Multiscale simulation in polymer science

The paper gives a short overview on recent approaches to link several time and length scales in soft matter simulations. Special attention is given to the fact that in contrast to low molecular weight compounds, intramolecular entropy is as important as the energetic contribution. First applications to industrially relevant problems are mentioned.     

Multiscale simulation of transmembrane proteins

Multiscale simulation is employed to examine changes in atomistic-level protein structure due to long wavelength membrane undulations and plane stress fields. An ensemble of atomistic-level simulations of a model of a transmembrane influenza A virus M2 proton channel in a dimyristoylphosphatidylcholine (DMPC) bilayer is coupled to a corresponding mesoscopic model of a DMPC bilayer in an explicit mesoscopic solvent. Structural variations in the key proton gating His37 residues of the M2 channel are examined. Small, but distinct variations in the structure of the His37 residues are observed in both the open and closed states of the channel as a result of the coupling to mesoscopic-level membrane motions.     

Multiscale kinetic analysis of proteins

The stochasticity of molecular motion results in the existence of multiple kinetically relevant pathways in many biomolecular mechanisms. Because it is highly demanding to characterize them for complex systems, mechanisms are often described with a single-pathway perspective. However, kinetic network analysis and sub-ensemble experimental insight are increasingly demonstrating not only the existence of competing pathways but also the importance of kinetic selection in biology. This review focuses on advances in multiscale kinetic analysis of proteins, which connects molecular level information from simulations to macroscopic data to characterize mechanistic reaction networks and the reactive flux through them. We describe a range of methods used and highlight several examples where kinetic modeling has revealed functional importance of pathway heterogeneity.     

Multiscale processing of mass spectrometry data

This work addresses the problem of extracting signal content from protein mass spectrometry data. A multiscale decomposition of these spectra is used to focus on local scale-based structure by defining scale-specific features. Quantification of features is accompanied by an efficient method for calculating the location of features which avoids estimation of signal-to-noise ratios or bandwidths. Scale-based histograms serve as spectral-density-like functions indicating the regions of high density of features in the data. These regions provide bins within which features are quantified and compared across samples. As a preliminary step, the locations of prominent features within coarse-scale bins may be used for a crude registration of spectra. The multiscale decomposition, the scale-based feature definition, the calculation of feature locations, and subsequent quantification of features are carried out by way of a translation-invariant wavelet analysis.     

Multiscale modeling of lipids and lipid bilayers

A multiscale modeling approach is applied for simulations of lipids and lipid assemblies on mesoscale. First, molecular dynamics simulation of initially disordered system of lipid molecules in water within all-atomic model was carried out. On the next stage, structural data obtained from the molecular dynamics (MD) simulation were used to build a coarse-grained (ten sites) lipid model, with effective interaction potentials computed by the inverse Monte Carlo method. Finally, several simulations of the coarse-grained model on longer length- and time-scale were performed, both within Monte Carlo and molecular dynamics simulations: a periodical sample of lipid molecules ordered in bilayer, a free sheet of such bilayer without periodic boundary conditions, formation of vesicle from a plain membrane, process of self-assembly of lipids randomly dispersed in volume. It was shown that the coarse-grained model, developed exclusively from all-atomic simulation data, reproduces well all the basic features of lipids in water solution.     

Multiscale analysis of pattern formation via intercellular signalling

Lateral inhibition, a juxtacrine signalling mechanism by which a cell adopting a particular fate inhibits neighbouring cells from doing likewise, has been shown to be a robust mechanism for the formation of fine-grained spatial patterns (in which adjacent cells in developing tissues diverge to achieve contrasting states of differentiation), provided that there is sufficiently strong feedback. The fine-grained nature of these patterns poses problems for analysis via traditional continuum methods since these require that significant variation takes place only over lengthscales much larger than an individual cell and such systems have therefore been investigated primarily using discrete methods. Here, however, we apply a multiscale method to derive systematically a continuum model from the discrete Delta-Notch signalling model of Collier et al. (J.R. Collier, N.A.M. Monk, P.K. Maini, J.H. Lewis, Pattern formation by lateral inhibition with feedback: a mathematical model of Delta-Notch intercellular signalling, J. Theor. Biol., 183, 1996, 429-446) under particular assumptions on the parameters, which we use to analyse the generation of fine-grained patterns. We show that, on the macroscale, the contact-dependent juxtacrine signalling interaction manifests itself as linear diffusion, motivating the use of reaction-diffusion-based models for such cell-signalling systems. We also analyse the travelling-wave behaviour of our system, obtaining good quantitative agreement with the discrete system.     

基于多尺度快速样本熵与随机森林的心电图分析

目的:探讨基于多尺度快速样本熵与随机森林的心电图分析方法对常见心律失常(房性早搏、室性早搏)的自动诊断的可行性和有效性。方法:利用不同心律失常疾病的心电信号存在复杂性差异的特点,通过多尺度熵计算心电信号在不同尺度下的样本熵值以组成特征向量;利用kd树提高多尺度熵的计算效率,增强算法的实时性。利用训练样本的特征向量构建随机森林分类器,再根据众多决策树的分类结果结合投票原则确定测试样本心律失常疾病的类型。结果:本文提出的心电图分析方法能够有效地识别正常心律、房性早搏(APB)及室性早搏(VPB),平均识别准确率达到91.60%。结论:本文提出的心电图分析方法对常见心律失常(APB,VPB)具有较高的识别准确率及临床实用价值。     

Multiscale simulation for thermo-hydrodynamic lubrication of a polymeric liquid between parallel plates

Thermo-hydrodynamic lubrication of a polymeric liquid composed of short chains between parallel plates is analysed by a multi-scale simulation, i.e. the synchronised molecular dynamics simulation via macroscopic heat and momentum transfer, which has been recently developed by us. The rheological properties and conformation of polymer chains coupled with the temperature rise caused by local viscous heating are investigated with a non-dimensional parameter, i.e. the Nahme–Griffith number, which is defined by the ratio of the viscous heating to the thermal conduction at the characteristic temperature required to sufficiently change the viscosity. The present simulation demonstrates that strong shear thinning and transitional behaviour of the conformation of the polymer chains occurs with a rapid temperature rise when the Nahme–Griffith number exceeds unity.     

Multiscale monitoring of a multispecies case study: two grass species at Sevilleta

Monitoring multiple species and their interactions at multiple scales is critical for any useful habitat conservation plans and for adaptive ecosystem management programs. Viability of single species can be understood only in the context of ecological interactions with other species at multiple spatial and temporal scales. Here, we present a case study of the spatial and temporal dynamics for two perennial grasses, Bouteloua eriopoda and B. gracilis, by using long-term, high resolution transect data from 1989 to 1998 at two sites in the Sevilleta National Wildlife Refuge (Deep Well and Five Points) in central New Mexico, USA. Information entropy was used to describe the spatial distribution of each species and the fractal dimension of information entropy was used to characterize the complexity of species dynamics across scales. When considered individually, the spatial distribution of each species was scale-invariant. However, species joint occurrences changed as scale of resolution increased at both sites. Interactions changed at scales less than 3.2 m at Deep Well and less than 1.6 m at Five Points. Across years, the interactions of these species at Deep Well were significantly different in 1989 from all other years. Our results argue that monitoring multiple species at multiple spatial and temporal scales is necessary to better understand multispecies interactions and community dynamics both of which have important conservation implications under changing environmental conditions.     

Multiscale simulations of large complexes in conjunction with cryo-EM analysis

The cellular environment is highly crowded with most proteins and RNA/DNA forming homomeric and heteromeric complexes. Essential questions regarding how these complexes switch between functional, rest, and abnormal states with regulators or modifications remain challenging and complicated. Here, we review the recent progress integrating cryoelectron microscopy and multiscale molecular modeling to understand the dynamics and function-related mechanism in protein–RNA/DNA complexes, protein–protein complexes/assemblies, and membrane protein complexes. One future direction of multiscale simulations will be to interpret the large complex multibody regulation in assembly-induced function enhancement in conjunction with advanced atomic resolution structural-biology techniques and specialized computing architectures.     

Coarse-grained Modeling and Simulation of Actin Filament Behavior Based on Brownian Dynamics Method

The actin filament, which is the most abundant component of the cytoskeleton, plays important roles in fundamental cellular activities such as shape determination, cell motility, and mechanosensing. In each activity, the actin filament dynamically changes its structure by polymerization, depolymerization, and severing. These phenomena occur on the scales ranging from the dynamics of actin molecules to filament structural changes with its deformation due to the various forces, for example, by the membrane and solvent. To better understand the actin filament dynamics, it is important to focus on these scales and develop its mathematical model. Thus, the objectives of this study were to model and simulate actin filament polymerization, depolymerization, and severing based on the Brownian dynamics method. In the model, the actin monomers and the solvent were considered as globular particles and a continuum, respectively. The motion of the actin molecules was assumed to follow the Langevin equation. The polymerization, which increases the filament length, was determined by the distance between the center of the actin particle at the barbed end and actin particles in the solvent. The depolymerization, which decreases the filament length, was modeled such that the number of dissociation particles from the filament end per unit time was constant. In addition, the filament severing, in which one filament divides into two, was modeled to occur at an equal rate along the filament. Then, we simulated the actin filament dynamics using the developed model, and analyzed the filament elongation rate, its turnover, and the effects of filament severing on the polymerization and depolymerization. Results indicated that the model reproduced the linear dependence of the filament elongation on time, filament turnover process by polymerization and depolymerization, and acceleration of the polymerization and depolymerization by severing, which qualitatively agreed with those observed in experiments.     

Detecting Genomic Aberrations Using Products in a Multiscale Analysis

Summary Genomic instability, such as copy‐number losses and gains, occurs in many genetic diseases. Recent technology developments enable researchers to measure copy numbers at tens of thousands of markers simultaneously. In this article, we propose a nonparametric approach for detecting the locations of copy‐number changes and provide a measure of significance for each change point. The proposed test is based on seeking scale‐based changes in the sequence of copy numbers, which is ordered by the marker locations along the chromosome. The method leads to a natural way to estimate the null distribution for the test of a change point and adjusted p‐values for the significance of a change point using a step‐down maxT permutation algorithm to control the family‐wise error rate. A simulation study investigates the finite sample performance of the proposed method and compares it with a more standard sequential testing method. The method is illustrated using two real data sets.     

Multiscale model for pulmonary oxygen uptake and its application to quantify hypoxemia in hepatopulmonary syndrome

This paper presents a novel multiscale methodology for quantitative analysis of pulmonary gas exchange. The process of oxygen uptake in the lungs is a complex multiscale process, characterized by multiple time and length scales which are coupled nonlinearly through the processes of diffusion, convection and reaction, and the overall oxygen uptake is significantly influenced by the transport and reaction rate processes at the small-scales. Based on the separation of length scales, we characterize these disparate scales by three representative ones, namely micro (red blood cell), meso (capillary and alveolus) and macro (lung). We start with the fundamental convection-diffusion-reaction (CDR) equation that quantifies transport and reaction rates at each scale and apply spatial averaging techniques to reduce the dimensionality of these models. The resultant low-dimensional models embed each scale hierarchically within the other while retaining the important parameters of the small-scales in the averaged equations, and drastically reduce the computational efforts involved in solving them. We use our multiscale model for pulmonary gas exchange to quantify the oxygen uptake abnormalities in patients with hepatopulmonary syndrome (HPS), a disease which is characterized by coupled abnormalities in multiple length scales. Based on our multiscale modeling, we suggest a strategy to stratify patients with HPS into two categories--those who are oxygen-responsive and those who are oxygen non-responsive with intractable hypoxemia.     

Multiscale Adaptive Marginal Analysis of Longitudinal Neuroimaging Data with Time‐Varying Covariates

Summary Neuroimaging data collected at repeated occasions are gaining increasing attention in the neuroimaging community due to their potential in answering questions regarding brain development, aging, and neurodegeneration. These datasets are large and complicated, characterized by the intricate spatial dependence structure of each response image, multiple response images per subject, and covariates that may vary with time. We propose a multiscale adaptive generalized method of moments (MA‐GMM) approach to estimate marginal regression models for imaging datasets that contain time‐varying, spatially related responses and some time‐varying covariates. Our method categorizes covariates into types to determine the valid moment conditions to combine during estimation. Further, instead of assuming independence of voxels (the components that make up each subject’s response image at each time point) as many current neuroimaging analysis techniques do, this method “adaptively smoothes” neuroimaging response data, computing parameter estimates by iteratively building spheres around each voxel and combining observations within the spheres with weights. MA‐GMM’s development adds to the few available modeling approaches intended for longitudinal imaging data analysis. Simulation studies and an analysis of a real longitudinal imaging dataset from the Alzheimer’s Disease Neuroimaging Initiative are used to assess the performance of MA‐GMM. Martha Skup, Hongtu Zhu, and Heping Zhang for the Alzheimer’s Disease Neuroimaging Initiative.     

CGDB: A database of membrane protein/lipid interactions by coarse-grained molecular dynamics simulations

Membrane protein function and stability has been shown to be dependent on the lipid environment. Recently, we developed a high-throughput computational approach for the prediction of membrane protein/lipid interactions. In the current study, we enhanced this approach with the addition of a new measure of the distortion caused by membrane proteins on a lipid bilayer. This is illustrated by considering the effect of lipid tail length and headgroup charge on the distortion caused by the integral membrane proteins MscS and FLAP, and by the voltage sensing domain from the channel KvAP. Changing the chain length of lipids alters the extent but not the pattern of distortion caused by MscS and FLAP; lipid headgroups distort in order to interact with very similar but not identical regions in these proteins for all bilayer widths investigated. Introducing anionic lipids into a DPPC bilayer containing the KvAP voltage sensor does not affect the extent of bilayer distortion.     

Characterization of noise and digitizer response variability in radiochromic film dosimetry. Impact on treatment verification

PurposeTo study how noise and scanner response variability affect radiochromic film dosimetry.MethodsFive treatment plans were analyzed in this work with two different multichannel protocols: the multichannel algorithm of Mayer et al. and the efficient protocol of Lewis et al.Results and conclusionThe multichannel protocol of Mayer et al. is not able to compensate variability in scanner response, which is an important issue for radiochromic film dosimetry. The efficient protocol compensates variations of scanner response, so dose values and gamma scores become more accurate and reproducible. The compensation of digitizer scan variability of the efficient protocol, together with time averaging improve radiochromic film dosimetry. Noise is related to selected resolution in the scanner, our results show that if high resolution measurements are required, de-noising should be considered.     

Chitosan treatment for skin ulcers associated with diabetes

Infections, ulcerations, gangrene and, in severe cases, extremity amputation, are common complications among diabetic subjects. Various biomaterials have been utilized for the treatment of these lesions. Chitosan is an amino sugar with a low risk of toxicity and immune response. In this study, we evaluated chitosan topical gel and film treatments for subjects with diabetic ulcerations and wounds associated with diabetes mellitus. In a pre-experimental design, we described the result of chitosan gel and film treatment for wounds and skin ulcers among patients with long-standing diabetes mellitus. We studied 8 diabetic patients with wounds and skin ulcers (long duration and Wagner degree 1–2). Initially, most lesions had some degree of infection, tissue damage and ulceration. At the end of the treatment (topical chitosan) period, the infections were cured. All patients experienced a significant improvement in the initial injury and developed granulation tissue and a healthy skin cover. This report represents one of the few published clinical experience regarding the chitosan for the treatment of skin lesions among diabetic subjects. These results are relevant and promising for the treatment of this disease.     

Enhanced boundary lubrication properties of engineered menisci by lubricin localization with insulin-like growth factor I treatment

In this study we analyzed the effects of IGF-I on the boundary lubricating ability of engineered meniscal tissue using a high density collagen gel seeded with meniscal fibrochondrocytes. Biochemical, histological, immunohistochemical, and tribological analyses were carried out to determine a construct's ability to functionally localize lubricin. Our study revealed that supplementation with IGF-I enhanced both the proliferation of cells within the construct as well as enhanced the anabolic activity of the seeded cells. Growth factor supplementation also facilitated the localization of ECM constituents (i.e. fibronectin and type II collagen) near the tissue surface that are important for the localization of lubricin, a boundary lubricant. Consequently, we found localized lubricin in the constructs supplemented with IGF-I. Tribologically, we demonstrated that lubricin serves as a boundary lubricant adsorbed to native meniscal surfaces. Lubricin removal from the native meniscus surface increased boundary friction coefficient by 40%. For the engineered constructs, the lubricin localization facilitated by growth factor supplementation also reduced friction coefficient by a similar margin, but similar results were not evident in control constructs. This study demonstrates that the use of growth factors in meniscal tissue engineering can enhance tribological properties by facilitating the localization of boundary lubricants at the surface of engineered tissue.