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Effective anticancer therapy can be achieved by designing a targeted drug-delivery system with high stability during circulation and efficient uptake by the target tumour cancer cells. We report here a novel nano-assembled drug-delivery system, formed by multivalent host-guest interactions between a polymer-cyclodextrin conjugate and a polymer-paclitaxel conjugate. The multivalent inclusion complexes confer high stability to the nano-assembly, which efficiently delivers paclitaxel into the targeted cancer cells via both passive and active targeting mechanisms. The ester linkages between paclitaxel and the polymer backbone permit efficient release of paclitaxel within the cell by degradation. This novel targeted nano-assembly exhibits significant antitumour activity in a mouse tumour model. The strategy established in this study also provides knowledge for the development of advanced anticancer drug delivery.

[1] A series of 200 year long integrations is performed using the Geophysical Fluid Dynamics Laboratory CM2.1 by varying the Tokioka parameter, a minimum entrainment rate threshold in the cumulus parameterization. Changing the threshold alters both the tropical Pacific mean state and the El Niño-Southern Oscillation (ENSO) variability. Increasing the Tokioka parameter causes a basin-wide cooling in the tropical Pacific with the reduction of high clouds. The degree of cooling in the western part of the basin is bigger than that in the east. As a result, the east-west asymmetry in the tropical Pacific sea surface temperature (SST) decreases with increasing the Tokioka parameter. Accompanied with the reduced east-west SST asymmetry are the increase of mean precipitation over the eastern Pacific and the eastward shift of the atmospheric responses to the ENSO-related SST forcing. The eastward shifted wind stress anomaly associated with ENSO leads to the stronger ENSO variability. In this way the magnitude of ENSO simulated in this model increases with the Tokioka parameter. Implication of our results on the relationship between the tropical Pacific mean state and ENSO is discussed.

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The selective monitoring of G-quadruplex (G4) structures in living cells is important to elucidate their functions and reveal their value as diagnostic or therapeutic targets. Here we report a fluorogenic probe (CV2) able to selectively light-up parallel G4 DNA over antiparallel topologies. CV2 was constructed by conjugating the excimer-forming CV dye with a peptide sequence (L-Arg-L-Gly-glutaric acid) that specifically recognizes G4s. CV2 forms self-assembled, red excimeremitting nanoaggregates in aqueous media, but specific binding to G4s triggers its disassembly into rigidified monomeric dyes, leading to a dramatic fluorescence enhancement. Moreover, selective permeation of CV2 stains G4s in mitochondria over the nucleus. CV2 was employed for tracking the folding and unfolding of G4s in living cells, and for monitoring mitochondrial DNA (mtDNA) damage. These properties make CV2 appealing to investigate the possible roles of mtDNA G4s in diseases that involve mitochondrial dysfunction.

An approach to probabilistic modeling of contaminant transport based on the first-and second-order reliability methods (FORM and SORM) is presented. FORM and SORM were initially developed for structural reliability applications to estimate the occurrence of low-probability events. They can be readily used with both analytical and numerical models and do not require restrictive assumptions about the problem geometry or about the properties of the media. Sensitivity information is obtained as an integral part of these analyses and is used to identify the variables or parameters which have a major influence on the estimate of probability. Example reliability analyses of one-and two-dimensional transport are used to illustrate the approach, and the accuracy of the reliability methods is evaluated in comparison with Monte Carlo simulations. The results show that FORM increasingly overestimates the probability of exceedance as the spatial variability of the domain increases. SORM, on the other hand, accounts for the nonlinearity of the limit state surface and gives results consistent with Monte Carlo simulation over a range of coefficient of variation of K from 0.1 to 0.7. In addition, the FORM/SORM analyses are shown to provide a computational advantage over the Monte Carlo simulation for low-probability events, because the computational effort is independent of the probability and the results also include sensitivity information. Finally, an example application of system reliability using FORM and SORM shows that problems with multiple limit state surfaces can be readily analyzed and the computational effort is proportional to the number and complexity of the limit state functions.

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