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Small aerial drones are used in a growing number of commercial applications. However, drones cannot fly in all weather, which impacts their reliability for time-sensitive operations. The magnitude and global variability of weather impact is poorly understood. We explore weather-limited drone flyability (the proportion of time drones can fly safely) by comparing historical wind speed, temperature, and precipitation data to manufacturer-reported thresholds of common commercial and weather-resistant drones with a computer simulation. We show that global flyability is highest in warm and dry continental regions and lowest over oceans and at high latitudes. Median global flyability for common drones is low: 5.7 h/day or 2.0 h/day if restricted to daylight hours. Weather-resistant drones have higher flyability (20.4 and 12.3 h/day, respectively). While these estimates do not consider all weather conditions, results suggest that improvements to weather resistance can increase flyability. An inverse analysis for major population centres shows the largest flyability gains for common drones can be achieved by increasing maximum wind speed and precipitation thresholds from 10 to 15 m/s and 0–1 mm/h, respectively.

Fugitive methane emissions from the oil and gas industry are targeted using leak detection and repair (LDAR) programs. Until recently, only a limited number of measurement standards have been permitted by most regulators, with emphasis on close-range methods (e.g. Method-21, optical gas imaging). Although close-range methods are essential for source identification, they can be labor-intensive. To improve LDAR efficiency, there has been a policy shift in Canada and the United States towards incorporating alternative technologies. However, the suitability of these technologies for LDAR remains unclear. In this paper, we systematically review and compare six technology classes for use in LDAR: handheld instruments, fixed sensors, mobile ground labs (MGLs), unmanned aerial vehicles (UAVs), aircraft, and satellites. These technologies encompass broad spatial and temporal scales of measurement. Minimum detection limits for technology classes range from <1 g h−1 for Method 21 instruments to 7.1 × 106 g h−1 for the GOSAT satellite, and uncertainties are poorly constrained. To leverage the diverse capabilities of these technologies, we introduce a hybrid screening-confirmation approach to LDAR called a comprehensive monitoring program. Here, a screening technology is used to rapidly tag high-emitting sites to direct close-range source identification. Currently, fixed sensors, MGLs, UAVs, and aircraft could be used as screening technologies, but their performances must be evaluated under a range of environmental and operational conditions to better constrain detection effectiveness. Methane-sensing satellites are improving rapidly and may soon be ready for facility-scale screening. We conclude with a speculative discussion of the future of LDAR, touching on integration, analytics, incentivization, and regulatory pathways.

Effective gene therapy approaches have been developed for many rare diseases, including inborn errors of immunity and metabolism, haemoglobinopathies and inherited blindness. Despite successful pre-clinical and clinical results, these gene therapies are not widely available, primarily for non-medical reasons. Lack of commercial interest in therapies for ultra-rare diseases, costs of development and complex manufacturing processes required for advanced therapy medicinal products (ATMPs) are some of the main problems that are restricting access. The complexities and costs of navigating the regulatory environments in different jurisdictions for treatments that affect small numbers of patients is a problem unique to ATMPS for rare and ultra-rare diseases. In this Perspective, we outline some of the challenges and potential solutions that, we hope, will improve access to gene therapy for rare diseases.

CD28 and CTLA-4 (CD152) play essential roles in regulating T cell immunity, balancing the activation and inhibition of T cell responses, respectively. Although both receptors share the same ligands, CD80 and CD86, the specific requirement for two distinct ligands remains obscure. In the present study, we demonstrate that, although CTLA-4 targets both CD80 and CD86 for destruction via transendocytosis, this process results in separate fates for CTLA-4 itself. In the presence of CD80, CTLA-4 remained ligand bound, and was ubiquitylated and trafficked via late endosomes and lysosomes. In contrast, in the presence of CD86, CTLA-4 detached in a pH-dependent manner and recycled back to the cell surface to permit further transendocytosis. Furthermore, we identified clinically relevant mutations that cause autoimmune disease, which selectively disrupted CD86 transendocytosis, by affecting either CTLA-4 recycling or CD86 binding. These observations provide a rationale for two distinct ligands and show that defects in CTLA-4-mediated transendocytosis of CD86 are associated with autoimmunity.The inhibitory receptor CTLA-4 recognizes two ligands on opposing antigen-presenting cells, CD80 and CD86. Sansom and colleagues show CTLA-4 captures ligands by transendocytosis, whereupon low-affinity CD86 releases CTLA-4 at low pH to promote CTLA-4 recycling; however, high-affinity CD80 remains bound and targets CTLA-4 for ubiquitination and destruction.

New mobile platforms such as vehicles, drones, aircraft, and satellites have emerged to help identify and reduce fugitive methane emissions from the oil and gas sector. When deployed as part of leak detection and repair (LDAR) programs, most of these technologies use multi-visit LDAR (MVL), which consists of four steps: (a) rapidly screen all facilities, (b) triage by emission rate, (c) follow-up with close-range methods at the highest-emitting sites, and (d) conduct repairs. The proposed value of MVL is to identify large leaks soon after they arise. Whether MVL offers an improvement over traditional single-visit LDAR (SVL), which relies on undirected close-range surveys, remains poorly understood. We use the Leak Detection and Repair Simulator (LDAR-Sim) to examine the performance and cost-effectiveness of MVL relative to SVL. Results suggest that facility-scale MVL programs can achieve fugitive emission reductions equivalent to SVL, but that improved cost-effectiveness is not guaranteed. Under a best-case scenario, we find that screening must cost < USD 100 per site for MVL to achieve 30% cost reductions relative to SVL. In scenarios with non-target vented emissions and screening quantification uncertainty, triaging errors force excessive close-range follow-up to achieve emissions reduction equivalence. The viability of MVL as a cost-effective alternative to SVL for reducing fugitive methane emissions hinges on accurate triaging after the screening phase.

Natural killer (NK) cell subsets with adaptive properties are emerging as regulators of vaccine-induced T and B cell responses and are specialized towards antibody-dependent functions contributing to SARS-CoV-2 control. Although HIV-1 infection is known to affect the NK cell pool, the additional impact of SARS-CoV-2 infection and/or vaccination on NK cell responses in people living with HIV (PLWH) has remained unexplored. Our data show that SARS-CoV-2 infection skews NK cells towards a more differentiated/adaptive CD57 + FcεRIγ − phenotype in PLWH. A similar subset was induced following vaccination in SARS-CoV-2 naïve PLWH in addition to a CD56 bright population with cytotoxic potential. Antibody-dependent NK cell function showed robust and durable responses to Spike up to 148 days post-infection, with responses enriched in adaptive NK cells. NK cell responses were further boosted by the first vaccine dose in SARS-CoV-2 exposed individuals and peaked after the second dose in SARS-CoV-2 naïve PLWH. The presence of adaptive NK cells associated with the magnitude of cellular and humoral responses. These data suggest that features of adaptive NK cells can be effectively engaged to complement and boost vaccine-induced adaptive immunity in potentially more vulnerable groups such as PLWH.

We analyse ice flow and structural glaciology of Shackleton Glacier, a dendritic glacier with multiple icefalls in the Canadian Rockies. A major tributary-trunk junction allows us to investigate the potential of tributaries to alter trunk flow and structure, and the formation of bedrock steps at confluences. Multi-year velocity-stake data and structural glaciology up-glacier from the junction were assimilated with glacier-wide velocity derived from Radarsat-2 speckle tracking. Maximum flow speeds are 65 m a−1 in the trunk and 175 m a−1 in icefalls. Field and remote-sensing velocities are in good agreement, except where velocity gradients are high. Although compression occurs in the trunk up-glacier of the tributary entrance, glacier flux is steady state because flow speed increases at the junction due to the funnelling of trunk ice towards an icefall related to a bedrock step. Drawing on a published erosion model, we relate the heights of the step and the hanging valley to the relative fluxes of the tributary and trunk. It is the first time that an extant glacier is used to test and support such model. Our study elucidates the inherent complexity of tributary/trunk interactions and provides a conceptual model for trunk flow restriction by a tributary in surge-type glaciers.

Interest has grown in using new screening technologies such as drones to search for methane leaks in hydrocarbon production infrastructure. Screening technologies may be less expensive and faster than traditional methods. However, including new technologies in emissions monitoring programs requires an accurate understanding of what leaks a system will detect and the resultant emissions mitigation. Here we examine source detection of a drone-based system with controlled releases. We examine different detection algorithm parameters to understand trade-offs between false positive rate and detection probability. Leak detection was poor under all conditions with an average detection probability of 0.21. Detection probability was not affected by emission rate, suggesting similar systems may commonly miss large leaks. Detection was best in moderate wind speeds and at 750–2000 m downwind from the source where the plume had diffused vertically above the minimum flight level of 40–50 m. Predicted concentration enhancement from a Gaussian plume model was a reasonable predictor of detection within the test suite. Enabling lower flight elevations may increase detection probability. Overall, the experiments suggest that controlled releases are useful and necessary to provide an understanding of detection probability of screening technologies for regulatory and deployment purposes, and the testing must be representative to support broad application.

Rats, birds or fish trained to find a reward in one corner of a small enclosure tend to learn the location of the reward using both nearby visual features and the geometric relationships of corners and walls. Because these studies are conducted under laboratory and thereby unnatural conditions, we sought to determine whether wild, free-living rufous hummingbirds ( Selasphorus rufus ) learning a single reward location within a rectangular array of flowers would similarly employ both nearby visual landmarks and the geometric relationships of the array. Once subjects had learned the location of the reward, we used test probes in which one or two experimental landmarks were moved or removed in order to reveal how the birds remembered the reward location. The hummingbirds showed no evidence that they used the geometry of the rectangular array of flowers to remember the reward. Rather, they used our experimental landmarks, and possibly nearby, natural landmarks, to orient and navigate to the reward. We believe this to be the first test of the use of rectangular geometry by wild animals, and we recommend further studies be conducted in ecologically relevant conditions in order to help determine how and when animals form complex geometric representations of their local environments.