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Flooding affects more people than any other environmental hazard and hinders sustainable development. Investing in flood adaptation strategies may reduce the loss of life and livelihood caused by floods. Where and how floods occur and who is exposed are changing as a result of rapid urbanization4, flood mitigation infrastructure and increasing settlements in floodplains6. Previous estimates of the global flood-exposed population have been limited by a lack of observational data, relying instead on models, which have high uncertainty. Here we use daily satellite imagery at 250-metre resolution to estimate flood extent and population exposure for 913 large flood events from 2000 to 2018. We determine a total inundation area of 2.23 million square kilometres, with 255–290 million people directly affected by floods. We estimate that the total population in locations with satellite-observed inundation grew by 58–86 million from 2000 to 2015. This represents an increase of 20 to 24 per cent in the proportion of the global population exposed to floods, ten times higher than previous estimates. Climate change projections for 2030 indicate that the proportion of the population exposed to floods will increase further. The high spatial and temporal resolution of the satellite observations will improve our understanding of where floods are changing and how best to adapt. The global flood database generated from these observations will help to improve vulnerability assessments, the accuracy of global and local flood models, the efficacy of adaptation interventions and our understanding of the interactions between landcover change, climate and floods.

This paper aims to bridge progress in neuroscience involving sophisticated quantitative analysis of behavior, including the use of robust control, with other relevant conceptual and theoretical frameworks from systems engineering, systems biology, and mathematics. Familiar and accessible case studies are used to illustrate concepts of robustness, organization, and architecture (modularity and protocols) that are central to understanding complex networks. These essential organizational features are hidden during normal function of a system but are fundamental for understanding the nature, design, and function of complex biologic and technologic systems.

Pollen and microspore development are essential steps in the life cycle of all land plants that generate male gametes. Within flowering plants, pollen development occurs inside of the anther. Here, we report the identification of two class III peroxidase-encoding genes, PEROXIDASE9 (PRX9) and PRX40, that are genetically redundant and essential for proper anther and pollen development in Arabidopsis (Arabidopsis thaliana). Arabidopsis double mutants devoid of functional PRX9 and PRX40 are male sterile. The mutant anthers display swollen, hypertrophic tapetal cells and pollen grains, suggesting disrupted cell wall integrity. These phenotypes lead to nearly 100%-penetrant pollen degeneration upon anther maturation. Using immunochemical and biochemical approaches, we show that PRX9 and PRX40 likely cross-link extensins to contribute to tapetal cell wall integrity during anther development. This work suggests that PRX9 and PRX40 encode Arabidopsis extensin peroxidases and highlights the importance of extensin cross-linking during pollen development.

Nervous systems sense, communicate, compute, and actuate movement using distributed components with severe trade-offs in speed, accuracy, sparsity, noise, and saturation. Nevertheless, brains achieve remarkably fast, accurate, and robust control performance due to a highly effective layered control architecture. Here, we introduce a driving task to study how a mountain biker mitigates the immediate disturbance of trail bumps and responds to changes in trail direction. We manipulated the time delays and accuracy of the control input from the wheel as a surrogate for manipulating the characteristics of neurons in the control loop. The observed speed–accuracy trade-offs motivated a theoretical framework consisting of two layers of control loops—a fast, but inaccurate, reflexive layer that corrects for bumps and a slow, but accurate, planning layer that computes the trajectory to follow—each with components having diverse speeds and accuracies within each physical level, such as nerve bundles containing axons with a wide range of sizes. Our model explains why the errors from two control loops are additive and shows how the errors in each control loop can be decomposed into the errors caused by the limited speeds and accuracies of the components. These results demonstrate that an appropriate diversity in the properties of neurons across layers helps to create “diversity-enabled sweet spots,” so that both fast and accurate control is achieved using slow or inaccurate components.

Fire is a worldwide phenomenon that appears in the geological record soon after the appearance of terrestrial plants. Fire influences global ecosystem patterns and processes, including vegetation distribution and structure, the carbon cycle, and climate. Although humans and fire have always coexisted, our capacity to manage fire remains imperfect and may become more difficult in the future as climate change alters fire regimes. This risk is difficult to assess, however, because fires are still poorly represented in global models. Here, we discuss some of the most important issues involved in developing a better understanding of the role of fire in the Earth system.

In those undergoing treatment for head and neck cancer (HNC), sarcopenia is a strong prognostic factor for outcomes and mortality. This review identified working definitions and methods used to objectively assess sarcopenia in HNC. The scoping review was performed in accordance with Arksey and O'Malley's five-stage methodology and the Joanna Briggs Institute guidelines. Eligible studies were identified using MEDLINE, Embase, Scopus, Cochrane Library, and CINAHL databases. Inclusion criteria represented studies of adult HNC patients in which sarcopenia was listed as an outcome, full-text articles written in English, and empirical research studies with a quantitative design. Eligible studies were assessed using a proprietary data extraction form. General information, article details and characteristics, and details related to the concept of the scoping review were extracted in an iterative process. Seventy-six studies published internationally from 2016 to 2021 on sarcopenia in HNC were included. The majority were retrospective (n = 56; 74%) and the prevalence of sarcopenia ranged from 3.8% to 78.7%. Approximately two-thirds of studies used computed tomography (CT) to assess sarcopenia. Skeletal muscle index (SMI) at the third lumbar vertebra (L3) (n = 53; 70%) was the most prevalent metric used to identify sarcopenia, followed by SMI at the third cervical vertebra (C3) (n = 4; 5%). Currently, the most effective strategy to assess sarcopenia in HNC depends on several factors, including access to resources, patient and treatment characteristics, and the prognostic significance of outcomes used to represent sarcopenia. Skeletal muscle mass (SMM) measured at C3 may represent a practical, precise, and cost-effective biomarker for the detection of sarcopenia. However, combining SMM measurements at C3 with other sarcopenic parameters-including muscle strength and physical performance-may provide a more accurate risk profile for sarcopenia assessment and allow for a greater understanding of this condition in HNC.

Both engineering and evolution are constrained by trade-offs between efficiency and robustness, but theory that formalizes this fact is limited. For a simple two-state model of glycolysis, we explicitly derive analytic equations for hard trade-offs between robustness and efficiency with oscillations as an inevitable side effect. The model describes how the trade-offs arise from individual parameters, including the interplay of feedback control with autocatalysis of network products necessary to power and catalyze intermediate reactions. We then use control theory to prove that the essential features of these hard trade-off \"laws\" are universal and fundamental, in that they depend minimally on the details of this system and generalize to the robust efficiency of any autocatalytic network. The theory also suggests worst-case conditions that are consistent with initial experiments.

Background Type 1 diabetes (T1D) places an extraordinary burden on individuals and their families, as well as on the healthcare system. Despite recent advances in glucose sensors and insulin pump technology, only a minority of patients meet their glucose targets and face the risk of both acute and long-term complications, some of which are life-threatening. The JAK-STAT pathway is critical for the immune-mediated pancreatic beta cell destruction in T1D. Our pre-clinical data show that inhibitors of JAK1/JAK2 prevent diabetes and reverse newly diagnosed diabetes in the T1D non-obese diabetic mouse model. The goal of this study is to determine if the JAK1/JAK2 inhibitor baricitinib impairs type 1 diabetes autoimmunity and preserves beta cell function. Methods This will be as a multicentre, two-arm, double-blind, placebo-controlled randomized trial in individuals aged 10–30 years with recent-onset T1D. Eighty-three participants will be randomized in a 2:1 ratio within 100 days of diagnosis to receive either baricitinib 4mg/day or placebo for 48 weeks and then monitored for a further 48 weeks after stopping study drug. The primary outcome is the plasma C-peptide 2h area under the curve following ingestion of a mixed meal. Secondary outcomes include HbA1c, insulin dose, continuous glucose profile and adverse events. Mechanistic assessments will characterize general and diabetes-specific immune responses. Discussion This study will determine if baricitinib slows the progressive, immune-mediated loss of beta cell function that occurs after clinical presentation of T1D. Preservation of beta cell function would be expected to improve glucose control and prevent diabetes complications, and justify additional trials of baricitinib combined with other therapies and of its use in at-risk populations to prevent T1D. Trial registration ANZCTR ACTRN12620000239965 . Registered on 26 February 2020. ClinicalTrials.gov NCT04774224. Registered on 01 March 2021

Advanced technologies and biology have extremely different physical implementations, but they are far more alike in systems-level organization than is widely appreciated. Convergent evolution in both domains produces modular architectures that are composed of elaborate hierarchies of protocols and layers of feedback regulation, are driven by demand for robustness to uncertain environments, and use often imprecise components. This complexity may be largely hidden in idealized laboratory settings and in normal operation, becoming conspicuous only when contributing to rare cascading failures. These puzzling and paradoxical features are neither accidental nor artificial, but derive from a deep and necessary interplay between complexity and robustness, modularity, feedback, and fragility. This review describes insights from engineering theory and practice that can shed some light on biological complexity.

The search for unifying properties of complex networks is popular, challenging, and important. For modeling approaches that focus on robustness and fragility as unifying concepts, the Internet is an especially attractive case study, mainly because its applications are ubiquitous and pervasive, and widely available expositions exist at every level of detail. Nevertheless, alternative approaches to modeling the Internet often make extremely different assumptions and derive opposite conclusions about fundamental properties of one and the same system. Fortunately, a detailed understanding of Internet technology combined with a unique ability to measure the network means that these differences can be understood thoroughly and resolved unambiguously. This article aims to make recent results of this process accessible beyond Internet specialists to the broader scientific community and to clarify several sources of basic methodological differences that are relevant beyond either the Internet or the two specific approaches focused on here (i.e., scale-free networks and highly optimized tolerance networks).