Finite element modeling of the left atrium to facilitate the design of an endoscopic atrial retractor

With the worldwide prevalence of cardiovascular diseases, much attention has been focused on simulating the characteristics of the human heart to better understand and treat cardiac disorders. The purpose of this study is to build a finite element model of the left atrium (LA) that incorporates detailed anatomical features and realistic material characteristics to investigate the interaction of heart tissue and surgical instruments. This model is used to facilitate the design of an endoscopically deployable atrial retractor for use in minimally invasive, robotically assisted mitral valve repair. Magnetic resonance imaging (MRI) scans of a pressurized explanted porcine heart were taken to provide a 3D solid model of the heart geometry, while uniaxial tensile tests of porcine left atrial tissue were conducted to obtain realistic material properties for noncontractile cardiac tissue. A finite element model of the LA was constructed using ANSYS Release 9.0 software and the MRI data. The Mooney-Rivlin hyperelastic material model was chosen to characterize the passive left atrial tissue; material constants were derived from tensile test data. Finite element analysis (FEA) models of a CardioVations Port Access retractor and a prototype endoscopic retractor were constructed to simulate interaction between each instrument and the LA. These contact simulations were used to compare the quality of retraction between the two instruments and to optimize the design of the prototype retractor. Model accuracy was verified by comparing simulated cardiac wall deflections to those measured by MRI. FEA simulations revealed that peak forces of approximately 2.85 N and 2.46 N were required to retract the LA using the Port Access and prototype retractors, respectively. These forces varied nonlinearly with retractor blade displacement. Dilation of the atrial walls and rigid body motion of the chamber were approximately the same for both retractors. Finite element analysis is shown to be an effective tool for analyzing instrument/tissue interactions and for designing surgical instruments. The benefits of this approach to medical device design are significant when compared to the alternatives: constructing prototypes and evaluating them via animal or clinical trials.     

Improving micropropagation of Mentha × piperita L. using a liquid culture system

In the current study, in vitro shoot proliferation and plant regeneration of Mentha × piperita L. (peppermint) cultivar ‘Black Mitcham’ was compared in semi-solid and liquid culture systems. Shoot tips from field-grown plants were used as explants to study shoot proliferation response on either Murashige and Skoog (MS) or Chee and Pool (C2D) medium containing varying levels of 6-benzylaminopurine (BAP), kinetin, and 6-γ,γ-dimethylallyl aminopurine (2iP). Differences in leaf ultrastructure and antioxidant capacity of greenhouse-grown and micropropagation-derived plants were studied to identify potential changes occurring during in vitro culture. Among the various media treatments tested, the maximum number of shoots was produced on the C2D medium with 4.0 μM BAP (40.7) followed by the MS medium with 4.0 μM BAP (32.2). Among the rooting treatments, shoots on the MS medium with 1.0 μM indole-3-butyric acid (IBA) produced the maximum number of roots (14.4). The number of shoots produced in Liquid Lab Rocker® (LLR) vessels containing liquid C2D medium with BAP (103.4) was significantly higher than that produced on semi-solid medium (40.7). No differences were observed in the leaf ultrastructure and antioxidant capacity of leaf extracts obtained from greenhouse-grown and micropropagation-derived plants. The study indicates that the liquid culture system under the described conditions can enhance peppermint micropropagation, with plant material being potentially valuable for use in herbal supplements and essential oil production.

     

Correction to: Improving micropropagation of Mentha × piperita L. using a liquid culture system

In Vitro Cellular & Developmental Biology - Plant - This correction reflects Sadanand A. Dhekney’s updated e-mail address and affiliation.     

Distance-dependent dielectric constants and their application to double-helical DNA

Detailed studies of structures of biological macromolecules, even in simplified models, involve many costly and time-consuming calculations. Any thorough methods require sampling of an extremely large conformation and momentum space. Calculations of electrostatic interactions, which depend on many physical factors, such as the details of solvent, solvent accessibility in macromolecules, and molecular polarizability, are always developed in a compromise between more rigorous, detailed models and the need for immediate application to complicated biological systems. In this paper, a middle ground is taken between the more exact theoretical models and the simplest constant values for the dielectric constant. The effects of solvent, counterions, and molecular polarizability are incorporated through a set of adjustable parameters that should be determined from experimental conditions. Several previous forms for the dielectric function are compared with the new ones. The present methods use Langevin functions to span the region of dielectric constant between bulk solvent and cavity values. Application of such dielectric models to double-helical DNA is important because base-stacking preferences were previously demonstrated [A. Sarai, J. Mazur, R. Nussinov, and R. L. Jernigan (1988) Biochemistry, vol. 27, pp. 8498-8502] to be sensitive to the electrostatic formulation. Here we find that poly(dG).poly(dC) can be A form for high screening and B form for low screening. By contrast, poly(dA).poly(dT) can only take the B form. Base stacking is more sensitive to the form of the dielectric function than are the sugar-phosphate backbone conformations. Also in B form, the backbone conformations are not so affected by the base types as in A form.     

A Consensus Data Mining secondary structure prediction by combining GOR V and Fragment Database Mining

The major aim of tertiary structure prediction is to obtain protein models with the highest possible accuracy. Fold recognition, homology modeling, and de novo prediction methods typically use predicted secondary structures as input, and all of these methods may significantly benefit from more accurate secondary structure predictions. Although there are many different secondary structure prediction methods available in the literature, their cross-validated prediction accuracy is generally <80%. In order to increase the prediction accuracy, we developed a novel hybrid algorithm called Consensus Data Mining (CDM) that combines our two previous successful methods: (1) Fragment Database Mining (FDM), which exploits the Protein Data Bank structures, and (2) GOR V, which is based on information theory, Bayesian statistics, and multiple sequence alignments (MSA). In CDM, the target sequence is dissected into smaller fragments that are compared with fragments obtained from related sequences in the PDB. For fragments with a sequence identity above a certain sequence identity threshold, the FDM method is applied for the prediction. The remainder of the fragments are predicted by GOR V. The results of the CDM are provided as a function of the upper sequence identities of aligned fragments and the sequence identity threshold. We observe that the value 50% is the optimum sequence identity threshold, and that the accuracy of the CDM method measured by Q(3) ranges from 67.5% to 93.2%, depending on the availability of known structural fragments with sufficiently high sequence identity. As the Protein Data Bank grows, it is anticipated that this consensus method will improve because it will rely more upon the structural fragments.     

An enhanced elastic network model to represent the motions of domain-swapped proteins

Domain swapping is a process where two (or more) protein molecules form a dimer (or higher oligomer) by exchanging an identical domain. In this article, based on the observation that domains are rigid and hinge loops are highly flexible, we propose a new Elastic Network Model, domain-ENM, for domain-swapped proteins. In this model, the rigidity of domains is taken into account by using a larger spring constant for intradomain contacts. The large-scale transition of domain swapping is then novelly decomposed into the relative motion between the rigid domains (only 6 degrees of freedom) plus the internal fluctuations of each domain. Consequently, this approach has the potential to produce much more meaningful transition pathways than other simulation approaches that try to find pathways in a search space of large numbers of dimensions. In this article, we also propose a new way to define the overlap measure. Past approaches used an inappropriate comparison of the large-scale conformation displacement against the computed infinitesimal motions of modes. Here, we propose an infinitesimal version of the large-scale conformation change and then compare it with the modes of motions. As a result, we obtain much better overlap values. Using this new overlap definition, we are also able for the first time to give a clear, intuitive explanation why "open" forms tend to produce better overlap values than "closed" forms with traditional ENMs. Finally, as an application, we present a simple approach to show how domain-ENM can be used to generated transition pathways for domain-swapped proteins.