To construct sophisticated biochemical circuits from scratch, one needs to understand how simple the building blocks can be and how robustly such circuits can scale up. Using a simple DNA reaction ...mechanism based on a reversible strand displacement process, we experimentally demonstrated several digital logic circuits, culminating in a four-bit square-root circuit that comprises 130 DNA strands. These multilayer circuits include thresholding and catalysis within every logical operation to perform digital signal restoration, which enables fast and reliable function in large circuits with roughly constant switching time and linear signal propagation delays. The design naturally incorporates other crucial elements for large-scale circuitry, such as general debugging tools, parallel circuit preparation, and an abstraction hierarchy supported by an automated circuit compiler.
The impressive capabilities of the mammalian brain--ranging from perception, pattern recognition and memory formation to decision making and motor activity control--have inspired their re-creation in ...a wide range of artificial intelligence systems for applications such as face recognition, anomaly detection, medical diagnosis and robotic vehicle control. Yet before neuron-based brains evolved, complex biomolecular circuits provided individual cells with the 'intelligent' behaviour required for survival. However, the study of how molecules can 'think' has not produced an equal variety of computational models and applications of artificial chemical systems. Although biomolecular systems have been hypothesized to carry out neural-network-like computations in vivo and the synthesis of artificial chemical analogues has been proposed theoretically, experimental work has so far fallen short of fully implementing even a single neuron. Here, building on the richness of DNA computing and strand displacement circuitry, we show how molecular systems can exhibit autonomous brain-like behaviours. Using a simple DNA gate architecture that allows experimental scale-up of multilayer digital circuits, we systematically transform arbitrary linear threshold circuits (an artificial neural network model) into DNA strand displacement cascades that function as small neural networks. Our approach even allows us to implement a Hopfield associative memory with four fully connected artificial neurons that, after training in silico, remembers four single-stranded DNA patterns and recalls the most similar one when presented with an incomplete pattern. Our results suggest that DNA strand displacement cascades could be used to endow autonomous chemical systems with the capability of recognizing patterns of molecular events, making decisions and responding to the environment.
The prospects of programming molecular systems to perform complex autonomous tasks have motivated research into the design of synthetic biochemical circuits. Of particular interest to us are ...cell-free nucleic acid systems that exploit non-covalent hybridization and strand displacement reactions to create cascades that implement digital and analogue circuits. To date, circuits involving at most tens of gates have been demonstrated experimentally. Here, we propose a simple DNA gate architecture that appears suitable for practical synthesis of large-scale circuits involving possibly thousands of gates.
The dynamic interactions between complex molecular structures underlie a wide range of sophisticated behaviors in biological systems. In building artificial molecular machines out of DNA, an ...outstanding challenge is to develop mechanisms that can control the kinetics of interacting DNA nanostructures and that can compose the interactions together to carry out system-level functions. Here we show a mechanism of DNA tile displacement that follows the principles of toehold binding and branch migration similar to DNA strand displacement, but occurs at a larger scale between interacting DNA origami structures. Utilizing this mechanism, we show controlled reaction kinetics over five orders of magnitude and programmed cascades of reactions in multi-structure systems. Furthermore, we demonstrate the generality of tile displacement for occurring at any location in an array in any order, illustrated as a tic-tac-toe game. Our results suggest that tile displacement is a simple-yet-powerful mechanism that opens up the possibility for complex structural components in artificial molecular machines to undergo information-based reconfiguration in response to their environments.
A cargo-sorting DNA robot Thubagere, Anupama J.; Li, Wei; Johnson, Robert F. ...
Science (American Association for the Advancement of Science),
09/2017, Letnik:
357, Številka:
6356
Journal Article
Recenzirano
Odprti dostop
Two critical challenges in the design and synthesis of molecular robots are modularity and algorithm simplicity. We demonstrate three modular building blocks for a DNA robot that performs cargo ...sorting at the molecular level. A simple algorithm encoding recognition between cargos and their destinations allows for a simple robot design: a single-stranded DNA with one leg and two foot domains for walking, and one arm and one hand domain for picking up and dropping off cargos. The robot explores a two-dimensional testing ground on the surface of DNA origami, picks up multiple cargos of two types that are initially at unordered locations, and delivers them to specified destinations until all molecules are sorted into two distinct piles. The robot is designed to perform a random walk without any energy supply. Exploiting this feature, a single robot can repeatedly sort multiple cargos. Localization on DNA origami allows for distinct cargo-sorting tasks to take place simultaneously in one test tube or for multiple robots to collectively perform the same task.
Models of well-mixed chemical reaction networks (CRNs) have provided a solid foundation for the study of programmable molecular systems, but the importance of spatial organization in such systems has ...increasingly been recognized. In this paper, we explore an alternative chemical computing model introduced by Qian & Winfree in 2014, the surface CRN, which uses molecules attached to a surface such that each molecule only interacts with its immediate neighbours. Expanding on the constructions in that work, we first demonstrate that surface CRNs can emulate asynchronous and synchronous deterministic cellular automata and implement continuously active Boolean logic circuits. We introduce three new techniques for enforcing synchronization within local regions, each with a different trade-off in spatial and chemical complexity. We also demonstrate that surface CRNs can manufacture complex spatial patterns from simple initial conditions and implement interesting swarm robotic behaviours using simple local rules. Throughout all example constructions of surface CRNs, we highlight the trade-off between the ability to precisely place molecules and the ability to precisely control molecular interactions. Finally, we provide a Python simulator for surface CRNs with an easy-to-use web interface, so that readers may follow along with our examples or create their own surface CRN designs.
Multi-scale feature fusion techniques and covariance pooling have been shown to have positive implications for completing computer vision tasks, including fine-grained image classification. However, ...existing algorithms that use multi-scale feature fusion techniques for fine-grained classification tend to consider only the first-order information of the features, failing to capture more discriminative features. Likewise, existing fine-grained classification algorithms using covariance pooling tend to focus only on the correlation between feature channels without considering how to better capture the global and local features of the image. Therefore, this paper proposes a multi-scale covariance pooling network (MSCPN) that can capture and better fuse features at different scales to generate more representative features. Experimental results on the CUB200 and MIT indoor67 datasets achieve state-of-the-art performance (CUB200: 94.31% and MIT indoor67: 92.11%).
The original version of this Article omitted a reference to previous work in 'Stojanovic, M. N. & Stefanovic, D. A deoxyribozyme-based molecular automaton. Nat. Biotechnol. 21, 1069-1074 (2003)'. ...This has been added as reference 42. The following has been added after the third sentence of the fifth paragraph of the Discussion: 'Integration could also allow more sophisticated information processing, for example as shown by the classic deoxyribozyme-based automaton that plays tic-tac-toe
, to direct structural reconfiguration (Supplementary Discussion)'. This has been corrected in the PDF and HTML versions of the Article.
The dynamic responses and load sharing features of a two-path split torque gear transmission system are investigated in this study. The possible combinations of shaft angles to ensure the gear pairs ...work properly are determined considering the adjacency relationship, concentric relationship, geometrical conditions and installation conditions. A dynamic model of the system considering time-varying mesh stiffness, backlash, static transmission error, stagger angle excitations and gyroscopic effects of gear body and flexible shaft is proposed. The natural characteristics of the system including natural frequencies and critical speeds are obtained. The influences of the shaft angle, asymmetric transmission error excitations and right-to-left stagger angle of double-helical gear teeth on the dynamic transmission error responses and load sharing features of the two-path split torque gear transmission system are investigated. Several references to determine the system parameters to improve the transmission property and load sharing performance of the system are provided based on the numerical simulation results.
Gastric cancer is one of the most common malignancies worldwide and vasculogenic mimicry (VM) is considered to be the leading cause for the failure of anti-angiogenesis therapy in advanced gastric ...cancer patients. In the present study, we investigate the role of tenascin-c (TNC) in the formation of VM in gastric cancer and found that TNC was upregulated in gastric cancer tissue than in the corresponding adjacent tissues and correlated with VM and poor prognosis of gastric cancer. Furthermore, knockdown of TNC significantly inhibited VM formation and proliferation of gastric cancer cells in vitro and in vivo, with a reduction in cell migration and invasion. Mechanistically, TNC knockdown suppressed the phosphorylation of ERK and subsequently inhibited the process of EMT, both of which play an important role in VM formation. Our results indicated that TNC plays an important role in VM formation in gastric cancer. Combining inhibition of TNC and ERK may be a potential therapeutic approach to inhibit gastric cancer growth and metastasis and decrease antiangiogenic therapeutic resistance.
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