Interactive Computer Model Research Articles

In vitro and in silico multidimensional modeling of oncolytic tumor virotherapy dynamics.

Tumor therapy with replication competent viruses is an exciting approach to cancer eradication where viruses are engineered to specifically infect, replicate, spread and kill tumor cells. The outcome of tumor virotherapy is complex due to the variable interactions between the cancer cell and virus populations as well as the immune response. Oncolytic viruses are highly efficient in killing tumor cells in vitro, especially in a 2D monolayer of tumor cells, their efficiency is significantly lower in a 3D environment, both in vitro and in vivo. This indicates that the spatial dimension may have a major influence on the dynamics of virus spread. We study the dynamic behavior of a spatially explicit computational model of tumor and virus interactions using a combination of in vitro 2D and 3D experimental studies to inform the models. We determine the number of nearest neighbor tumor cells in 2D (median = 6) and 3D tumor spheroids (median = 16) and how this influences virus spread and the outcome of therapy. The parameter range leading to tumor eradication is small and even harder to achieve in 3D. The lower efficiency in 3D exists despite the presence of many more adjacent cells in the 3D environment that results in a shorter time to reach equilibrium. The mean field mathematical models generally used to describe tumor virotherapy appear to provide an overoptimistic view of the outcomes of therapy. Three dimensional space provides a significant barrier to efficient and complete virus spread within tumors and needs to be explicitly taken into account for virus optimization to achieve the desired outcome of therapy.

Reaction systems with influence on environment

Reaction systems, motivated by the functioning of the living cell, became a novel model of interactive computation. In this paper, we pursue this line of research. More specifically, we present a systematic investigation of possible interactions of a reaction system with its environment (context). While in the original definition this interaction is one-way, i.e., the behavior of a reaction system is influenced by its environment, we investigate now also the influence of the system on its environment, where a possible time delay of this influence is also considered. To understand the behavior of reaction systems when such a two-way interaction takes place, we establish its relationship to their context-independent behavior (i.e., the behavior which is not influenced by the environment).

Multi-Scale Computational Modeling of Tubulin-Tubulin Interactions in Microtubule Self-Assembly from Atoms to Cells

Multi-Scale Computational Modeling of Tubulin-Tubulin Interactions in Microtubule Self-Assembly from Atoms to Cells

Appearance-Based Gaze Estimator for Natural Interaction Control of Surgical Robots

Robots are playing an increasingly important role in modern surgery. However, conventional human–computer interaction methods, such as joystick control and sound control, have some shortcomings, and medical personnel are required to specifically practice operating the robot. We propose a human–computer interaction model based on eye movement with which medical staff can conveniently use their eye movements to control the robot. Our algorithm requires only an RGB camera to perform tasks without requiring expensive eye-tracking devices. Two kinds of eye control modes are designed in this paper. The first type is the pick and place movement, with which the user uses eye gaze to specify the point where the robotic arm is required to move. The second type is user command movement, with which the user can use eye gaze to select the direction in which the user desires the robot to move. The experimental results demonstrate the feasibility and convenience of these two modes of movement.

Effect of perturbation amplitudes on water film stiffness coefficients of water-lubricated plain journal bearings based on CFD–FSI methods

A numerical three-dimensional computational fluid dynamics-fluid structure interaction (CFD-FSI) model including lining deformation and cavitation is developed to evaluate the effect of perturbatio...

Fluid–structure interactions modeling the venous valve

In this study, a fully coupled fluid–structure interaction computational model for a pulsatile flow in the venous valve was developed. An arbitrary Lagrangian–Eulerian formulation is used in the coupled model, considering two domains, specifically the blood flow and the valve leaflets. The effect of the gap width between the valve leaflets (venous valve incompetence) on the valve reverse flow (reflux) has been investigated.

Mesoscale Computational Modeling of Protein-Membrane Interactions Based on Continuum Mean-Field Theory.

Quantitative computational modeling of protein-membrane interactions is of great importance as it aids in the interpretation of experimental results and enables design and exploration of new experimental systems. This review describes one such computational approach conceived specifically to treat electrostatically driven interactions between a lipid membrane and a protein (or protein domains) adsorbing onto the membrane. The methodology is based on self-consistent minimization of the governing free energy functional which is expressed in the mean-field approximation and has contributions from electrostatic interactions as well as from mixing entropy of lipids in the membrane and ions in the solution. The method enables calculation of the free energy of the binding process and quantification of the steady-state lipid distribution around the adsorbing protein. The extension of the method to include membrane deformation degrees of freedom further allows calculation of the equilibrium bilayer shape upon the protein binding.

Construction of computer model in tissue morphometry

Background. In a microscopic study of animal and human tissues, researchers are faced with the problem of their objective assessment. Descriptive microscopy is subjective and does not allow to make exact conclusions. A partial counting of some selective elements of tissue is often not sufficiently informative. Use of high-grade morphometry is a very laborious procedure, which is difficult to conduct, repeat and recheck. Descriptive microscopy does not allow to make a model of research for a comprehensive assessment of the results, which complicates making conclusions.
 Aim. To solve the problem of objective assessment of tissue condition in histomorphological studies and accelerate their implementation with the help of computer modeling.
 Materials and Methods. The whole process from making micropreparations to the end of their full analysis was divided into 4 stages: photographing the entire area of micropreparations using a video eyepiece microscope, counting histomorphological elements in the photos, construction of a computer model, analysis of the obtained data.
 Results. An interactive computer model of the experiment was constructed, in which all parameters were combined into a single set, and a change of any value influenced the entire model. It was possible to visualize the obtained results, calculate new parameters, find out the relationship between them and to use additional tools, as, for example, machine training for finding non-obvious relationships between components or for speeding up further calculations.
 Conclusions. The advantages of computer modeling consist in that it significantly accelerates histomorphological examinations, improves the quality of their processing, makes the procedure more transparent and provides scientists with more opportunities for in-depth analysis. An important advantage is that this technique is suitable for any histomorphological studies.

Construction of computer model in tissue morphometry

Background. In a microscopic study of animal and human tissues, researchers are faced with the problem of their objective assessment. Descriptive microscopy is subjective and does not allow to make exact conclusions. A partial counting of some selective elements of tissue is often not sufficiently informative. Use of high-grade morphometry is a very laborious procedure, which is difficult to conduct, repeat and recheck. Descriptive microscopy does not allow to make a model of research for a comprehensive assessment of the results, which complicates making conclusions.
 Aim. To solve the problem of objective assessment of tissue condition in histomorphological studies and accelerate their implementation with the help of computer modeling.
 Materials and Methods. The whole process from making micropreparations to the end of their full analysis was divided into 4 stages: photographing the entire area of micropreparations using a video eyepiece microscope, counting histomorphological elements in the photos, construction of a computer model, analysis of the obtained data.
 Results. An interactive computer model of the experiment was constructed, in which all parameters were combined into a single set, and a change of any value influenced the entire model. It was possible to visualize the obtained results, calculate new parameters, find out the relationship between them and to use additional tools, as, for example, machine training for finding non-obvious relationships between components or for speeding up further calculations.
 Conclusions. The advantages of computer modeling consist in that it significantly accelerates histomorphological examinations, improves the quality of their processing, makes the procedure more transparent and provides scientists with more opportunities for in-depth analysis. An important advantage is that this technique is suitable for any histomorphological studies.

Effect of Longitudinal Variation of Vocal Fold Inner Layer Thickness on Fluid-Structure Interaction During Voice Production.

A three-dimensional fluid-structure interaction computational model was used to investigate the effect of the longitudinal variation of vocal fold inner layer thickness on voice production. The computational model coupled a finite element method based continuum vocal fold model and a Navier-Stokes equation based incompressible flow model. Four vocal fold models, one with constant layer thickness and the others with different degrees of layer thickness variation in the longitudinal direction, were studied. It was found that the varied thickness resulted in up to 24% stiffness reduction at the middle and up to 47% stiffness increase near the anterior and posterior ends of the vocal fold; however, the average stiffness was not affected. The fluid-structure interaction simulations on the four models showed that the thickness variation did not affect vibration amplitude, glottal flow rate, and the waveform related parameters. However, it increased glottal angles at the middle of the vocal fold, suggesting that vocal fold vibration amplitude was determined by the average stiffness of the vocal fold, while the glottal angle was determined by the local stiffness. The models with longitudinal variation of layer thickness consumed less energy during the vibrations compared with the constant layer thickness one.

Development and Evaluation of a Computational Human Performance Model of In-vehicle Manual and Speech Interactions

Usability evaluation traditionally relies on costly and time-consuming human-subject experiments, which typically involve developing physical prototypes, designing usability experiment, and recruiting human subjects. To minimize the limitations of human-subject experiments, computational human performance models can be used as an alternative. Human performance models generate digital simulations of human performance and examine the underlying psychological and physiological mechanisms to help understand and predict human performance. A variety of in-vehicle information systems (IVISs) using advanced automotive technologies have been developed to improve driver interactions with the in-vehicle systems. Numerous studies have used human subjects to evaluate in-vehicle human-system interactions; however, there are few modeling studies to estimate and simulate human performance, especially in in-vehicle manual and speech interactions. This paper presents a computational human performance modeling study for a usability test of IVISs using manual and speech interactions. Specifically, the model was aimed to generate digital simulations of human performance for a driver seat adjustment task to decrease the comfort level of a part of driver seat (i.e., the lower lumbar), using three different IVIS controls: direct-manual, indirect-manual, and voice controls. The direct-manual control is an input method to press buttons on the touchscreen display located on the center stack in the vehicle. The indirect-manual control is to press physical buttons mounted on the steering wheel to control a small display in the dashboard-cluster, which requires confirming visual feedback on the cluster display located on the dashboard. The voice control is to say a voice command, “ deflate lower lumbar” through an in-vehicle speaker. The model was developed to estimate task completion time and workload for the driver seat adjustment task, using the Queueing Network cognitive architecture (Liu, Feyen, & Tsimhoni, 2006). Processing times in the model were recorded every 50 msec and used as the estimates of task completion time. The estimated workload was measured by percentage utilization of servers used in the architecture. After the model was developed, the model was evaluated using an empirical data set of thirty-five human subjects from Chen, Tonshal, Rankin, & Feng (2016), in which the task completion times for the driver seat adjustment task using commercial in-vehicle systems (i.e., SYNC with MyFord Touch) were recorded. Driver workload was measured by NASA’s task load index (TLX). The average of the values from the NASA-TLX’s six categories was used to compare to the model’s estimated workload. The model produced results similar to actual human performance (i.e., task completion time, workload). The real-world engineering example presented in this study contributes to the literature of computational human performance modeling research.

Computational modeling of synergistic interaction between αVβ3 integrin and VEGFR2 in endothelial cells: Implications for the mechanism of action of angiogenesis-modulating integrin-binding peptides

Cooperation between VEGFR2 and integrin αVβ3 is critical for neovascularization in wound healing, cardiovascular ischemic diseases, ocular diseases, and tumor angiogenesis. In the present study, we developed a rule-based computational model to investigate the potential mechanism by which the Src-induced integrin association with VEGFR2 enhances VEGFR2 activation. Simulations demonstrated that the main function of integrin is to reduce the degradation of VEGFR2 and hence stabilize the activation signal. In addition, receptor synthesis rate and recruitment from internal compartment were found to be sensitive determinants of the activation state of VEGFR2. The model was then applied to simulate the effect of integrin-binding peptides such as tumstatin and cilengitide on VEGFR2 signaling. Further, computational modeling proposed potential molecular mechanisms for the angiogenesis-modulating activity of other integrin-binding peptides. The model highlights the complexity of the crosstalk between αVβ3 integrin and VEGFR2 and the necessity of utilizing models to elucidate potential mechanisms in angiogenesis-modulating peptide therapy.

Computer modeling of interaction of lysine dendrimer with epithalon peptides

Subject of Study.Dendrimers are hyperbranched polymeric molecules that regularly branch from a single center. Dendrimers are used in biomedical applications to deliver drugs and genetic material to cells. The present work considers the study of the formation of lysine dendrimer complexes with therapeutic tetrapeptides and the equilibrium properties of the complex. Two systems were studied consisting of one second-generation lysine dendrimer and 16 tetrapeptides. In the first case, the system consisted of a dendrimer and 16 free molecules of Epithalon peptide. In the second case, the system consisted of a dendrimer and 16 chemically bound to its ends Epithalon peptide molecules. Method. The study was carried out by computer simulation by the molecular dynamics method. Main Results. The sizes and internal structure of the complex and conjugate of peptide molecules with dendrimer were compared. It is found that in the case of free Epithalon, peptide molecules are adsorbed not only on the surface but can also penetrate into the dendrimer to form a stable complex with it. In the case of a conjugate, the peptides penetrate less into the dendrimer, but, being mainly on the dendrimer surface, they compress the dendrimer inwards, forming a more compact structure than the structure of complex. Practical Relevance. Such complexes and conjugates can be used in the future to deliver various therapeutic peptides and other drug molecules to target organs

Experimental and computational modeling of interaction of kolaviron-kolaflavanone with aldehyde dehydrogenase

Aldehyde dehydrogenases (ALDHs) are a diverse family of enzymes that catalyze the NAD(P)+-dependent detoxification of toxic aldehyde compounds. ALDHs are also involved in non-enzymatic ligand binding to endobiotics and xenobiotics. Here, the enzyme crucial non-canonical and non-catalytic interaction with kolaflavanone, a component of kolaviron, and a major bioflavonoid isolated from Garcinia kola (Bitter kola) was characterized by various spectroscopic and in silico approaches under simulated physiological condition. Kolaflavanone quenched the intrinsic fluorescence of ALDH in a concentration dependent manner with an effective quenching constant (Ksv) of 1.14 × 103 L.mol−1 at 25 °C. The enzyme has one binding site for kolaflavanone with a binding constant (Ka) of 2.57 × 104 L.mol−1 and effective Forster resonance energy transfer (FRET) of 4.87 nm. The bonding process was enthalpically driven. The reaction was not spontaneous and was predominantly characterized by Van der Waals forces and hydrogen bond. The flavonoid bonding slightly perturbed the secondary and tertiary structures of ALDH that was ‘tryptophan-gated’. The interaction was regulated by both diffusion and ionic strength. Molecular docking showed the binding of kolaflavanone was at the active site of ALDH and the participation of some amino acid residues in the complex formation with −9.6 kcal mol−1 binding energy. The profiles of atomic fluctuations indicated the rigidity of the ligand-binding site during the simulation. With these, ALDH as a subtle nano-particle determinant of kolaviron bioavailability and efficacy is hereby proposed.

Digital Karnak:

Archaeologists, historians, and art historians are increasingly turning to three-dimensional computer modeling to create dynamic visualizations of ancient monuments and urban spaces, but the resulting 3-D content is not always accepted as scholarship and integrated into discipline-specific dialogue. In Digital Karnak: An Experiment in Publication and Peer Review of Interactive, Three-Dimensional Content, Elaine A. Sullivan and Lisa M. Snyder propose a reconceptualization of computer modeling as a new means and form of knowledge production, offer a framework for peer review and publication of 3-D content, and describe an experiment to develop an innovative publication with an interactive computer model at its core. The Digital Karnak model, a geotemporal model of an ancient Egyptian temple, is their case study, a 3-D publication package of which they posted for peer review. This article describes the model's creation, the software interface used for the publication prototype (VSim), and the ways in which this project addresses the challenges of publishing 3-D scholarly content.

STREET NETWORK STRUCTURE AND CRIME RISK: AN AGENT‐BASED INVESTIGATION OF THE ENCOUNTER AND ENCLOSURE HYPOTHESES

AbstractStreet networks shape day‐to‐day activities in complex ways, dictating where, when, and in what contexts potential victims, offenders, and crime preventers interact with one another. Identifying generalizable principles of such influence offers considerable utility to theorists, policy makers, and practitioners. Unfortunately, key difficulties associated with the observation of these interactions, and control of the settings within which they take place, limit traditional empirical approaches that aim to uncover mechanisms linking street network structure with crime risk. By drawing on parallel advances in the formal analyses of street networks and the computational modeling of crime events interactions, we present a theoretically informed and empirically validated agent‐based model of residential burglary that permits investigation of the relationship between street network structure and crime commission and prevention through guardianship. Through the use of this model, we explore the validity of competing theoretical accounts of street network permeability and crime risk—the encounter (eyes on the street) and enclosure (defensible space) hypotheses. The results of our analyses provide support for both hypotheses, but in doing so, they reveal that the relationship between street network permeability and crime is likely nonlinear. We discuss the ramifications of these findings for both criminological theory and crime prevention practice.

Computational modelling of full interaction between crystal plasticity and oxygen diffusion at a crack tip

Oxidation-promoted crack growth, one of the major concerns for nickel-based superalloys, is closely linked to the diffusion of oxygen into the crack tip. The phenomenon is still not well understood yet, especially the full interaction between oxygen diffusion and severe near-tip mechanical deformation. This work aimed at the development of a robust numerical strategy to model the full coupling of crystal plasticity and oxygen diffusion in a single crystal nickel-based superalloy. In order to accomplish this, finite element package ABAQUS is used as a platform to develop a series of user-defined subroutines to model the fully coupled process of deformation and diffusion. The formulation allowed easy incorporation of nonlinear material behaviour, various loading conditions and arbitrary model geometries. Using this method, finite element analyses of oxygen diffusion, coupled with crystal plastic deformation, were carried out to simulate oxygen penetration at a crack tip and associated change of near-tip stress field, which has significance in understanding crack growth acceleration in oxidation environment. Based on fully coupled diffusion-deformation analyses, a case study was carried out to predict crack growth rate in oxidation environment and under dwell-fatigue loading conditions, for which a two-parameter failure criterion, in terms of accumulated inelastic strain and oxygen concentration at the crack tip, has been utilized.

Lateral Interaction between Molecules Adsorbed on the Surfaces of Non-Metals

Spectral manifestations of lateral interactions between molecules adsorbed on non-metallic adsorbents, mostly oxides are considered. Static interaction, repulsive or attractive can be distinguished from the dynamic or resonance dipole–dipole interaction (RDDI) by means of isotopic dilution. Analysis of spectral data on CO adsorbed at low temperatures on ZnO, some other oxides or halogenides as well as recent quantum chemical calculations shows that static effect is enhanced by the solid due to the effect of surface relaxation induced by adsorption. Computer modelling of static and dynamic interactions enable one to explain the structure of the bands of adsorbed CO, frequency shifts, and other details in the spectra. Attractive interactions between different molecules can lead to mutual enhancement of adsorption and to the phenomena of induced Bronsted acidity and basicity, or the superacidity of some oxides exposed to gaseous acids. The theory and new experimental data on the influence of RDDI on the band shape of adsorbed SF6 and CF4 are discussed. Spectral evidence for RDDI and vibrational energy transfer between NF3 and pre-adsorbed SF6 on ZnO is reported.

Agent Based Modeling on Dynamic Spreading Dengue Fever Epidemic

Agent based model (ABM) is a computational model for simulation, behavioral representation and interaction of autonomous agents. The main problem definition related to how to make a dynamic model of dengue fever with consideration of their behavioral and interaction agent. This paper aims to develop interactive behavioral agents and related simulation models for such dynamic spreading dengue fever epidemic. This model construction consists of two agents, namely a human agent as a host and mosquito as a vector, where temperature and humidity are the environmental parameters. These environmental parameters deployed data and information from National Meteorology Climatology and Geophysics agency and supported by recent community health data of Bogor region. The verification stage evaluated model performance of two periods between January to June and between July to December 2015 showed the fitness of the model. During simulation stage where 100 humans agent and 10 mosquitoes agent were observed, indicating the decreasing of mosquito by 26.3% and the number of infected human decrease to 16% from the period of January until June to July until December 2015 respectively. These evaluation results showed that the agent based model results succeeded to follow a similar trend of decreasing pattern as actual data.

Structural Prediction of Protein-Protein Interactions by Docking: Application to Biomedical Problems.

A huge amount of genetic information is available thanks to the recent advances in sequencing technologies and the larger computational capabilities, but the interpretation of such genetic data at phenotypic level remains elusive. One of the reasons is that proteins are not acting alone, but are specifically interacting with other proteins and biomolecules, forming intricate interaction networks that are essential for the majority of cell processes and pathological conditions. Thus, characterizing such interaction networks is an important step in understanding how information flows from gene to phenotype. Indeed, structural characterization of protein-protein interactions at atomic resolution has many applications in biomedicine, from diagnosis and vaccine design, to drug discovery. However, despite the advances of experimental structural determination, the number of interactions for which there is available structural data is still very small. In this context, a complementary approach is computational modeling of protein interactions by docking, which is usually composed of two major phases: (i) sampling of the possible binding modes between the interacting molecules and (ii) scoring for the identification of the correct orientations. In addition, prediction of interface and hot-spot residues is very useful in order to guide and interpret mutagenesis experiments, as well as to understand functional and mechanistic aspects of the interaction. Computational docking is already being applied to specific biomedical problems within the context of personalized medicine, for instance, helping to interpret pathological mutations involved in protein-protein interactions, or providing modeled structural data for drug discovery targeting protein-protein interactions.