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Chemotaxis is an oriented movement of cells and organisms in response to chemical signals, and plays an important role in the life of many cells and microorganisms, such as the transport of embryonic cells to developing tissues and immune cells to infection sites. Since the pioneering works of Keller and Segel, there has been a great deal of literature on the qualitative analysis of chemotaxis systems. As an important extension of the Keller–Segel system, a variety of chemotaxis–haptotaxis models have been proposed in order to gain a comprehensive understanding of the invasion–metastasis cascade. From a mathematical point of view, the rigorous analysis thereof is a nontrivial issue due to the fact that partial differential equations (PDEs) for the quantities on the macroscale are strongly coupled with ordinary differential equations (ODEs) modeling the subcellular events. It is the goal of this paper to describe recent results of some chemotaxis–haptotaxis models, inter alia macro cancer invasion models proposed by Chaplain et al., and multiscale cancer invasion models by Stinner et al., and also to introduce some open problems.

Being the central metabolic organ of vertebrates, the liver possesses the largest repertoire of metabolic enzymes among all tissues and organs. Almost all metabolic pathways are resident in the parenchymal cell, hepatocyte, but the pathway capacities may largely differ depending on the localization of hepatocytes within the liver acinus-a phenomenon that is commonly referred to as metabolic zonation. Metabolic zonation is rather dynamic since gene expression patterns of metabolic enzymes may change in response to nutrition, drugs, hormones and pathological states of the liver (e.g., fibrosis and inflammation). This fact has to be ultimately taken into account in mathematical models aiming at the prediction of metabolic liver functions in different physiological and pathological settings. Here we present a spatially resolved kinetic tissue model of hepatic glucose metabolism which includes zone-specific temporal changes of enzyme abundances which are driven by concentration gradients of nutrients, hormones and oxygen along the hepatic sinusoids. As key modulators of enzyme expression we included oxygen, glucose and the hormones insulin and glucagon which also control enzyme activities by cAMP-dependent reversible phosphorylation. Starting with an initially non-zonated model using plasma profiles under fed, fasted and diabetic conditions, zonal patterns of glycolytic and gluconeogenetic enzymes as well as glucose uptake and release rates are created as an emergent property. We show that mechanisms controlling the adaptation of enzyme abundances to varying external conditions necessarily lead to the zonation of hepatic carbohydrate metabolism. To the best of our knowledge, this is the first kinetic tissue model which takes into account in a semi-mechanistic way all relevant levels of enzyme regulation.

Highlights • We develop agent-based and continuous models to describe green sea turtle homing to Ascension Island. • We explicitly model turtle navigation in response to ocean and wind transported odour plumes and magnetic field intensity and inclination. • We show how multimodal homing markedly improves the ability of turtles to find their way home. Abstract A dot in the vastness of the Atlantic, Ascension Island remains a lifelong goal for the green sea turtles that hatched there, returning as adults every three or four years to nest. This navigating puzzle was brought to the scientific community's attention by Charles Darwin and remains a topic of considerable speculation. Various cues have been suggested, with orientation to geomagnetic field elements and following odour plumes to their island source among the most compelling. Via a comprehensive in silico investigation we test the hypothesis that multimodal cue following, in which turtles utilise multiple guidance cues, is the most effective strategy. Specifically, we combine agent-based and continuous-level modelling to simulate displaced virtual turtles as they attempt to return to the island. Our analysis shows how population homing efficiency improves as the number of utilised cues is increased, even under "extreme" scenarios where the overall strength of navigating information decreases. Beyond the paradigm case of green turtles returning to Ascension Island, we believe this could commonly apply throughout animal navigation. [ABSTRACT FROM AUTHOR]

Angiogenesis, a formation of blood vessels from an existing vasculature, plays a key role in tumor growth and its progression into cancer. The lining of blood vessels consists of endothelial cells (ECs) which proliferate and migrate, allowing the capillaries to sprout towards the tumor to deliver the needed oxygen. Various treatments aiming to suppress or even inhibit angiogenesis have been explored. Mesenchymal stem cells (MSCs) have recently been undergoing development in cell-based therapy for cancer due to their ability to migrate towards the capillaries and induce the apoptosis of the ECs, causing capillary degeneration. However, further investigations in this direction are needed as it is usually difficult to preclinically assess the efficacy of such therapy. We develop a hybrid multiscale model that integrates molecular, cellular, tissue and extracellular components of tumor system to investigate angiogenesis and tumor growth under MSC-mediated therapy. Our simulations produce angiogenesis and vascular tumor growth profiles as observed in the experiments. Furthermore, the simulations show that the effectiveness of MSCs in inducing EC apoptosis is density dependent and its full effect is reached within several days after MSCs application. Quantitative agreements with experimental data indicate the predictive potential of our model for evaluating the efficacy of cell-based therapies targeting angiogenesis. [ABSTRACT FROM AUTHOR]

A numerical multiscale model is used to resolve the high computation complexity in the ac loss calculation of large-scale superconducting devices and proves advantageous with regard to time and memory requirements. In the multiscale model, the background field estimation method is of crucial importance to the calculation accuracy. In this paper, we propose four new background field estimation methods, including the Jacobi Gauss–Seidel hybrid and iteration methods, to improve the accuracy and expand the application scope of the multiscale model. A high temperature superconducting solenoid magnet is used to test the performance of these four methods and the results are compared with those of the H-formulation reference model and the multiscale model with a J0 uniform background field estimation method. Results show that in the 19 A/50 Hz ac transport current test case: the Jacobi Gauss– hybrid and iteration methods reduce the error of the ac loss mean value/peak value to 7.88%/5.89%, 5.71%/2.4%, 3.22%/1.22%, and 1.83%/0.69% with the total time cost reduced by 15.7, 8.9, 13.5, and 7.8 times. The multiscale model is expected to achieve even higher accuracy in applications where the ac loss is relatively small due to its coincidence property. The greatly improved accuracy makes the multiscale model a reliable substitute for the H-formulation model. In addition, the idea of iteration and back substitution in background field correction widely expands the application scope of the multiscale model. Alternative background field estimation methods allow the multiscale model to be applied flexibly according to the requirement of the calculation speed and accuracy. The feature of small degrees of freedom resolves the high computation complexity of the ac loss calculation model and reduces the memory requirement. All these merits make the multiscale model competitive in the calculation of ac loss. [ABSTRACT FROM AUTHOR]

Abstract A new materials-genome-based multiscale modeling method is proposed to predict the thermal conductivity of SiC/SiC composites subjected to neutron irradiation. The modeling method bridges different scales from the atomic scale to the macro scale of a 2D SiC/SiC composite. The irradiation-induced point defects in the interphase of SiC/SiC composites are first studied using molecular dynamics simulations to compute the degradation of thermal conductivity as a function of irradiation dose and temperature. The thermal conductivities of SiC fibers, matrices and interphase are then used as input for the new materials genome model to compute the thermal conductivities of 2D SiC/SiC composites subject to neutron irradiation. The predicted thermal conductivities for both unirradiated and irradiated SiC/SiC composites are found to decrease with an increase of temperature while the irradiation effect on interphase needs to be considered for irradiated SiC/SiC composites. [ABSTRACT FROM AUTHOR]

Being the central metabolic organ of vertebrates, the liver possesses the largest repertoire of metabolic enzymes among all tissues and organs. Almost all metabolic pathways are resident in the parenchymal cell, hepatocyte, but the pathway capacities may largely differ depending on the localization of hepatocytes within the liver acinus-a phenomenon that is commonly referred to as metabolic zonation. Metabolic zonation is rather dynamic since gene expression patterns of metabolic enzymes may change in response to nutrition, drugs, hormones and pathological states of the liver (e.g., fibrosis and inflammation). This fact has to be ultimately taken into account in mathematical models aiming at the prediction of metabolic liver functions in different physiological and pathological settings. Here we present a spatially resolved kinetic tissue model of hepatic glucose metabolism which includes zone-specific temporal changes of enzyme abundances which are driven by concentration gradients of nutrients, hormones and oxygen along the hepatic sinusoids. As key modulators of enzyme expression we included oxygen, glucose and the hormones insulin and glucagon which also control enzyme activities by cAMP-dependent reversible phosphorylation. Starting with an initially non-zonated model using plasma profiles under fed, fasted and diabetic conditions, zonal patterns of glycolytic and gluconeogenetic enzymes as well as glucose uptake and release rates are created as an emergent property. We show that mechanisms controlling the adaptation of enzyme abundances to varying external conditions necessarily lead to the zonation of hepatic carbohydrate metabolism. To the best of our knowledge, this is the first kinetic tissue model which takes into account in a semi-mechanistic way all relevant levels of enzyme regulation. [ABSTRACT FROM AUTHOR]

Highlights • A new coupled multiscale genome and XFEM modeling method is proposed to predict crack formation. • The new method is much more computationally efficient in predicting crack formation in heterogeneous materials. • The modeling is applied to SiC ceramics under various loading conditions. • The validity of the new model is demonstrated with comparison with experiments. Abstract Because of the complex heterogeneous microstructure of ceramics, predicting crack formation within ceramics is still a challenge. The extended finite element method (XFEM) serves as a good tool for fracture prediction but is incapable of considering heterogeneous microstructure. In this paper, a numerical framework is developed to model cracks within ceramics by coupling a multiscale genome model with XFEM. XFEM is embedded in the formulation of the multiscale genome through the variational asymptotic method for unit cell homogenization (VAMUCH). The implementation of both multiscale genome model and XFEM retains the capabilities of XFEM in modeling fracture while providing accurate predictions by considering heterogeneous microstructure. The crack formation within SiC ceramics under different loading conditions is simulated in comparison with experiments in order to assess the validity of the proposed method. It is shown that the developed model captures the typical characteristics of crack formation within silicon carbide (SiC) ceramics under bending and indentation loadings. The predicted cutting forces and crack depth exhibit a good agreement with the experimental results during machining processes. [ABSTRACT FROM AUTHOR]

Highlights • Develop an integrated fractional PDE (FPDE) and molecular dynamics (MD) modeling of anomalous diffusive transport in nano-scale porous media. • Use MD simulation to generate diffusivity coefficient at nano scale. • Develop fast solution methods to solve the FPDE model on a micro-scale domain, which has significantly reduced CPU time and memory requirement than the MD simulation. • Recover effective diffusivity coefficient at the micron-scale. • Numerical experiments show that the FPDE-and-MD model has a significantly improved computational efficiency and modeling capability, which can model a micro-scale anomalous diffusive transport on a laptop in a matter of hours. This would require MD simulation the CPU time on the orders of at least years on a parallel computer. Abstract Fluid flows confined in nano-pore structures exhibit physical behaviors that are not observed in large-scale structures. Molecular dynamics simulation has been used for modeling nano-scale fluid flows at nanoscale, but is deemed to be computationally very expensive and is often limited to problems with simple geometry. We develop an integrated fractional partial differential equation and molecular dynamics upscaling modeling of anomalously diffusive transport in heterogeneous nano-pore structures, which has a significantly improved computational efficiency and memory requirement over the molecular dynamics simulation. Representative applications demonstrate the usage of the new model, which takes the model a few hours on a laptop that would otherwise require a molecular dynamics simulation in the matter of at least 100 years of CPU time on a parallel computer. [ABSTRACT FROM AUTHOR]

Highlights • A multiscale model of the cardiovascular system was built based on a human myocyte model. • The effects of halothane, an anesthetic that at high doses elicits acute cardiac dysfunction, were simulated in the myocyte and analyzed at the myocyte, ventricular and circulatory levels. • The multiscale model effectively reproduced contractile and hemodynamic dysfunction in sheep induced by an overdose of halothane. Abstract Cardiac contractile dysfunction (CD) is a multifactorial syndrome caused by different acute or progressive diseases which hamper assessing the role of the underlying mechanisms characterizing a defined pathological condition. Mathematical modeling can help to understand the processes involved in CD and analyze their relative impact in the overall response. The aim of this study was thus to use a myocyte-based multiscale model of the circulatory system to simulate the effects of halothane, a volatile anesthetic which at high doses elicits significant acute CD both in isolated myocytes and intact animals. Ventricular chambers built using a human myocyte model were incorporated into a whole circulatory system represented by resistances and capacitances. Halothane-induced decreased sarco(endo)plasmic reticulum Ca2+ (SERCA2a) reuptake pump, transient outward K+ (I to), Na+-Ca2+ exchanger (I NCX) and L-type Ca2+ channel (I CaL) currents, together with ryanodine receptor (RyR2) increased open probability (P o) and reduced myofilament Ca2+ sensitivity, reproduced equivalent decreased action potential duration at 90% repolarization and intracellular Ca2+ concentration at the myocyte level reported in the literature. In the whole circulatory system, model reduction in mean arterial pressure, cardiac output and regional wall thickening fraction was similar to experimental results in open-chest sheep subjected to acute halothane overdose. Effective model performance indicates that the model structure could be used to study other changes in myocyte targets eliciting CD. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Resistance of CTB to dislocation slip was quantitatively evaluated by MD simulations. • Discrete dislocation formulation revealed the dependence of microscopic threshold on material nature and loading condition. • A multiscale model was established to describe FCG for short cracks. Abstract An atomistics-informed multiscale modeling approach was proposed to quantify the transgranular short crack growth during fatigue in polycrystalline metals. The approach solved the two scale inconsistency problems of the classical N-R model, replacing the arbitrary materials strength parameter by the atomistically determined ideal shear strength in the evaluation of both the fatigue crack growth (FCG) rate and the corresponding range of short-crack-featured fluctuations, and incorporating atomistically simulated Peierls stress into the discrete dislocation formulation to quantify the microscopic threshold of FCG through explicitly modeling the interactions between dislocations and grain boundaries. The model-predicted FCG results were compared with the experimental FCG data of GH4169 Ni-based superalloy, demonstrating improved predictive capability than the classical N-R model. Our study provides new physical insights and improved predictability towards accurate quantification of the short crack growth in polycrystalline metals. [ABSTRACT FROM AUTHOR]

We propose and analyze a multiscale model for acid-mediated tumor invasion accounting for stochastic effects on the subcellular level. The setting involves a PDE of reaction-diffusion-taxis type describing the evolution of the tumor cell density, the movement being directed towards pH gradients in the local microenvironment, which is coupled to a PDE-SDE system characterizing the dynamics of extracellular and intracellular proton concentrations, respectively. The global well-posedness of the model is shown and numerical simulations are performed in order to illustrate the solution behavior. [ABSTRACT FROM AUTHOR]

The set pressure in pressure relief valves (PRVs) varying with the type of sealed medium has been a puzzling problem in the field of chemical machinery and equipment for many years. Here we propose a novel viewpoint to interpret this phenomenon, by which the set pressure difference is ascribed to the additional adsorption pressure of sealed medium adsorbed in the intrinsic nanoscale apertures of PRVs. To demonstrate, two individual types of medium gases (i.e., saturated steam and air) sealed in different PRVs are investigated, and upon a multiscale model of the apertures in PRVs, the additional adsorption pressures are evaluated by using classical density functional theory (DFT). Our calculation shows that the adsorption force of steam is always higher than that of air, resulting in a lower set pressure disregarding the use of different PRVs. The theoretical results are compared with the experimental measurements, displaying qualitatively good agreement, which supports our surmise. Finally, possible solution to reduce the set pressure difference is discussed. This work cast helpful insights for the design and application of PRVs. [ABSTRACT FROM AUTHOR]

Tumour recurrence post chemotherapy is an established clinical problem and many cancer types are often observed to be increasingly drug resistant subsequent to chemotherapy treatments. Drug resistance in cancer is a multipart phenomenon which can be derived from several origins and in many cases it has been observed that cancer cells have the ability to possess, acquire and communicate drug resistant traits. Here, an in silico framework is developed in order to study drug resistance and drug response in cancer cell populations exhibiting various drug resistant features. The framework is based on an on-lattice hybrid multiscale mathematical model and is equipped to simulate multiple mechanisms on different scales that contribute towards chemotherapeutic drug resistance in cancer. This study demonstrates how drug resistant tumour features may depend on the interplay amongst intracellular, extracelluar and intercellular factors. On a cellular level, drug resistant cell phenotypes are here derived from inheritance or mutations that are spontaneous, drug-induced or communicated via exosomes. Furthermore intratumoural heterogeneity and spatio-temporal drug dynamics heavily influences drug delivery and the development of drug resistant cancer cell subpopulations. Chemotherapy treatment strategies are here optimised for various in silico tumour scenarios and treatment objectives. We demonstrate that optimal chemotherapy treatment strategies drastically depend on which drug resistant mechanisms are activated, and that furthermore suboptimal chemotherapy administration may promote drug resistance. [ABSTRACT FROM AUTHOR]

Highlights • Development of a force-based formulations for curved beam finite elements. • Multiscale model for the analysis of masonry arches. • Adoption of a damage-plastic constitutive behavior for the mortar response. • Nonlinear hinge detection exploiting the numerical integration scheme along the arch axis. • Numerical applications on masonry arches subjected to in-plane bending until failure. Abstract This paper presents a Timoshenko beam finite element for nonlinear analysis of planar masonry arches. Considering small displacement and strain assumption, the element governing equations are defined according to a force-based formulation that adopts three different parametrizations of the axis planar curve, permitting the exact description of the element geometry for arbitrarily curved arches. Specific quadrature techniques are illustrated to perform numerical integration over the curved axis. A two-scale arch-to-beam homogenization procedure reproduces the nonlinear response of periodic masonry materials, where an equivalent Timoshenko straight beam describes the behavior of the reference Unit Cell made of a single linear elastic brick and a nonlinear mortar layer. Formation of the hinges characterizing the collapse mechanism of the arch is detected taking advantage of the quadrature rule along the axis and a fracture energy based regularization technique is employed to avoid damage localization. The proposed curved beam model is implemented in a standard FE analysis code and is used to perform several numerical applications. After validating the proposed formulation through benchmarking tests under linear elastic material response, the numerical simulation of six experimental tests is shown, concerning masonry arches characterized by different shapes and undergoing in-plane bending. The numerical results are validated through experimental outcomes and other FE models. [ABSTRACT FROM AUTHOR]

More precise modeling on ductile fracture of metals at the scale from micron to meter is still urgently needed in many engineering applications. Due to the variety of metal and its alloys, a lack of understanding on the mechanisms and quantitative experimental data impede building and assessing mechanics models for ductile fracture at different length scales. In this paper, in situ tensile tests are carried out in Transmission Electronic Microscope (TEM) on copper, high entropy alloy and aluminium alloy. We examine the full process of void growth and coalescence of neighboring voids under the view of the TEM. Nanotwins on the ligament between neighboring voids lead to a new coalescence mechanism for copper and high entropy alloy. Necking and shearing coalescence of aluminium alloys are clearly illustrated, which are demonstrated by the samples with manually drilled hole before by SEM (Scanning Electronic Microscope). The quantitative data on the evolution of void geometry are recorded, and are then used to verify the existing coalescence models in the literature. It is found that the McClintock model for void coalescence provides a better prediction than the Brown-Embury model (including the modified Brown-Embury model). A multiscale homogenization framework for in situ experiments can be further used to extract the stress state around the voids, and explaining the importance of stress-state on cavitation/nucleation, growth and coalescence of voids. [ABSTRACT FROM AUTHOR]

A multiscale model is presented for predicting the magnitude and rate of powder blending in a rotating drum blender. The model combines particle diffusion coefficient correlations from the literature with advective flow field information from blender finite element method simulations. The multiscale model predictions for overall mixing and local concentration variance closely match results from discrete element method (DEM) simulations for a rotating drum, but take only hours to compute as opposed to taking days of computation time for the DEM simulations. Parametric studies were performed using the multiscale model to investigate the influence of various parameters on mixing behavior. The multiscale model is expected to be more amenable to predicting mixing in complex geometries and scale more efficiently to industrial‐scale blenders than DEM simulations or analytical solutions. © 2018 American Institute of Chemical Engineers AIChE J, 64: 3277–3292, 2018 [ABSTRACT FROM AUTHOR]

In a fuel cell vehicle, a direct current boost converter (DCC) is required to link a polymer electrolyte membrane fuel cell system (FCS) and lithium battery packages. The DCC is installed to regulate the output power of the FCS, and can be controlled in different ways, via current, voltage, or power modes. Interactions between a DCC and FCS have attracted growing interests in recent years, because they affect dynamic and stable performances of the entire system. This paper outlines a simulation study on interactions between high-frequency switching operations of a DCC and internal states of an FCS based on a multiscale model. Results are as follows. (1) High-frequency switching operations have a major influence on the cathode overpotential, voltage ohmic loss and water transport through the membrane, whereas the influence on the partial pressures of gas species inside the stack is slight. (2) The FCS is more stable in the case of membrane dehydration than in that of water flooding. DCC's control mode has a greater influence on the FCS when water flooding occurs than membrane dehydration. The power control mode is the most unstable of the three, whereas the current control mode is the most stable. [ABSTRACT FROM AUTHOR]

Starting from a two-scale description involving receptor binding dynamics and a kinetic transport equation for the evolution of the cell density function under velocity reorientations, we deduce macroscopic models for glioma invasion featuring partial differential equations for the mass density and momentum of a population of glioma cells migrating through the anisotropic brain tissue. The proposed first and higher-order moment closure methods enable numerical simulations of the kinetic equation. Their performance is then compared to that of the diffusion limit. The approach allows for diffusion tensor imaging (DTI)-based, patient-specific predictions of the tumor extent and its dynamic behavior. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a multiscale finite element framework is developed based on the first‐order homogenization method for fully coupled saturated porous media using an extension of the Hill‐Mandel theory in the presence of microdynamic effects. The multiscale method is employed for the consolidation problem of a 2‐dimensional saturated soil medium generated from the periodic arrangement of circular particles embedded in a square matrix, which is compared with the direct numerical simulation method. The effects of various issues, including the boundary conditions, size effects, particle arrangements, and the integral domain constraints for the microscale boundary value problem, are numerically investigated to illustrate the performance of a representative volume element in the proposed computational homogenization method of fully coupled saturated porous media. This study is aimed to clarify the effect of scale separation and size dependence, and to introduce characteristics of a proper representative volume element in multiscale modeling of saturated porous media. [ABSTRACT FROM AUTHOR]

Direct-acting antivirals (DAAs) treat hepatitis C virus (HCV) by targeting its intracellular viral replication. DAAs are effective and deliver high clinical performance against HCV infection, but optimization of the DAA treatment regimen is ongoing. Different classes of DAAs are currently under development, and HCV treatments that combine two or three DAAs with different action mechanisms are being improved. To accurately quantify the antiviral effect of these DAA treatments and optimize multi-drug combinations, we must describe the intracellular viral replication processes corresponding to the action mechanisms by multiscale mathematical models. Previous multiscale models of HCV treatment have been formulated by partial differential equations (PDEs). However, estimating the parameters from clinical datasets requires comprehensive numerical PDE computations that are time consuming and often converge poorly. Here, we propose a user-friendly approach that transforms a standard PDE multiscale model of HCV infection (Guedj J et al., Proc. Natl. Acad. Sci. USA 2013; 110(10):3991–6) to mathematically identical ordinary differential equations (ODEs) without any assumptions. We also confirm consistency between the numerical solutions of our transformed ODE model and the original PDE model. This relationship between a detailed structured model and a simple model is called ``model aggregation problem'' and a fundamental important in theoretical biology. In particular, as the parameters of ODEs can be estimated by already established methods, our transformed ODE model and its modified version avoid the time-consuming computations and are broadly available for further data analysis. [ABSTRACT FROM AUTHOR]

This study presents a two-scale model to describe the out-of-plane masonry response. One-dimensional (1D) structural elements, like masonry columns or strips of long wall characterized by the periodic repetition of bricks and mortar arranged in stack bond, are considered. A damage-friction plasticity law is adopted to model the mortar joint constitutive response, while the bricks are assumed as linear elastic. A 1D beam formulation is introduced at both the structural and micromechanical scale, linking the two levels by means of a kinematic map. This expresses the microscopic beam strains in the masonry unit cell (UC) as function of the macroscopic generalized strains. The kinematic field in the UC is completed by adding an unknown periodic fluctuation term. A nonlinear homogenization procedure is developed, proposing a semi-analytical solution for the micromechanical problem, based on the fiber discretization of the mortar joints. A force-based beam-column finite element procedure is adopted at the structural scale and the solution algorithm for the element state determination is illustrated in details. Some numerical applications, showing the UC constitutive response and the behavior of masonry structural elements, are finally presented. [ABSTRACT FROM AUTHOR]

Drug-induced nephrotoxicity is a major cause of acute kidney injury, and thus detecting the potential for nephrotoxicity early in the drug development process is critical. Various urinary biomarkers exhibit different patterns following druginduced injury, which may provide greater information than traditional biomarkers like serum creatinine. In this study, we developed a multiscale quantitative systems pharmacology model relating drug exposure to proximal tubule (PT) epithelial cell injury and subsequently to expression of multiple urinary biomarkers and organ-level functional changes.We utilized urinary kidney injury molecule-1 (Kim-1), alpha glutathione S-transferase, albumin (αGST), glucose, and urine volume time profiles as well as serum creatinine and histopathology data obtained from rats treated with the nephrotoxicant cisplatin to develop the model. Although the model was developed using single-dose response to cisplatin, the model predicted the serum creatinine response to multidose cisplatin regimens. Further, using only the urinary Kim-1 response to gentamicin (a nephrotoxicant with a distinctly different injury time course than cisplatin), the model detected and predicted mild to moderate PT injury, as confirmed with histopathology, even when serum creatinine was unchanged. Thus, the model is generalizable, and can be used to deconvolute the underlying degree and time course of drug-induced PT injury and renal dysfunction from a small number of urinary biomarkers, and may provide a tool to determine optimal dosing regimens that minimize renal injury. [ABSTRACT FROM AUTHOR]

Fundamental understanding of interfacial phenomena in asperity interactions at the nanoscale is prompted by advances in tribology. In this work, we established a multiscale model of asperity–asperity sliding interaction to study the effects of both crystalline anisotropy and crystallographic orientation matching degree on the tribological behavior. Asperity pairs in cases of both mismatched and matched crystallographic orientations were considered. The results revealed that the crystallographic orientation and its matching degree had a tremendous influence on tribological characteristics. The combination effects of internal defect generation and interfacial adhesion anisotropies were found to be responsible for the anisotropic tribological properties. Wear mechanism for the matched case behaved as adhesion wear, whereas wear mechanism for the mismatched case was identified as abrasive wear. [ABSTRACT FROM AUTHOR]

Soil freezing is often used to provide temporary support of soft soils in geotechnical interventions. During the freezing process, the strength properties of the soil–water–ice mixture change from the original properties of the water-saturated soil to the properties of fully frozen soils. In the paper, a multiscale homogenization model for the upscaling of the macroscopic strength of freezing soil based upon information on three individual material phases—the solid particle phase (S), the crystal ice phase (C) and the liquid water phase (L)—is proposed. The homogenization procedure for the partially frozen soil–water–ice composite is based upon an extension of the linear comparison composite (LCC) method for a two-phase matrix–inclusion composite, using a two-step homogenization procedure. In each step, the LCC methodology is implemented by estimating the strength criterion of a two-phase nonlinear matrix–inclusion composite in terms of an optimally chosen linear elastic comparison composite with a similar underlying microstructure. The solid particle phase (S) and the crystal ice phase (C) are assumed to be characterized by two different Drucker–Prager strength criteria, and the liquid water phase (L) is assumed to have zero strength capacity under drained conditions. For the validation of the proposed upscaling strategy, the predicted strength properties for fully and partially frozen fine sands are compared with experimental results, focussing on the investigation of the influence of the porosity and the degree of ice saturation on the predicted failure envelope. [ABSTRACT FROM AUTHOR]

In the present research, a combined molecular structural/micromechanics multiscale model was developed to predict the viscoelastic properties of carbon nanotube (CNT) reinforced polymer composites. At the nanoscale, transversely isotropic time-dependent properties of an embedded CNT in the matrix were obtained using a finite element (FE) based molecular structural model in which the beam, solid continuum and nonlinear spring elements were used for carbon bonds, surrounding matrix and van der Waals interactions, respectively. To homogenize the heterogeneous nature of nanocomposites at microscale, Mori-Tanaka method was applied and the corresponding overall viscoelastic properties were obtained. To this end, nano-structural equivalent structures (equivalent fiber (EF) and equivalent inclusion (EI)) were developed to consider the nano-structural interactions. To apply micromechanics formulations, using the Fourier transform viscoelastic properties were transformed to frequency domain in algebraic forms. Additionally, an iterative-based solution for the Mori-Tanaka method was introduced and performed to use the time-dependent properties in the micromechanics model. The overall time dependent, storage and loss moduli of nanocomposites obtained by different methods were presented. A comparison of the creep response of the two models with available experimental data reveals that the EI model can predict more realistic properties compared to those obtained by the EF model. [ABSTRACT FROM AUTHOR]

The facet capsular ligaments encapsulate the bilateral spinal facet joints and are common sources of painful injury due to afferent innervation. These ligaments exhibit architectural complexity, which is suspected to contribute to the experimentally observed lack of co-localization between macroscopic strain and microstructural tissue damage. The heterogeneous and multiscale nature of this ligament, combined with challenges in experimentally measuring its microscale mechanics, hinders the ability to understand sensory mechanisms under normal or injurious loading. Therefore, image-based, subject-specific, multiscale finite-element models were constructed to predict the mechanical responses of the human cervical facet capsular ligament under uniaxial tensile stretch. The models precisely simulated the force–displacement responses for all samples (R2=0.99±0.01) and showed promise in predicting the magnitude and location of peak regional strains at two different displacements. Yet, there was a loss of agreement between the model and experiment in terms of fiber organization at large tissue stretch, possibly due to a lack of accounting for tissue failure. The mean fiber stretch ratio predicted by the models was found to be significantly higher in regions that exhibited anomalous fiber realignment experimentally than in regions with normal realignment (p<0.002). The development of microstructural abnormalities was associated with the predicted fiber-level stretch (p<0.009), but not with the elemental maximum principal stress or maximum principal strain by logistic regression. The multiscale models elucidate a potential mechanical basis for predicting injury-prone tissue domains and for defining the relationships between macroscopic ligament stretch and microscale pathophysiology in the subfailure regime. [ABSTRACT FROM AUTHOR]