Triangular node for Transmission-Line Modeling (TLM) applied to bio-heat transfer

Transmission-Line Modeling (TLM) is a numerical method used to solve complex and time-domain bio-heat transfer problems. In TLM, rectangles are used to discretize two-dimensional problems. The drawback in using rectangular shapes is that instead of refining only the domain of interest, a large additional domain will also be refined in the x and y axes, which results in increased computational time and memory space. In this paper, we developed a triangular node for TLM applied to bio-heat transfer that does not have the drawback associated with the rectangular nodes. The model includes heat source, blood perfusion (advection), boundary conditions and initial conditions. The boundary conditions could be adiabatic, temperature, heat flux, or convection. A matrix equation for TLM, which simplifies the solution of time-domain problems or solves steady-state problems, was also developed. The predicted results were compared against results obtained from the solution of a simplified two-dimensional problem, and they agreed within 1% for a mesh length of triangular faces of 59 µm±9 µm (mean±standard deviation) and a time step of 1 ms.     

A generalized finite difference method for modeling cardiac electrical activation on arbitrary, irregular computational meshes

A generalized finite difference (GFD) method is presented that can be used to solve the bi-domain equations modeling cardiac electrical activity. Classical finite difference methods have been applied by many researchers to the bi-domain equations. However, these methods suffer from the limitation of requiring computational meshes that are structured and orthogonal. Finite element or finite volume methods enable the bi-domain equations to be solved on unstructured meshes, although implementations of such methods do not always cater for meshes with varying element topology. The GFD method solves the bi-domain equations on arbitrary and irregular computational meshes without any need to specify element basis functions. The method is useful as it can be easily applied to activation problems using existing meshes that have originally been created for use by finite element or finite difference methods. In addition, the GFD method employs an innovative approach to enforcing nodal and non-nodal boundary conditions. The GFD method performs effectively for a range of two and three-dimensional test problems and when computing bi-domain electrical activation moving through a fully anisotropic three-dimensional model of canine ventricles.     

Optimizing reduced-space sequence analysis

MOTIVATION: Dynamic programming is the core algorithm of sequence comparison, alignment and linear hidden Markov model (HMM) training. For a pair of sequence lengths m and n, the problem can be solved readily in O(mn)time and O(mn)space. The checkpoint algorithm introduced by Grice et al. (CABIOS, 13, 45--53, 1997) runs in O(Lmn)time and O(Lm(L) square root of n)space, where L is a positive integer determined by m, n, and the amount of available workspace. The algorithm is appropriate for many string comparison problems, including all-paths and single-best-path hidden Markov model training, and is readily parallelizable. The checkpoint algorithm has a diagonal version that can solve the single-best-path alignment problem in O(mn)time and O(m + n)space. RESULTS: In this work, we improve performance by analyzing optimal checkpoint placement. The improved row checkpoint algorithm performs up to one half the computation of the original algorithm. The improved diagonal checkpoint algorithm performs up to 35% fewer computational steps than the original. We modified the SAM hidden Markov modeling package to use the improved row checkpoint algorithm. For a fixed sequence length, the new version is up to 33% faster for all-paths and 56% faster for single-best-path HMM training, depending on sequence length and allocated memory. Over a typical set of protein sequence lengths, the improvement is approximately 10%.     

Computational framework to model and design surgical meshes for hernia repair

Surgical procedures for hernia surgery are usually performed using prosthetic meshes. In spite of all the improvements in these biomaterials, the perfect match between the prosthesis and the implant site has not been achieved. Thus, new designs of surgical meshes are still being developed. Previous to implantation in humans, the validity of the meshes has to be addressed, and to date experimental studies have been the gold standard in testing and validating new implants. Nevertheless, these procedures involve long periods of time and are expensive. Thus, a computational framework for the simulation of prosthesis and surgical procedures may overcome some disadvantages of the experimental methods. The computational framework includes two computational models for designing and validating the behaviour of new meshes, respectively. Firstly, the beam model, which reproduces the exact geometry of the mesh, is set to design the weave and determine the stiffness of the surgical prosthesis. However, this implies a high computational cost whereas the membrane model, defined within the framework of the large deformation hyperelasticity, is a relatively inexpensive computational tool, which also enables a prosthesis to be included in more complex geometries such as human or animal bodies.     

Recent Advances in Computational Simulation of Macro-, Meso-, and Micro-Scale Biomimetics Related Fluid Flow Problems

Over the last decade, computational methods have been intensively applied to a variety of scientific researches and engineering designs. Although the computational fluid dynamics （CFD） method has played a dominant role in studying and simulating transport phenomena involving fluid flow and heat and mass transfers, in recent years, other numerical methods for the simulations at meso- and micro-scales have also been actively applied to solve the physics of complex flow and fluid-interface interactions. This paper presents a review of recent advances in multi-scale computational simulation of biomimetics related fluid flow problems. The state-of-the-art numerical techniques, such as lattice Boltzmann method （LBM）, molecular dynamics （MD）, and conventional CFD, applied to different problems such as fish flow, electro-osmosis effect of earthworm motion, and self-cleaning hydrophobic surface, and the numerical approaches are introduced. The new challenging of modelling biomimetics problems in developing the physical conditions of self-clean hydrophobic surfaces is discussed.     

Bridging the gaps in systems biology

Systems biology aims at creating mathematical models, i.e., computational reconstructions of biological systems and processes that will result in a new level of understanding—the elucidation of the basic and presumably conserved “design” and “engineering” principles of biomolecular systems. Thus, systems biology will move biology from a phenomenological to a predictive science. Mathematical modeling of biological networks and processes has already greatly improved our understanding of many cellular processes. However, given the massive amount of qualitative and quantitative data currently produced and number of burning questions in health care and biotechnology needed to be solved is still in its early phases. The field requires novel approaches for abstraction, for modeling bioprocesses that follow different biochemical and biophysical rules, and for combining different modules into larger models that still allow realistic simulation with the computational power available today. We have identified and discussed currently most prominent problems in systems biology: (1) how to bridge different scales of modeling abstraction, (2) how to bridge the gap between topological and mechanistic modeling, and (3) how to bridge the wet and dry laboratory gap. The future success of systems biology largely depends on bridging the recognized gaps.     

Effects of intracortical porosity on fracture toughness in aging human bone: a microCT-based cohesive finite element study

The extent to which increased intracortical porosity affects the fracture properties of aging and osteoporotic bone is unknown. Here, we report the development and application of a microcomputed tomography based finite element approach that allows determining the effects of intracortical porosity on bone fracture by blocking all other age-related changes in bone. Previously tested compact tension specimens from human tibiae were scanned using microcomputed tomography and converted to finite element meshes containing three-dimensional cohesive finite elements in the direction of the crack growth. Simulations were run incorporating age-related increase in intracortical porosity but keeping cohesive parameters representing other age-related effects constant. Additional simulations were performed with reduced cohesive parameters. The results showed a 6% decrease in initiation toughness and a 62% decrease in propagation toughness with a 4% increase in porosity. The reduction in toughnesses became even more pronounced when other age-related effects in addition to porosity were introduced. The initiation and propagation toughness decreased by 51% and 83%, respectively, with the combined effect of 4% increase in porosity and decrease in the cohesive properties reflecting other age-related changes in bone. These results show that intracortical porosity is a significant contributor to the fracture toughness of the cortical bone and that the combination of computational modeling with advanced imaging improves the prediction of the fracture properties of the aged and the osteoporotic cortical bone.     

An efficient two-stage approach for image-based FSI analysis of atherosclerotic arteries

Patient-specific biomechanical modeling of atherosclerotic arteries has the potential to aid clinicians in characterizing lesions and determining optimal treatment plans. To attain high levels of accuracy, recent models use medical imaging data to determine plaque component boundaries in three dimensions, and fluid–structure interaction is used to capture mechanical loading of the diseased vessel. As the plaque components and vessel wall are often highly complex in shape, constructing a suitable structured computational mesh is very challenging and can require a great deal of time. Models based on unstructured computational meshes require relatively less time to construct and are capable of accurately representing plaque components in three dimensions. These models unfortunately require additional computational resources and computing time for accurate and meaningful results. A two-stage modeling strategy based on unstructured computational meshes is proposed to achieve a reasonable balance between meshing difficulty and computational resource and time demand. In this method, a coarsegrained simulation of the full arterial domain is used to guide and constrain a fine-scale simulation of a smaller region of interest within the full domain. Results for a patient-specific carotid bifurcation model demonstrate that the two-stage approach can afford a large savings in both time for mesh generation and time and resources needed for computation. The effects of solid and fluid domain truncation were explored, and were shown to minimally affect accuracy of the stress fields predicted with the two-stage approach.     

Improve islet yields and quality when clinical grade pancreata are preserved by the two-layer method

Background: Research grade pancreata preserved by the two-layer method (TLM) yield significantly greater numbers of islets than organs stored with University of Wisconsin solution (UW). The goal of this study was to determine whether this would hold true for pancreata that meet selection criteria for clinical grade organs. Methods: Pancreata were chosen based upon a pre-defined set of criteria used for selecting clinical grade pancreata. Thirteen of these organs were preserved in UW and five pancreata were preserved by the TLM. Islets were isolated and evaluated according to the Edmonton protocol. Results: The average preservation time was significantly longer for organ preserved with TLM (9.5 + 2.0 h) as compared to UW (5.8 + 0.6 h, p = 0.015). The pancreata of TLM group resulted in a significant increase in islet yields (3588 ± 500 vs. 2536 ± 312 IE/g pancreas, p<0.05). Visual scoring of islets indicated that islets were better from TLM group (8.3 ± 0.3 vs. 7.3 ± 0.2), and islet survival rates after culture were higher from organs stored with the TLM (87 ± 17 vs. 55 ± 7.4, p<0.05). Other parameters such as viability, insulin content, and stimulation index were similar between the two groups. All the preparations from the TLM group, but only 54% of preparations from the UW group, qualified for islet transplantation. The two recipients receiving islets from TLM group, daily insulin requirements were reduced and C-peptide levels were increased. Conclusion: Compared to storage with UW, exposure of pancreata to the TLM resulted in greater islet yields and improved quality of islets despite longer preservation period. Consequently, pancreata that meet clinical grade status should be preserved by the TLM prior to islet isolation.     

Stochastic modeling of RNA pseudoknotted structures: a grammatical approach

MOTIVATION: Modeling RNA pseudoknotted structures remains challenging. Methods have previously been developed to model RNA stem-loops successfully using stochastic context-free grammars (SCFG) adapted from computational linguistics; however, the additional complexity of pseudoknots has made modeling them more difficult. Formally a context-sensitive grammar is required, which would impose a large increase in complexity. RESULTS: We introduce a new grammar modeling approach for RNA pseudoknotted structures based on parallel communicating grammar systems (PCGS). Our new approach can specify pseudoknotted structures, while avoiding context-sensitive rules, using a single CFG synchronized with a number of regular grammars. Technically, the stochastic version of the grammar model can be as simple as an SCFG. As with SCFG, the new approach permits automatic generation of a single-RNA structure prediction algorithm for each specified pseudoknotted structure model. This approach also makes it possible to develop full probabilistic models of pseudoknotted structures to allow the prediction of consensus structures by comparative analysis and structural homology recognition in database searches.     

A systems‐level approach to mapping the telomere length maintenance gene circuitry

The ends of eukaryotic chromosomes are protected by telomeres, nucleoprotein structures that are essential for chromosomal stability and integrity. Understanding how telomere length is controlled has significant medical implications, especially in the fields of aging and cancer. Two recent systematic genome‐wide surveys measuring the telomere length of deleted mutants in the yeast Saccharomyces cerevisiae have identified hundreds of telomere length maintenance (TLM) genes, which span a large array of functional categories and different localizations within the cell. This study presents a novel general method that integrates large‐scale screening mutant data with protein–protein interaction information to rigorously chart the cellular subnetwork underlying the function investigated. Applying this method to the yeast telomere length control data, we identify pathways that connect the TLM proteins to the telomere‐processing machinery, and predict new TLM genes and their effect on telomere length. We experimentally validate some of these predictions, demonstrating that our method is remarkably accurate. Our results both uncover the complex cellular network underlying TLM and validate a new method for inferring such networks.     

Slow Onset Inhibition of Bacterial ��-Ketoacyl-acyl Carrier Protein Synthases by Thiolactomycin

Thiolactomycin (TLM), a natural product thiolactone antibiotic produced by species of Nocardia and Streptomyces, is an inhibitor of the β-ketoacyl-acyl carrier protein synthase (KAS) enzymes in the bacterial fatty acid synthase pathway. Using enzyme kinetics and direct binding studies, TLM has been shown to bind preferentially to the acyl-enzyme intermediates of the KASI and KASII enzymes from Mycobacterium tuberculosis and Escherichia coli. These studies, which utilized acyl-enzyme mimics in which the active site cysteine was replaced by a glutamine, also revealed that TLM is a slow onset inhibitor of the KASI enzymes KasA and ecFabB but not of the KASII enzymes KasB and ecFabF. The differential affinity of TLM for the acyl-KAS enzymes is proposed to result from structural change involving the movement of helices α5 and α6 that prepare the enzyme to bind malonyl-AcpM or TLM and that is initiated by formation of hydrogen bonds between the acyl-enzyme thioester and the oxyanion hole. The finding that TLM is a slow onset inhibitor of ecFabB supports the proposal that the long residence time of TLM on the ecFabB homologues in Serratia marcescens and Klebsiella pneumonia is an important factor for the in vivo antibacterial activity of TLM against these two organisms despite the fact that the in vitro MIC values are only 100–200 μg/ml. The mechanistic data on the interaction of TLM with KasA will provide an important foundation for the rational development of high affinity KasA inhibitors based on the thiolactone skeleton.     

Thiolactomycin and related analogues as novel anti-mycobacterial agents targeting KasA and KasB condensing enzymes in Mycobacterium tuberculosis

Prevention efforts and control of tuberculosis are seriously hampered by the appearance of multidrug-resistant strains of Mycobacterium tuberculosis, dictating new approaches to the treatment of the disease. Thiolactomycin (TLM) is a unique thiolactone that has been shown to exhibit anti-mycobacterial activity by specifically inhibiting fatty acid and mycolic acid biosynthesis. In this study, we present evidence that TLM targets two beta-ketoacyl-acyl-carrier protein synthases, KasA and KasB, consistent with the fact that both enzymes belong to the fatty-acid synthase type II system involved in fatty acid and mycolic acid biosynthesis. Overexpression of KasA, KasB, and KasAB in Mycobacterium bovis BCG increased in vivo and in vitro resistance against TLM. In addition, a multidrug-resistant clinical isolate was also found to be highly sensitive to TLM, indicating promise in counteracting multidrug-resistant strains of M. tuberculosis. The design and synthesis of several TLM derivatives have led to compounds more potent both in vitro against fatty acid and mycolic acid biosynthesis and in vivo against M. tuberculosis. Finally, a three-dimensional structural model of KasA has also been generated to improve understanding of the catalytic site of mycobacterial Kas proteins and to provide a more rational approach to the design of new drugs.     

Age differences in knee extension power, contractile velocity, and fatigability.

The purposes of this study were to examine age and gender differences in knee extensor strength, power, and fatigue using open- and closed-chain testing procedures. We tested the hypothesis that specific strength (strength/unit muscle mass) would not differ by age, whereas age differences in specific power and fatigue would remain consequent to blunted maximal contractile velocity. Skeletal muscle performance was examined in 28 young (26.9 +/- 0.7 yr) and 24 older (63.6 +/- 0.8 yr) men and women. Assessments included one-repetition maximum strength for knee extension, leg press, and squat; concentric knee extensor peak power, velocity, and fatigability; and sit-to-stand power, fatigability, and relative neural activation (electromyograph activity during sit-to-stand movement normalized to electromyograph activity during isometric maximum voluntary contraction). Thigh lean mass (TLM; kg) was assessed by dual-energy X-ray absorptiometry. Specific strength (N/kg TLM) and specific power (W/kg TLM) were estimated by dividing absolute values by TLM. Age differences in specific strength were observed for knee extension only (young, 41.2 +/- 1.0 N/kg TLM; older, 32.4 +/- 1.0 N/kg TLM; P < 0.05). Adjustment for TLM did not negate age differences in knee extension specific power (25-41% lower in older; P < 0.05) across loads tested. Older adults experienced fatigue across 10 repetitions of knee extension as peak velocity fell by 24% (P < 0.05). Deficits in concentric power persist after adjustment for TLM as maximum contractile velocity falls markedly with aging. Older adults are less capable of sustaining maximum concentric velocity during repetitive contractions. These findings suggest that velocity impairments are a possible contributor to mobility loss and falls risk among older adults. Interventions for improving contractile velocity should be pursued.     

Improved production of the tallysomycin H-1 in Streptoalloteichus hindustanus SB8005 strain by fermentation optimization

Tallysomycin (TLM) H-1, a novel TLM analog, is the major product isolated from Streptoalloteichus hindustanus SB8005, a genetically engineered strain from S. hindustanus E465-94 ATCC 31158. Based on the structural comparison and experimental assays, TLM H-1 represents a novel bleomycin (BLM) analog displaying DNA cleavage activity similar to its parent compounds TLM and BLM, both representatives of the glycopeptide anticancer antibiotics. The low titer of TLM H-1 in the engineered SB8005 strain has greatly limited its further study. In this paper, fermentation optimization for TLM H-1 production in the SB8005 strain is described; single-factor optimization and response surface methodology proved invaluable. The results indicated that three variables including distiller’s grains and solubles, copper sulfate, and maltose out of eight parameters could significantly influence the TLM H-1 production. With systematic comparison and evaluation, the final optimized fermentation medium was determined. The optimized yield of TLM H-1 in the bench-top fermentor was 249.9 mg/L, which is 26.8 times higher than reported using the original medium, and 12.9-fold higher than that of the parent compound TLM produced by the wild-type strain. This work provides important parameters for TLM H-1 production by fermentation and should facilitate further mechanistic studies and clinical developments of TLM H-1 as an anticancer agent.     

Numerical discretization-based estimation methods for ordinary differential equation models via penalized spline smoothing with applications in biomedical research

Differential equations are extensively used for modeling dynamics of physical processes in many scientific fields such as engineering, physics, and biomedical sciences. Parameter estimation of differential equation models is a challenging problem because of high computational cost and high-dimensional parameter space. In this article, we propose a novel class of methods for estimating parameters in ordinary differential equation (ODE) models, which is motivated by HIV dynamics modeling. The new methods exploit the form of numerical discretization algorithms for an ODE solver to formulate estimating equations. First, a penalized-spline approach is employed to estimate the state variables and the estimated state variables are then plugged in a discretization formula of an ODE solver to obtain the ODE parameter estimates via a regression approach. We consider three different order of discretization methods, Euler's method, trapezoidal rule, and Runge-Kutta method. A higher-order numerical algorithm reduces numerical error in the approximation of the derivative, which produces a more accurate estimate, but its computational cost is higher. To balance the computational cost and estimation accuracy, we demonstrate, via simulation studies, that the trapezoidal discretization-based estimate is the best and is recommended for practical use. The asymptotic properties for the proposed numerical discretization-based estimators are established. Comparisons between the proposed methods and existing methods show a clear benefit of the proposed methods in regards to the trade-off between computational cost and estimation accuracy. We apply the proposed methods t an HIV study to further illustrate the usefulness of the proposed approaches.     

HBx-EGFP-TLM融合蛋白表达载体的构建、蛋白表达纯化及活性检测

乙型肝炎病毒X蛋白 (HBx) 具有广泛的转录激活作用,但是由于细胞类型和实验条件的差异,外源启动子介导的HBx瞬时表达水平常表现出不均一性,为其功能的研究带来困难。为了解决HBx研究过程中遇到的这些难题,利用PCR扩增获得HBx及含转导肽TLM的EGFP编码序列,经酶切后插入pGEX-4T-1原核表达载体,成功构建重组质粒pGEX-HBx-EGFP-TLM和pGEX-EGFP-TLM。重组质粒转化大肠杆菌BL21(DE3) 感受态细胞,融合蛋白经IPTG诱导表达,采用?KTATM Purifier 蛋白纯化系统纯化并进行SDS-PAGE和Western blotting分析,确定为目的蛋白。将纯化后的融合蛋白分别与AML12和SMMC-7721细胞共孵育,Western blotting和激光共聚焦显微镜检测证实TLM转导肽能够介导HBx-EGFP和EGFP进入细胞,同时进入细胞的HBx-EGFP-TLM能够发挥转录激活活性,为HBx功能的深入研究奠定了基础。     

On the analysis of protein self-association by sedimentation velocity analytical ultracentrifugation

Analytical ultracentrifugation is one of the classical techniques for the study of protein interactions and protein self-association. Recent instrumental and computational developments have significantly enhanced this methodology. In this paper, new tools for the analysis of protein self-association by sedimentation velocity are developed, their statistical properties are examined, and considerations for optimal experimental design are discussed. A traditional strategy is the analysis of the isotherm of weight-average sedimentation coefficients s(w) as a function of protein concentration. From theoretical considerations, it is shown that integration of any differential sedimentation coefficient distribution c(s), ls-g(*)(s), or g(s(*)) can give a thermodynamically well-defined isotherm, as long as it provides a good model for the sedimentation profiles. To test this condition for the g(s(*)) distribution, a back-transform into the original data space is proposed. Deconvoluting diffusion in the sedimentation coefficient distribution c(s) can be advantageous to identify species that do not participate in the association. Because of the large number of scans that can be analyzed in the c(s) approach, its s(w) values are very precise and allow extension of the isotherm to very low concentrations. For all differential sedimentation coefficients, corrections are derived for the slowing of the sedimentation boundaries caused by radial dilution. As an alternative to the interpretation of the isotherm of the weight-average s value, direct global modeling of several sedimentation experiments with Lamm equation solutions was studied. For this purpose, a new software SEDPHAT is introduced, allowing the global analysis of several sedimentation velocity and equilibrium experiments. In this approach, information from the shape of the sedimentation profiles is exploited, which permits the identification of the association scheme and requires fewer experiments to precisely characterize the association. Further, under suitable conditions, fractions of incompetent material that are not part of the reversible equilibrium can be detected.     

Modeling auditory system nonlinearities through Volterra series

A computational method is reviewed, in which the solution of systems of nonlinear differential equations is written in terms of a Volterra functional series. Results of implementing the aforementioned technique in a computer program (exploiting new software for symbolic manipulation) and of applying it to a nonlinear oscillator model are presented. The relevance of this approach to Auditory System modeling is discussed. Suggestions are given, regarding possible applications to Speech Recognition problems.