Three-dimensional Simulation of Fracture Repair in the Human Tibia

Finite element models of bones can be generated based on images obtained non-invasively in the clinic. One area where such models may prove useful is in the assessment of fracture healing of long bones. To establish the feasibility of such a proposal, a three dimensional finite element model of a fractured tibia was generated, and a model of tissue differentiation and bone regeneration was used to simulate the progress of healing under two different loading magnitudes. Healing is successful under the lower load and unsuccessful under the higher load--this proves that the model has the potential to identify loads that would cause healing to fail. Following a proposal by Richardson et al. [J. Bone Jt Surg. Vol. 76B (1994) pp. 389-394] that the bending stiffness can be used to assess the extent of healing, the bending stiffness was computed during healing--it was shown that the stiffness changed in a similar manner that observed clinically. In conclusion, the paper establishes that 3D computer simulation could be a tool for assessment of the fracture healing under different orthopedic treatments.     

Numerical Models for the Simulation of Flexible Artificial Heart Valves: Part I - Computational Methods

Abstract

A numerical model of the coupled motion of a flexing surface in a high Reynolds number flow is presented for the simulation of flexible polyurethane heart valves in the aortic position. This is achieved by matching a Lagrangian dynamic leaflet model with a panel method based flow solver. The two models are coupled via the time-dependent pressure field using the unsteady Bernoulli equation.

Incorporation of sub-cycling in the dynamic model equations and fast pre conditioning techniques in the panel method solver yields efficient convergence and near real-time simulations of valve motion. The generality of dynamic model allows different material properties and/or geometries to be studied easily and interactively. This interactivity is realized by embedding the models within a design environment created using the software IRIS Explorer ^TM.

Two flow domains are developed, an infinite domain and an internal domain using conformal mapping theory. In addition bending stress on the valve is computed using a simple stress model based on spline and circle equation techniques.     

A comparison of six DNA bending models

The predictions of six DNA bending models were compared with experimental relative mobility data. The study showed that all the models are reasonably accurate in predicting bending in synthetic sequences and in a natural sequence. The least accurate of these models is the Calladine-Dickerson model. The most consistent model is the ApA Wedge, possibly because it distributes the bends into base-roll and base-tilt components.     

A convolution neural network for higher resolution dose prediction in prostate volumetric modulated arc therapy

PurposeThis study aims to investigate the feasibility of using convolutional neural networks to predict an accurate and high resolution dose distribution from an approximated and low resolution input dose.MethodsSixty-six patients were treated for prostate cancer with VMAT. We created the treatment plans using the Acuros XB algorithm with 2 mm grid size, followed by the dose calculated using the anisotropic analytical algorithm with 5 mm grid with the same plan parameters. U-net model was used to predict 2 mm grid dose from 5 mm grid dose. We investigated the two models differing for the training data used as input, one used just the low resolution dose (D model) and the other combined the low resolution dose with CT data (DC model). Dice similarity coefficient (DSC) was calculated to ascertain how well the shape of the dose-volume is matched. We conducted gamma analysis for the following: DVH from the two models and the reference DVH for all prostate structures.ResultsThe DSC values in the DC model were significantly higher than those in the D model (p < 0.01). For the CTV, PTV, and bladder, the gamma passing rates in the DC model were significantly higher than those in the D model (p < 0.002–0.02). The mean doses in the CTV and PTV for the DC model were significantly better matched to those in the reference dose (p < 0.0001).ConclusionsThe proposed U-net model with dose and CT image used as input predicted more accurate dose.     

A Refined Prediction Method for Gel Retardation of DNA Oligonucleotides from Dinucleotide Step Parameters: Reconciliation of DNA Bending Models with Crystal Structure Data

Abstract

The development and assessment of a prediction method for gel retardation and sequence dependent curvature of DNA based on dinucleotide step parameters are described. The method is formulated using the Babcock-Olson equations for base pair step geometry (1) and employs Monte Carlo simulated annealing for parameter optimization against experimental data. The refined base pair step parameters define a structural construct which, when the width of observed parameter distributions is taken into account, is consistent with the results of DNA oligonucleotide crystal structures. The predictive power of the method is demonstrated and tested via comparisons with DNA bending data on sets of sequences not included in the training set, including A-tracts with and without periodic helix phasing, phased A₄T₄ and T₄A₄ motifs, a sequence with a phased GGGCCC motif, some “unconventional” helix phasing sequences, and three short fragments of kinetoplast DNA from Crithidia fasiculata that exhibit significantly different behavior on non-denaturing polyacrylamide gels. The nature of the structural construct produced by the methodology is discussed with respect to static and dynamic models of structure and representations of bending and bendability. An independent theoretical account of sequence dependent chemical footprinting results is provided. Detailed analysis of sequences with A-tract induced axis bending forms the basis for a critical discussion of the applicability of wedge models, junction models and non A-tract, general sequence models for understanding the origin of DNA curvature at the molecular level.     

Cyclic Bending Contributes to High Stress in a Human Coronary Atherosclerotic Plaque and Rupture Risk: In Vitro Experimental Modeling and Ex Vivo MRI-Based Computational Modeling Approach

Many acute cardiovascular syndromes such as heart attack and stroke are caused by atherosclerotic plaque ruptures which often happen without warning. MRI-based models with fluid-structure interactions (FSI) have been introduced to perform flow and stress/strain analysis for atherosclerotic plaques and identify possible mechanical and morphological indices for accurate plaque vulnerability assessment. In this paper, cyclic bending was added to 3D FSI coronary plaque models for more accurate mechanical predictions. Curvature variation was prescribed using the data of a human left anterior descending (LAD) coronary artery. Five computational models were constructed based on ex vivo MRI human coronary plaque data to assess the effects of cyclic bending, pulsating pressure, plaque structure, and axial stretch on plaque stress/strain distributions. In vitro experiments using a hydrogel stenosis model with cyclical bending were performed to observe effect of cyclical bending on flow conditions. Our results indicate that cyclical bending may cause more than 100% or even up to more than 1000% increase in maximum principal stress values at locations where the plaque is bent most. Stress increase is higher when bending is coupled with axial stretch, non-smooth plaque structure, or resonant pressure conditions (zero phase angle shift). Effects of cyclic bending on flow behaviors are more modest (21.6% decrease in maximum velocity, 10.8% decrease in flow rate, maximum flow shear stress changes were < 5%). Computational FSI models including cyclic bending, plaque components and structure, axial stretch, accurate in vivo measurements of pressure, curvature, and material properties should lead to significant improvement on stress-based plaque mechanical analysis and more accurate coronary plaque vulnerability assessment.     

Estimating dengue transmission intensity from serological data: A comparative analysis using mixture and catalytic models

BackgroundDengue virus (DENV) infection is a global health concern of increasing magnitude. To target intervention strategies, accurate estimates of the force of infection (FOI) are necessary. Catalytic models have been widely used to estimate DENV FOI and rely on a binary classification of serostatus as seropositive or seronegative, according to pre-defined antibody thresholds. Previous work has demonstrated the use of thresholds can cause serostatus misclassification and biased estimates. In contrast, mixture models do not rely on thresholds and use the full distribution of antibody titres. To date, there has been limited application of mixture models to estimate DENV FOI.MethodsWe compare the application of mixture models and time-constant and time-varying catalytic models to simulated data and to serological data collected in Vietnam from 2004 to 2009 (N ≥ 2178) and Indonesia in 2014 (N = 3194).ResultsThe simulation study showed larger mean FOI estimate bias from the time-constant and time-varying catalytic models (-0.007 (95% Confidence Interval (CI): -0.069, 0.029) and -0.006 (95% CI -0.095, 0.043)) than from the mixture model (0.001 (95% CI -0.036, 0.065)). Coverage of the true FOI was > 95% for estimates from both the time-varying catalytic and mixture model, however the latter had reduced uncertainty. When applied to real data from Vietnam, the mixture model frequently produced higher FOI and seroprevalence estimates than the catalytic models.ConclusionsOur results suggest mixture models represent valid, potentially less biased, alternatives to catalytic models, which could be particularly useful when estimating FOI from data with largely overlapping antibody titre distributions.     

拉曼光谱分析技术在资源微生物发酵性能评价中的应用

微生物发酵过程是细胞新陈代谢进行物质转化的过程,为了提高目标产物的转化率,需要对微生物发酵动态特性进行实时分析,以便实时优化发酵过程。拉曼光谱(Raman spectroscopy)量化测试作为一种有应用前景的在线过程分析技术,可以在避免微生物污染的条件下,实现精准监测,进而用于优化控制微生物发酵过程。【目的】以运动发酵单胞菌(Zymomonas mobilis)为例,建立微生物发酵过程中葡萄糖、木糖、乙醇和乳酸浓度拉曼光谱预测模型,并进行准确性验证。【方法】采用浸入式在线拉曼探头,收集运动发酵单胞菌发酵过程中多个组分的拉曼光谱,采用偏最小二乘法对光谱信号进行预处理和多元数据分析,结合离线色谱分析数据,对拉曼光谱进行建模分析和浓度预测。【结果】针对运动发酵单胞菌,首先实现拉曼分析仪对单一产品乙醇发酵过程的精准检测,其次基于多元变量分析,建立葡萄糖、乙醇和乳酸浓度变化的预测模型,实现对发酵过程中各成分浓度变化的准确有效分析。【结论】成功建立了一种评价资源微生物尤其是工业菌株发酵液多种组分的拉曼光谱分析方法。该方法为运动发酵单胞菌等工业菌株利用多组分底物工业化生产不同产物的实时检测,以及其他微生物尤其工业菌株的选育和过程优化提供了新方法。     

Estimating the Risk of Chronic Pain: Development and Validation of a Prognostic Model (PICKUP) for Patients with Acute Low Back Pain

BackgroundLow back pain (LBP) is a major health problem. Globally it is responsible for the most years lived with disability. The most problematic type of LBP is chronic LBP (pain lasting longer than 3 mo); it has a poor prognosis and is costly, and interventions are only moderately effective. Targeting interventions according to risk profile is a promising approach to prevent the onset of chronic LBP. Developing accurate prognostic models is the first step. No validated prognostic models are available to accurately predict the onset of chronic LBP. The primary aim of this study was to develop and validate a prognostic model to estimate the risk of chronic LBP.ConclusionsBased on its performance in these cohorts, this five-item prognostic model for patients with acute LBP may be a useful tool for estimating risk of chronic LBP. Further validation is required to determine whether screening with this model leads to a net reduction in unnecessary interventions provided to low-risk patients.     

Structure and Dynamics of Double Helices in Solution: Modes of DNA Bending

Abstract

The long range structure of DNA restriction fragments has been analysed by electro-optical measurements. The overall rotation time constants observed in a low salt buffer with monovalent ions is shown to decrease upon addition of Mg²⁺ or spermine. Since the circular dichroism and also the limiting value of the linear dichroism remain almost constant under these conditions, the effect is attributed to a change of the long range structure. According to a weakly bending rod model, the persistence length decreases from about 600 Å in the absence of Mg²⁺ or spermine to about 350 Å in the presence of these ions. The persistence length measured in the presence of Mg²⁺ is almost independent of temperature in the range of 10 to 40 °C. The nature of DNA bending is analysed by measurements of bending amplitudes and time constants from dichroism decay curves. The observed absence of changes in the bending amplitudes upon addition of Mg²⁺ or spermine, even though addition induces changes of the persistence length by a factor of 2, is hardly consistent with simple thermal bending. The combined results, including the remarkably small temperature dependence of persistence length and bending amplitude, can be explained by the existence of two bending effects: inherent curvature of DNA dominates at low temperature, whereas thermal bending prevails at high temperature. Analysis of bending amplitudes from dichroism decay curves according to an arc model provides an approximate measure for the degree of bending in restriction fragments. The model is consistent with the observed chain length dependence of bending amplitudes and provides an approximate curvature corresponding to a radius of ab out400Å. Thus the curvature observed in restriction fragments is similar to that observed for high molecular DNA condensed into toroids by addition of ions like spermine.

Particularly strong bending of DNA is induced by [CO(NH₃)₆]³⁺, indicated by an apparent persistence length of 200 Å and an increased bending amplitude together with a reduced limit value of the linear dichroism. This effect is attributed to the high charge density of this ion and potential site binding.     

A Computer Graphics Study of Sequence-Directed Bending in DNA

Abstract

We present theoretical results to account for the unusual physical properties of a 423 bp DNA restriction fragment isolated from the kinetoplast of the trypanosomatid Leishmania tarentolae. This fragment has an anomalously low electrophoretic mobility in Polyacrylamide gels and a rotational relaxation time smaller than that of normally-behaved control fragments of the same molecular weight. Our earlier work (Proc. Natl. Acad. Sci. USA 79, 7664, 1982) has attributed these anomalies to the highly periodic distribution of the dinucleotide ApA in the DNA sequence. As originally proposed by Trifonov and Sussman (Proc. Natl. Acad. Sci. USA 77, 3816,1980) local features of the DNA structure such as a small bend at ApA, if repeated with the periodicity of the helix, will cause systematic bending of the molecule.

Computer graphics representations of DNA chain trajectories are presented for different structural models. It is shown that the structural model of Calladine (J. Mol. Biol. 161, 343, 1982) which is based on crystallographic data, is unsuccessful in predicting the systematic bending of DNA in solution.     

Free body analysis,beam mechanics,and finite element modeling of the mandible of Alligator mississippiensis

The mechanical behavior of mammalian mandibles is well‐studied, but a comprehensive biomechanical analysis (incorporating detailed muscle architecture, accurate material properties, and three‐dimensional mechanical behavior) of an extant archosaur mandible has never been carried out. This makes it unclear how closely models of extant and extinct archosaur mandibles reflect reality and prevents comparisons of structure–function relationships in mammalian and archosaur mandibles. We tested hypotheses regarding the mechanical behavior of the mandible of Alligator mississippiensis by analyzing reaction forces and bending, shear, and torsional stress regimes in six models of varying complexity. Models included free body analysis using basic lever arm mechanics, 2D and 3D beam models, and three high‐resolution finite element models of the Alligator mandible, incorporating, respectively, isotropic bone without sutures, anisotropic bone with sutures, and anisotropic bone with sutures and contact between the mandible and the pterygoid flange. Compared with the beam models, the Alligator finite element models exhibited less spatial variability in dorsoventral bending and sagittal shear stress, as well as lower peak values for these stresses, suggesting that Alligator mandibular morphology is in part designed to reduce these stresses during biting. However, the Alligator models exhibited greater variability in the distribution of mediolateral and torsional stresses than the beam models. Incorporating anisotropic bone material properties and sutures into the model reduced dorsoventral and torsional stresses within the mandible, but led to elevated mediolateral stresses. These mediolateral stresses were mitigated by the addition of a pterygoid‐mandibular contact, suggesting important contributions from, and trade‐offs between, material properties and external constraints in Alligator mandible design. Our results suggest that beam modeling does not accurately represent the mechanical behavior of the Alligator mandible, including important performance metrics such as magnitude and orientation of reaction forces, and mediolateral bending and torsional stress distributions. J.Morphol. 2011. © 2011 Wiley‐Liss, Inc.     

Forest above-ground volume assessments with terrestrial laser scanning: a ground-truth validation experiment in temperate,managed forests

Background and AimsQuantifying the Earth’s forest above-ground biomass (AGB) is indispensable for effective climate action and developing forest policy. Yet, current allometric scaling models (ASMs) to estimate AGB suffer several drawbacks related to model selection and uncertainties about calibration data traceability. Terrestrial laser scanning (TLS) offers a promising non-destructive alternative. Tree volume is reconstructed from TLS point clouds with quantitative structure models (QSMs) and converted to AGB with wood basic density. Earlier studies have found overall TLS-derived forest volume estimates to be accurate, but highlighted problems for reconstructing finer branches. Our objective was to evaluate TLS for estimating tree volumes by comparison with reference volumes and volumes from ASMs.MethodsWe quantified the woody volume of 65 trees in Belgium (from 77 to 2800 L; Pinus sylvestris, Fagus sylvatica, Larix decidua, and Fraxinus excelsior) with QSMs and destructive reference measurements. We tested a volume expansion factor (VEF) approach by multiplying the solid and merchantable volume from QSMs by literature VEF values.Key ResultsStem volume was reliably estimated with TLS. Total volume was overestimated by +21 % using original QSMs, by +9 % and –12 % using two sets of VEF-augmented QSMs, and by –7.3 % using best-available ASMs. The most accurate method differed per site, and the prediction errors for each method varied considerably between sites.ConclusionsVEF-augmented QSMs were only slightly better than original QSMs for estimating tree volume for common species in temperate forests. Despite satisfying estimates with ASMs, the model choice was a large source of uncertainty, and species-specific models did not always exist. Therefore, we advocate for further improving tree volume reconstructions with QSMs, especially for fine branches, instead of collecting more ground-truth data to calibrate VEF and allometric models. Promising developments such as improved co-registration and smarter filtering approaches are ongoing to further constrain volumetric errors in TLS-derived estimates.     

The Practical Calculation of Interionic Potentials

Abstract

Most molecular simulations assume a potential model. In some cases, where one is interested only in qualitative behaviour, the details of the potential are not important provided the basic form is physically sensible. However, if one requires quantitative results, it is essential to obtain an accurate potential model. In the past, such models have been obtained by empirical fitting to suitable bulk crystal properties. Increasingly, they are now being calculated. This paper reviews the relative merits of these approaches and suggests criteria that any “good” potential should fulfill.     

Morbidity Rate Prediction of Dengue Hemorrhagic Fever (DHF) Using the Support Vector Machine and the Aedes aegypti Infection Rate in Similar Climates and Geographical Areas

BackgroundIn the past few decades, several researchers have proposed highly accurate prediction models that have typically relied on climate parameters. However, climate factors can be unreliable and can lower the effectiveness of prediction when they are applied in locations where climate factors do not differ significantly. The purpose of this study was to improve a dengue surveillance system in areas with similar climate by exploiting the infection rate in the Aedes aegypti mosquito and using the support vector machine (SVM) technique for forecasting the dengue morbidity rate.ConclusionsThe infection rates of the Ae. aegypti female mosquitoes and larvae improved the morbidity rate forecasting efficiency better than the climate parameters used in classical frameworks. We demonstrated that the SVM-R-based model has high generalization performance and obtained the highest prediction performance compared to classical models as measured by the accuracy, sensitivity, specificity, and mean absolute error (MAE).     

Effect of turbulent models on left ventricle diastolic flow patterns simulation

Abstract

Vortex structures, as one of the most important features of cardiac flow, have a crucial impact on the left ventricle function and pathological conditions. These swirling flows are closely related to the presence of turbulence in left ventricle which is investigated in the current study. Using an extended model of the left heart, including a fluid-structure interaction (FSI) model of the mitral valve with a realistic geometry, the effect of using two numerical turbulent models, k-ε and Spalart-Allmaras (SA), on diastolic flow patterns is studied and compared with results from laminar flow model. As a result of the higher dissipation rate in turbulent models (k-ε and SA), vortices are larger and stronger in the laminar flow model. Comparing E/A ratio in the three models (Laminar, k-ε, and SA) with experimental data from healthy subjects, it is concluded that the results from k-ε model are more accurate.     

Two decades of biomonitoring polar bear health in Greenland: a review

Background

Different animal models are used as fracture models in orthopaedic research prior to implant use in humans, although biomechanical forces can differ to a great extend between species due to variable anatomic conditions, particularly with regard to the gait. The rabbit is an often used fracture model, but biomechanical data are very rare. The objective of the present study was to measure axial forces, bending moments, and bending axis directly in the rabbit tibia in vivo. The following hypothesis was tested: Axial forces and bending moments in the mid-diaphysis of rabbit tibia differ from other experimental animals or indirectly calculated data.

Methods

A minifixateur system with 4 force sensors was developed and attached to rabbit tibia (n = 4), which were subsequently ostectomised. Axial forces, bending moments and bending angles were calculated telemetrically during weight bearing in motion between 6 and 42 days post operation.

Results

Highest single values were 201% body weight [% bw] for axial forces and 409% bw cm for bending moments. Whereas there was a continous decrease in axial forces over time after day 10 (P = 0.03 on day 15), a decrease in bending moments was inconsistent (P = 0.03 on day 27). High values for bending moments were frequently, but not consistently, associated with high values for axial forces.

Conclusion

Axial forces in rabbit tibia exceeded axial forces in sheep, and differed from indirectly calculated data. The rabbit is an appropriate fracture model because axial loads and bending moments in rabbit tibia were more closely to human conditions than in sheep tibia as an animal model.     

Good Manufacturing Practices (GMP) manufacturing of advanced therapy medicinal products: a novel tailored model for optimizing performance and estimating costs

Background aimsAdvanced therapy medicinal products (ATMP) have gained considerable attention in academia due to their therapeutic potential. Good Manufacturing Practice (GMP) principles ensure the quality and sterility of manufacturing these products. We developed a model for estimating the manufacturing costs of cell therapy products and optimizing the performance of academic GMP-facilities.MethodsThe “Clean-Room Technology Assessment Technique” (CTAT) was tested prospectively in the GMP facility of BCRT, Berlin, Germany, then retrospectively in the GMP facility of the University of California-Davis, California, USA. CTAT is a two-level model: level one identifies operational (core) processes and measures their fixed costs; level two identifies production (supporting) processes and measures their variable costs. The model comprises several tools to measure and optimize performance of these processes. Manufacturing costs were itemized using adjusted micro-costing system.ResultsCTAT identified GMP activities with strong correlation to the manufacturing process of cell-based products. Building best practice standards allowed for performance improvement and elimination of human errors. The model also demonstrated the unidirectional dependencies that may exist among the core GMP activities. When compared to traditional business models, the CTAT assessment resulted in a more accurate allocation of annual expenses. The estimated expenses were used to set a fee structure for both GMP facilities. A mathematical equation was also developed to provide the final product cost.ConclusionsCTAT can be a useful tool in estimating accurate costs for the ATMPs manufactured in an optimized GMP process. These estimates are useful when analyzing the cost-effectiveness of these novel interventions.     

Proposing a Radial Basis Function and CSDM Indices to Predict the Traumatic Brain Injury Risk

BackgroundMany head injury indices and finite element (FE) head models have been proposed to predict traumatic brain injury (TBI). Although FE head models are suitable methods with high accuracy, they are computationally intensive. Head motion-based brain injury criteria are usually fast tools with lower accuracy. So, the objective of this study is to propose new criteria along with an artificial neural network model to predict TBI risks, which can be fast and accurate.MethodsFor this purpose, 250 FE head simulations have been carried out at 5 magnitudes and 50 rotational impact directions using the SIMon model. The effects of directions and magnitudes of rotational impacts were assessed for cumulative strain damage measure (CSDM) values. Next, statistical analysis and neural network were applied to predict CSDM values.ResultsThe results of the present research showed that the direction of rotation in the sagittal and frontal planes had a considerable effect on the CSDM values. Furthermore, new brain injury indices and a radial basis function neural network have been proposed to predict CSDM values which having high correlation coefficients with SIMon responses.ConclusionsThe results of this research demonstrated that rotational impact directions should be used to develop new head injury criteria being able to predict CSDM values. However, findings of present research proved that head motion-based brain injury criteria and RBF network can be used to predict FE head model responses with high speed and accuracy.