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Ambient fine particulate matter (PM 2.5 ) is the world’s leading environmental health risk factor. Reducing the PM 2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM 2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74–1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM 2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52–0.95] million deaths; 19.2%), industrial (0.45 [0.32–0.58] million deaths; 11.7%), and energy (0.39 [0.28–0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources. Ambient fine particulate matter (PM 2.5 ) is one of the most important environmental health risk factors in many regions. Here, the authors present an assessment of PM 2.5 emission sources and the related health impacts across global to sub-national scales and find that over 1 million deaths were avoidable in 2017 by eliminating PM 2.5 mass associated with fossil fuel combustion emissions.

The concentration of fine particulate matter (PM 2.5 ) across China has decreased by 30–50% over the period 2013–2018 due to stringent emission controls. However, the nitrate component of PM 2.5 has not responded effectively to decreasing emissions of nitrogen oxides and has actually increased during winter haze pollution events in the North China Plain. Here, we show that the GEOS-Chem atmospheric chemistry model successfully simulates the nitrate concentrations and trends. We find that winter mean nitrate would have increased over 2013–2018 were it not for favourable meteorology. The principal cause of this nitrate increase is weaker deposition. The fraction of total inorganic nitrate as particulate nitrate instead of gaseous nitric acid over the North China Plain in winter increased from 90% in 2013 to 98% in 2017, as emissions of nitrogen oxides and sulfur dioxide decreased while ammonia emissions remained high. This small increase in the particulate fraction greatly slows down deposition of total inorganic nitrate and hence drives the particulate nitrate increase. Our results suggest that decreasing ammonia emissions would decrease particulate nitrate by driving faster deposition of total inorganic nitrate. Decreasing nitrogen oxide emissions is less effective because it drives faster oxidation of nitrogen oxides and slower deposition of total inorganic nitrate. Reduction of ammonia emissions may be effective in reducing the nitrate component of fine particulate matter air pollution across the North China Plain, according to the simulation of nitrate trends using the GEOS-Chem atmospheric chemistry model.

Abstract Context Use of continuous glucose monitoring (CGM) is increasing for insulin-requiring patients with diabetes. Although data on glycemic profiles of healthy, nondiabetic individuals exist for older sensors, assessment of glycemic metrics with new-generation CGM devices is lacking. Objective To establish reference sensor glucose ranges in healthy, nondiabetic individuals across different age groups using a current generation CGM sensor. Design Multicenter, prospective study. Setting Twelve centers within the T1D Exchange Clinic Network. Patients or Participants Nonpregnant, healthy, nondiabetic children and adults (age ≥6 years) with nonobese body mass index. Intervention Each participant wore a blinded Dexcom G6 CGM, with once-daily calibration, for up to 10 days. Main Outcome Measures CGM metrics of mean glucose, hyperglycemia, hypoglycemia, and glycemic variability. Results A total of 153 participants (age 7 to 80 years) were included in the analyses. Mean average glucose was 98 to 99 mg/dL (5.4 to 5.5 mmol/L) for all age groups except those over 60 years, in whom mean average glucose was 104 mg/dL (5.8 mmol/L). The median time between 70 to 140 mg/dL (3.9 to 7.8 mmol/L) was 96% (interquartile range, 93 to 98). Mean within-individual coefficient of variation was 17 ± 3%. Median time spent with glucose levels >140 mg/dL was 2.1% (30 min/d), and median time spent with glucose levels <70 mg/dL (3.9 mmol/L) was 1.1% (15 min/d). Conclusion By assessing across age groups in a healthy, nondiabetic population, normative sensor glucose data have been derived and will be useful as a benchmark for future research studies. This study provides normative sensor glucose data in a healthy, nondiabetic population of children and adults.

Conservation practitioners have long recognized ecological connectivity as a global priority for preserving biodiversity and ecosystem function. In the early years of conservation science, ecologists extended principles of island biogeography to assess connectivity based on source patch proximity and other metrics derived from binary maps of habitat. From 2006 to 2008, the late Brad McRae introduced circuit theory as an alternative approach to model gene flow and the dispersal or movement routes of organisms. He posited concepts and metrics from electrical circuit theory as a robust way to quantify movement across multiple possible paths in a landscape, not just a single least-cost path or corridor. Circuit theory offers many theoretical, conceptual, and practical linkages to conservation science. We reviewed 459 recent studies citing circuit theory or the open-source software Circuitscape. We focused on applications of circuit theory to the science and practice of connectivity conservation, including topics in landscape and population genetics, movement and dispersal paths of organisms, anthropogenic barriers to connectivity, fire behavior, water flow, and ecosystem services. Circuit theory is likely to have an effect on conservation science and practitioners through improved insights into landscape dynamics, animal movement, and habitat-use studies and through the development of new software tools for data analysis and visualization. The influence of circuit theory on conservation comes from the theoretical basis and elegance of the approach and the powerful collaborations and active user community that have emerged. Circuit theory provides a springboard for ecological understanding and will remain an important conservation tool for researchers and practitioners around the globe. Quienes practican la conservación han reconocido durante mucho tiempo que la conectividad ecológica es una prioridad mundial para la preservación de la biodiversidad y el funcionamiento del ecosistema. Durante los primeros años de la ciencia de la conservación los ecólogos difundieron los principios de la biografía de islas para evaluar la conectividad con base en la proximidad entre el origen y el fragmento, así como otras medidas derivadas de los mapas binarios de los hábitats. Entre 2006 y 2008 el fallecido Brad McRae introdujo la teoría de circuitos como una estrategia alternativa para modelar el flujo génico y la dispersión o las rutas de movimiento de los organismos. McRae propuso conceptos y medidas de la teoría de circuitos eléctricos como una manera robusta para cuantificar el movimiento a lo largo demúltiplescaminos posibles en un paisaje, no solamente a lo largo de un camino o corredor de menor costo. La teoría de circuitos ofrece muchos enlaces teóricos, conceptuales y prácticos con la ciencia de la conservación. Revisamos 459 estudios recientes que citan la teoría de circuitos o el software de fuente abierta Circuitscape. Nos enfocamos en las aplicaciones de la teoría de circuitos a la ciencia y a la práctica de la conservación de la conectividad, incluyendo temas como la genética poblacional y del paisaje, movimiento y caminos de dispersión de los organismos, barreras antropogénicas de la conectividad, comportamiento ante incendios, flujo del agua, y servicios ambientales. La teoría de circuitos probablemente tenga un efecto sobre la ciencia de la conservación y quienes la practican por medio de una percepción mejorada de las dinámicas del paisaje, el movimiento animal, y los estudios de uso de hábitat, y por medio del desarrollo de nuevas herramientas de software para el análisis de datos y su visualización. La influencia de la teoría de circuitos sobre la conservación viene de la base teórica y la elegancia de la estrategia y de las colaboraciones fuertes y la comunidad activa de usuarios que han surgido recientemente. La teoría de circuitos proporciona un trampolín para el entendimiento ecológico y seguirá siendo una importante herramienta de conservación para los investigadores y practicantes en todo el mundo. 保护实践者长期以来一直将生态连接度视为保护生物多祥性和生态系统功能的当务之急。在保护科学发 展早期，生态学家将岛屿生物地理学的原理进行扩展，基于源斑块邻近度和其它来_ ニ元生境图的指标来评估连 接度。2006 年到 2008 年，已故的 Brad McRae 引入了电路理论，作为模拟基因流和生物体扩散或移动路径的新 方法。他用电路理论中的概念和指标开发了一种稳健的方法来量化景观中多种可能的移动路径，而这不只是ー 条最低成本的路径或廊道。电路理论为保护科学提供了许多理论、概念和实践方面的联系。我们综述了近期引 用电路理论或是开源软件Circidtscape的459项研究，重点关注电路理论在连接度保护科学与实践中的应用，包 括景观和种群遗传学、生物体运动和扩散路径、连接度的人为障碍、火灾、水流和生态系统服务等间题。电路 理论通过帮助理解景观动力学、动物移动和生境利用研究，以及开发新的数据分析和可视化软件工具，影响着 保护科学和实践者。电路理论对保护的影响来自于该方法的理论基础和优雅性，以及现已出现的強大的合作队 伍和活跃的用户群体。电路理论为生态学理解提供了跳板，并将继续作为全球研究人员和实践者的重要保护エ 具。

Fine particulate matter (PM2.5) decreased by 30–40% across China during 2013–2017 in response to the governmental Clean Air Action. However, surface ozone pollution worsened over the same period. Model simulations have suggested that the increase in ozone could be driven by the decrease in PM2.5, because PM2.5 scavenges hydroperoxy (HO2) and NOx radicals that would otherwise produce ozone. Here we show observational evidence for this effect with 2013–2018 summer data of hourly ozone and PM2.5 concentrations from 106 sites in the North China Plain. The observations show suppression of ozone pollution at high PM2.5 concentrations, consistent with a model simulation in which PM2.5 scavenging of HO2 and NOx depresses ozone concentrations by 25 ppb relative to PM2.5-free conditions. PM2.5 chemistry makes ozone pollution less sensitive to NOx emission controls, emphasizing the need for controlling emissions of volatile organic compounds (VOCs), which so far have not decreased in China. The new 2018–2020 Clean Air Action plan calls for a 10% decrease in VOC emissions that should begin to reverse the long-term ozone increase even as PM2.5 continues to decrease. Aggressive reduction of NOx and aromatic VOC emissions should be particularly effective for decreasing both PM2.5 and ozone.

Shah and Rajagopal discuss the study by Cai et al which investigates the role of ionocytes in cystic fibrosis (CF) airways. Previous research suggested that ionocytes play a role in regulating airway physiology, but their abundance in human small airways was questioned. Cai et al provide evidence supporting the central role of ionocytes in CF airways. They found that sonic hedgehog (SHH) signaling pathway activation is increased in CF, leading to an increased number of ionocytes. Importantly, the increased number of ionocytes was associated with an increased CFTR current. The researchers also observed a decrease in secretory cell numbers. Overall, this study demonstrates that elevated SHH signaling in CF epithelia leads to an increase in ionocytes and a decrease in secretory cells. These findings contribute to the understanding of the pathophysiology of CF and highlight the importance of ionocytes in CF airways.

Bridging cultures that have often been distant, Julia combines expertise from the diverse fields of computer science and computational science to create a new approach to numerical computing. Julia is designed to be easy and fast and questions notions generally held to be \"laws of nature\" by practitioners of numerical computing: 1. High-level dynamic programs have to be slow. 2. One must prototype in one language and then rewrite in another language for speed or deployment. 3. There are parts of a system appropriate for the programmer, and other parts that are best left untouched as they have been built by the experts. We introduce the Julia programming language and its design—a dance between specialization and abstraction. Specialization allows for custom treatment. Multiple dispatch, a technique from computer science, picks the right algorithm for the right circumstance. Abstraction, which is what good computation is really about, recognizes what remains the same after differences are stripped away. Abstractions in mathematics are captured as code through another technique from computer science, generic programming. Julia shows that one can achieve machine performance without sacrificing human convenience.

Connectivity among populations and habitats is important for a wide range of ecological processes. Understanding, preserving, and restoring connectivity in complex landscapes requires connectivity models and metrics that are reliable, efficient, and process based. We introduce a new class of ecological connectivity models based in electrical circuit theory. Although they have been applied in other disciplines, circuit-theoretic connectivity models are new to ecology. They offer distinct advantages over common analytic connectivity models, including a theoretical basis in random walk theory and an ability to evaluate contributions of multiple dispersal pathways. Resistance, current, and voltage calculated across graphs or raster grids can be related to ecological processes (such as individual movement and gene flow) that occur across large population networks or landscapes. Efficient algorithms can quickly solve networks with millions of nodes, or landscapes with millions of raster cells. Here we review basic circuit theory, discuss relationships between circuit and random walk theories, and describe applications in ecology, evolution, and conservation. We provide examples of how circuit models can be used to predict movement patterns and fates of random walkers in complex landscapes and to identify important habitat patches and movement corridors for conservation planning.

Abstract Context Minority young adults (YA) currently represent the largest growing population with type 1 diabetes (T1D) and experience very poor outcomes. Modifiable drivers of disparities need to be identified, but are not well-studied. Objective To describe racial-ethnic disparities among YA with T1D and identify drivers of glycemic disparity other than socioeconomic status (SES). Design Cross-sectional multicenter collection of patient and chart-reported variables, including SES, social determinants of health, and diabetes-specific factors, with comparison between non-Hispanic White, non-Hispanic Black, and Hispanic YA and multilevel modeling to identify variables that account for glycemic disparity apart from SES. Setting Six diabetes centers across the United States. Participants A total of 300 YA with T1D (18-28 years: 33% non-Hispanic White, 32% non-Hispanic Black, and 34% Hispanic). Main Outcome Racial-ethnic disparity in HbA1c levels. Results Non-Hispanic Black and Hispanic YA had lower SES, higher HbA1c levels, and much lower diabetes technology use than non-Hispanic White YA (P < 0.001). Non-Hispanic Black YA differed from Hispanic, reporting higher diabetes distress and lower self-management (P < 0.001). After accounting for SES, differences in HbA1c levels disappeared between non-Hispanic White and Hispanic YA, whereas they remained for non-Hispanic Black YA (+ 2.26% [24 mmol/mol], P < 0.001). Diabetes technology use, diabetes distress, and disease self-management accounted for a significant portion of the remaining non-Hispanic Black–White glycemic disparity. Conclusion This study demonstrated large racial-ethnic inequity in YA with T1D, especially among non-Hispanic Black participants. Our findings reveal key opportunities for clinicians to potentially mitigate glycemic disparity in minority YA by promoting diabetes technology use, connecting with social programs, and tailoring support for disease self-management and diabetes distress to account for social contextual factors.