Arsenic, an ancient drug used in traditional Chinese medicine, has attracted worldwide interest because it shows substantial anticancer activity in patients with acute promyelocytic leukemia (APL). Arsenic trioxide (As2O3) exerts its therapeutic effect by promoting degradation of an oncogenic protein that drives the growth of APL cells, PML-RARalpha (a fusion protein containing sequences from the PML zinc finger protein and retinoic acid receptor alpha). PML and PML-RARalpha degradation is triggered by their SUMOylation, but the mechanism by which As2O3 induces this posttranslational modification is unclear. Here we show that arsenic binds directly to cysteine residues in zinc fingers located within the RBCC domain of PML-RARalpha and PML. Arsenic binding induces PML oligomerization, which increases its interaction with the small ubiquitin-like protein modifier (SUMO)-conjugating enzyme UBC9, resulting in enhanced SUMOylation and degradation. The identification of PML as a direct target of As2O3 provides new insights into the drug's mechanism of action and its specificity for APL.

local scanning. First, an objectness-based segmentation method is introduced to extract semantic objects from the current scene surface via a multi-class graph cuts minimization. Then, an object of interest (OOI) is identified as the NBO which the robot aims to visit and scan. The robot then conducts fine scanning on the OOI with views determined by the NBV strategy. When the OOI is recognized as a full object, it can be replaced by its most similar 3D model in a shape database. The algorithm iterates until all of the objects are recognized and reconstructed in the scene. Various experiments and comparisons have shown the feasibility of our proposed approach.

This work aims to help the designers to make decisions in the early stage of new product development. Design concept evaluation is very critical in design process, it may affect the later stages. However, facing to uncertain circumstance, mostly, the raw data in early stage are subjective and imprecise. This work proposes a novel approach to solve this problem. The whole work is based on rough numbers, Shannon entropy, technique for order performance by similarity to ideal solution method and preference selection index method. Firstly, rough numbers and Shannon entropy are integrated to determine the weight of evaluation criteria based on their interrelationships. After that, a novel technique for order performance by similarity to ideal solution method improved by rough numbers and preference selection index method is proposed to evaluate and rank the alternatives. Then, a comparative case is carried out with proposed method and two other methods in this study. The comparation of evaluation processes indicates that the proposed method’s advantage. Compared the other methods, proposed approach is objective, simple and do not need additional input. The results of three methods are similar. It means that the proposed method is not only effective and efficient in design concept evaluation, but also can save time and cost in the early stage of new product development.

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