Toward Community-Driven Big Open Brain Science: Open Big Data and Tools for Structure, Function, and Genetics.

As acquiring bigger data becomes easier in experimental brain science, computational and statistical brain science must achieve similar advances to fully capitalize on these data. Tackling these problems will benefit from a more explicit and concerted effort to work together. Specifically, brain science can be further democratized by harnessing the power of community-driven tools, which both are built by and benefit from many different people with different backgrounds and expertise. This perspective can be applied across modalities and scales and enables collaborations across previously siloed communities.

Reassessing the role of urban green space in air pollution control.

The assumption that vegetation improves air quality is prevalent in scientific, popular, and political discourse. However, experimental and modeling studies show the effect of green space on air pollutant concentrations in urban settings is highly variable and context specific. We revisited the link between vegetation and air quality using satellite-derived changes of urban green space and air pollutant concentrations from 2,615 established monitoring stations over Europe and the United States. Between 2010 and 2019, stations recorded declines in ambient NO2, (particulate matter) PM10, and PM2.5 (average of -3.14% y-1), but not O3 (+0.5% y-1), pointing to the general success of recent policy interventions to restrict anthropogenic emissions. The effect size of total green space on air pollution was weak and highly variable, particularly at the street scale (15 to 60 m radius) where vegetation can restrict ventilation. However, when isolating changes in tree cover, we found a negative association with air pollution at borough to city scales (120 to 16,000 m) particularly for O3 and PM. The effect of green space was smaller than the pollutant deposition and dispersion effects of meteorological drivers including precipitation, humidity, and wind speed. When averaged across spatial scales, a one SD increase in green space resulted in a 0.8% (95% CI: -3.5 to 2%) decline in air pollution. Our findings suggest that while urban greening may improve air quality at the borough-to-city scale, the impact is moderate and may have detrimental street-level effects depending on aerodynamic factors like vegetation type and urban form.

Transforming the grid for a more environmentally and socially sustainable electricity system in Great Britain is a slow and uneven process.

Electricity system decarbonization is key for environmental sustainability. From a consumption-production perspective, much attention has been paid to changes in how electricity is generated and used, but electricity systems also rely on a grid infrastructure that connects and integrates production and consumption, and which will also need to transform. At the same time, new technologies in the electricity system, including the grid, offer the potential for more socially sustainable ways of producing and consuming energy. However, in practice, change has been slow, uneven, and often dysfunctional. A socio-technical transitions approach offers insights into why this is so, seeing electricity system change not simply in technical and economic terms, but also as the outcomes of interactions between technology and social and political processes. The approach draws attention to the particular challenges of achieving rapid transitions in complex critical infrastructures like electricity with strong institutional logics of security. This article applies this approach to the case of Great Britain, where despite strong commitments to sustainability in the form of high-level climate policy, the electricity grid has often been a constraint on the pace of change. The nature of the British transition is explained partly by weak links between these high-level goals on the one hand and the detailed rules and practices in the electricity system on the other. It is also explained by patterns of ownership and grid regulation in the British case that protect incumbents and make it difficult for new actors to develop the system in more socially sustainable directions.

Bikeability and the induced demand for cycling.

To what extent is the volume of urban bicycle traffic affected by the provision of bicycle infrastructure? In this study, we exploit a large dataset of GPS trajectories of bicycle trips in combination with a fine-grained representation of the Copenhagen bicycle-relevant network. We apply a model for bicyclists' choice of route from origin to destination that takes the complete network into account. This enables us to determine bicyclists' preferences for a range of infrastructure and land-use types. We use the estimated preferences to compute a generalized cost of bicycle travel, which we correlate with the number of bicycle trips across a large number of origin-destination pairs. Simulations suggest that the extensive Copenhagen bicycle lane network has caused the number of bicycle trips and the bicycle kilometers traveled to increase by 60% and 90%, respectively, compared with a counterfactual without the bicycle lane network. This translates into an annual benefit of €0.4M per km of bicycle lane owing to changes in generalized travel cost, health, and accidents. Our results thus strongly support the provision of bicycle infrastructure.

Climate oscillation impacts on water supply augmentation planning.

Climate oscillations ranging from years to decades drive precipitation variability in many river basins globally. As a result, many regions will require new water infrastructure investments to maintain reliable water supply. However, current adaptation approaches focus on long-term trends, preparing for average climate conditions at mid- or end-of-century. The impact of climate oscillations, which bring prolonged and variable but temporary dry periods, on water supply augmentation needs is unknown. Current approaches for theory development in nature-society systems are limited in their ability to realistically capture the impacts of climate oscillations on water supply. Here, we develop an approach to build middle-range theory on how common climate oscillations affect low-cost, reliable water supply augmentation strategies. We extract contrasting climate oscillation patterns across sub-Saharan Africa and study their impacts on a generic water supply system. Our approach integrates climate model projections, nonstationary signal processing, stochastic weather generation, and reinforcement learning-based advances in stochastic dynamic control. We find that longer climate oscillations often require greater water supply augmentation capacity but benefit more from dynamic approaches. Therefore, in settings with the adaptive capacity to revisit planning decisions frequently, longer climate oscillations do not require greater capacity. By building theory on the relationship between climate oscillations and least-cost reliable water supply augmentation, our findings can help planners target scarce resources and guide water technology and policy innovation. This approach can be used to support climate adaptation planning across large spatial scales in sectors impacted by climate variability.

Neurodevelopmental copy-number variants: A roadmap to improving outcomes by uniting patient advocates, researchers, and clinicians for collective impact.

Copy-number variants and structural variants (CNVs/SVs) drive many neurodevelopmental-related disorders. While many neurodevelopmental-related CNVs/SVs give rise to complex phenotypes, the overlap in phenotypic presentation between independent CNVs can be extensive and provides a motivation for shared approaches. This confluence at the level of clinical phenotype implies convergence in at least some aspects of the underlying genomic mechanisms. With this perspective, our Commission on Novel Technologies for Neurodevelopmental CNVs asserts that the time has arrived to approach neurodevelopmental-related CNVs/SVs as a class of disorders that can be identified, investigated, and treated on the basis of shared mechanisms and/or pathways (e.g., molecular, neurological, or developmental). To identify common etiologic mechanisms among uncommon neurodevelopmental-related disorders and to potentially identify common therapies, it is paramount for teams of scientists, clinicians, and patients to unite their efforts. We bring forward novel, collaborative, and integrative strategies to translational CNV/SV research that engages diverse stakeholders to help expedite therapeutic outcomes. We articulate a clear vision for piloted roadmap strategies to reduce patient/caregiver burden and redundancies, increase efficiency, avoid siloed data, and accelerate translational discovery across CNV/SV-based syndromes.

Efficacy of Centers of Biomedical Research Excellence (CoBRE) grants to build research capacity in underrepresented states.

Federal funding for research has immediate and long-term economic impact. Since federal research funding is regionally concentrated and not geographically distributed, the benefits are not fully realized in some regions of the country. The Established (previously Experimental) Program to Stimulate Competitive Research (EPSCoR) programs at several agencies, for example, the National Science Foundation, and the Institutional Development Award (IDeA) program at the National Institutes of Health were created to increase competitiveness for funding in states with historically low levels of federal funding. The Centers of Biomedical Research Excellence (CoBRE) award program is a component of the IDeA program. The CoBRE grants support research core facilities to develop research infrastructure. These grants also support the research projects of junior investigators, under the guidance of mentoring teams of senior investigators, to develop human resources at these institutions. Few studies have assessed the effectiveness of these programs. This study examines the investment and outcomes of the CoBRE grants from 2000 through 2022. The maturation of junior investigators into independently funded principal investigators is comparable to other mentoring programs supported by NIH. The investment in research cores resulted in substantial research productivity, measured by publications. Despite the successes of individual investigators and increased research infrastructure and productivity, the geographic distribution of federal and NIH research dollars has not changed. These results will be informative in consideration of policies designed to enhance the geographic distribution of federal research dollars.

Global expansion of sustainable irrigation limited by water storage.

Providing affordable and nutritious food to a growing and increasingly affluent global population requires multifaceted approaches to target supply and demand aspects. On the supply side, expanding irrigation is key to increase future food production, yet associated needs for storing water and implications of providing that water storage, remain unknown. Here, we quantify biophysical potentials for storage-fed sustainable irrigation-irrigation that neither depletes freshwater resources nor expands croplands but requires water to be stored before use-and study implications for food security and infrastructure. We find that water storage is crucial for future food systems because 460 km3/yr of sustainable blue water, enough to grow food for 1.15 billion people, can only be used for irrigation after storage. Even if all identified future dams were to contribute water to irrigation, water stored in dammed reservoirs could only supply 209 ± 50 km3/yr to irrigation and grow food for 631 ± 145 million people. In the face of this gap and the major socioecologic externalities from future dams, our results highlight limits of gray infrastructure for future irrigation and urge to increase irrigation efficiency, change to less water-intensive cropping systems, and deploy alternative storage solutions at scale.

Satellite mapping of urban built-up heights reveals extreme infrastructure gaps and inequalities in the Global South.

Information on urban built-up infrastructure is essential to understand the role of cities in shaping environmental, economic, and social outcomes. The lack of data on built-up heights over large areas has limited our ability to characterize urban infrastructure and its spatial variations across the world. Here, we developed a global atlas of urban built-up heights circa 2015 at 500-m resolution from the Sentinel-1 Ground Range Detected satellite data. Results show extreme gaps in per capita urban built-up infrastructure in the Global South compared with the global average, and even larger gaps compared with the average levels in the Global North. Per capita urban built-up infrastructures in some countries in the Global North are more than 30 times higher than those in the Global South. The results also show that the built-up infrastructure in 45 countries in the Global North combined, with ∼16% of the global population, is roughly equivalent to that of 114 countries in the Global South, with ∼74% of the global population. The inequality in urban built-up infrastructure, as measured by an inequality index, is large in most countries, but the largest in the Global South compared with the Global North. Our analysis reveals the scale of infrastructure demand in the Global South that is required in order to meet sustainable development goals.

Machine learning-driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins.

RAS is a signaling protein associated with the cell membrane that is mutated in up to 30% of human cancers. RAS signaling has been proposed to be regulated by dynamic heterogeneity of the cell membrane. Investigating such a mechanism requires near-atomistic detail at macroscopic temporal and spatial scales, which is not possible with conventional computational or experimental techniques. We demonstrate here a multiscale simulation infrastructure that uses machine learning to create a scale-bridging ensemble of over 100,000 simulations of active wild-type KRAS on a complex, asymmetric membrane. Initialized and validated with experimental data (including a new structure of active wild-type KRAS), these simulations represent a substantial advance in the ability to characterize RAS-membrane biology. We report distinctive patterns of local lipid composition that correlate with interfacially promiscuous RAS multimerization. These lipid fingerprints are coupled to RAS dynamics, predicted to influence effector binding, and therefore may be a mechanism for regulating cell signaling cascades.