including standard biochemical enrichment and recent nucleotide conversion protocols each require special experimental and computational treatment. Despite their immediate relevance, these technologies have not yet been assessed and benchmarked, and no data are currently available to advance reproducible research and the development of better inference tools. Here, we present a systematic evaluation and comparison of four RNA labeling protocols: 4sU-tagging biochemical enrichment, including spike-in RNA controls, SLAM-seq, TimeLapse-seq and TUC-seq. All protocols are evaluated based on practical considerations, conversion efficiency and wet lab requirements to handle hazardous substances. We also compute decay rate estimates and confidence intervals for each protocol using two alternative statistical frameworks, pulseR and GRAND-SLAM, for over 11 600 human genes and evaluate the underlying computational workflows for their robustness and ease of use. Overall, we demonstrate a high inter-method reliability across eight use case scenarios. Our results and data will facilitate reproducible research and serve as a resource contributing to a fuller understanding of RNA biology

Additional file 1 of Magnetique: an interactive web application to explore transcriptome signatures of heart failure

Supplementary Material

A novel method for non-invasively detecting the severity and location of aortic aneurysms

© The Author(s) 2017. The influence of an aortic aneurysm on blood flow waveforms is well established, but how to exploit this link for diagnostic purposes still remains challenging. This work uses a combination of experimental and computational modelling to study how aneurysms of various size affect the waveforms. Experimental studies are carried out on fusiform-type aneurysm models, and a comparison of results with those from a one-dimensional fluid–structure interaction model shows close agreement. Further mathematical analysis of these results allows the definition of several indicators that characterize the impact of an aneurysm on waveforms. These indicators are then further studied in a computational model of a systemic blood flow network. This demonstrates the methods’ ability to detect the location and severity of an aortic aneurysm through the analysis of flow waveforms in clinically accessible locations. Therefore, the proposed methodology shows a high potential for non-invasive aneurysm detectors/monitors