Novel coiled hollow fiber module for high-performance membrane distillation

Membrane distillation (MD) scale-up is challenged by ineffective heat recovery and the temperature polarization effect. Direct contact membrane distillation (DCMD) modules suffer high thermal conduction losses due to feed flow direction along the length of the membrane, resulting in low thermal efficiency. We propose a novel module design named coiled hollow fiber (CHF) to decouple the flow direction from the membrane surface in hollow fiber (HF) DCMD. Experimental and computational analyses were employed to compare the performance of CHF and the conventional design. The CHF module design successfully mitigates the TP effect in HF DCMD, increasing the flux by 148 % and 163 % in cross-flow and localized heating (LH) modes, respectively. Moreover, CHF operated in LH mode exhibits the lowest energy consumption of all configurations (81 % decrease) compared to the conventional design. This novel module design represents a new pathway for efficient and highly performing DCMD module.

Fluoride Transport and Inhibition Across CLC Transporters

The Chloride Channel (CLC) family includes proton-coupled chloride and fluoride transporters. Despite their similar protein architecture, the former exchange two chloride ions for each proton and are inhibited by fluoride, whereas the latter efficiently transport one fluoride in exchange for one proton. The combination of structural, mutagenesis, and functional experiments with molecular simulations has pinpointed several amino acid changes in the permeation pathway that capitalize on the different chemical properties of chloride and fluoride to fine-tune protein function. Here we summarize recent findings on fluoride inhibition and transport in the two prototypical members of the CLC family, the chloride/proton transporter from Escherichia coli (CLC-ec1) and the fluoride/proton transporter from Enterococcus casseliflavus (CLCF-eca).

How does the same ligand activate signaling of different receptors in TNFR superfamily: a computational study

TNFα is a highly pleiotropic cytokine inducing inflammatory signaling pathways. It is initially presented on plasma membrane of cells (mTNFα), and also exists in a soluble variant (sTNFα) after cleavage. The ligand is shared by two structurally similar receptors, TNFR1 and TNFR2. Interestingly, while sTNFα preferentially stimulates TNFR1, TNFR2 signaling can only be activated by mTNFα. How can two similar receptors respond to the same ligand in such a different way? We employed computational simulations in multiple scales to address this question. We found that both mTNFα and sTNFα can trigger the clustering of TNFR1. The size of clusters induced by sTNFα is constantly larger than the clusters induced by mTNFα. The systems of TNFR2, on the other hand, show very different behaviors. Only when the interactions between TNFR2 are very weak, mTNFα can trigger the receptors to form very large clusters. Given the same weak binding affinity, only small oligomers were obtained in the system of sTNFα. Considering that TNF-mediated signaling is modulated by the ligand-induced clustering of receptors on cell surface, our study provided the mechanistic foundation to the phenomenon that different isoforms of the ligand can lead to highly distinctive signaling patterns for its receptors.

Multiscale modeling of thermomechanical properties of stereoregular polymers

Multiscale coarse-grained (CG) models are expected to play the critical roles in molecular simulations of complex polymers. However, this poses a great challenge for accurately simulating their thermomechanical properties, for which excellent representability and transferability are required for the CG potentials. In this work, virtual sites and elastic network bonds are introduced to improve the structural and volumetric property-based CG models including explicit electrostatic interactions, which is exemplarily applied to the iso- and syndio-tactic poly(methyl methacrylate). A variety of thermomechanical properties of the two stereoregular polymer bulks are reasonably reproduced by the extensive molecular dynamics simulations with the so-parameterized CG potentials. In particular, the attractive nature of electrostatic interactions and tacticity effects on glass transition temperatures (T_g) are well captured. Furthermore, stronger electrostatic interactions lead to higher mass density and bulk modulus, and their effects on Young's modulus, Poisson's ratio, and shear modulus depend upon the chain tacticity. It is also demonstrated that all these elastic constants can be effectively modulated by imposing external electric field. The proposed multiscale scheme can be very valuable to molecular designs of polar polymer materials.

Simulating realistic membrane shapes

Biological membranes exhibit diversity in their shapes and complexity in chemical compositions that are linked to many cellular functions. These two central features of biomembranes have been the subject of numerous simulation studies, using a diverse range of computational techniques. Currently, the field is able to capture this complexity at increasing levels of realism and connect the microscopic view on protein-lipid interactions to cellular morphologies at the level of entire organelles. Here we highlight recent advances in this topic, identify current bottlenecks, and sketch possible ways ahead.

A predictive multiscale model for simulating flow-induced platelet activation: Correlating in silico results with in vitro results

Flow-induced platelet activation prompts complex filopodial formation. Continuum methods fail to capture such molecular-scale mechanisms. A multiscale numerical model was developed to simulate this activation process, where a Dissipative Particle Dynamics (DPD) model of viscous blood flow is interfaced with a Coarse Grained Molecular Dynamics (CGMD) platelet model. Embedded in DPD blood flow, the macroscopic dynamic stresses are interactively transferred to the CGMD model, inducing intra-platelet associated events. The platelets activate by a biomechanical transductive linkage chain and dynamically change their shape in response. The models are fully coupled via a hybrid-potential interface and multiple time-stepping (MTS) schemes for handling the disparity between the spatiotemporal scales. Cumulative hemodynamic stresses that may lead to platelet activation are mapped on the surface membrane and simultaneously transmitted to the cytoplasm and cytoskeleton. Upon activation, the flowing platelets lose their quiescent discoid shape and evolve by forming filopodia. The model predictions were validated by a set of in vitro experiments, Platelets were exposed to various combinations of shear stresses and durations in our programmable hemodynamic shearing device (HSD). Their shape change was measured at multiple time points using scanning electron microscopy (SEM). The CGMD model parameters were fine-tuned by interrogating a parameter space established in these experiments. Segmentation of the SEM imaging streams was conducted by a deep machine learning system. This model can be further employed to simulate shear mediated platelet activation thrombosis initiation and to study the effects of modulating platelet properties to enhance their shear resistance via mechanotransduction pathways.

Sensitivity analysis of a strongly-coupled human-based electromechanical cardiac model: Effect of mechanical parameters on physiologically relevant biomarkers

The human heart beats as a result of multiscale nonlinear dynamics coupling subcellular to whole organ processes, achieving electrophysiologically-driven mechanical contraction. Computational cardiac modelling and simulation have achieved a great degree of maturity, both in terms of mathematical models of underlying biophysical processes and the development of simulation software. In this study, we present the detailed description of a human-based physiologically-based, and fully-coupled ventricular electromechanical modelling and simulation framework, and a sensitivity analysis focused on its mechanical properties. The biophysical detail of the model, from ionic to whole-organ, is crucial to enable future simulations of disease and drug action. Key novelties include the coupling of state-of-the-art human-based electrophysiology membrane kinetics, excitation-contraction and active contraction models, and the incorporation of a pre-stress model to allow for pre-stressing and pre-loading the ventricles in a dynamical regime. Through high performance computing simulations, we demonstrate that 50% to 200% - 1000% variations in key parameters result in changes in clinically-relevant mechanical biomarkers ranging from diseased to healthy values in clinical studies. Furthermore mechanical biomarkers are primarily affected by only one or two parameters. Specifically, ejection fraction is dominated by the scaling parameter of the active tension model and its scaling parameter in the normal direction ( k ort 2 ); the end systolic pressure is dominated by the pressure at which the ejection phase is triggered ( P ej ) and the compliance of the Windkessel fluid model ( C ); and the longitudinal fractional shortening is dominated by the fibre angle ( ϕ ) and k ort 2 . The wall thickening does not seem to be clearly dominated by any of the considered input parameters. In summary, this study presents in detail the description and implementation of a human-based coupled electromechanical modelling and simulation framework, and a high performance computing study on the sensitivity of mechanical biomarkers to key model parameters. The tools and knowledge generated enable future investigations into disease and drug action on human ventricles.

Modeling MesoBioNano systems with MBN Studio made easy

This paper introduces MesoBioNano (MBN) Studio - a graphical user interface for a popular multiscale simulation package MBN Explorer. MBN Studio has been developed to facilitate setting up and starting MBN Explorer calculations, monitoring their progress and examining the calculation results. It is tailored for any calculations that are supported by MBN Explorer, such as for example the single-point energy calculations, structure optimization, molecular dynamics, and kinetic Monte Carlo simulations. Apart from that MBN Studio has built-in tools allowing the calculation and analysis of specific characteristics that are determined by the output of the simulations, such as the diffusion coefficients of molecular species, melting temperatures and associated heat capacities, radial distribution function; a dedicated modeling plug-in allows constructing molecular systems in a quick and efficient manner. Employing this plug-in, one can easily construct molecular systems of different geometries (e.g., spherical or ellipsoidal nanoparticles, cubic crystalline samples) with various atomic composition. The paper presents the first public release of MBN Studio and provides an overview of its significant capabilities, as well as the reference point for further extensions.

Efficient potential of mean force calculation from multiscale simulations: Solute insertion in a lipid membrane

The determination of potentials of mean force for solute insertion in a lipid membrane by means of all-atom molecular dynamics simulations is often hampered by sampling issues. Recently, a multiscale method has been proposed to leverage the conformational ensemble of a lower-resolution model as starting point for higher resolution simulations. In this work, we analyze the efficiency of this method by comparing its predictions for propanol insertion into a lipid membrane against conventional atomistic umbrella sampling simulation results. The multiscale approach is confirmed to provide accurate results with a gain of one order of magnitude in computational time. We then investigate the role of the coarse-grained representation. We find that the accuracy of the results is tightly connected to the presence of a good configurational overlap between the coarse-grained and atomistic models-a general requirement when developing multiscale simulation methods.

Hemodynamic analysis of outflow grafting positions of a ventricular assist device using closed-loop multiscale CFD simulations: Preliminary results

Subclavian arteries are a possible alternate location for left ventricular assist device (LVAD) outflow grafts due to easier surgical access and application in high risk patients. As vascular blood flow mechanics strongly influence the clinical outcome, insights into the hemodynamics during LVAD support can be used to evaluate different grafting locations. In this study, the feasibility of left and right subclavian artery (SA) grafting was investigated for the HeartWare HVAD with a numerical multiscale model. A 3-D CFD model of the aortic arch was coupled to a lumped parameter model of the cardiovascular system under LVAD support. Grafts in the left and right SA were placed at three different anastomoses angles (90°, 60° and 30°). Additionally, standard grafting of the ascending and descending aorta was modelled. Full support LVAD (5l/min) and partial support LVAD (3l/min) in co-pulsation and counter-pulsation mode were analysed. The grafting positions were investigated regarding coronary and cerebral perfusion. Furthermore, the influence of the anastomosis angle on wall shear stress (WSS) was evaluated. Grafting of left or right subclavian arteries has similar hemodynamic performance in comparison to standard cannula positions. Angularity change of the graft anastomosis from 90° to 30° slightly increases the coronary and cerebral blood flow by 6-9% while significantly reduces the WSS by 35%. Cannulation of the SA is a feasible anastomosis location for the HVAD in the investigated vessel geometry.

Effects of Lys to Glu mutations in GsMTx4 on membrane binding, peptide orientation, and self-association propensity, as analyzed by molecular dynamics simulations

GsMTx4, a gating modifier peptide acting on cationic mechanosensitive channels, has a positive charge (+5e) due to six Lys residues. The peptide does not have a stereospecific binding site on the channel but acts from the boundary lipids within a Debye length of the pore probably by changing local stress. To gain insight into how these Lys residues interact with membranes, we performed molecular dynamics simulations of Lys to Glu mutants in parallel with our experimental work. In silico, K15E had higher affinity for 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine bilayers than wild-type (WT) peptide or any other mutant tested, and showed deeper penetration than WT, a finding consistent with the experimental data. Experimentally, the inhibitory activities of K15E and K25E were most compromised, whereas K8E and K28E inhibitory activities remained similar to WT peptide. Binding of WT in an interfacial mode did not influence membrane thickness. With interfacial binding, the direction of the dipole moments of K15E and K25E was predicted to differ from WT, whereas those of K8E and K28E oriented similarly to that of WT. These results support a model in which binding of GsMTx4 to the membrane acts like an immersible wedge that serves as a membrane expansion buffer reducing local stress and thus inhibiting channel activity. In simulations, membrane-bound WT attracted other WT peptides to form aggregates. This may account for the positive cooperativity observed in the ion channel experiments. The Lys residues seem to fine-tune the depth of membrane binding, the tilt angle, and the dipole moments.

Multiscale Particle-Based Modeling of Flowing Platelets in Blood Plasma Using Dissipative Particle Dynamics and Coarse Grained Molecular Dynamics

We developed a multiscale particle-based model of platelets, to study the transport dynamics of shear stresses between the surrounding fluid and the platelet membrane. This model facilitates a more accurate prediction of the activation potential of platelets by viscous shear stresses - one of the major mechanisms leading to thrombus formation in cardiovascular diseases and in prosthetic cardiovascular devices. The interface of the model couples coarse-grained molecular dynamics (CGMD) with dissipative particle dynamics (DPD). The CGMD handles individual platelets while the DPD models the macroscopic transport of blood plasma in vessels. A hybrid force field is formulated for establishing a functional interface between the platelet membrane and the surrounding fluid, in which the microstructural changes of platelets may respond to the extracellular viscous shear stresses transferred to them. The interaction between the two systems preserves dynamic properties of the flowing platelets, such as the flipping motion. Using this multiscale particle-based approach, we have further studied the effects of the platelet elastic modulus by comparing the action of the flow-induced shear stresses on rigid and deformable platelet models. The results indicate that neglecting the platelet deformability may overestimate the stress on the platelet membrane, which in turn may lead to erroneous predictions of the platelet activation under viscous shear flow conditions. This particle-based fluid-structure interaction multiscale model offers for the first time a computationally feasible approach for simulating deformable platelets interacting with viscous blood flow, aimed at predicting flow induced platelet activation by using a highly resolved mapping of the stress distribution on the platelet membrane under dynamic flow conditions.