Formation of stable, long-circulating siRNA polyplexes is a significant challenge in translation of intravenously-delivered, polymeric RNAi cancer therapies. Here, we report that siRNA hydrophobization through conjugation to palmitic acid (siPA) improves stability, in vivo pharmacokinetics, and tumor gene silencing of PEGylated nanopolyplexes (siPA-NPs) with balanced cationic and hydrophobic content in the core (relative to the analogous polyplexes formed with unmodified siRNA, si-NPs). Hydrophobized siPA loaded into the NPs at a lower charge ratio (N+:P−) relative to unmodified siRNA, and the siPA-NPs had superior resistance to siRNA cargo unpackaging in comparison to si-NPs upon exposure to the competing polyanion heparin and serum. In vitro, siPA-NPs increased uptake in MDA-MB-231 breast cancer cells (100% positive cells vs. 60% positive cells) but exhibited equivalent silencing of the model gene luciferase relative to si-NPs. In vivo in a murine model, the circulation half-life of intravenously-injected siPA-NPs was double that of si-NPs, resulting in a >2-fold increase in siRNA biodistribution to orthotopic MDA-MB-231 mammary tumors. The increased circulation half-life of siPA-NPs was dependent upon the hydrophobic interactions of the siRNA and the NP core component and not just siRNA hydrophobization, as siPA did not contribute to improved circulation time relative to unmodified siRNA when delivered using polyplexes with a fully cationic core. Intravenous delivery of siPA-NPs also achieved significant silencing of the model gene luciferase in vivo (~40% at 24 hours after one treatment and ~60% at 48 hours after two treatments) in the murine MDA-MB-231 tumor model, while si-NPs only produced a significant silencing effect after two treatments. These data suggest that stabilization of PEGylated siRNA polyplexes through a combination of hydrophobic and electrostatic interactions between siRNA cargo and the polymeric carrier improves in vivo pharmacokinetics and tumor gene silencing relative to conventional formulations comprising only electrostatic interactions.

Clinical application of injectable, thermoresponsive hydrogels is hindered by lack of degradability and controlled drug release. To overcome these challenges, a family of thermoresponsive, ABC triblock polymer-based hydrogels has been engineered to degrade and release drug cargo through either oxidative or hydrolytic/enzymatic mechanisms dictated by the “A” block composition. Three ABC triblock copolymers are synthesized with varying “A” blocks, including oxidation-sensitive poly(propylene sulfide), slow hydrolytically/enzymatically degradable poly(ε-caprolactone), and fast hydrolytically/enzymatically degradable poly(D,L-lactide-co-glycolide), forming the respective formulations PPS135-b-PDMA152-b-PNIPAAM225 (PDN), PCL85-b-PDMA150-b-PNIPAAM150 (CDN), and PLGA60-b-PDMA148-b-PNIPAAM152 (LGDN). For all three polymers, hydrophilic poly(N,N-dimethylacrylamide) and thermally responsive poly(N-isopropylacrylamide) comprise the “B” and “C” blocks, respectively. These copolymers form micelles in aqueous solutions at ambient temperature that can be preloaded with small molecule drugs. These solutions quickly transition into hydrogels upon heating to 37 °C, forming a supra-assembly of physically crosslinked, drug-loaded micelles. PDN hydrogels are selectively degraded under oxidative conditions while CDN and LGDN hydrogels are inert to oxidation but show differential rates of hydrolytic/enzymatic decomposition. All three hydrogels are cytocompatible in vitro and in vivo, and drug-loaded hydrogels demonstrate differential release kinetics in vivo corresponding with their specific degradation mechanism. These collective data highlight the potential cell and drug delivery use of this tunable class of ABC triblock polymer thermogels.

We constructed a bench-scale continuous-flow (8 L total volume, 4.3 L/day) woodchip bioreactor and operated the reactor under field-like conditions to evaluate joint pesticide and nitrate removal. The continuous-flow reactor achieved 83.5 ± 8% diuron removal and 61.6 ± 11.9% imidacloprid removal with a 24 h hydraulic retention time (HRT). We designed a sequencing-batch reactor configuration (8 L total volume) to evaluate the impact of an aerobic phase on denitrification and pesticide removal performance. The sequencing-batch reactor achieved 89.2 ± 8.8% nitrate removal with a hydraulic retention time (HRT) of 12 h, while the continuous-flow design achieved 55.6 ± 9.1% nitrate removal with a 12 h HRT. There was no significant difference between pesticide removal between sequencing-batch and continuous-flow reactor types (p = 0.655 and p = 0.316 for diuron and imidacloprid removal, respectively). Kinetic batch tests revealed sorption, not microbial degradation, as the main mechanism of removal for both diuron and imidacloprid under denitrifying conditions. Imidacloprid removal ranged from 440.4 to 532.0 ng/gwoodchip (dry mass) and diuron removal between 468.6 and 553.8 ng/g-woodchip (dry mass) over 24 h. The bench-scale evaluation of pesticide behavior in woodchip bioreactors highlights the need to improve microbial degradation in such best management practices for pesticide removal.

Nontarget chemical analysis using high-resolution mass spectrometry has increasingly been used to discern spatial patterns and temporal trends in anthropogenic chemical abundance in natural and engineered systems. A critical experimental design consideration in such applications, especially those monitoring complex matrices over long time periods, is a choice between analyzing samples in multiple batches as they are collected, or in one batch after all samples have been processed. While datasets acquired in multiple analytical batches can include the effects of instrumental variability over time, datasets acquired in a single batch risk compound degradation during sample storage. To assess the influence of batch effects on the analysis and interpretation of nontarget data, this study examined a set of 56 samples collected from a municipal wastewater system over 7 months. Each month’s samples included 6 from sites within the collection system, one combined influent, and one treated effluent sample. Samples were analyzed using liquid chromatography high-resolution mass spectrometry in positive electrospray ionization mode in multiple batches as the samples were collected and in a single batch at the conclusion of the study. Data were aligned and normalized using internal standard scaling and ComBat, an empirical Bayes method developed for estimating and removing batch effects in microarrays. As judged by multiple lines of evidence, including comparing principal variance component analysis between single and multi-batch datasets and through patterns in principal components and hierarchical clustering analyses, ComBat appeared to significantly reduce the influence of batch effects. For this reason, we recommend the use of more, small batches with an appropriate batch correction step rather than acquisition in one large batch. Graphical abstract