Polyomaviruses are non-enveloped viruses with a small, circular double-stranded DNA (dsDNA) genomes that have been identified in a variety of mammals, birds and fish and are known to cause various diseases. Arthropolviridae is a proposed family of circular, large tumor antigen encoding dsDNA viruses that have a unidirectional genome organization. Genomoviruses and anelloviruses are ssDNA viruses that have circular genomes ranging in size from 2–2.4 kb and 2.1–3.8 kb, respectively. Genomoviruses are ubiquitous in the environment, having been identified in a wide range of animal, plant and environmental samples, while anelloviruses have been associated with a plethora of animals.
Here, 16 novel viruses are reported that span four viral families. Eight novel polyomaviruses were recovered from bark scorpions, three arthropolviruses were recovered from dog ticks and one arthropolvirus from a hairy scorpion. Viruses belonging to the families Polyomaviridae and Arthropolviridae are highly divergent. This is the first more extensive study of these viruses in arachnids. Three genomoviruses were recovered from both dog and deer ticks and one anellovirus was recovered from deer ticks, which are the first records of these viruses being recovered from ticks. This work highlights the diversity of dsDNA and ssDNA viruses in the arachnid population and emphasizes the importance of performing viral surveys on these populations.
In LAC, residential electricity demand could increase as much as 55-68% between 2020 and 2060, and building technology lock-in has constricted the options for mitigating energy demand, as major changes to the building stock itself are not possible, as only a small portion of the stock is turned over every year. Aggressive and timely efficiency upgrades to residential appliances and building thermal shells can significantly offset the projected increases, potentially avoiding installation of new generation capacity, but regulations on new construction will likely be ineffectual due to the long residence time of the stock (60+ years and increasing). These findings can be extrapolated to other U.S. cities where the majority of urban expansion has already occurred, such as the older cities on the eastern coast. U.S. population is projected to increase 40% by 2060, with growth occurring in the warmer southern and western regions. In these growing cities, improving new construction buildings can help offset electricity demand increases before the city reaches the lock-in phase.
At ~100-nm, a DNA origami macromolecule represents one such bridge, acting as a breadboard for the decoration of single molecules with 3-5 nm resolution. It relies on the programmed self-assembly of a long, scaffold strand into arbitrary 2D or 3D structures guided via approximately two hundred, short, staple strands. Once synthesized, this nanostructure falls in the spatial manipulation regime of a nanofabrication tool such as electron-beam lithography (EBL), facilitating its high efficiency immobilization in predetermined binding sites on an experimentally relevant substrate. This placement technology, however, is expensive and requires specialized training, thereby limiting accessibility.
The work described here introduces a method for bench-top, cleanroom/lithography-free, DNA origami placement in meso-to-macro-scale grids using tunable colloidal nanosphere masks, and organosilane-based surface chemistry modification. Bench-top DNA origami placement is the first demonstration of its kind which facilitates precision placement of single molecules with high efficiency in diffraction-limited sites at a cost of $1/chip. The comprehensive characterization of this technique, and its application as a robust platform for high-throughput biophysics and digital counting of biomarkers through enzyme-free amplification are elucidated here. Furthermore, this technique can serve as a template for the bottom-up fabrication of invaluable biophysical tools such as zero mode waveguides, making them significantly cheaper and more accessible to the scientific community. This platform has the potential to democratize high-throughput single molecule experiments in laboratories worldwide.
A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations.
We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data.
Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy-relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. In addition, uncertainties for each observation data-stream should be assessed. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases interoperable, and on the calibration of each component of the system to agreed-upon international scales.
Errors in the specification or utilization of fossil fuel CO2 emissions within carbon budget or atmospheric CO2 inverse studies can alias the estimation of biospheric and oceanic carbon exchange. A key component in the simulation of CO2 concentrations arising from fossil fuel emissions is the spatial distribution of the emission near coastlines. Regridding of fossil fuel CO2 emissions (FFCO2) from fine to coarse grids to enable atmospheric transport simulations can give rise to mismatches between the emissions and simulated atmospheric dynamics which differ over land or water. For example, emissions originally emanating from the land are emitted from a grid cell for which the vertical mixing reflects the roughness and/or surface energy exchange of an ocean surface. We test this potential "dynamical inconsistency" by examining simulated global atmospheric CO2 concentration driven by two different approaches to regridding fossil fuel CO2 emissions. The two approaches are as follows: (1) a commonly used method that allocates emissions to grid cells with no attempt to ensure dynamical consistency with atmospheric transport and (2) an improved method that reallocates emissions to grid cells to ensure dynamically consistent results. Results show large spatial and temporal differences in the simulated CO2 concentration when comparing these two approaches. The emissions difference ranges from −30.3 TgC grid cell-1 yr-1 (−3.39 kgC m-2 yr-1) to +30.0 TgC grid cell-1 yr-1 (+2.6 kgC m-2 yr-1) along coastal margins. Maximum simulated annual mean CO2 concentration differences at the surface exceed ±6 ppm at various locations and times. Examination of the current CO2 monitoring locations during the local afternoon, consistent with inversion modeling system sampling and measurement protocols, finds maximum hourly differences at 38 stations exceed ±0.10 ppm with individual station differences exceeding −32 ppm. The differences implied by not accounting for this dynamical consistency problem are largest at monitoring sites proximal to large coastal urban areas and point sources. These results suggest that studies comparing simulated to observed atmospheric CO2 concentration, such as atmospheric CO2 inversions, must take measures to correct for this potential problem and ensure flux and dynamical consistency.