Self-assembled poly(ethylene glycol) methyl ether-grafted gelatin nanogels for efficient delivery of curcumin in cancer treatment

Curcumin (CUR) is a natural active ingredient that attracted much attention for its chemotherapeutic activity against tumors without causing toxicity in healthy cells. However, it has certain limitations for being used in chemotherapy such as low aqueous solubility and hydrolytic instability in the physiological environment. In this study, self-assembled poly(ethylene glycol) methyl ether-grafted gelatin (Gel-mPEG) nanogels were fabricated as delivery systems to improve the applicability of CUR in cancer treatment. CUR-loaded Gel-mPEG nanogels exhibited desired size range, relatively colloidal stability, and provided enhanced CUR stability in aqueous solutions. Especially, they showed significant high CUR loading capacity and better anticancer activity than free CUR as compared to previously reported CUR-loaded nanogels according to the best of our knowledge. Moreover, the in vitro release of CUR from the nanogels was controlled and prolonged up to 96 h. These results demonstrated that Gel-mPEG nanogels are the promising modality for the efficient delivery of CUR in cancer treatment. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47544.     

An effective approach for maintenance of pre-large-based frequent-itemset lattice in incremental mining

Incremental mining has attracted the attention of many researchers due to its usefulness in online applications. Many algorithms have thus been proposed for incrementally mining frequent itemsets. Maintaining a frequent-itemset lattice (FIL) is difficult for databases with large numbers of frequent itemsets, especially huge databases, due to the storage of links of nodes in the lattice. However, generating association rules from a FIL has been shown to be more effective than traditional methods such as directly generating rules from frequent itemsets or frequent closed itemsets. Therefore, when the number of frequent itemsets is not huge (i.e., they can be stored in the lattice without excessive memory overhead), the lattice-based approach outperforms approaches which mine association rules from frequent itemsets/frequent closed itemsets. However, incremental algorithms for building FILs have not yet been proposed. This paper proposes an effective approach for the maintenance of a FIL based on the pre-large concept in incremental mining. The building process of a FIL is first improved using two proposed theorems regarding the paternity relation between two nodes in the lattice. An effective approach for maintaining a FIL with dynamically inserted data is then proposed based on the pre-large and the diffset concepts. The experimental results show that the proposed approach outperforms the batch approach for building a FIL in terms of execution time.     

A new method for mining Frequent Weighted Itemsets based on WIT-trees

The mining frequent itemsets plays an important role in the mining of association rules. Frequent itemsets are typically mined from binary databases where each item in a transaction may have a different significance. Mining Frequent Weighted Itemsets (FWI) from weighted items transaction databases addresses this issue. This paper therefore proposes algorithms for the fast mining of FWI from weighted item transaction databases. Firstly, an algorithm for directly mining FWI using WIT-trees is presented. After that, some theorems are developed concerning the fast mining of FWI. Based on these theorems, an advanced algorithm for mining FWI is proposed. Finally, a Diffset strategy for the efficient computation of the weighted support for itemsets is described, and an algorithm for mining FWI using Diffsets presented. A complete evaluation of the proposed algorithms is also presented.     

Left invertibility,flatness and identifiability of switched linear dynamical systems: a framework for cryptographic applications

The purpose of this article is to illustrate the potential interest of the control theory framework for cryptographic applications. It is shown that under the properties of left invertibility and flatness, dynamical systems are structurally equivalent to some specific cryptographic primitives called self-synchronising stream ciphers. After having motivated the interest of considering hybrid systems for such ciphers, the development is particularised for the special class of switched linear systems. We also show that identifiability is a necessary condition for security, and we describe an identification procedure as a possible attack and assess its complexity.     

Querying and creating visualizations by analogy

While there have been advances in visualization systems, particularly in multi-view visualizations and visual exploration, the process of building visualizations remains a major bottleneck in data exploration. We show that provenance metadata collected during the creation of pipelines can be reused to suggest similar content in related visualizations and guide semi-automated changes. We introduce the idea of query-by-example in the context of an ensemble of visualizations, and the use of analogies as first-class operations in a system to guide scalable interactions. We describe an implementation of these techniques in VisTrails, a publicly-available, open-source system.     

Noise-adaptive synthetic oversampling technique

Applied Intelligence - In the field of supervised learning, the problem of class imbalance is one of the most difficult problems, and has attracted a great deal of research attention in recent...     

Virtual Inflation of the Cerebral Artery Wall for the Integrated Exploration of OCT and Histology Data

Intravascular imaging provides new insights into the condition of vessel walls. This is crucial for cerebrovascular diseases including stroke and cerebral aneurysms, where it may present an important factor for indication of therapy. In this work, we provide new information of cerebral artery walls by combining ex vivo optical coherence tomography (OCT) imaging with histology data sets. To overcome the obstacles of deflated and collapsed vessels due to the missing blood pressure, the lack of co‐alignment as well as the geometrical shape deformations due to catheter probing, we developed the new image processing method virtual inflation. We locally sample the vessel wall thickness based on the (deflated) vessel lumen border instead of the vessel's centerline. Our method is embedded in a multi‐view framework where correspondences between OCT and histology can be highlighted via brushing and linking yielding OCT signal characteristics of the cerebral artery wall and its pathologies. Finally, we enrich the data views with a hierarchical clustering representation which is linked via virtual inflation and further supports the deduction of vessel wall pathologies.     

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