The recent decades have seen a surge of new nanomaterials designed for efficient drug delivery. DNA nanotechnology has been developed to construct sophisticated 3D nanostructures and artificial ...molecular devices that can be operated at the nanoscale, giving rise to a variety of programmable functions and fascinating applications. In particular, DNA‐origami nanostructures feature rationally designed geometries and precise spatial addressability, as well as marked biocompatibility, thus providing a promising candidate for drug delivery. Here, the recent successful efforts to employ self‐assembled DNA‐origami nanostructures as drug‐delivery vehicles are summarized. The remaining challenges and open opportunities are also discussed.
Structural DNA nanotechnology provides a biocompatible platform to construct customized nanocarriers. Recent developments of DNA‐origami‐based drug‐delivery systems are summarized. Multifunctional, highly tunable, and biologically amenable, DNA‐based nanomaterials will provide powerful strategies to understand and treat disease.
Multidrug resistance (MDR) is a major obstacle in the clinical treatment of cancer. Herein, a facile strategy is reported to construct a versatile DNA nanostructure as a co‐delivery vector of RNA ...interference (RNAi) and chemodrugs to combat multidrug‐resistant tumor (MCF‐7R) in vitro and in vivo. In the tailored nanocarrier, two linear small hairpin RNA (shRNA) transcription templates targeting MDR‐associated genes (gene of P‐glycoprotein, a typical drug efflux pump; and gene of survivin, a representative anti‐apoptotic protein) are precisely organized in the chemodrug (doxorubicin, DOX) pre‐loaded DNA origami. With the incorporation of active targeting and controlled‐release elements, these multifunctional DNA nanocarriers can successfully enter the target MCF‐7R cells and synergistically inhibit tumor growth without apparent systemic toxicity. This tailored DNA nanoplatform, which combines RNAi therapy and chemotherapy, provides a new strategy for the treatment of multidrug‐resistant tumors.
A DNA nanoplatform‐based co‐delivery system containing two linear shRNA transcription templates against tumor‐associated genes (Pgp and survive) and a chemotherapeutic drug (doxorubicin, DOX) was constructed for synergistic therapy of multidrug resistant (MDR) tumors in vivo.
The efficient delivery of a therapeutic gene into target tissues has remained a major obstacle in realizing a viable gene-based medicine. Herein, we introduce a facile and universal strategy to ...construct a DNA nanostructure-based codelivery system containing a linear tumor therapeutic gene (p53) and a chemotherapeutic drug (doxorubicin, DOX) for combined therapy of multidrug resistant tumor (MCF-7R). This novel codelivery system, which is structurally similar to a kite, is rationally designed to contain multiple functional groups for the targeted delivery and controlled release of the therapeutic cargoes. The self-assembled DNA nanokite achieves efficient gene delivery and exhibits effective inhibition of tumor growth in vitro and in vivo without apparent systemic toxicity. These structurally and chemically well-defined codelivery nanovectors provide a new platform for the development of gene therapeutics for not only cancer but also a wide range of diseases.
Using the DNA origami technique, we constructed a DNA nanodevice functionalized with small interfering RNA (siRNA) within its inner cavity and the chemotherapeutic drug doxorubicin (DOX), ...intercalated in the DNA duplexes. The incorporation of disulfide bonds allows the triggered mechanical opening and release of siRNA in response to intracellular glutathione (GSH) in tumors to knockdown genes key to cancer progression. Combining RNA interference and chemotherapy, the nanodevice induced potent cytotoxicity and tumor growth inhibition, without observable systematic toxicity. Given its autonomous behavior, exceptional designability, potent antitumor activity and marked biocompatibility, this DNA nanodevice represents a promising strategy for precise drug design for cancer therapy.
An autonomous tubular DNA nanodevice is constructed to deliver a chemotherapeutic drug and siRNAs. This nanodevice can realize on‐demand targeting, respond to stimuli in the intracellular environment and release multiple molecular payloads for combined antitumor activity.
Nanoscale robots have potential as intelligent drug delivery systems that respond to molecular triggers. Using DNA origami we constructed an autonomous DNA robot programmed to transport payloads and ...present them specifically in tumors. Our nanorobot is functionalized on the outside with a DNA aptamer that binds nucleolin, a protein specifically expressed on tumor-associated endothelial cells, and the blood coagulation protease thrombin within its inner cavity. The nucleolin-targeting aptamer serves both as a targeting domain and as a molecular trigger for the mechanical opening of the DNA nanorobot. The thrombin inside is thus exposed and activates coagulation at the tumor site. Using tumor-bearing mouse models, we demonstrate that intravenously injected DNA nanorobots deliver thrombin specifically to tumor-associated blood vessels and induce intravascular thrombosis, resulting in tumor necrosis and inhibition of tumor growth. The nanorobot proved safe and immunologically inert in mice and Bama miniature pigs. Our data show that DNA nanorobots represent a promising strategy for precise drug delivery in cancer therapy.
A graphene oxide (GO) modified glassy carbon electrode (GCE), namely GO/GCE was prepared by covalent coupling method, which was characterized by atomic force microscope (AFM), cyclic voltammetry (CV) ...and electrochemical impedance spectra (EIS). On this modified electrode, it is found that the electrochemistry of dopamine (DA) is greatly enhanced, while that of ascorbic acid (AA) is totally impressed, showing that the modified layer of GO has completely different impact on the electrochemical response of DA and AA. The probable mechanism to cause the different impact was proposed. GO/GCE was further applied as a biosensor for the determination of DA in the presence of with AA, and the results showed that the coexisted AA has no interference toward the electrochemistry of DA. The oxidation peak currents of DA present a good linear relationship with the concentrations in the range from 1.0μM to 15.0μM with a detection limit of 0.27μM. The electrochemical parameters such as the electron transfer rate constant, catalytic rate constant, diffusion coefficient, and electron/proton transfer number of DA on GO/GCE were also studied.
DaDianNao: A Neural Network Supercomputer Tao Luo; Shaoli Liu; Ling Li ...
IEEE transactions on computers,
2017-Jan.-1, 2017-1-1, 20170101, Letnik:
66, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Many companies are deploying services largely based on machine-learning algorithms for sophisticated processing of large amounts of data, either for consumers or industry. The state-of-the-art and ...most popular such machine-learning algorithms are Convolutional and Deep Neural Networks (CNNs and DNNs), which are known to be computationally and memory intensive. A number of neural network accelerators have been recently proposed which can offer high computational capacity/area ratio, but which remain hampered by memory accesses. However, unlike the memory wall faced by processors on general-purpose workloads, the CNNs and DNNs memory footprint, while large, is not beyond the capability of the on-chip storage of a multi-chip system. This property, combined with the CNN/DNN algorithmic characteristics, can lead to high internal bandwidth and low external communications, which can in turn enable high-degree parallelism at a reasonable area cost. In this article, we introduce a custom multi-chip machine-learning architecture along those lines, and evaluate performance by integrating electrical and optical inter-chip interconnects separately. We show that, on a subset of the largest known neural network layers, it is possible to achieve a speedup of 656.63× over a GPU, and reduce the energy by 184.05× on average for a 64-chip system. We implement the node down to the place and route at 28 nm, containing a combination of custom storage and computational units, with electrical inter-chip interconnects.
Neural networks (NNs) have been demonstrated to be useful in a broad range of applications such as image recognition, automatic translation and advertisement recommendation. State-of-the-art NNs are ...known to be both computationally and memory intensive, due to the ever-increasing deep structure, i.e., multiple layers with massive neurons and connections (i.e., synapses). Sparse neural networks have emerged as an effective solution to reduce the amount of computation and memory required. Though existing NN accelerators are able to efficiently process dense and regular networks, they cannot benefit from the reduction of synaptic weights. In this paper, we propose a novel accelerator, Cambricon-X, to exploit the sparsity and irregularity of NN models for increased efficiency. The proposed accelerator features a PE-based architecture consisting of multiple Processing Elements (PE). An Indexing Module (IM) efficiently selects and transfers needed neurons to connected PEs with reduced bandwidth requirement, while each PE stores irregular and compressed synapses for local computation in an asynchronous fashion. With 16 PEs, our accelerator is able to achieve at most 544 GOP/s in a small form factor (6.38 mm 2 and 954 mW at 65 nm). Experimental results over a number of representative sparse networks show that our accelerator achieves, on average, 7.23x speedup and 6.43x energy saving against the state-of-the-art NN accelerator.
Cambricon-s Zhou, Xuda; Du, Zidong; Guo, Qi ...
2018 51st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO),
10/2018
Conference Proceeding
Neural networks have become the dominant algorithms rapidly as they achieve state-of-the-art performance in a broad range of applications such as image recognition, speech recognition and natural ...language processing. However, neural networks keep moving towards deeper and larger architectures, posing a great challenge to the huge amount of data and computations. Although sparsity has emerged as an effective solution for reducing the intensity of computation and memory accesses directly, irregularity caused by sparsity (including sparse synapses and neurons) prevents accelerators from completely leveraging the benefits; it also introduces costly indexing module in accelerators.
In this paper, we propose a cooperative software/hardware approach to address the irregularity of sparse neural networks efficiently. Initially, we observe the local convergence, namely larger weights tend to gather into small clusters during training. Based on that key observation, we propose a software-based coarse-grained pruning technique to reduce the irregularity of sparse synapses drastically. The coarse-grained pruning technique, together with local quantization, significantly reduces the size of indexes and improves the network compression ratio. We further design a hardware accelerator, Cambricon-S, to address the remaining irregularity of sparse synapses and neurons efficiently. The novel accelerator features a selector module to filter unnecessary synapses and neurons. Compared with a state-of-the-art sparse neural network accelerator, our accelerator is 1.71x and 1.37x better in terms of performance and energy efficiency, respectively.
•Coupling non-Darcy flow was produced by pumping wells and diaphragm wall.•Coupling non-Darcy flow was used in foundation pit dewatering for larger drawdown.•Coupling non-Darcy flow occurred between ...pumping wells and diaphragm wall toe.•Diaphragm wall significantly increased non-Darcy area of the pumping wells.•Short filter tube, large pumping rate well close to diaphragm wall was suggested.
High-velocity non-Darcy flow produced larger drawdown than Darcy flow under the same pumping rate. When the non-Darcy flow caused by curtain met non-Darcy flow caused by pumping wells, superposition and amplification effect occurred in the coupling area, the non-Darcy flow was defined as coupling non-Darcy flow. The coupling non-Darcy flow can be produced and controlled using different combination of curtain and pumping wells in foundation pit dewatering to obtain the maximum drawdown using the minimum pumping rate. The Qianjiang Century City Station foundation pit of Hangzhou subway, China, was selected as background. Field experiments were performed to observe the coupling non-Darcy flow in round gravel. A generalized conceptual model was established to study the coupling effect under different combination of curtain and pumping wells. Numerical simulations of the coupling non-Darcy flow in foundation pit dewatering were carried out based on the Forchheimer equation. The non-Darcy flow area and flow velocity were influenced by the coupling effect. Short filter tube, large pumping rate, small horizontal distance between filter tube and diaphragm wall, and small vertical distance between the filter tube and confined aquifer roof effectively strengthened the coupling effect and obtained a large drawdown. The pumping wells installed close to a curtain was an intentional choice designed to create coupling non-Darcy flow and obtain the maximize drawdown. It can be used in the dewatering of a long and narrow foundation pit, such as a subway foundation pit.
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