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.     

Detailed finite element modelling of deep needle insertions into a soft tissue phantom using a cohesive approach

Detailed finite element modelling of needle insertions into soft tissue phantoms encounters difficulties of large deformations, high friction, contact loading and material failure. This paper demonstrates the use of cohesive elements in high-resolution finite element models to overcome some of the issues associated with these factors. Experiments are presented enabling extraction of the strain energy release rate during crack formation. Using data from these experiments, cohesive elements are calibrated and then implemented in models for validation of the needle insertion process. Successful modelling enables direct comparison of finite element and experimental force–displacement plots and energy distributions. Regions of crack creation, relaxation, cutting and full penetration are identified. By closing the loop between experiments and detailed finite element modelling, a methodology is established which will enable design modifications of a soft tissue probe that steers through complex mechanical interactions with the surrounding material.     

Validation of the Boussinesq equation for use in traction field determination

Cell traction force plays an important role in many biological processes. Several traction force microscopy methods have been developed to determine cell traction forces based on the Boussinesq solution. This approach, however, is rooted in a half-space assumption. The purpose of this study was to determine the error induced in the half-space assumption using a finite element method (FEM). It demonstrates that displacement error between the FEM and the Boussinesq equation can be used to measure the accuracy of the Boussinesq equation, although singularity exists in the loading point. For one concentrated force, significant difference between the FEM and the Boussinesq equation occurs in the whole field; this difference decreases with an increase in the plate thickness. However, in the case of the balanced forces, the offset of the balanced forces decreases the errors in the middle area. Overall, this study demonstrates that increasing the thickness of the polyacrylamide gel is important for reducing the error of the Boussinesq equation when determining the displacement field of the gel under loads.     

Evolution of the silver and gold stains in neurohistology

Scientific investigations depend on the reliability of the observations that can be made. This reliability is determined in part by the understanding of the techniques and technology used to make the observations. The limitations and the strengths of the methodology and the equipment used must be evaluated thoroughly. The extent to which this is and has been the case for the use of the metal based stains in neuroscience is the subject of this paper. I evaluate the metallic stains used for neuroscience from several perspectives. I review briefly the state of neurohistology prior to its “golden years,” 1870–1910. Then I trace the development of the silver based stains used for neurohistology. I wanted to discuss the reasoning used by the originators of the silver based techniques in developing their specific procedures, but discovered that while procedures may be published, the methods and ideas used to arrive at the final procedures are not usually described in published work.     

A Review of: “Progress in Separation and Purification Vol. 3, E. S. Perry and C. J,van Oss,eds., Willy/Intersciencc,New York, 1970; xi + 316 pares; hard cover; 515.95”

The optimal culture conditions of exopolysaccharides (EPS) production in submerged culture medium by Pleurotus geesteranus 5 ^# were determined using an orthogonal matrix method. The optimal defined medium (per liter) was 60.0 g maltose, 5.0 g tryptone, 1 mM NaCl, 5 mM KH₂PO₄, and initial pH 6.0 at 28 °C. In the optimal culture medium, the maximum EPS production was 16.97 g/L in a shake flask. Two groups of EPSs (designated as Fr-I and Fr-II) were obtained from the culture filtrates by size exclusion chromatography (SEC), and their molecular characteristics were examined by a multiangle laser-light scattering (MALLS) and refractive index (RI) detector system. The approximate weight-average molar masses of the Fr-I and Fr-II of EPS were determined to be 3.263 × 10⁴ and 5.738 × 10³ g/mol, respectively. The low values of polydispersity ratio (1.176 and 1.124 for Fr-I and Fr-II, respectively) of EPSs mean that these EPS molecules exist much less dispersed in aqueous solution without forming large aggregates. Furthermore, the experiments in vitro indicated that P. geesteranus 5^# EPS exhibit high antitumor and antioxidative effects.     

On‐target ultrasonic digestion of proteins

In the present work, we report a novel on‐target protein cleavage method. The method utilizes ultrasonic energy and allows up to 20 samples to be cleaved in 5 min for protein identification and one sample in 30 s for on‐tissue digestion. The standard proteins were spotted on a conductive glass slide in a volume of 0.5 μL followed by 5 min of ultrasonication after trypsin addition. Controls (5 min, 37°C no ultrasonication) were also assayed. After trypsin addition, digestion of the tissues was enhanced by 30 s of ultrasonication. The samples were analyzed and compared to those obtained by using conventional 3 h heating proteolysis. The low sample volume needed for the digestion and reduction in sample‐handling steps and time are the features that make this method appealing to the many laboratories working with high‐throughput sample treatment.     

榆耳不同极性提取物的体外抑菌活性

采用圆滤纸片法,以金黄色葡萄球菌O41ermc、S19NMA1、ATCC25923和大肠杆菌ERcat、EΠ￡R、ATCC25923为受试菌种,对榆耳石油醚、氯仿、乙酸乙酯、丙酮、甲醇和水不同极性提取物进行抑菌活性研究。结果表明:榆耳不同极性提取物对不同的菌种均有不同程度的抑制作用。     

Computational model for autophagic vesicle dynamics in single cells

Macroautophagy (autophagy) is a cellular recycling program essential for homeostasis and survival during cytotoxic stress. This process, which has an emerging role in disease etiology and treatment, is executed in four stages through the coordinated action of more than 30 proteins. An effective strategy for studying complicated cellular processes, such as autophagy, involves the construction and analysis of mathematical or computational models. When developed and refined from experimental knowledge, these models can be used to interrogate signaling pathways, formulate novel hypotheses about systems, and make predictions about cell signaling changes induced by specific interventions. Here, we present the development of a computational model describing autophagic vesicle dynamics in a mammalian system. We used time-resolved, live-cell microscopy to measure the synthesis and turnover of autophagic vesicles in single cells. The stochastically simulated model was consistent with data acquired during conditions of both basal and chemically-induced autophagy. The model was tested by genetic modulation of autophagic machinery and found to accurately predict vesicle dynamics observed experimentally. Furthermore, the model generated an unforeseen prediction about vesicle size that is consistent with both published findings and our experimental observations. Taken together, this model is accurate and useful and can serve as the foundation for future efforts aimed at quantitative characterization of autophagy.