Predictive Simulation Generates Human Adaptations during Loaded and Inclined Walking

Predictive simulation is a powerful approach for analyzing human locomotion. Unlike techniques that track experimental data, predictive simulations synthesize gaits by minimizing a high-level objective such as metabolic energy expenditure while satisfying task requirements like achieving a target velocity. The fidelity of predictive gait simulations has only been systematically evaluated for locomotion data on flat ground. In this study, we construct a predictive simulation framework based on energy minimization and use it to generate normal walking, along with walking with a range of carried loads and up a range of inclines. The simulation is muscle-driven and includes controllers based on muscle force and stretch reflexes and contact state of the legs. We demonstrate how human-like locomotor strategies emerge from adapting the model to a range of environmental changes. Our simulation dynamics not only show good agreement with experimental data for normal walking on flat ground (92% of joint angle trajectories and 78% of joint torque trajectories lie within 1 standard deviation of experimental data), but also reproduce many of the salient changes in joint angles, joint moments, muscle coordination, and metabolic energy expenditure observed in experimental studies of loaded and inclined walking.     

Cholesterol surrogates: a comparison of cholesterol and 16:0 ceramide in POPC bilayers

Experimental evidence indicates that, under some circumstances, "surrogate" molecules may play the same role as cholesterol in ordering membrane lipids. The simplest molecule in this class is Ceramide. In this article, we describe atomic-level molecular dynamics simulations designed to shed light on this phenomenon. We run simulations of hydrated phosphoryl-oleoyl phosphatidylcholine (POPC) bilayers containing cholesterol, and containing ceramide, in concentrations ranging from 5% to 33%. We also perform a simulation of a pure POPC bilayer to verify the simulation force fields against experimental structural data for POPC. Our simulation data are in good agreement with experimental data for the partial molecular volumes, areas, form factors, and order parameters. These simulations suggest that ceramide and cholesterol have a very similar effect on the POPC bilayer, although ceramide is less effective in inducing order in the bilayer compared with cholesterol at the same concentrations.     

Simulation of dynamic contrast-enhanced ultrasound sequences using example-based texture generation

Simulation of dynamic contrast-enhanced ultrasound sequences with known perfusion characteristics and speckle characteristics that are consistent with those observed in experimental data would provide a useful tool for the evaluation of new perfusion quantification and image-processing techniques. A framework is proposed to simulate such perfusion data. It is based on the use of an example-based texture generation method. The generated texture of noise is compared to experimental data in terms of its statistical distribution and spatial correlation. Results show that the example-based method generates data that are closer to the experimental data than those obtained using a conventional parametric simulation method (33 to 80% smaller Hellinger squared distance). This fast and simple method allows simulation of dynamic contrast-enhanced ultrasound data for complex perfusion patterns, and should be useful for the validation of registration, segmentation or perfusion quantification methods.     

MRI-based finite element modeling of facial mimics: a case study on the paired zygomaticus major muscles

Finite element simulation of facial mimics provides objective indicators about soft tissue functions for improving diagnosis, treatment and follow-up of facial disorders. There is a lack of in vivo experimental data for model development and validation. In this study, the contribution of the paired Zygomaticus Major (ZM) muscle contraction on the facial mimics was investigated using in vivo experimental data derived from MRI. Maximal relative differences of 7.7% and 37% were noted between MRI-based measurements and numerical outcomes for ZM and skin deformation behaviors respectively. This study opens a new direction to simulate facial mimics with in vivo data.     

Computer simulation of cytoplasmic pH regulation mediated by the F-type H+-ATPase

Cytoplasmic pH regulation mediated by the H(+)-ATPase was examined with the aid of computer simulation. The data obtained with our simulation model were consistent with the experimental data and the simulation clarified the following points that may be difficult to be clarified with experimental studies. (1) The change in the enzyme amount controlled by cytoplasmic pH was essential for the pH regulation. (2) No significant change in internal pH was observed in acidic surroundings even if the proton transport activity of the H(+)-ATPase changed greater than sixfold. (3) The cytoplasmic pH homeostasis can be maintained even when the biosynthetic rate of the enzyme decreased by 50%. These results suggested that this regulatory system has an ability to maintain the pH in homeostasis even under harsh conditions that decrease cellular metabolic activities.     

Development of a novel MATLAB-based framework for implementing mechanical joint stability constraints within OpenSim musculoskeletal models

The Static Optimization (SO) solver in OpenSim estimates muscle activations and forces that only equilibrate applied moments. In this study, SO was enhanced through an open-access MATLAB interface, where calculated muscle activations can additionally satisfy crucial mechanical stability requirements. This Stability-Constrained SO (SCSO) is applicable to many OpenSim models and can potentially produce more biofidelic results than SO alone, especially when antagonistic muscle co-contraction is required to stabilize body joints. This hypothesis was tested using existing models and experimental data in the literature. Muscle activations were calculated by SO and SCSO for a spine model during two series of static trials (i.e. simulation 1 and 2), and also for a lower limb model (supplementary material 2). In simulation 1, symmetric and asymmetric flexion postures were compared, while in simulation 2, various external load heights were compared, where increases in load height did not change the external lumbar flexion moment, but necessitated higher EMG activations. During the tasks in simulation 1, the predicted muscle activations by SCSO demonstrated less average deviation from the EMG data (6.8% −7.5%) compared to those from SO (10.2%). In simulation 2, SO predicts constant muscle activations and forces, while SCSO predicts increases in the average activations of back and abdominal muscles that better match experimental data. Although the SCSO results are sensitive to some parameters (e.g. musculotendon stiffness), when considering the strategy of the central nervous system in distributing muscle forces and in activating antagonistic muscles, the assigned activations by SCSO are more biofidelic than SO.     

Experimental validation of molecular dynamics simulations of lipid bilayers: a new approach

A novel protocol has been developed for comparing the structural properties of lipid bilayers determined by simulation with those determined by diffraction experiments, which makes it possible to test critically the ability of molecular dynamics simulations to reproduce experimental data. This model-independent method consists of analyzing data from molecular dynamics bilayer simulations in the same way as experimental data by determining the structure factors of the system and, via Fourier reconstruction, the overall transbilayer scattering-density profiles. Multi-nanosecond molecular dynamics simulations of a dioleoylphosphatidylcholine bilayer at 66% RH (5.4 waters/lipid) were performed in the constant pressure and temperature ensemble using the united-atom GROMACS and the all-atom CHARMM22/27 force fields with the GROMACS and NAMD software packages, respectively. The quality of the simulated bilayer structures was evaluated by comparing simulation with experimental results for bilayer thickness, area/lipid, individual molecular-component distributions, continuous and discrete structure factors, and overall scattering-density profiles. Neither the GROMACS nor the CHARMM22/27 simulations reproduced experimental data within experimental error. The widths of the simulated terminal methyl distributions showed a particularly strong disagreement with the experimentally observed distributions. A comparison of the older CHARMM22 with the newer CHARMM27 force fields shows that significant progress is being made in the development of atomic force fields for describing lipid bilayer systems empirically.     

Analysis of compressive creep behavior of the vertebral unit subjected to a uniform axial loading using exact parametric solution equations of Kelvin-solid models--Part II. Rhesus monkey intervertebral joints

The simulation of long-term creep response behavior, observed on 54 Rhesus monkey intervertebral joints subjected to a constant axial compressive stress, is attempted by two- and three-parameter-solid models utilizing the Burns- Kaleps 'exact analysis scheme'. Model parameters identified by the analysis of each specimen's experimental strain data were optimized via a computer program and the mechanical properties (Young's moduli and the viscosity coefficient) appropriate to each model were calculated for individual spinal segments. Simulation results for the two-parameter-solid (one- Kelvin -unit) model demonstrate its general ineptness in predicting the observed strain-time behavior of normal spinal sements . The three-parameter-solid model yielded excellent results in the simulation of observed spinal segment compressive creep phenomena. It produced an average error between the model predicted and experimental strain values that ranged from a low of 0.4000% to a high of 3.290% for the 54 Rhesus monkey intervertebral joints, with a collective average error for all specimens of only 1.363%.     

Simulation of alpha-helix and beta-hairpin formation in water-soluble proteins by the code physics method

One of the possible ways for complete and final solution of the problem of determination of three-dimensional structure of proteins on amino acid sequence is simulation of protein three-dimensional structure formation. The use of the code physics method developed by the author has been suggested to fulfill this task. The simulation of alpha-helix and beta-hairpin formation in water-soluble proteins as a start of realization of the plan is described here. The results of the simulation were compared with the experimental data for 14 proteins of no more than 50 amino acids and therefore with little number of alpha-helices and beta-strands (to meet limits of simulation process) and with secondary structure predictions by the best to data methods of protein secondary structure prediction, PSIpred, PORTER and PROFsec. Secondary structure of the proteins, obtained as a result of the simulation of alpha-helix and beta-hairpin formation using the code physics method, corresponded completely to experimental data while the secondary structure predicted by the PSIpred, PORTER and PROFsec methods differed from these data significantly.     

Continuous modeling of metabolic networks with gene regulation in yeast and in vivo determination of rate parameters

A continuous model of a metabolic network including gene regulation to simulate metabolic fluxes during batch cultivation of yeast Saccharomyces cerevisiae was developed. The metabolic network includes reactions of glycolysis, gluconeogenesis, glycerol and ethanol synthesis and consumption, the tricarboxylic acid cycle, and protein synthesis. Carbon sources considered were glucose and then ethanol synthesized during growth on glucose. The metabolic network has 39 fluxes, which represent the action of 50 enzymes and 64 genes and it is coupled with a gene regulation network which defines enzyme synthesis (activities) and incorporates regulation by glucose (enzyme induction and repression), modeled using ordinary differential equations. The model includes enzyme kinetics, equations that follow both mass-action law and transport as well as inducible, repressible, and constitutive enzymes of metabolism. The model was able to simulate a fermentation of S. cerevisiae during the exponential growth phase on glucose and the exponential growth phase on ethanol using only one set of kinetic parameters. All fluxes in the continuous model followed the behavior shown by the metabolic flux analysis (MFA) obtained from experimental results. The differences obtained between the fluxes given by the model and the fluxes determined by the MFA do not exceed 25% in 75% of the cases during exponential growth on glucose, and 20% in 90% of the cases during exponential growth on ethanol. Furthermore, the adjustment of the fermentation profiles of biomass, glucose, and ethanol were 95%, 95%, and 79%, respectively. With these results the simulation was considered successful. A comparison between the simulation of the continuous model and the experimental data of the diauxic yeast fermentation for glucose, biomass, and ethanol, shows an extremely good match using the parameters found. The small discrepancies between the fluxes obtained through MFA and those predicted by the differential equations, as well as the good match between the profiles of glucose, biomass, and ethanol, and our simulation, show that this simple model, that does not rely on complex kinetic expressions, is able to capture the global behavior of the experimental data. Also, the determination of parameters using a straightforward minimization technique using data at only two points in time was sufficient to produce a relatively accurate model. Thus, even with a small amount of experimental data (rates and not concentrations) it was possible to estimate the parameters minimizing a simple objective function. The method proposed allows the obtention of reasonable parameters and concentrations in a system with a much larger number of unknowns than equations. Hence a contribution of this study is to present a convenient way to find in vivo rate parameters to model metabolic and genetic networks under different conditions.     

On extending the usefulness of projectors in teaching biology

This paper reports the design of an interactive computer program in microbial genetics. The computer program is divided into three stages, background information, simulation, and data treatment. The results obtained from the simulation allow four genes to be sequenced along the bacterial chromosome. The simulation mimics experimental errors, the production of exconjugants and backmutants. The data can be analysed using options contained in the program. The simulation is of particular educational value because it allows the student to work at his own pace and to develop his ability to analyse data in relation to a complex conceptual model.     

A physiological systems approach to modeling and resetting of mouse thermoregulation under heat stress

Heat stroke (HS) is a serious civilian and military health issue. Due to the limited amount of experimental data available in humans, this study was conducted on a mouse mathematical model fitted on experimental data collected from mice under HS conditions, with the assumption there is good agreement among mammals. Core temperature (T(c)) recovery responses in a mouse model consist of hypothermia and delayed fever during 24 h of recovery that represent potential biomarkers of HS severity. The objective of this study was to develop a simulation model of mouse T(c) responses and identify optimal treatment windows for HS recovery using a three-dimensional predictive heat transfer simulation model. Several bioenergetic simulation variables, including nonlinear metabolic heat production (W/m3), temperature-dependent convective heat transfer through blood mass perfusion (W/m3), and activity-related changes in circadian T(c) were used for model simulation. The simulation results predicted the experimental data with few disparities. Using this simulation model, we tested a series of ambient temperature treatment strategies to minimize hypothermia and delayed fever to accelerate HS recovery. Using a genetic algorithm, we identified eight time segments (ambient temperature = 27, 30, 31, 29, 28, 28, 27, 26°C) of 110 min total duration that optimized HS recovery in our model simulation.     

Molecular dynamics simulations of charged and neutral lipid bilayers: treatment of electrostatic interactions

Molecular dynamics (MD) simulations complement experimental methods in studies of the structure and dynamics of lipid bilayers. The choice of algorithms employed in this computational method represents a trade-off between the accuracy and real calculation time. The largest portion of the simulation time is devoted to calculation of long-range electrostatic interactions. To speed-up evaluation of these interactions, various approximations have been used. The most common ones are the truncation of long-range interactions with the use of cut-offs, and the particle-mesh Ewald (PME) method. In this study, several multi-nanosecond cut-off and PME simulations were performed to establish the influence of the simulation protocol on the bilayer properties. Two bilayers were used. One consisted of neutral phosphatidylcholine molecules. The other was a mixed lipid bilayer consisting of neutral phosphatidylethanolamine and negatively charged phosphatidylglycerol molecules. The study shows that the cut-off simulation of a bilayer containing charge molecules generates artefacts; in particular the mobility and order of the charged molecules are vastly different from those determined experimentally. In the PME simulation, the bilayer properties are in general agreement with experimental data. The cut-off simulation of bilayers containing only uncharged molecules does not generate artefacts, nevertheless, the PME simulation gives generally better agreement with experimental data.     

Resources, standards and tools for systems biology.

Modelling and simulation techniques are valuable tools for the understanding of complex biological systems. The design of a computer model necessarily has many diverse inputs, such as information on the model topology, reaction kinetics and experimental data, derived either from the literature, databases or direct experimental investigation. In this review, we describe different data resources, standards and modelling and simulation tools that are relevant to integrative systems biology.     

Simulation tools for biochemical networks: evaluation of performance and usability

MOTIVATION: Simulation of dynamic biochemical systems is receiving considerable attention due to increasing availability of experimental data of complex cellular functions. Numerous simulation tools have been developed for numerical simulation of the behavior of a system described in mathematical form. However, there exist only a few evaluation studies of these tools. Knowledge of the properties and capabilities of the simulation tools would help bioscientists in building models based on experimental data. RESULTS: We examine selected simulation tools that are intended for the simulation of biochemical systems. We choose four of them for more detailed study and perform time series simulations using a specific pathway describing the concentration of the active form of protein kinase C. We conclude that the simulation results are convergent between the chosen simulation tools. However, the tools differ in their usability, support for data transfer to other programs and support for automatic parameter estimation. From the experimentalists' point of view, all these are properties that need to be emphasized in the future.     

Experimental and probabilistic analysis of distal femoral periprosthetic fracture: a comparison of locking plate and intramedullary nail fixation. Part B: probabilistic investigation

The following is Part B of a two-part study. Part A evaluated, biomechanically, intramedullary (IM) nails versus locking plates for fixation of an extra-articular, metaphyseal wedge fracture in synthetic osteoporotic bone. Part B of this study introduces deterministic finite element (FE) models of each construct type in synthetic osteoporotic bone and investigates the probability of periprosthetic fracture of the locking plate compared with the retrograde IM nail using Monte Carlo simulation. Deterministic FE models of the fractured femur implanted with IM nail and locking plate, respectively, were developed and validated using experimental data presented in Part A of this study. The models were validated by comparing the load-displacement curve of the experimental data with the load-displacement curve of the FE simulation with a root-mean square error of less than 3?mm. The validated FE models were then modified by defining the cortical and cancellous bone modulus of elasticity as uncertain variables that could be assumed to vary randomly. Monte Carlo simulation was used to evaluate the probability of fracture (POF) of each fixation. The POF represents the cumulative probability that the predicted shear stresses in the cortical bone will exceed the expected shear strength of the cortical bone. This investigation provides information regarding the significance of post-operative damage accumulation on the POF of the implanted bones when the two fixations are used. The probabilistic analysis found the locking plate fixation to have a higher POF than the IM nail fixation under the applied loading conditions (locking plate 21.8% versus IM nail 0.019%).     

Predicting the effect of relative humidity on skin temperature and skin wettedness

The purpose of this research is to investigate the relative humidity effects on skin temperature and skin wettedness for different operative temperatures. For this aim, thermal interactions between human body and environment are simulated. In this simulation, Gagge 2-node model is used but includes some significant modifications. The simulation is to apply the Gagge 2-node model to individual segments rather than to whole body. Also, the results of the simulation are compared with present measurements, and available experimental data and simulated results in the literature in order to present reliability of the 16 segments-Gagge 2-node model. It is determined that the simulation results are in good agreement with measured results obtained from present experiments, and simulated results and experimental data in the literature.     

Two-step validation of a Monte Carlo dosimetry framework for general radiology

The Monte Carlo technique is considered gold standard when it comes to patient-specific dosimetry. Any newly developed Monte Carlo simulation framework, however, has to be carefully calibrated and validated prior to its use. For many researchers this is a tedious work. We propose a two-step validation procedure for our newly built Monte Carlo framework and provide all input data to make it feasible for future related application by the wider community. The validation was at first performed by benchmarking against simulation data available in literature. The American Association of Physicists in Medicine (AAPM) report of task group 195 (case 2) was considered most appropriate for our application. Secondly, the framework was calibrated and validated against experimental measurements for trunk X-ray imaging protocols using a water phantom. The dose results obtained from all simulations and measurements were compared. Our Monte Carlo framework proved to agree with literature data, by showing a maximal difference below 4% to the AAPM report. The mean difference with the water phantom measurements was around 7%. The statistical uncertainty for clinical applications of the dosimetry model is expected to be within 10%. This makes it reliable for clinical dose calculations in general radiology. Input data and the described procedure allow for the validation of other Monte Carlo frameworks.     

A Review of fMRI Simulation Studies

Simulation studies that validate statistical techniques for fMRI data are challenging due to the complexity of the data. Therefore, it is not surprising that no common data generating process is available (i.e. several models can be found to model BOLD activation and noise). Based on a literature search, a database of simulation studies was compiled. The information in this database was analysed and critically evaluated focusing on the parameters in the simulation design, the adopted model to generate fMRI data, and on how the simulation studies are reported. Our literature analysis demonstrates that many fMRI simulation studies do not report a thorough experimental design and almost consistently ignore crucial knowledge on how fMRI data are acquired. Advice is provided on how the quality of fMRI simulation studies can be improved.