Optimum coding framework for error detection in the self-assembly of the Sierpinski triangle.

This study presents a coding framework by which DNA self-assembly can be analysed for error detection. The proposed framework relies on coding and mapping functions that allow establishing the correctness of bonding each tile based on the codes of the tiles along a so-called traversal path. This method is different from the one that relies on comparing the pattern to be assembled (as defined by the tile set) and the current aggregate (as resulting from previously assembled tiles). As a widely used pattern and instantiation of this process, the Sierpinski triangle self-assembly is analysed in detail. The Sierpinski triangle is therefore utilised as an example to show the application of the proposed method. Different properties are proposed and its optimum coding is achieved for error detection. Simulation results are presented.

Parallel growth and healing of DNA self-assembly for interconnects.

Self-assembly has been employed in nano-technology to build crystals using individual components (commonly referred to as tiles) with limited control. Templates of regular lattice structures for two-dimensional scaffolds and interconnects have been recently implemented by self-assembly. This study proposes a diagonally based growth scheme that is applicable to these templates of interconnects (as an example). Differently from previous techniques (mostly sequential in execution), growth is allowed along two different directions in the aggregate, thus permitting a parallel mode of operation. This is made possible by utilising a tile set and binding scheme to allow multiple seed tiles to grow along the main diagonal of the pattern. The conditions by which this type of new growth is possible at a reduced error occurrence in mismatched tiles, are presented; error tolerance is achieved by employing healing and so-called robust generation of the seed tiles, thus ensuring that pattern growth is controlled along both directions. Simulation results are presented under different scenarios of growth direction (inclusive of backward growth for healing).

Healing assessment of tile sets for error tolerance in DNA self-assembly.

An assessment of the effectiveness of healing for error tolerance in DNA self-assembly tile sets for algorithmic/nano-manufacturing applications is presented. Initially, the conditions for correct binding of a tile to an existing aggregate are analysed using a Markovian approach; based on this analysis, it is proved that correct aggregation (as identified with a so-called ideal tile set) is not always met for the existing tile sets for nano-manufacturing. A metric for assessing tile sets for healing by utilising punctures is proposed. Tile sets are investigated and assessed with respect to features such as error (mismatched tile) movement, punctured area and bond types. Subsequently, it is shown that the proposed metric can comprehensively assess the healing effectiveness of a puncture type for a tile set and its capability to attain error tolerance for the desired pattern. Extensive simulation results are provided.

Analysis of punctures in DNA self-assembly under forward growth.

This paper deals with the characterization and analysis of intentionally induced punctures on a DNA self-assembly. Based on forward growth, punctures are utilized to remove errors in DNA tiles from the self-assembly. Initially, a Markov model is proposed by considering different types of punctures under various bonding conditions in the tiles. For different values of on and off rates (as corresponding to the parameters G(se) and G(mc)), it is shown that the proposed models can assess the types of puncture for removing mismatched tiles as errors. Subsequently, a novel model of puncturing is introduced to establish the condition by which a generic aggregate can utilize punctures for error resilience. It is proven that by using the correct puncture(s), errors as frozen mismatched tiles are moved toward the boundaries, thus ensuring the generation of the target assembly and ease in removal of the errors. As an example, the Sierpinski tile set is analyzed based on the proposed models to fully assess the appropriate type of puncture for this pattern. Simulation results are provided as evidence that the proposed models are effective.

Altered neuroendocrine response and gastric dysmotility in the Flinders Sensitive Line rat.

In the search for animal models that can replicate some features of functional dyspepsia (FD) patients, we turned our interest to the Flinders Sensitive Line (FSL) rat. Gastric motility disturbances prevalent in FD patients as well as urine corticosterone and plasma prolactin were measured following buspirone challenge. Flinders Resistant Line (FRL) rat was used as control. The results show that the FSL rats have a disturbed gastric motility, reflected as both an increased gastric accommodation rate and gastric volume during gastric distension as well as a delayed gastric emptying, the latter possibly as a consequence of the former. Lipid administration resulted in a significant increase in maximal gastric volume only in the FRL rats. Both the corticosterone response to buspirone and the 24-h urinary output of corticosterone were normal in FSL rats. Similar to FD patients, the FSL rat showed supersensitivity to buspirone in the increase in prolactin release. Although FSL rats show some features similar to a subset of FD patients, the increased gastric accommodation contrasts to the reduced accommodation often seen in FD patients. Further studies are warranted to determine the relevance of this rat strain as a model for FD.