Establishment of a biomimetic device based on tri-layer polymer actuators--propulsion fins

We propose to use bending type tri-layer polymer actuators as propulsion fins for a biomimetic device consisting of a rigid body, like a box fish having a carapace, and paired fins running through the rigid body, like a fish having pectoral fins. The fins or polymer bending actuators can be considered as individually controlled flexible membranes. Each fin is activated with sinusoidal inputs such that there is a phase lag between the movements of successive fins to create enough thrust force for propulsion. Eight fins with 0.125 aspect ratio have been used along both sides of the rigid body to move the device in the direction perpendicular to the longitudinal axis of the body. The designed device with the paired fins was successfully tested, moving in an organic solution consisting of solvent, propylene carbonate (PC), and electrolyte. The design procedure outlined in this study is offered as a guide to making functional devices based on polymer actuators and sensors.     

Cutting edge: Role of Toll-like receptor 9 in CpG DNA-induced activation of human cells

Unmethylated CpG motifs present in bacterial DNA stimulate a rapid and robust innate immune response. Human cell lines and PBMC that recognize CpG DNA express membrane-bound human Toll-like receptor 9 (hTLR9). Cells that are not responsive to CpG DNA become responsive when transfected with hTLR9. Expression of hTLR9 dramatically increases uptake of CpG (but not control) DNA into endocytic vesicles. Upon cell stimulation, hTLR9 and CpG DNA are found in the same endocytic vesicles. Cells expressing hTLR9 are stimulated by CpG motifs that are active in primates but not rodents, suggesting that evolutionary divergence between TLR9 molecules underlies species-specific differences in the recognition of bacterial DNA. These findings indicate that hTLR9 plays a critical role in the CpG DNA-mediated activation of human cells.     

Simulation of deformable models with the Poisson equation

In this paper, we present a new methodology for the deformation of soft objects by drawing an analogy between the Poisson equation and elastic deformation from the viewpoint of energy propagation. The potential energy stored due to a deformation caused by an external force is calculated and treated as the source injected into the Poisson system, as described by the law of conservation of energy. An improved Poisson model is developed for propagating the energy generated by the external force in a natural manner. An autonomous cellular neural network (CNN) model is established by using the analogy between the Poisson equation and CNN to solve the Poisson model for the real-time requirement of soft object deformation. A method is presented to derive the internal forces from the potential energy distribution. The proposed methodology models non-linear materials with the non-linear Poisson equation and thus non-linear CNN, rather than geometric non-linearity. It not only deals with large-range deformations, but also accommodates isotropic, anisotropic and inhomogeneous materials by simply modifying constitutive coefficients. A haptic virtual reality system has been developed for deformation simulation with force feedback. Examples are presented to demonstrate the efficiency of the proposed methodology.     

Exploiting mid-range DNA patterns for sequence classification: binary abstraction Markov models

Messenger RNA sequences possess specific nucleotide patterns distinguishing them from non-coding genomic sequences. In this study, we explore the utilization of modified Markov models to analyze sequences up to 44 bp, far beyond the 8-bp limit of conventional Markov models, for exon/intron discrimination. In order to analyze nucleotide sequences of this length, their information content is first reduced by conversion into shorter binary patterns via the application of numerous abstraction schemes. After the conversion of genomic sequences to binary strings, homogenous Markov models trained on the binary sequences are used to discriminate between exons and introns. We term this approach the Binary Abstraction Markov Model (BAMM). High-quality abstraction schemes for exon/intron discrimination are selected using optimization algorithms on supercomputers. The best MM classifiers are then combined using support vector machines into a single classifier. With this approach, over 95% classification accuracy is achieved without taking reading frame into account. With further development, the BAMM approach can be applied to sequences lacking the genetic code such as ncRNAs and 5'-untranslated regions.     

Biosorption of phenol and 2-chlorophenol by Funaliatrogii pellets

The removal of phenol (Ph) and 2-chlorophenol (2-CPh) from aqueous solution by native and heat inactivated fungus Funaliatrogii pellets were investigated. The effects of contact time, solid/liquid ratio, optimum pH and temperature on the phenols removal capacity by the pellets were established. The removal efficiency of phenols increased significantly with increasing biomass dose. The optimum pH was detected to be 8.0. The second-order equations are described and evaluated on the basis of a comparative estimation of the corresponding coefficients. The phenol removal equilibrium isotherm was modeled by the Langmuir equations. The enthalpy change values were obtained between −7.62 and −10.64 kJ/mol. This indicated that the uptake of phenols either on native or heat inactivated fungal pellets was based on a physical adsorption process.     

The discovery of novel calcium sensing receptor negative allosteric modulators

The design and profile of a series of zwitterionic calcium sensing receptor negative allosteric modulators is described. Evaluation of key analogues using a rat model demonstrate a robust response, significantly improved potency over ronacaleret and have the potential as an oral, anabolic treatment for osteoporosis.