Efficient calculation of the robustness measure R for complex networks

In a recent work, Schneider et al. (2011) proposed a new measure R for network robustness, where the value of R is calculated within the entire process of malicious node attacks. In this paper, we present an approach to improve the calculation efficiency of R, in which a computationally efficient robustness measure R' is introduced when the fraction of failed nodes reaches to a critical threshold qc. Simulation results on three different types of network models and three real networks show that these networks all exhibit a computationally efficient robustness measure R'. The relationships between R' and the network size N and the network average degree are also explored. It is found that the value of R' decreases with N while increases with . Our results would be useful for improving the calculation efficiency of network robustness measure R for complex networks.Peer ReviewedPostprint (author's final draft

Cascades tolerance of scale-free networks with attack cost

Network robustness against cascades is a major topic in the fields of complex networks. In this paper, we propose an attack-cost-based cascading failure model, where the attack cost of nodes is positively related to its degree. We compare four attacking strategies: the random removal strategy (RRS), the low-degree removal strategy (LDRS), the high-degree removal strategy (HDRS) and the genetic algorithm removal strategy (GARS). It is shown that the network robustness against cascades is heavily affected by attack costs and the network exhibits the weakest robustness under GARS. We also explore the relationship between the network robustness and tolerance parameter under these attacking strategies. The simulation results indicate that the critical value of tolerance parameter under GARS is greatly larger than that of other attacking strategies. Our work can supply insight into the robustness and vulnerability of complex networks corresponding to cascading failures.Peer ReviewedPostprint (published version

High-Resolution Imaging of Dendrimers Used in Drug Delivery via Scanning Probe Microscopy

Dendrimers and telodendrimer micelles represent two new classes of vehicles for drug delivery that have attracted much attention recently. Their structural characterization at the molecular and submolecular level remains a challenge due to the difficulties in reaching high resolution when imaging small particles in their native media. This investigation offers a new approach towards this challenge, using scanning tunneling microscopy (STM) and atomic force microscopy (AFM). By using new sample preparation protocols, this work demonstrates that (a) intramolecular features such as drug molecules and dendrimer termini can be resolved; and (b) telodendrimer micelles can be immobilized on the surface without compromising structural integrity, and as such, high resolution AFM imaging may be performed to attain 3D information. This high-resolution structural information should enhance our knowledge of the nanocarrier structure and nanocarrier-drug interaction and, therefore, facilitate design and optimization of the efficiency in drug delivery

High-Resolution Imaging of Polyethylene Glycol Coated Dendrimers via Combined Atomic Force and Scanning Tunneling Microscopy

Dendrimers have shown great promise as drug delivery vehicles in recent years because they can be synthesized with designed size and functionalities for optimal transportation, targeting, and biocompatibility. One of the most well-known termini used for biocompatibility is polyethylene glycol (PEG), whose performance is affected by its actual conformation. However, the conformation of individual PEG bound to soft materials such as dendrimers has not been directly observed. Using atomic force microscopy (AFM) and scanning tunneling microscopy (STM), this work characterizes the structure adopted by PEGylated dendrimers with the highest resolution reported to date. AFM imaging enables visualization of the individual dendrimers, as well as the differentiation and characterization of the dendrimer core and PEG shell. STM provides direct imaging of the PEG extensions with high-resolution. Collectively, this investigation provides important insight into the structure of coated dendrimers, which is crucial for the design and development of better drug delivery vehicles

Efficient calculation of the robustness measure R for complex networks

In a recent work, Schneider et al. (2011) proposed a new measure R for network robustness, where the value of R is calculated within the entire process of malicious node attacks. In this paper, we present an approach to improve the calculation efficiency of R, in which a computationally efficient robustness measure R' is introduced when the fraction of failed nodes reaches to a critical threshold qc. Simulation results on three different types of network models and three real networks show that these networks all exhibit a computationally efficient robustness measure R'. The relationships between R' and the network size N and the network average degree are also explored. It is found that the value of R' decreases with N while increases with . Our results would be useful for improving the calculation efficiency of network robustness measure R for complex networks.Peer Reviewe

Vibrational Signature of Double-End-Linked Molecules at Au Nanojunctions Probed by Surface-Enhanced Raman Spectroscopy

National Basic Research Program of China [2009CB930703, 2007CB935603, 2007DFC40440]; Natural Science Foundation of China [20673086, 20620130427, 20825313, 20827003]; NFFTBS [J0630429]; NCETFJ ; HPC of Xiamen Universit

Table1_Identification and characterization of candidate detoxification genes in Pharsalia antennata Gahan (Coleoptera: Cerambycidae).DOCX

The wood-boring beetles, including the majority of Cerambycidae, have developed the ability to metabolize a variety of toxic compounds derived from host plants and the surrounding environment. However, detoxification mechanisms underlying the evolutionary adaptation of a cerambycid beetle Pharsalia antennata to hosts and habitats are largely unexplored. Here, we characterized three key gene families in relation to detoxification (cytochrome P450 monooxygenases: P450s, carboxylesterases: COEs and glutathione-S-transferases: GSTs), by combinations of transcriptomics, gene identification, phylogenetics and expression profiles. Illumina sequencing generated 668,701,566 filtered reads in 12 tissues of P. antennata, summing to 100.28 gigabases data. From the transcriptome, 215 genes encoding 106 P450s, 77 COEs and 32 GSTs were identified, of which 107 relatives were differentially expressed genes. Of the identified 215 genes, a number of relatives showed the orthology to those in Anoplophora glabripennis, revealing 1:1 relationships in 94 phylogenetic clades. In the trees, P. antennata detoxification genes mainly clustered into one or two subfamilies, including 64 P450s in the CYP3 clan, 33 COEs in clade A, and 20 GSTs in Delta and Epsilon subclasses. Combining transcriptomic data and PCR approaches, the numbers of detoxification genes expressed in abdomens, antennae and legs were 188, 148 and 141, respectively. Notably, some genes exhibited significantly sex-biased levels in antennae or legs of both sexes. The findings provide valuable reference resources for further exploring xenobiotics metabolism and odorant detection in P. antennata.</p

Table2_Identification and characterization of candidate detoxification genes in Pharsalia antennata Gahan (Coleoptera: Cerambycidae).DOCX

The wood-boring beetles, including the majority of Cerambycidae, have developed the ability to metabolize a variety of toxic compounds derived from host plants and the surrounding environment. However, detoxification mechanisms underlying the evolutionary adaptation of a cerambycid beetle Pharsalia antennata to hosts and habitats are largely unexplored. Here, we characterized three key gene families in relation to detoxification (cytochrome P450 monooxygenases: P450s, carboxylesterases: COEs and glutathione-S-transferases: GSTs), by combinations of transcriptomics, gene identification, phylogenetics and expression profiles. Illumina sequencing generated 668,701,566 filtered reads in 12 tissues of P. antennata, summing to 100.28 gigabases data. From the transcriptome, 215 genes encoding 106 P450s, 77 COEs and 32 GSTs were identified, of which 107 relatives were differentially expressed genes. Of the identified 215 genes, a number of relatives showed the orthology to those in Anoplophora glabripennis, revealing 1:1 relationships in 94 phylogenetic clades. In the trees, P. antennata detoxification genes mainly clustered into one or two subfamilies, including 64 P450s in the CYP3 clan, 33 COEs in clade A, and 20 GSTs in Delta and Epsilon subclasses. Combining transcriptomic data and PCR approaches, the numbers of detoxification genes expressed in abdomens, antennae and legs were 188, 148 and 141, respectively. Notably, some genes exhibited significantly sex-biased levels in antennae or legs of both sexes. The findings provide valuable reference resources for further exploring xenobiotics metabolism and odorant detection in P. antennata.</p