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Epoxy-based polymer networks from step-growth polymerizations are ubiquitous in coatings, adhesives, and as matrices in composite materials. Dynamic covalent bonds in the network allow its degradation into small molecules and thus, enable chemical recycling; however, such degradation often requires elevated temperatures and costly chemicals, resulting in various small molecules. Here, we design crosslinked polyesters from structurally similar epoxy and anhydride monomers derived from phthalic acid. We achieve selective degradation of the polyesters through transesterification reactions at near-ambient conditions using an alkali carbonate catalyst, resulting in a singular phthalic ester. We also demonstrate upcycling the network polyesters to photopolymers by one-step depolymerization using a functional alcohol. 

Climate change projections provided by global climate models (GCM) are generally too coarse for local and regional applications. Local and regional climate change impact studies therefore use downscaled datasets. While there are studies that evaluate downscaling methodologies, there is no study comparing the downscaled datasets that are actually distributed and used in climate change impact studies, and there is no guidance for selecting a published downscaled dataset. We compare five widely used statistically downscaled climate change projection datasets that cover the conterminous USA (CONUS): ClimateNA, LOCA, MACAv2-LIVNEH, MACAv2-METDATA, and NEX-DCP30. All of the datasets are derived from CMIP5 GCMs and are publicly distributed. The five datasets generally have good agreement across CONUS for Representative Concentration Pathways (RCP) 4.5 and 8.5, although the agreement among the datasets vary greatly depending on the GCM, and there are many localized areas of sharp disagreements. Areas of higher dataset disagreement emerge over time, and their importance relative to differences among GCMs is comparable between RCP4.5 and RCP8.5. Dataset disagreement displays distinct regional patterns, with greater disagreement in △Tmax and △Tmin in the interior West and in the North, and disagreement in △P in California and the Southeast. LOCA and ClimateNA are often the outlier dataset, while the seasonal timing of ClimateNA is somewhat shifted from the others. To easily identify regional study areas with high disagreement, we generated maps of dataset disagreement aggregated to states, ecoregions, watersheds, and forests. Climate change assessment studies can use the maps to evaluate and select one or more downscaled datasets for their study area.

 

Forests play a critical role in mitigating climate change, and, at the same time, are predicted to experience large-scale impacts of climate change that will affect the efficiency of forests in mitigation efforts. Projections of future carbon sequestration potential typically do not account for the changing economic costs of timber and agricultural production and land use change. We integrated a dynamic forward-looking economic optimization model of global land use with results from a dynamic global vegetation model and meta-analysis of climate impacts on crop yields to project future carbon sequestration in forests. We find that the direct impacts of climate change on forests, represented by changes in dieback and forest growth, and indirect effects due to lost crop productivity, together result in a net gain of 17 Gt C in aboveground forest carbon storage from 2000 to 2100. Increases in climate-driven forest growth rates will result in an 81%–99% reduction in costs of reaching a range of global forest carbon stock targets in 2100, while the increases in dieback rates are projected to raise the costs by 57%–132%. When combined, these two direct impacts are expected to reduce the global costs of climate change mitigation in forests by more than 70%. Inclusion of the third, indirect impact of climate change on forests through reduction in crop yields, and the resulting expansion of cropland, raises the costs by 11%–38% and widens the uncertainty range. While we cannot rule out the possibility of climate change increasing mitigation costs, the central outcomes of the simultaneous impacts of climate change on forests and agriculture are 64%–86% reductions in the mitigation costs. Overall, the results suggest that concerns about climate driven dieback in forests should not inhibit the ambitions of policy makers in expanding forest-based climate solutions.

 

ABSTRACT Biological organisms carry a rich potential for removing toxins from our environment, but identifying suitable candidates and improving them remain challenging. We explore the use of computational tools to discover strains and enzymes that detoxify harmful compounds. In particular, we focus on mycotoxins—fungus-produced toxins that contaminate food and feed—and biological enzymes that are capable of rendering them less harmful. We discuss the use of established and novel computational tools to complement existing empirical data in three directions: discovering the prospect of detoxification among underexplored organisms, finding important cellular processes that contribute to detoxification, and improving the performance of detoxifying enzymes. We hope to create a synergistic conversation between researchers in computational biology and those in the bioremediation field. We showcase open bioremediation questions where computational researchers can contribute and highlight relevant existing and emerging computational tools that could benefit bioremediation researchers. 

A promising new field of genetically encoded ultrasound contrast agents in the form of gas vesicles has recently emerged, which could extend the specificity of medical ultrasound imaging. However, given the delicate genetic nature of how these genes are integrated and expressed, current methods of producing gas vesicle‐expressing mammalian cell lines requires significant cell processing time to establish a clonal/polyclonal line that robustly expresses the gas vesicles sufficiently enough for ultrasound contrast. Here, we describe an inducible and drug‐selectable acoustic reporter gene system that can enable gas vesicle expression in mammalian cell lines, which we demonstrate using HEK293T cells. Our drug‐selectable construct design increases the stability and proportion of cells that successfully integrate all plasmids into their genome, thus reducing the amount of cell processing time required. Additionally, we demonstrate that our drug‐selectable strategy forgoes the need for single‐cell cloning and fluorescence‐activated cell sorting, and that a drug‐selected mixed population is sufficient to generate robust ultrasound contrast. Successful gas vesicle expression was optically and ultrasonically verified, with cells expressing gas vesicles exhibiting an 80% greater signal‐to‐noise ratio compared to negative controls and a 500% greater signal‐to‐noise ratio compared to wild‐type HEK293T cells. This technology presents a new reporter gene paradigm by which ultrasound can be harnessed to visualize specific cell types for applications including cellular reporting and cell therapies.

 

As far as plastron is sustained, superhydrophobic (SHPo) surfaces are expected to reduce skin-friction drag in any flow conditions including large-scale turbulent boundary-layer flows of marine vessels. However, despite many successful drag reductions reported using laboratory facilities, the plastron on SHPo surfaces was persistently lost in high-Reynolds-number flows on open water, and no reduction has been reported until a recent study using certain microtrench SHPo surfaces underneath a boat (Xu et al., Phys. Rev. Appl. , vol. 13, no. 3, 2020, 034056). Since scientific studies with controlled flows are difficult with a boat on ocean water, in this paper we test similar SHPo surfaces in a high-speed towing tank, which provides well-controlled open-water flows, by developing a novel $0.7\ \textrm {m} \times 1.4\ \textrm {m}$ towing plate, which subjects a $4\ \textrm {cm} \times 7\ \textrm {cm}$ sample to the high-Reynolds-number flows of the plate. In addition to the 7 cm long microtrenches, trenches divided into two in length are also tested and reveal an improvement. The skin-friction drag ratio relative to a smooth surface is found to be decreasing with increasing Reynolds number, down to 73 % (i.e. 27 % drag reduction) at $Re_x\sim 8\times 10^6$ , before starting to increase at higher speeds. For a given gas fraction, the trench width non-dimensionalized to the viscous length scale is found to govern the drag reduction, in agreement with previous numerical results.