Dalian University of Technology

About: Dalian University of Technology is a education organization based out in Dalian, China. It is known for research contribution in the topics: Catalysis & Finite element method. The organization has 60890 authors who have published 71921 publications receiving 1188356 citations. The organization is also known as: Dàlián Lǐgōng Dàxué.

Ultralow-Power Near Infrared Lamp Light Operable Targeted Organic Nanoparticle Photodynamic Therapy

Abstract: Tissue penetration depth is a major challenge in practical photodynamic therapy (PDT) A biocompatible and highly effective near infrared (NIR)-light-absorbing carbazole-substituted BODIPY (Car-BDP) molecule is reported as a class of imaging-guidable deep-tissue activatable photosensitizers for PDT Car-BDP possesses an intense, broad NIR absorption band (600–800 nm) with a remarkably high singlet oxygen quantum yield (ΦΔ = 67%) After being encapsulated with biodegradable PLA–PEG-FA polymers, Car-BDP can form uniform and small organic nanoparticles that are water-soluble and tumor-targetable Rather than using laser light, such nanoparticles offer an unprecedented deep-tissue, tumor targeting photodynamic therapeutic effect by using an exceptionally low-power-density and cost-effective lamp light (12 mW cm–2) In addition, these nanoparticles can be simultaneously traced in vivo due to their excellent NIR fluorescence This study signals a major step forward in photodynamic therapy by developing a new cl

Metal–Organic Polymers Containing Discrete Single-Walled Nanotube as a Heterogeneous Catalyst for the Cycloaddition of Carbon Dioxide to Epoxides

Abstract: The cycloaddition of carbon dioxide to epoxides to produce cyclic carbonates is quite promising and does not result in any side products. A discrete single-walled metal-organic nanotube was synthesized by incorporating a tetraphenyl-ethylene moiety as the four-point connected node. The assembled complex has a large cross-section, with an exterior wall diameter of 3.6 nm and an interior channel diameter of 2.1 nm. It features excellent activity toward the cycloaddition of carbon dioxide, with a turnover number of 17,500 per mole of catalyst and an initial turnover frequency as high as 1000 per mole of catalyst per hour. Only minimal decreases in the catalytic activity were observed after 70 h under identical reaction conditions, and a total turnover number as high as 35,000 was achieved. A simple comparison of relative porous MOFs suggested that the cross-section of the channels is an important factor influencing the transport of the substrates and products through the channel.

Inhibiting the Corrosion-Promotion Activity of Graphene

Abstract: Though an excellent protection material, graphene possesses an unpleasant adverse side effect, which refers to the phenomenon that graphene can aggravate metal corrosion. This effect potentially impedes its applications in metal protection. This work aims to demonstrate a facile graphene encapsulation strategy to effectively inhibit the corrosion-promotion activity of graphene. We encapsulated reduced graphene oxide (rGO) with (3-aminopropyl)triethoxysilane (APTES). The composite of encapsulated rGO (rGO@APTES) has a flake-like structure with high aspect-ratio. Embedding appropriate amounts of rGO@APTES in polyvinyl butyral coating effectively enhances the barrier properties of the coating by suppressing the penetration of aggressive species. Besides, scratch tests further reveal that the corrosion-promotion activity of the graphene incorporated into the coating is completely inhibited. The strategy of graphene encapsulation can be extended to develop new graphene-based materials with superior physical an...

Inferring MicroRNA-Disease Associations by Random Walk on a Heterogeneous Network with Multiple Data Sources

Abstract: Since the discovery of the regulatory function of microRNA (miRNA), increased attention has focused on identifying the relationship between miRNA and disease. It has been suggested that computational method is an efficient way to identify potential disease-related miRNAs for further confirmation using biological experiments. In this paper, we first highlighted three limitations commonly associated with previous computational methods. To resolve these limitations, we established disease similarity subnetwork and miRNA similarity subnetwork by integrating multiple data sources, where the disease similarity is composed of disease semantic similarity and disease functional similarity, and the miRNA similarity is calculated using the miRNA-target gene and miRNA-lncRNA (long non-coding RNA) associations. Then, a heterogeneous network was constructed by connecting the disease similarity subnetwork and the miRNA similarity subnetwork using the known miRNA-disease associations. We extended random walk with restart to predict miRNA-disease associations in the heterogeneous network. The leave-one-out cross-validation achieved an average area under the curve (AUC) of $0.8049$ across $341$ diseases and $476$ miRNAs. For five-fold cross-validation, our method achieved an AUC from $0.7970$ to $0.9249$ for $15$ human diseases. Case studies further demonstrated the feasibility of our method to discover potential miRNA-disease associations. An online service for prediction is freely available at http://ifmda.aliapp.com .