Hairpin formation by single-stranded DNA molecules was exploited in a DNA-based computation in order to explore the feasibility of autonomous molecular computing. An instance of the satisfiability problem, a famous hard combinatorial problem, was solved by using molecular biology techniques. The satisfiability of a given Boolean formula was examined autonomously, on the basis of hairpin formation by the molecules that represent the formula. This computation algorithm can test several clauses in the given formula simultaneously, which could reduce the number of laboratory steps required for computation.

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We present methods for computation of flow-driven string dynamics in a pump and related residence time. The string dynamics computations help us understand how the strings carried by a fluid interact with the pump surfaces, including the blades, and get stuck on or around those surfaces. The residence time computations help us to have a simplified but quick understanding of the string behavior. The core computational method is the Space–Time Variational Multiscale (ST-VMS) method, and the other key methods are the ST Isogeometric Analysis (ST-IGA), ST Slip Interface (ST-SI) method, ST/NURBS Mesh Update Method (STNMUM), a general-purpose NURBS mesh generation method for complex geometries, and a one-way-dependence model for the string dynamics. The ST-IGA with NURBS basis functions in space is used in both fluid mechanics and string structural dynamics. The ST framework provides higher-order accuracy. The VMS feature of the ST-VMS addresses the computational challenges associated with the turbulent nature of the unsteady flow, and the moving-mesh feature of the ST framework enables high-resolution computation near the rotor surface. The ST-SI enables moving-mesh computation of the spinning rotor. The mesh covering the rotor spins with it, and the SI between the spinning mesh and the rest of the mesh accurately connects the two sides of the solution. The ST-IGA enables more accurate representation of the pump geometry and increased accuracy in the flow solution. The IGA discretization also enables increased accuracy in the structural dynamics solution, as well as smoothness in the string shape and fluid dynamics forces computed on the string. The STNMUM enables exact representation of the mesh rotation. The general-purpose NURBS mesh generation method makes it easier to deal with the complex geometry we have here. With the one-way-dependence model, we compute the influence of the flow on the string dynamics, while avoiding the formidable task of computing the influence of the string on the flow, which we expect to be small.

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In our previous paper, we described a method by which a state machine is implemented by a single-stranded DNA molecule whose 3%-end sequence encodes the current state of the machine. Successive state transitions are performed in such a way that the current state is annealed onto an appropriate portion of DNA encoding the transition table of the state machine and the next state is copied to the 3%-end by extension with polymerase. In this paper, we first show that combined with parallel overlap assembly, a single series of successive transitions can solve NP-complete problems. This means that the number of necessary laboratory steps is independent from the problem size. We then report the results of two experiments concerning the implementation of our method. One is on isothermal reactions which greatly increase the efficiency of state transitions compared with reactions controlled by thermal cycles. The other is on the use of unnatural bases for avoiding out-of-frame annealing. The latter result can also be applied to many DNA-based computing paradigms.

Computational fluid dynamics simulation is useful for precise evaluation of hemodynamics related to bicuspid aortic valve aortopathy. Such evaluation will advance our understanding of the disease pathophysiology and may facilitate molecular biological investigation.

An artificial DNA circuit in giant unilamellar vesicles allows isothermal amplification of DNA by over 5000-fold within several hours.

In this work, we report the development and experimental validation of a coupled statistical thermodynamic model allowing prediction of the structural transitions executed by a novel DNA nanodevice, for quantitative operational design. The efficiency of target structure formation by this nanodevice, implemented with a bistable DNA molecule designed to transform between three distinct structures, is modeled by coupling the isolated equilibrium models for the individual structures. A peculiar behavior is predicted for this nanodevice, which forms the target structure within a limited temperature range by sensing thermal variations. The predicted thermal response is then validated via fluorescence measurements to quantitatively assess whether the nanodevice performs as designed. Agreement between predictions and experiment was substantial, with a 0.95 correlation for overall curve shape over a wide temperature range, from 30C to 90C. The obtained accuracy, which is comparable to that of conventional melting behavior prediction for DNA duplexes in isolation, ensures the applicability of the coupled model for illustrating general DNA reaction systems involving competitive duplex formation. Finally, tuning of the nanodevice using the current model towards design of a thermal band pass filter to control chemical circuits, as a novel function of DNA nanodevices is proposed.