Personalized pathology test for Cardio-vascular disease: Approximate Bayesian computation with discriminative summary statistics learning.

Cardio/cerebrovascular diseases (CVD) have become one of the major health issue in our societies. But recent studies show that the present pathology tests to detect CVD are ineffectual as they do not consider different stages of platelet activation or the molecular dynamics involved in platelet interactions and are incapable to consider inter-individual variability. Here we propose a stochastic platelet deposition model and an inferential scheme to estimate the biologically meaningful model parameters using approximate Bayesian computation with a summary statistic that maximally discriminates between different types of patients. Inferred parameters from data collected on healthy volunteers and different patient types help us to identify specific biological parameters and hence biological reasoning behind the dysfunction for each type of patients. This work opens up an unprecedented opportunity of personalized pathology test for CVD detection and medical treatment.

Investigating the two regimes of fibrin clot lysis: an experimental and computational approach.

It has been observed in vitro that complete clot lysis is generally preceded by a slow phase of lysis during which the degradation seems to be inefficient. However, this slow regime was merely noticed, but not yet quantitatively discussed. In our experiments, we observed that the lysis ubiquitously occurred in two distinct regimes, a slow and a fast lysis regime. We quantified extensively the duration of these regimes for a wide spectrum of experimental conditions and found that on average, the slow regime lasts longer than the fast one, meaning that during most of the process, the lysis is ineffective. We proposed a computational model in which the properties of the binding of the proteins change during the lysis: first, the biochemical reactions take place at the surface of the fibrin fibers, then in the bulk, resulting in the observed fast lysis regime. This simple hypothesis appeared to be sufficient to reproduce with a great accuracy the lysis profiles obtained experimentally.

Redistribution of TPA Fluxes in the Presence of PAI-1 Regulates Spatial Thrombolysis.

The fibrin clot is gelatinous matter formed upon injury to stop blood loss and is later destroyed by fibrinolysis, an enzymatic cascade with feedback. Pharmacological fibrinolysis stimulation is also used to destroy pathological, life-threatening clots and thrombi (thrombolysis). The regulation of the nonlinear spatially nonuniform fibrinolytic process in thrombolysis is not currently well understood. We developed a reaction-diffusion-advection model of thrombolysis by tissue plasminogen activator (TPA) in an occluded vessel with a pressure gradient. Sensitivity-analysis-based model reduction was used to reveal the critical processes controlling different steps of thrombolysis. The propagation of thrombolysis in the system without flow was predominantly controlled by TPA diffusion, whereas transport of other active components was rendered nonessential either by their high fibrin-binding parameters and short lifetimes or their initial uniform distribution. The concentration of the main TPA inhibitor plasminogen activator inhibitor 1 (PAI-1) controlled both the extent of lysis propagation and the shape of fibrin spatial distribution during lysis. Interestingly, PAI-1 remained important even when its concentration was an order of magnitude below that of TPA because of its role at the edge of the diffusing TPA front. The system was robust to reaction rate constant perturbations. Using these data, a reduced model of thrombolysis was proposed. In the presence of flow, convection of TPA was the critical controlling process; although the role of PAI-1 concentration was much less in the presence of flow, its influence became greater in the presence of collateral bypassing vessels, which sufficiently reduced TPA flux through the thrombus. Flow bypass through the collateral vessel caused a decrease in TPA flux in the clotted vessel, which increased the PAI-1/TPA ratio, thus making PAI-1-induced inhibition relevant for the regulation of spatial lysis up to its arrest.

Multiscale computing for science and engineering in the era of exascale performance.

In this position paper, we discuss two relevant topics: (i) generic multiscale computing on emerging exascale high-performing computing environments, and (ii) the scaling of such applications towards the exascale. We will introduce the different phases when developing a multiscale model and simulating it on available computing infrastructure, and argue that we could rely on it both on the conceptual modelling level and also when actually executing the multiscale simulation, and maybe should further develop generic frameworks and software tools to facilitate multiscale computing. Next, we focus on simulating multiscale models on high-end computing resources in the face of emerging exascale performance levels. We will argue that although applications could scale to exascale performance relying on weak scaling and maybe even on strong scaling, there are also clear arguments that such scaling may no longer apply for many applications on these emerging exascale machines and that we need to resort to what we would call multi-scaling. This article is part of the theme issue 'Multiscale modelling, simulation and computing: from the desktop to the exascale'.

Accelerating Bayesian inference for evolutionary biology models.

Motivation: Bayesian inference is widely used nowadays and relies largely on Markov chain Monte Carlo (MCMC) methods. Evolutionary biology has greatly benefited from the developments of MCMC methods, but the design of more complex and realistic models and the ever growing availability of novel data is pushing the limits of the current use of these methods. Results: We present a parallel Metropolis-Hastings (M-H) framework built with a novel combination of enhancements aimed towards parameter-rich and complex models. We show on a parameter-rich macroevolutionary model increases of the sampling speed up to 35 times with 32 processors when compared to a sequential M-H process. More importantly, our framework achieves up to a twentyfold faster convergence to estimate the posterior probability of phylogenetic trees using 32 processors when compared to the well-known software MrBayes for Bayesian inference of phylogenetic trees. Availability and Implementation: https://bitbucket.org/XavMeyer/hogan. Contact: nicolas.salamin@unil.ch. Supplementary information: Supplementary data are available at Bioinformatics online.

The mechanical properties of a cell-based numerical model of epithelium.

In this work we use a computational cell-based model to study the influence of the mechanical properties of cells on the mechanics of epithelial tissues. We analyze the effect of the model parameters on the elasticity and the mechanical response of tissues subjected to stress loading application. We compare our numerical results with experimental measurements of epithelial cell monolayer mechanics. Unlike previous studies, we have been able to estimate in physical units the parameter values that match the experimental results. A key observation is that the model parameters must vary with the tissue strain. In particular, it was found that, while the perimeter contractility and the area elasticity of cells remain constant at lower strains (<20%), they must increase to respond to larger strains (>20%). However, above a threshold of 50% extension, the cells stop counteracting the tissue strain and reduce both their perimeter contractility and area elasticity.

Towards the patient-specific design of flow diverters made from helix-like wires: an optimization study.

BACKGROUND: Flow diverter (FD) intervention is an emerging endovascular technique for treating intracranial aneurysms. High flow-diversion efficiency is desired to accelerate thrombotic occlusion inside the aneurysm; however, the risk of post-stenting stenosis in the parent artery is posed when flow-diversion efficiency is pursued by simply decreasing device porosity. For improving the prognosis of FD intervention, we develop an optimization method for the design of patient-specific FD devices that maintain high levels of porosity. METHODS: An automated structure optimization method for FDs with helix-like wires was developed by applying a combination of lattice Boltzmann fluid simulation and simulated annealing procedure. Employing intra-aneurysmal average velocity as the objective function, the proposed method tailored the wire structure of an FD to a given vascular geometry by rearranging the starting phase of the helix wires. RESULTS: FD optimization was applied to two idealized (S and C) vascular models and one realistic (R) model. Without altering the original device porosity of 80%, the flow-reduction rates of optimized FDs were improved by 5, 2, and 28% for the S, C, and R models, respectively. Furthermore, the aneurysmal flow patterns after optimization exhibited marked alterations. We confirmed that the disruption of bundle of inflow is of great help in blocking aneurysmal inflow. Axial displacement tests suggested that the optimal FD implanted in the R model possesses good robustness to tolerate uncertain axial positioning errors. CONCLUSIONS: The optimization method developed in this study can be used to identify the FD wire structure with the optimal flow-diversion efficiency. For a given vascular geometry, custom-designed FD structure can maximally reduce the aneurysmal inflow with its porosity maintained at a high level, thereby lowering the risk of post-stenting stenosis. This method facilitates the study of patient-specific designs for FD devices.

Motifs tree: a new method for predicting post-translational modifications.

MOTIVATION: Post-translational modifications (PTMs) are important steps in the maturation of proteins. Several models exist to predict specific PTMs, from manually detected patterns to machine learning methods. On one hand, the manual detection of patterns does not provide the most efficient classifiers and requires an important workload, and on the other hand, models built by machine learning methods are hard to interpret and do not increase biological knowledge. Therefore, we developed a novel method based on patterns discovery and decision trees to predict PTMs. The proposed algorithm builds a decision tree, by coupling the C4.5 algorithm with genetic algorithms, producing high-performance white box classifiers. Our method was tested on the initiator methionine cleavage (IMC) and N(α)-terminal acetylation (N-Ac), two of the most common PTMs. RESULTS: The resulting classifiers perform well when compared with existing models. On a set of eukaryotic proteins, they display a cross-validated Matthews correlation coefficient of 0.83 (IMC) and 0.65 (N-Ac). When used to predict potential substrates of N-terminal acetyltransferaseB and N-terminal acetyltransferaseC, our classifiers display better performance than the state of the art. Moreover, we present an analysis of the model predicting IMC for Homo sapiens proteins and demonstrate that we are able to extract experimentally known facts without prior knowledge. Those results validate the fact that our method produces white box models. AVAILABILITY AND IMPLEMENTATION: Predictors for IMC and N-Ac and all datasets are freely available at http://terminus.unige.ch/.

Optimization of strut placement in flow diverter stents for four different aneurysm configurations.

A modern technique for the treatment of cerebral aneurysms involves insertion of a flow diverter stent. Flow stagnation, produced by the fine mesh structure of the diverter, is thought to promote blood clotting in an aneurysm. However, apart from its effect on flow reduction, the insertion of the metal device poses the risk of occlusion of a parent artery. One strategy for avoiding the risk of arterial occlusion is the use of a device with a higher porosity. To aid the development of optimal stents in the view point of flow reduction maintaining a high porosity, we used lattice Boltzmann flow simulations and simulated annealing optimization to investigate the optimal placement of stent struts. We constructed four idealized aneurysm geometries that resulted in four different inflow characteristics and employed a stent model with 36 unconnected struts corresponding to the porosity of 80%. Assuming intracranial flow, steady flow simulation with Reynolds number of 200 was applied for each aneurysm. Optimization of strut position was performed to minimize the average velocity in an aneurysm while maintaining the porosity. As the results of optimization, we obtained nonuniformed structure as optimized stent for each aneurysm geometry. And all optimized stents were characterized by denser struts in the inflow area. The variety of inflow patterns that resulted from differing aneurysm geometries led to unique strut placements for each aneurysm type.

Unified directional parabolic-accurate lattice Boltzmann boundary schemes for grid-rotated narrow gaps and curved walls in creeping and inertial fluid flows.

The goal of this work is to advance the characteristics of existing lattice Boltzmann Dirichlet velocity boundary schemes in terms of the accuracy, locality, stability, and mass conservation for arbitrarily grid-inclined straight walls, curved surfaces, and narrow fluid gaps, for both creeping and inertial flow regimes. We reach this objective with two infinite-member boundary classes: (1) the single-node "Linear Plus" (LI^{+}) and (2) the two-node "Extended Multireflection" (EMR). The LI^{+} unifies all directional rules relying on the linear combinations of up to three pre- or postcollision populations, including their "ghost-node" interpolations and adjustable nonequilibrium approximations. On this basis, we propose three groups of LI^{+} nonequilibrium local corrections: (1) the LI_{1}^{+} is parametrized, meaning that its steady-state solution is physically consistent: the momentum accuracy is viscosity-independent in Stokes flow, and it is fixed by the Reynolds number (Re) in inertial flow; (2) the LI_{3}^{+} is parametrized, exact for arbitrary grid-rotated Poiseuille force-driven Stokes flow and thus most accurate in porous flow; and (3) the LI_{4}^{+} is parametrized, exact for pressure and inertial term gradients, and hence advantageous in very narrow porous gaps and at higher Reynolds range. The directional, two-relaxation-time collision operator plays a crucial role for all these features, but also for efficiency and robustness of the boundary schemes due to a proposed nonequilibrium linear stability criterion which reliably delineates their suitable coefficients and relaxation space. Our methodology allows one to improve any directional rule for Stokes or Navier-Stokes accuracy, but their parametrization is not guaranteed. In this context, the parametrized two-node EMR class enlarges the single-node schemes to match exactness in a grid-rotated linear Couette flow modeled with an equilibrium distribution designed for the Navier-Stokes equation (NSE). However, exactness of a grid-rotated Poiseuille NSE flow requires us to perform (1) the modification of the standard NSE term for exact bulk solvability and (2) the EMR extension towards the third neighbor node. A unique relaxation and equilibrium exact configuration for grid-rotated Poiseuille NSE flow allows us to classify the Galilean invariance characteristics of the boundary schemes without any bulk interference; in turn, its truncated solution suggests how, when increasing the Reynolds number, to avoid a deterioration of the mass-leakage rate and momentum accuracy due to a specific Reynolds scaling of the kinetic relaxation collision rate. The optimal schemes and strategies for creeping and inertial regimes are then singled out through a series of numerical tests, such as grid-rotated channels and rotated Couette flow with wall-normal injection, cylindrical porous array, and Couette flow between concentric cylinders, also comparing them against circular-shape fitted FEM solutions.

Emergent patterns in global health diplomacy: a network analysis of the resolutions adopted by the World Health Assembly from 1948 to 2022.

From a complexity perspective on governance, multilateral diplomacy is based on interactions between people, ideas, norms, policies and institutions. This article uses a computer-assisted methodology to better understand governance systems as a network of norms. All World Health Assembly (WHA) resolutions that were available from 1948 to 2022 were collected from the WHO Institutional Repository for Information Sharing (IRIS) database. Regular expressions were used to identify how resolutions cite other resolutions and the resulting relationships were analysed as a normative network. The findings show that WHA resolutions constitute a complex network of interconnected global health issues. This network is characterised by several community patterns. While chain-like patterns are associated with specific diseases programmes, radial patterns are characteristic of highly important procedural decisions that member states reaffirm in similar situations. Finally, densely connected communities correspond to contested topics and emergencies. While these emergeng patterns suggest the relevance of using network analysis to understand global health norms in international organisations, we reflect on how this computational approach can be extended to provide new understandings of how multilateral governance systems work, and to address some important contemporary questions about the effects of regime complexity on global health diplomacy.

A simplified mesoscale 3D model for characterizing fibrinolysis under flow conditions.

One of the routine clinical treatments to eliminate ischemic stroke thrombi is injecting a biochemical product into the patient's bloodstream, which breaks down the thrombi's fibrin fibers: intravenous or intravascular thrombolysis. However, this procedure is not without risk for the patient; the worst circumstances can cause a brain hemorrhage or embolism that can be fatal. Improvement in patient management drastically reduced these risks, and patients who benefited from thrombolysis soon after the onset of the stroke have a significantly better 3-month prognosis, but treatment success is highly variable. The causes of this variability remain unclear, and it is likely that some fundamental aspects still require thorough investigations. For that reason, we conducted in vitro flow-driven fibrinolysis experiments to study pure fibrin thrombi breakdown in controlled conditions and observed that the lysis front evolved non-linearly in time. To understand these results, we developed an analytical 1D lysis model in which the thrombus is considered a porous medium. The lytic cascade is reduced to a second-order reaction involving fibrin and a surrogate pro-fibrinolytic agent. The model was able to reproduce the observed lysis evolution under the assumptions of constant fluid velocity and lysis occurring only at the front. For adding complexity, such as clot heterogeneity or complex flow conditions, we propose a 3-dimensional mesoscopic numerical model of blood flow and fibrinolysis, which validates the analytical model's results. Such a numerical model could help us better understand the spatial evolution of the thrombi breakdown, extract the most relevant physiological parameters to lysis efficiency, and possibly explain the failure of the clinical treatment. These findings suggest that even though real-world fibrinolysis is a complex biological process, a simplified model can recover the main features of lysis evolution.

Thrombolysis: Observations and numerical models.

This perspective paper considers thrombolysis in the context of ischemic strokes, intending to build eventually a numerical model capable of simulating the thrombolytic treatment and predicting patient outcomes. Numerical modeling is a scientific methodology based on an abstraction of a system but requires understanding their spatio-temporal interactions. However, although important, the current knowledge on thrombolysis is fragmented in contributions from which it is difficult to obtain a complete picture of the process, especially in a clinically relevant setup. This paper discusses, from a general point of view, how to develop a numerical model to describe the evolution of a patient clot under the action of a thrombolytic drug. We will present critical, yet fundamental, open questions that have emerged during this elaboration and discuss original experimental observations that challenge some of our current knowledge of thrombolysis.

Shear induced diffusion of platelets revisited.

The transport of platelets in blood is commonly assumed to obey an advection-diffusion equation with a diffusion constant given by the so-called Zydney-Colton theory. Here we reconsider this hypothesis based on experimental observations and numerical simulations including a fully resolved suspension of red blood cells and platelets subject to a shear. We observe that the transport of platelets perpendicular to the flow can be characterized by a non-trivial distribution of velocities with and exponential decreasing bulk, followed by a power law tail. We conclude that such distribution of velocities leads to diffusion of platelets about two orders of magnitude higher than predicted by Zydney-Colton theory. We tested this distribution with a minimal stochastic model of platelets deposition to cover space and time scales similar to our experimental results, and confirm that the exponential-powerlaw distribution of velocities results in a coefficient of diffusion significantly larger than predicted by the Zydney-Colton theory.

Three-dimensional analysis of blood platelet spreading using digital holographic microscopy: a statistical study of the differential effect of coatings in healthy volunteers and dialyzed patients.

In cardiovascular disorders, the study of thrombocytes, commonly known as platelets, is highly important since they are involved in blood clotting, essential in hemostasis, and they can in pathological situations affect the blood circulation. In this paper, single deposited platelets are measured using interferometric digital holographic microscopy. We have shown that the average optical height of platelets is significantly lower in healthy volunteers than in dialyzed patients, meaning a better spreading. It demonstrates the great interest for assessing this parameter in any patients, and therefore the high potential of analyzing single spread platelets using digital holographic microscopy in fundamental research as well as a diagnostic tool in routine laboratories, for usual blood tests.

Choreography Controlled (ChoCo) brain MRI artifact generation for labeled motion-corrupted datasets.

MRI is a non-invasive medical imaging modality that is sensitive to patient motion, which constitutes a major limitation in most clinical applications. Solutions may arise from the reduction of acquisition times or from motion-correction techniques, either prospective or retrospective. Benchmarking the latter methods requires labeled motion-corrupted datasets, which are uncommon. Up to our best knowledge, no protocol for generating labeled datasets of MRI images corrupted by controlled motion has yet been proposed. Hence, we present a methodology allowing the acquisition of reproducible motion-corrupted MRI images as well as validation of the system's performance by motion estimation through rigid-body volume registration of fast 3D echo-planar imaging (EPI) time series. A proof-of-concept is presented, to show how the protocol can be implemented to provide qualitative and quantitative results. An MRI-compatible video system displays a moving target that volunteers equipped with customized plastic glasses must follow to perform predefined head choreographies. Motion estimation using rigid-body EPI time series registration demonstrated that head position can be accurately determined (with an average standard deviation of about 0.39 degrees). A spatio-temporal upsampling and interpolation method to cope with fast motion is also proposed in order to improve motion estimation. The proposed protocol is versatile and straightforward. It is compatible with all MRI systems and may provide insights on the origins of specific motion artifacts. The MRI and artificial intelligence research communities could benefit from this work to build in-vivo labeled datasets of motion-corrupted MRI images suitable for training/testing any retrospective motion correction or machine learning algorithm.

Effects of the flow diversion technique on nucleotide levels in intra-cranial aneurysms: A feasibility study providing new research perspectives.

Introduction: The flow diverter stent (FDS) has become a first-line treatment for numerous intra-cranial aneurysms (IAs) by promoting aneurysm thrombosis. However, the biological phenomena underlying its efficacy remain unknown. We proposed a method to collect in situ blood samples to explore the flow diversion effect within the aneurysm sac. In this feasibility study, we assessed the plasma levels of nucleotides within the aneurysm sac before and after flow diversion treatment. Materials and methods: In total, 14 patients with unruptured IAs who were selected for FDS implantation were prospectively recruited from February 2015 to November 2015. Two catheters dedicated to (1) FDS deployment and (2) the aneurysm sac were used to collect blood samples within the parent artery (P1) and the aneurysm sac before (P2) and after (P3) flow diversion treatment. The plasma levels of adenosine monophosphate (AMP), adenosine diphosphate (ADP), and adenosine triphosphate (ATP) at each collection point were quantified with liquid chromatography and tandem mass spectrometry. Results: The aneurysms were extradural in nine (64.3%) patients and intra-dural in five (35.7%) patients. They presented an average diameter of 15.5 ± 7.1 mm, height of 15.8 ± 4.6 mm, and volume of 2,549 ± 2,794 ml. In all patients (100%), 16 FDS implantations and 42 in situ blood collections were performed successfully without any complications associated with the procedure. The ATP, ADP, and AMP concentrations within the aneurysm sac were decreased after flow diversion (p = 0.005, p = 0.03, and p = 0.12, respectively). Only the ATP levels within the aneurysm sac after flow diversion were significantly correlated with aneurysm volume (adjusted R 2 = 0.43; p = 0.01). Conclusion: In situ blood collection within unruptured IAs during a flow diversion procedure is feasible and safe. Our results suggest that the flow diversion technique is associated with changes in the nucleotide plasma levels within the aneurysm sac.

Digital blood in massively parallel CPU/GPU systems for the study of platelet transport.

We propose a highly versatile computational framework for the simulation of cellular blood flow focusing on extreme performance without compromising accuracy or complexity. The tool couples the lattice Boltzmann solver Palabos for the simulation of blood plasma, a novel finite-element method (FEM) solver for the resolution of deformable blood cells, and an immersed boundary method for the coupling of the two phases. The design of the tool supports hybrid CPU-GPU executions (fluid, fluid-solid interaction on CPUs, deformable bodies on GPUs), and is non-intrusive, as each of the three components can be replaced in a modular way. The FEM-based kernel for solid dynamics outperforms other FEM solvers and its performance is comparable to state-of-the-art mass-spring systems. We perform an exhaustive performance analysis on Piz Daint at the Swiss National Supercomputing Centre and provide case studies focused on platelet transport, implicitly validating the accuracy of our tool. The tests show that this versatile framework combines unprecedented accuracy with massive performance, rendering it suitable for upcoming exascale architectures.

Implementation of lattice Boltzmann free-surface and shallow water models and their two-way coupling.

•A detailed, practical description of a 2D lattice Boltzmann (LB) free-surface model and its coupling with a 1D LB shallow water model is provided.•A Python code is provided, that implements the Gaussian droplet benchmark of the research article (Thorimbert et al., 2019) corresponding to this method article.•Particular attention is given to the details of the free-surface implementation which, in the literature, vary among authors. These ambiguities must be addressed in order to build a reproducible scheme, as well as the exact implementation and parameters of the coupling model proposed in the associated research article.

Enhanced single-node lattice Boltzmann boundary condition for fluid flows.

We propose a procedure to implement Dirichlet velocity boundary conditions for complex shapes that use data from a single node only, in the context of the lattice Boltzmann method. Two ideas are at the base of this approach. The first is to generalize the geometrical description of boundary conditions combining bounce-back rule with interpolations. The second is to enhance them by limiting the interpolation extension to the proximity of the boundary. Despite its local nature, the resulting method exhibits second-order convergence for the velocity field and shows similar or better accuracy than the well-established Bouzidi's scheme for curved walls [M. Bouzidi, M. Firdaouss, and P. Lallemand, Phys. Fluids 13, 3452 (2001)]PHFLE61070-663110.1063/1.1399290. Among the infinite number of possibilities, we identify several meaningful variants of the method, discerned by their approximation of the second-order nonequilibrium terms and their interpolation coefficients. For each one, we provide two parametrized versions that produce viscosity independent accuracy at steady state. The method proves to be suitable to simulate moving rigid objects or surfaces moving following either the rigid body dynamics or a prescribed kinematic. Also, it applies uniformly and without modifications in the whole domain for any shape, including corners, narrow gaps, or any other singular geometry.