Here, we describe a concept for localized and long-term delivery of short interfering RNA (siRNA) using an injectable polyplex hydrogel possessing thermosensitivity and biodegradability properties. We prepared a low molecular weight polyethyleneimine-poly(organophosphazene) conjugate as a thermosensitive and cationic polymer that has a cleavable ester linkage. The conjugates formed about 100 nm sized polyplexes with siRNAs, and the polyplex solution turned into a polyplex hydrogel at body temperature via a hydrophobic interaction. We injected the polyplex hydrogel with siRNA of cyclin B1, an essential protein for controlling the cell cycle, into the tumor xenograft model. Polyplexes were slowly released from the polyplex hydrogel by dissolution and degradation, allowing an in vivo antitumor effect via cyclin B1 gene silencing for 4 weeks with only a single injection.

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One contribution of 18 to a Discussion Meeting Issue 'Next-generation molecular and evolutionary epidemiology of infectious disease'. When pathogens encounter a novel environment, such as a new host species or treatment with an antimicrobial drug, their fitness may be reduced so that adaptation is necessary to avoid extinction. Evolutionary emergence is the process by which new pathogen strains arise in response to such selective pressures. Theoretical studies over the last decade have clarified some determinants of emergence risk, but have neglected the influence of fitness on evolutionary rates and have not accounted for the multiple scales at which pathogens must compete successfully. We present a cross-scale theory for evolutionary emergence, which embeds a mechanistic model of withinhost selection into a stochastic model for emergence at the population scale. We explore how fitness landscapes at within-host and between-host scales can interact to influence the probability that a pathogen lineage will emerge successfully. Results show that positive correlations between fitnesses across scales can greatly facilitate emergence, while cross-scale conflicts in selection can lead to evolutionary dead ends. The local genotype space of the initial strain of a pathogen can have disproportionate influence on emergence probability. Our cross-scale model represents a step towards integrating laboratory experiments with field surveillance data to create a rational framework to assess emergence risk.