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Two phase 2 trials assessed the efficacy and safety of intravenous infusions of a broadly neutralizing antibody, VRCO1, to prevent HIV-1 infection. VRC01 did not cause adverse events and did not prevent overall HIV-1 acquisition significantly more effectively than placebo. In secondary analyses, VRC01 prevented transmission of VRC01-sensitive HIV-1 isolates.

Representative Concentration Pathway (RCP) 4.5 is a scenario that stabilizes radiative forcing at 4.5 W m −2 in the year 2100 without ever exceeding that value. Simulated with the Global Change Assessment Model (GCAM), RCP4.5 includes long-term, global emissions of greenhouse gases, short-lived species, and land-use-land-cover in a global economic framework. RCP4.5 was updated from earlier GCAM scenarios to incorporate historical emissions and land cover information common to the RCP process and follows a cost-minimizing pathway to reach the target radiative forcing. The imperative to limit emissions in order to reach this target drives changes in the energy system, including shifts to electricity, to lower emissions energy technologies and to the deployment of carbon capture and geologic storage technology. In addition, the RCP4.5 emissions price also applies to land use emissions; as a result, forest lands expand from their present day extent. The simulated future emissions and land use were downscaled from the regional simulation to a grid to facilitate transfer to climate models. While there are many alternative pathways to achieve a radiative forcing level of 4.5 W m −2 , the application of the RCP4.5 provides a common platform for climate models to explore the climate system response to stabilizing the anthropogenic components of radiative forcing.

Disparity in air pollution exposure arises from variation at multiple spatial scales: along urban-to-rural gradients, between individual cities within a metropolitan region, within individual neighborhoods, and between city blocks. Here, we improve on existing capabilities to systematically compare urban variation at several scales, from hyperlocal (<100 m) to regional (>10 km), and to assess consequences for outdoor air pollution experienced by residents of different races and ethnicities, by creating a set of uniquely extensive and high-resolution observations of spatially variable pollutants: NO, NO₂, black carbon (BC), and ultrafine particles (UFP). We conducted full-coverage monitoring of a wide sample of urban and suburban neighborhoods (93 km² and 450,000 residents) in four counties of the San Francisco Bay Area using Google Street View cars equipped with the Aclima mobile platform. Comparing scales of variation across the sampled population, greater differences arise from localized pollution gradients for BC and NO (pollutants dominated by primary sources) and from regional gradients for UFP and NO₂ (pollutants dominated by secondary contributions). Median concentrations of UFP, NO, and NO₂ are, for Hispanic and Black populations, 8 to 30% higher than the population average; for White populations, average exposures to these pollutants are 9 to 14% lower than the population average. Systematic racial/ethnic disparities are influenced by regional concentration gradients due to sharp contrasts in demographic composition among cities and urban districts, while within-group extremes arise from local peaks. Our results illustrate how detailed and extensive fine-scale pollution observations can add new insights about differences and disparities in air pollution exposures at the population scale.

The koala, the only extant species of the marsupial family Phascolarctidae, is classified as ‘vulnerable’ due to habitat loss and widespread disease. We sequenced the koala genome, producing a complete and contiguous marsupial reference genome, including centromeres. We reveal that the koala’s ability to detoxify eucalypt foliage may be due to expansions within a cytochrome P450 gene family, and its ability to smell, taste and moderate ingestion of plant secondary metabolites may be due to expansions in the vomeronasal and taste receptors. We characterized novel lactation proteins that protect young in the pouch and annotated immune genes important for response to chlamydial disease. Historical demography showed a substantial population crash coincident with the decline of Australian megafauna, while contemporary populations had biogeographic boundaries and increased inbreeding in populations affected by historic translocations. We identified genetically diverse populations that require habitat corridors and instituting of translocation programs to aid the koala’s survival in the wild. The assembly of the genome of the koala provides insights into its adaptive biology and identifies gene expansions that contribute to its ability to detoxify eucalyptus-derived compounds and perceive plant secondary metabolites.

Comprehensive descriptions of animal behavior require precise three-dimensional (3D) measurements of whole-body movements. Although two-dimensional approaches can track visible landmarks in restrictive environments, performance drops in freely moving animals, due to occlusions and appearance changes. Therefore, we designed DANNCE to robustly track anatomical landmarks in 3D across species and behaviors. DANNCE uses projective geometry to construct inputs to a convolutional neural network that leverages learned 3D geometric reasoning. We trained and benchmarked DANNCE using a dataset of nearly seven million frames that relates color videos and rodent 3D poses. In rats and mice, DANNCE robustly tracked dozens of landmarks on the head, trunk, and limbs of freely moving animals in naturalistic settings. We extended DANNCE to datasets from rat pups, marmosets, and chickadees, and demonstrate quantitative profiling of behavioral lineage during development.DANNCE enables robust 3D tracking of animals’ limbs and other features in naturalistic environments by making use of a deep learning approach that incorporates geometric reasoning. DANNCE is demonstrated on behavioral sequences from rodents, marmosets, and chickadees.

Future changes in climate and socioeconomic systems will drive both the availability and use of water resources, leading to evolutions in scarcity. The contributions of both systems can be quantified individually to understand the impacts around the world, but also combined to explore how the coevolution of energy-water-land systems affects not only the driver behind water scarcity changes, but how human and climate systems interact in tandem to alter water scarcity. Here we investigate the relative contributions of climate and socioeconomic systems on water scarcity under the Shared Socioeconomic Pathways-Representative Concentration Pathways framework. While human systems dominate changes in water scarcity independent of socioeconomic or climate future, the sign of these changes depend particularly on the socioeconomic scenario. Under specific socioeconomic futures, human-driven water scarcity reductions occur in up to 44% of the global land area by the end of the century.

Many papers have shown that bioenergy and land-use are potentially important elements in a strategy to limit anthropogenic climate change. But, significant expansion of bioenergy production can have a large terrestrial footprint. In this paper, we test the implications for land use, the global energy system, emissions and mitigation costs of meeting a specific climate target, using a single fossil fuel and industrial sector policy instrument, but with five alternative bioenergy and land-use policy architectures. These scenarios are illustrative in nature, and designed to explore trade-offs. We find that the policies we examined have differing effects on the different segments of the economy. Comprehensive land policies can reduce land-use change emissions, increasing allowable emissions in the energy system, but have implications for the cost of food. Bioenergy penalties and constraints, on the other hand, have little effect on food prices, but result in less bioenergy and thus can increase mitigation costs and energy prices.

Protection at the peak of Plasmodium chabaudi blood-stage malaria infection is provided by CD4 T cells. We have shown that an increase in Th1 cells also correlates with protection during the persistent phase of malaria; however, it is unclear how these T cells are maintained. Persistent malaria infection promotes protection and generates both effector T cells (Teff), and effector memory T cells (Tem). We have previously defined new CD4 Teff (IL-7Rα-) subsets from Early (TeffEarly, CD62LhiCD27+) to Late (TeffLate, CD62LloCD27-) activation states. Here, we tested these effector and memory T cell subsets for their ability to survive and protect in vivo. We found that both polyclonal and P. chabaudi Merozoite Surface Protein-1 (MSP-1)-specific B5 TCR transgenic Tem survive better than Teff. Surprisingly, as Tem are associated with antigen persistence, Tem survive well even after clearance of infection. As previously shown during T cell contraction, TeffEarly, which can generate Tem, also survive better than other Teff subsets in uninfected recipients. Two other Tem survival mechanisms identified here are that low-level chronic infection promotes Tem both by driving their proliferation, and by programming production of Tem from Tcm. Protective CD4 T cell phenotypes have not been precisely determined in malaria, or other persistent infections. Therefore, we tested purified memory (Tmem) and Teff subsets in protection from peak pathology and parasitemia in immunocompromised recipient mice. Strikingly, among Tmem (IL-7Rαhi) subsets, only TemLate (CD62LloCD27-) reduced peak parasitemia (19%), though the dominant memory subset is TemEarly, which is not protective. In contrast, all Teff subsets reduced peak parasitemia by more than half, and mature Teff can generate Tem, though less. In summary, we have elucidated four mechanisms of Tem maintenance, and identified two long-lived T cell subsets (TemLate, TeffEarly) that may represent correlates of protection or a target for longer-lived vaccine-induced protection against malaria blood-stages.

Crop residues are potential biofuel feedstocks, but residue removal may reduce soil carbon (C). The inclusion of a cover crop in a corn bioenergy system could provide additional biomass, mitigating the negative effects of residue removal by adding to stable soil C pools. In a no‐till continuous corn bioenergy system in the northern US Corn Belt, we used 13CO2 pulse labeling to trace plant C from a winter rye (Secale cereale) cover crop into different soil C pools for 2 years following rye cover crop termination. Corn stover left as residue (30% of total stover) contributed 66, corn roots 57, rye shoots 61, rye roots 50, and rye rhizodeposits 25 g C m−2 to soil. Five months following cover crop termination, belowground cover crop inputs were three times more likely to remain in soil C pools than were aboveground inputs, and much of the root‐derived C was in mineral‐associated soil fractions. After 2 years, both above‐ and belowground inputs had declined substantially, indicating that the majority of both root and shoot inputs are eventually mineralized. Our results underscore the importance of cover crop roots vs. shoots and the importance of cover crop rhizodeposition (33% of total belowground cover crop C inputs) as a source of soil C. However, the eventual loss of most cover crop C from these soils indicates that cover crops will likely need to be included every year in rotations to accumulate soil C.

Water scarcity conditions over the 21st century both globally and regionally are assessed in the context of climate change and climate mitigation policies, by estimating both water availability and water demand within the Global Change Assessment Model (GCAM), a leading community-integrated assessment model of energy, agriculture, climate, and water. To quantify changes in future water availability, a new gridded water-balance global hydrologic model – namely, the Global Water Availability Model (GWAM) – is developed and evaluated. Global water demands for six major demand sectors (irrigation, livestock, domestic, electricity generation, primary energy production, and manufacturing) are modeled in GCAM at the regional scale (14 geopolitical regions, 151 sub-regions) and then spatially downscaled to 0.5° × 0.5° resolution to match the scale of GWAM. Using a baseline scenario (i.e., no climate change mitigation policy) with radiative forcing reaching 8.8 W m−2 (equivalent to the SRES A1Fi emission scenario) and three climate policy scenarios with increasing mitigation stringency of 7.7, 5.5, and 4.2 W m−2 (equivalent to the SRES A2, B2, and B1 emission scenarios, respectively), we investigate the effects of emission mitigation policies on water scarcity. Two carbon tax regimes (a universal carbon tax (UCT) which includes land use change emissions, and a fossil fuel and industrial emissions carbon tax (FFICT) which excludes land use change emissions) are analyzed. The baseline scenario results in more than half of the world population living under extreme water scarcity by the end of the 21st century. Additionally, in years 2050 and 2095, 36% (28%) and 44% (39%) of the global population, respectively, is projected to live in grid cells (in basins) that will experience greater water demands than the amount of available water in a year (i.e., the water scarcity index (WSI) > 1.0). When comparing the climate policy scenarios to the baseline scenario while maintaining the same baseline socioeconomic assumptions, water scarcity declines under a UCT mitigation policy but increases with a FFICT mitigation scenario by the year 2095, particularly with more stringent climate mitigation targets. Under the FFICT scenario, water scarcity is projected to increase, driven by higher water demands for bio-energy crops.