Showing papers in "Proceedings of the National Academy of Sciences of the United States of America in 2016"

Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates

Abstract: The most widely used task functional magnetic resonance imaging (fMRI) analyses use parametric statistical methods that depend on a variety of assumptions. In this work, we use real resting-state data and a total of 3 million random task group analyses to compute empirical familywise error rates for the fMRI software packages SPM, FSL, and AFNI, as well as a nonparametric permutation method. For a nominal familywise error rate of 5%, the parametric statistical methods are shown to be conservative for voxelwise inference and invalid for clusterwise inference. Our results suggest that the principal cause of the invalid cluster inferences is spatial autocorrelation functions that do not follow the assumed Gaussian shape. By comparison, the nonparametric permutation test is found to produce nominal results for voxelwise as well as clusterwise inference. These findings speak to the need of validating the statistical methods being used in the field of neuroimaging.

Discovering governing equations from data by sparse identification of nonlinear dynamical systems

Abstract: Extracting governing equations from data is a central challenge in many diverse areas of science and engineering. Data are abundant whereas models often remain elusive, as in climate science, neuroscience, ecology, finance, and epidemiology, to name only a few examples. In this work, we combine sparsity-promoting techniques and machine learning with nonlinear dynamical systems to discover governing equations from noisy measurement data. The only assumption about the structure of the model is that there are only a few important terms that govern the dynamics, so that the equations are sparse in the space of possible functions; this assumption holds for many physical systems in an appropriate basis. In particular, we use sparse regression to determine the fewest terms in the dynamic governing equations required to accurately represent the data. This results in parsimonious models that balance accuracy with model complexity to avoid overfitting. We demonstrate the algorithm on a wide range of problems, from simple canonical systems, including linear and nonlinear oscillators and the chaotic Lorenz system, to the fluid vortex shedding behind an obstacle. The fluid example illustrates the ability of this method to discover the underlying dynamics of a system that took experts in the community nearly 30 years to resolve. We also show that this method generalizes to parameterized systems and systems that are time-varying or have external forcing.

Proteomic comparison defines novel markers to characterize heterogeneous populations of extracellular vesicle subtypes.

Abstract: Extracellular vesicles (EVs) have become the focus of rising interest because of their numerous functions in physiology and pathology. Cells release heterogeneous vesicles of different sizes and intracellular origins, including small EVs formed inside endosomal compartments (i.e., exosomes) and EVs of various sizes budding from the plasma membrane. Specific markers for the analysis and isolation of different EV populations are missing, imposing important limitations to understanding EV functions. Here, EVs from human dendritic cells were first separated by their sedimentation speed, and then either by their behavior upon upward floatation into iodixanol gradients or by immuno-isolation. Extensive quantitative proteomic analysis allowing comparison of the isolated populations showed that several classically used exosome markers, like major histocompatibility complex, flotillin, and heat-shock 70-kDa proteins, are similarly present in all EVs. We identified proteins specifically enriched in small EVs, and define a set of five protein categories displaying different relative abundance in distinct EV populations. We demonstrate the presence of exosomal and nonexosomal subpopulations within small EVs, and propose their differential separation by immuno-isolation using either CD63, CD81, or CD9. Our work thus provides guidelines to define subtypes of EVs for future functional studies.

Impact of anthropogenic climate change on wildfire across western US forests

Abstract: Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000–2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ∼55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984–2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting.

The spreading of misinformation online

Abstract: The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. However, the World Wide Web (WWW) also allows for the rapid dissemination of unsubstantiated rumors and conspiracy theories that often elicit rapid, large, but naive social responses such as the recent case of Jade Helm 15––where a simple military exercise turned out to be perceived as the beginning of a new civil war in the United States. In this work, we address the determinants governing misinformation spreading through a thorough quantitative analysis. In particular, we focus on how Facebook users consume information related to two distinct narratives: scientific and conspiracy news. We find that, although consumers of scientific and conspiracy stories present similar consumption patterns with respect to content, cascade dynamics differ. Selective exposure to content is the primary driver of content diffusion and generates the formation of homogeneous clusters, i.e., “echo chambers.” Indeed, homogeneity appears to be the primary driver for the diffusion of contents and each echo chamber has its own cascade dynamics. Finally, we introduce a data-driven percolation model mimicking rumor spreading and we show that homogeneity and polarization are the main determinants for predicting cascades’ size.

Situating the default-mode network along a principal gradient of macroscale cortical organization

Abstract: Understanding how the structure of cognition arises from the topographical organization of the cortex is a primary goal in neuroscience. Previous work has described local functional gradients extending from perceptual and motor regions to cortical areas representing more abstract functions, but an overarching framework for the association between structure and function is still lacking. Here, we show that the principal gradient revealed by the decomposition of connectivity data in humans and the macaque monkey is anchored by, at one end, regions serving primary sensory/motor functions and at the other end, transmodal regions that, in humans, are known as the default-mode network (DMN). These DMN regions exhibit the greatest geodesic distance along the cortical surface-and are precisely equidistant-from primary sensory/motor morphological landmarks. The principal gradient also provides an organizing spatial framework for multiple large-scale networks and characterizes a spectrum from unimodal to heteromodal activity in a functional metaanalysis. Together, these observations provide a characterization of the topographical organization of cortex and indicate that the role of the DMN in cognition might arise from its position at one extreme of a hierarchy, allowing it to process transmodal information that is unrelated to immediate sensory input.

New tools for studying microglia in the mouse and human CNS.

Abstract: The specific function of microglia, the tissue resident macrophages of the brain and spinal cord, has been difficult to ascertain because of a lack of tools to distinguish microglia from other immune cells, thereby limiting specific immunostaining, purification, and manipulation. Because of their unique developmental origins and predicted functions, the distinction of microglia from other myeloid cells is critically important for understanding brain development and disease; better tools would greatly facilitate studies of microglia function in the developing, adult, and injured CNS. Here, we identify transmembrane protein 119 (Tmem119), a cell-surface protein of unknown function, as a highly expressed microglia-specific marker in both mouse and human. We developed monoclonal antibodies to its intracellular and extracellular domains that enable the immunostaining of microglia in histological sections in healthy and diseased brains, as well as isolation of pure nonactivated microglia by FACS. Using our antibodies, we provide, to our knowledge, the first RNAseq profiles of highly pure mouse microglia during development and after an immune challenge. We used these to demonstrate that mouse microglia mature by the second postnatal week and to predict novel microglial functions. Together, we anticipate these resources will be valuable for the future study and understanding of microglia in health and disease.

Racial bias in pain assessment and treatment recommendations, and false beliefs about biological differences between blacks and whites

Abstract: Black Americans are systematically undertreated for pain relative to white Americans. We examine whether this racial bias is related to false beliefs about biological differences between blacks and whites (e.g., “black people’s skin is thicker than white people’s skin”). Study 1 documented these beliefs among white laypersons and revealed that participants who more strongly endorsed false beliefs about biological differences reported lower pain ratings for a black (vs. white) target. Study 2 extended these findings to the medical context and found that half of a sample of white medical students and residents endorsed these beliefs. Moreover, participants who endorsed these beliefs rated the black (vs. white) patient’s pain as lower and made less accurate treatment recommendations. Participants who did not endorse these beliefs rated the black (vs. white) patient’s pain as higher, but showed no bias in treatment recommendations. These findings suggest that individuals with at least some medical training hold and may use false beliefs about biological differences between blacks and whites to inform medical judgments, which may contribute to racial disparities in pain assessment and treatment.

Oyster reproduction is affected by exposure to polystyrene microplastics

Abstract: Plastics are persistent synthetic polymers that accumulate as waste in the marine environment. Microplastic (MP) particles are derived from the breakdown of larger debris or can enter the environment as microscopic fragments. Because filter-feeder organisms ingest MP while feeding, they are likely to be impacted by MP pollution. To assess the impact of polystyrene microspheres (micro-PS) on the physiology of the Pacific oyster, adult oysters were experimentally exposed to virgin micro-PS (2 and 6 µm in diameter; 0.023 mg·L−1) for 2 mo during a reproductive cycle. Effects were investigated on ecophysiological parameters; cellular, transcriptomic, and proteomic responses; fecundity; and offspring development. Oysters preferentially ingested the 6-µm micro-PS over the 2-µm-diameter particles. Consumption of microalgae and absorption efficiency were significantly higher in exposed oysters, suggesting compensatory and physical effects on both digestive parameters. After 2 mo, exposed oysters had significant decreases in oocyte number (−38%), diameter (−5%), and sperm velocity (−23%). The D-larval yield and larval development of offspring derived from exposed parents decreased by 41% and 18%, respectively, compared with control offspring. Dynamic energy budget modeling, supported by transcriptomic profiles, suggested a significant shift of energy allocation from reproduction to structural growth, and elevated maintenance costs in exposed oysters, which is thought to be caused by interference with energy uptake. Molecular signatures of endocrine disruption were also revealed, but no endocrine disruptors were found in the biological samples. This study provides evidence that micro-PS cause feeding modifications and reproductive disruption in oysters, with significant impacts on offspring.

Three-dimensional bioprinting of thick vascularized tissues.

Abstract: The advancement of tissue and, ultimately, organ engineering requires the ability to pattern human tissues composed of cells, extracellular matrix, and vasculature with controlled microenvironments that can be sustained over prolonged time periods. To date, bioprinting methods have yielded thin tissues that only survive for short durations. To improve their physiological relevance, we report a method for bioprinting 3D cell-laden, vascularized tissues that exceed 1 cm in thickness and can be perfused on chip for long time periods (>6 wk). Specifically, we integrate parenchyma, stroma, and endothelium into a single thick tissue by coprinting multiple inks composed of human mesenchymal stem cells (hMSCs) and human neonatal dermal fibroblasts (hNDFs) within a customized extracellular matrix alongside embedded vasculature, which is subsequently lined with human umbilical vein endothelial cells (HUVECs). These thick vascularized tissues are actively perfused with growth factors to differentiate hMSCs toward an osteogenic lineage in situ. This longitudinal study of emergent biological phenomena in complex microenvironments represents a foundational step in human tissue generation.

Peroxidation of polyunsaturated fatty acids by lipoxygenases drives ferroptosis.

Abstract: Ferroptosis is form of regulated nonapoptotic cell death that is involved in diverse disease contexts. Small molecules that inhibit glutathione peroxidase 4 (GPX4), a phospholipid peroxidase, cause lethal accumulation of lipid peroxides and induce ferroptotic cell death. Although ferroptosis has been suggested to involve accumulation of reactive oxygen species (ROS) in lipid environments, the mediators and substrates of ROS generation and the pharmacological mechanism of GPX4 inhibition that generates ROS in lipid environments are unknown. We report here the mechanism of lipid peroxidation during ferroptosis, which involves phosphorylase kinase G2 (PHKG2) regulation of iron availability to lipoxygenase enzymes, which in turn drive ferroptosis through peroxidation of polyunsaturated fatty acids (PUFAs) at the bis-allylic position; indeed, pretreating cells with PUFAs containing the heavy hydrogen isotope deuterium at the site of peroxidation (D-PUFA) prevented PUFA oxidation and blocked ferroptosis. We further found that ferroptosis inducers inhibit GPX4 by covalently targeting the active site selenocysteine, leading to accumulation of PUFA hydroperoxides. In summary, we found that PUFA oxidation by lipoxygenases via a PHKG2-dependent iron pool is necessary for ferroptosis and that the covalent inhibition of the catalytic selenocysteine in Gpx4 prevents elimination of PUFA hydroperoxides; these findings suggest new strategies for controlling ferroptosis in diverse contexts.

Persistent sulfate formation from London Fog to Chinese haze

Abstract: Sulfate aerosols exert profound impacts on human and ecosystem health, weather, and climate, but their formation mechanism remains uncertain. Atmospheric models consistently underpredict sulfate levels under diverse environmental conditions. From atmospheric measurements in two Chinese megacities and complementary laboratory experiments, we show that the aqueous oxidation of SO2 by NO2 is key to efficient sulfate formation but is only feasible under two atmospheric conditions: on fine aerosols with high relative humidity and NH3 neutralization or under cloud conditions. Under polluted environments, this SO2 oxidation process leads to large sulfate production rates and promotes formation of nitrate and organic matter on aqueous particles, exacerbating severe haze development. Effective haze mitigation is achievable by intervening in the sulfate formation process with enforced NH3 and NO2 control measures. In addition to explaining the polluted episodes currently occurring in China and during the 1952 London Fog, this sulfate production mechanism is widespread, and our results suggest a way to tackle this growing problem in China and much of the developing world.

Opinion: Why protect nature? Rethinking values and the environment

Abstract: A cornerstone of environmental policy is the debate over protecting nature for humans’ sake (instrumental values) or for nature’s (intrinsic values) (1). We propose that focusing only on instrumental or intrinsic values may fail to resonate with views on personal and collective well-being, or “what is right,” with regard to nature and the environment. Without complementary attention to other ways that value is expressed and realized by people, such a focus may inadvertently promote worldviews at odds with fair and desirable futures. It is time to engage seriously with a third class of values, one with diverse roots and current expressions: relational values. By doing so, we reframe the discussion about environmental protection, and open the door to new, potentially more productive policy approaches.

Recursive partitioning for heterogeneous causal effects

Abstract: In this paper we propose methods for estimating heterogeneity in causal effects in experimental and observational studies and for conducting hypothesis tests about the magnitude of differences in treatment effects across subsets of the population. We provide a data-driven approach to partition the data into subpopulations that differ in the magnitude of their treatment effects. The approach enables the construction of valid confidence intervals for treatment effects, even with many covariates relative to the sample size, and without “sparsity” assumptions. We propose an “honest” approach to estimation, whereby one sample is used to construct the partition and another to estimate treatment effects for each subpopulation. Our approach builds on regression tree methods, modified to optimize for goodness of fit in treatment effects and to account for honest estimation. Our model selection criterion anticipates that bias will be eliminated by honest estimation and also accounts for the effect of making additional splits on the variance of treatment effect estimates within each subpopulation. We address the challenge that the “ground truth” for a causal effect is not observed for any individual unit, so that standard approaches to cross-validation must be modified. Through a simulation study, we show that for our preferred method honest estimation results in nominal coverage for 90% confidence intervals, whereas coverage ranges between 74% and 84% for nonhonest approaches. Honest estimation requires estimating the model with a smaller sample size; the cost in terms of mean squared error of treatment effects for our preferred method ranges between 7–22%.

Graphene oxide-based efficient and scalable solar desalination under one sun with a confined 2D water path

Abstract: Because it is able to produce desalinated water directly using solar energy with minimum carbon footprint, solar steam generation and desalination is considered one of the most important technologies to address the increasingly pressing global water scarcity. Despite tremendous progress in the past few years, efficient solar steam generation and desalination can only be achieved for rather limited water quantity with the assistance of concentrators and thermal insulation, not feasible for large-scale applications. The fundamental paradox is that the conventional design of direct absorber−bulk water contact ensures efficient energy transfer and water supply but also has intrinsic thermal loss through bulk water. Here, enabled by a confined 2D water path, we report an efficient (80% under one-sun illumination) and effective (four orders salinity decrement) solar desalination device. More strikingly, because of minimized heat loss, high efficiency of solar desalination is independent of the water quantity and can be maintained without thermal insulation of the container. A foldable graphene oxide film, fabricated by a scalable process, serves as efficient solar absorbers (>94%), vapor channels, and thermal insulators. With unique structure designs fabricated by scalable processes and high and stable efficiency achieved under normal solar illumination independent of water quantity without any supporting systems, our device represents a concrete step for solar desalination to emerge as a complementary portable and personalized clean water solution.

Hypoxia induces the breast cancer stem cell phenotype by HIF-dependent and ALKBH5-mediated m6A-demethylation of NANOG mRNA

Abstract: N(6)-methyladenosine (m(6)A) modification of mRNA plays a role in regulating embryonic stem cell pluripotency. However, the physiological signals that determine the balance between methylation and demethylation have not been described, nor have studies addressed the role of m(6)A in cancer stem cells. We report that exposure of breast cancer cells to hypoxia stimulated hypoxia-inducible factor (HIF)-1α- and HIF-2α-dependent expression of AlkB homolog 5 (ALKBH5), an m(6)A demethylase, which demethylated NANOG mRNA, which encodes a pluripotency factor, at an m(6)A residue in the 3'-UTR. Increased NANOG mRNA and protein expression, and the breast cancer stem cell (BCSC) phenotype, were induced by hypoxia in an HIF- and ALKBH5-dependent manner. Insertion of the NANOG 3'-UTR into a luciferase reporter gene led to regulation of luciferase activity by O2, HIFs, and ALKBH5, which was lost upon mutation of the methylated residue. ALKBH5 overexpression decreased NANOG mRNA methylation, increased NANOG levels, and increased the percentage of BCSCs, phenocopying the effect of hypoxia. Knockdown of ALKBH5 expression in MDA-MB-231 human breast cancer cells significantly reduced their capacity for tumor initiation as a result of reduced numbers of BCSCs. Thus, HIF-dependent ALKBH5 expression mediates enrichment of BCSCs in the hypoxic tumor microenvironment.

Scaling laws predict global microbial diversity

Abstract: Scaling laws underpin unifying theories of biodiversity and are among the most predictively powerful relationships in biology. However, scaling laws developed for plants and animals often go untested or fail to hold for microorganisms. As a result, it is unclear whether scaling laws of biodiversity will span evolutionarily distant domains of life that encompass all modes of metabolism and scales of abundance. Using a global-scale compilation of ∼35,000 sites and ∼5.6⋅106 species, including the largest ever inventory of high-throughput molecular data and one of the largest compilations of plant and animal community data, we show similar rates of scaling in commonness and rarity across microorganisms and macroscopic plants and animals. We document a universal dominance scaling law that holds across 30 orders of magnitude, an unprecedented expanse that predicts the abundance of dominant ocean bacteria. In combining this scaling law with the lognormal model of biodiversity, we predict that Earth is home to upward of 1 trillion (1012) microbial species. Microbial biodiversity seems greater than ever anticipated yet predictable from the smallest to the largest microbiome.

Analysis and valuation of the health and climate change cobenefits of dietary change

Abstract: What we eat greatly influences our personal health and the environment we all share. Recent analyses have highlighted the likely dual health and environmental benefits of reducing the fraction of animal-sourced foods in our diets. Here, we couple for the first time, to our knowledge, a region-specific global health model based on dietary and weight-related risk factors with emissions accounting and economic valuation modules to quantify the linked health and environmental consequences of dietary changes. We find that the impacts of dietary changes toward less meat and more plant-based diets vary greatly among regions. The largest absolute environmental and health benefits result from diet shifts in developing countries whereas Western high-income and middle-income countries gain most in per capita terms. Transitioning toward more plant-based diets that are in line with standard dietary guidelines could reduce global mortality by 6–10% and food-related greenhouse gas emissions by 29–70% compared with a reference scenario in 2050. We find that the monetized value of the improvements in health would be comparable with, or exceed, the value of the environmental benefits although the exact valuation method used considerably affects the estimated amounts. Overall, we estimate the economic benefits of improving diets to be 1–31 trillion US dollars, which is equivalent to 0.4–13% of global gross domestic product (GDP) in 2050. However, significant changes in the global food system would be necessary for regional diets to match the dietary patterns studied here.

Convolutional networks for fast, energy-efficient neuromorphic computing

Abstract: Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware’s underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer.

Composite lithium metal anode by melt infusion of lithium into a 3D conducting scaffold with lithiophilic coating.

Abstract: Lithium metal-based battery is considered one of the best energy storage systems due to its high theoretical capacity and lowest anode potential of all. However, dendritic growth and virtually relative infinity volume change during long-term cycling often lead to severe safety hazards and catastrophic failure. Here, a stable lithium–scaffold composite electrode is developed by lithium melt infusion into a 3D porous carbon matrix with “lithiophilic” coating. Lithium is uniformly entrapped on the matrix surface and in the 3D structure. The resulting composite electrode possesses a high conductive surface area and excellent structural stability upon galvanostatic cycling. We showed stable cycling of this composite electrode with small Li plating/stripping overpotential (

Rates and drivers of mangrove deforestation in Southeast Asia, 2000–2012

Abstract: The mangrove forests of Southeast Asia are highly biodiverse and provide multiple ecosystem services upon which millions of people depend. Mangroves enhance fisheries and coastal protection, and store among the highest densities of carbon of any ecosystem globally. Mangrove forests have experienced extensive deforestation owing to global demand for commodities, and previous studies have identified the expansion of aquaculture as largely responsible. The proportional conversion of mangroves to different land use types has not been systematically quantified across Southeast Asia, however, particularly in recent years. In this study we apply a combined geographic information system and remote sensing method to quantify the key proximate drivers (i.e., replacement land uses) of mangrove deforestation in Southeast Asia between 2000 and 2012. Mangrove forests were lost at an average rate of 0.18% per year, which is lower than previously published estimates. In total, more than 100,000 ha of mangroves were removed during the study period, with aquaculture accounting for 30% of this total forest change. The rapid expansion of rice agriculture in Myanmar, and the sustained conversion of mangroves to oil palm plantations in Malaysia and Indonesia, are identified as additional increasing and under-recognized threats to mangrove ecosystems. Our study highlights frontiers of mangrove deforestation in the border states of Myanmar, on Borneo, and in Indonesian Papua. To implement policies that conserve mangrove forests across Southeast Asia, it is essential to consider the national and subnational variation in the land uses that follow deforestation.

Magnetite pollution nanoparticles in the human brain.

Abstract: Biologically formed nanoparticles of the strongly magnetic mineral, magnetite, were first detected in the human brain over 20 y ago [Kirschvink JL, Kobayashi-Kirschvink A, Woodford BJ (1992) Proc Natl Acad Sci USA 89(16):7683-7687]. Magnetite can have potentially large impacts on the brain due to its unique combination of redox activity, surface charge, and strongly magnetic behavior. We used magnetic analyses and electron microscopy to identify the abundant presence in the brain of magnetite nanoparticles that are consistent with high-temperature formation, suggesting, therefore, an external, not internal, source. Comprising a separate nanoparticle population from the euhedral particles ascribed to endogenous sources, these brain magnetites are often found with other transition metal nanoparticles, and they display rounded crystal morphologies and fused surface textures, reflecting crystallization upon cooling from an initially heated, iron-bearing source material. Such high-temperature magnetite nanospheres are ubiquitous and abundant in airborne particulate matter pollution. They arise as combustion-derived, iron-rich particles, often associated with other transition metal particles, which condense and/or oxidize upon airborne release. Those magnetite pollutant particles which are <∼200 nm in diameter can enter the brain directly via the olfactory bulb. Their presence proves that externally sourced iron-bearing nanoparticles, rather than their soluble compounds, can be transported directly into the brain, where they may pose hazard to human health.

Invasive predators and global biodiversity loss

Abstract: Invasive species threaten biodiversity globally, and invasive mammalian predators are particularly damaging, having contributed to considerable species decline and extinction. We provide a global metaanalysis of these impacts and reveal their full extent. Invasive predators are implicated in 87 bird, 45 mammal, and 10 reptile species extinctions—58% of these groups’ contemporary extinctions worldwide. These figures are likely underestimated because 23 critically endangered species that we assessed are classed as “possibly extinct.” Invasive mammalian predators endanger a further 596 species at risk of extinction, with cats, rodents, dogs, and pigs threatening the most species overall. Species most at risk from predators have high evolutionary distinctiveness and inhabit insular environments. Invasive mammalian predators are therefore important drivers of irreversible loss of phylogenetic diversity worldwide. That most impacted species are insular indicates that management of invasive predators on islands should be a global conservation priority. Understanding and mitigating the impact of invasive mammalian predators is essential for reducing the rate of global biodiversity loss.

Atomic-resolution structure of a disease-relevant Aβ(1–42) amyloid fibril

Abstract: Amyloid-β (Aβ) is present in humans as a 39- to 42-amino acid residue metabolic product of the amyloid precursor protein. Although the two predominant forms, Aβ(1–40) and Aβ(1–42), differ in only two residues, they display different biophysical, biological, and clinical behavior. Aβ(1–42) is the more neurotoxic species, aggregates much faster, and dominates in senile plaque of Alzheimer’s disease (AD) patients. Although small Aβ oligomers are believed to be the neurotoxic species, Aβ amyloid fibrils are, because of their presence in plaques, a pathological hallmark of AD and appear to play an important role in disease progression through cell-to-cell transmissibility. Here, we solved the 3D structure of a disease-relevant Aβ(1–42) fibril polymorph, combining data from solid-state NMR spectroscopy and mass-per-length measurements from EM. The 3D structure is composed of two molecules per fibril layer, with residues 15–42 forming a double-horseshoe–like cross–β-sheet entity with maximally buried hydrophobic side chains. Residues 1–14 are partially ordered and in a β-strand conformation, but do not display unambiguous distance restraints to the remainder of the core structure.

Driver crash risk factors and prevalence evaluation using naturalistic driving data.

Abstract: The accurate evaluation of crash causal factors can provide fundamental information for effective transportation policy, vehicle design, and driver education. Naturalistic driving (ND) data collected with multiple onboard video cameras and sensors provide a unique opportunity to evaluate risk factors during the seconds leading up to a crash. This paper uses a National Academy of Sciences-sponsored ND dataset comprising 905 injurious and property damage crash events, the magnitude of which allows the first direct analysis (to our knowledge) of causal factors using crashes only. The results show that crash causation has shifted dramatically in recent years, with driver-related factors (i.e., error, impairment, fatigue, and distraction) present in almost 90% of crashes. The results also definitively show that distraction is detrimental to driver safety, with handheld electronic devices having high use rates and risk.

Flexible, solid-state, ion-conducting membrane with 3D garnet nanofiber networks for lithium batteries

Abstract: Beyond state-of-the-art lithium-ion battery (LIB) technology with metallic lithium anodes to replace conventional ion intercalation anode materials is highly desirable because of lithium's highest specific capacity (3,860 mA/g) and lowest negative electrochemical potential (∼3.040 V vs. the standard hydrogen electrode). In this work, we report for the first time, to our knowledge, a 3D lithium-ion-conducting ceramic network based on garnet-type Li6.4La3Zr2Al0.2O12 (LLZO) lithium-ion conductor to provide continuous Li(+) transfer channels in a polyethylene oxide (PEO)-based composite. This composite structure further provides structural reinforcement to enhance the mechanical properties of the polymer matrix. The flexible solid-state electrolyte composite membrane exhibited an ionic conductivity of 2.5 × 10(-4) S/cm at room temperature. The membrane can effectively block dendrites in a symmetric Li | electrolyte | Li cell during repeated lithium stripping/plating at room temperature, with a current density of 0.2 mA/cm(2) for around 500 h and a current density of 0.5 mA/cm(2) for over 300 h. These results provide an all solid ion-conducting membrane that can be applied to flexible LIBs and other electrochemical energy storage systems, such as lithium-sulfur batteries.

Vagus nerve stimulation inhibits cytokine production and attenuates disease severity in rheumatoid arthritis

Abstract: Rheumatoid arthritis (RA) is a heterogeneous, prevalent, chronic autoimmune disease characterized by painful swollen joints and significant disabilities. Symptomatic relief can be achieved in up to 50% of patients using biological agents that inhibit tumor necrosis factor (TNF) or other mechanisms of action, but there are no universally effective therapies. Recent advances in basic and preclinical science reveal that reflex neural circuits inhibit the production of cytokines and inflammation in animal models. One well-characterized cytokine-inhibiting mechanism, termed the "inflammatory reflex," is dependent upon vagus nerve signals that inhibit cytokine production and attenuate experimental arthritis severity in mice and rats. It previously was unknown whether directly stimulating the inflammatory reflex in humans inhibits TNF production. Here we show that an implantable vagus nerve-stimulating device in epilepsy patients inhibits peripheral blood production of TNF, IL-1β, and IL-6. Vagus nerve stimulation (up to four times daily) in RA patients significantly inhibited TNF production for up to 84 d. Moreover, RA disease severity, as measured by standardized clinical composite scores, improved significantly. Together, these results establish that vagus nerve stimulation targeting the inflammatory reflex modulates TNF production and reduces inflammation in humans. These findings suggest that it is possible to use mechanism-based neuromodulating devices in the experimental therapy of RA and possibly other autoimmune and autoinflammatory diseases.

Costimulatory b7-h1 in renal cell carcinoma patients: indicator of tumor aggressiveness and potential therapeutic target

Abstract: The invention features methods of diagnosis by assessing B7-H1 expression in a tissue from a subject that has, or is suspected of having, cancer, methods of treatment with agents that interfere with B7-H1-receptor interaction, methods of selecting candidate subjects likely to benefit from cancer immunotherapy, and methods of inhibiting expression of B7-H1.

Contributions of microbiome and mechanical deformation to intestinal bacterial overgrowth and inflammation in a human gut-on-a-chip

Abstract: A human gut-on-a-chip microdevice was used to coculture multiple commensal microbes in contact with living human intestinal epithelial cells for more than a week in vitro and to analyze how gut microbiome, inflammatory cells, and peristalsis-associated mechanical deformations independently contribute to intestinal bacterial overgrowth and inflammation. This in vitro model replicated results from past animal and human studies, including demonstration that probiotic and antibiotic therapies can suppress villus injury induced by pathogenic bacteria. By ceasing peristalsis-like motions while maintaining luminal flow, lack of epithelial deformation was shown to trigger bacterial overgrowth similar to that observed in patients with ileus and inflammatory bowel disease. Analysis of intestinal inflammation on-chip revealed that immune cells and lipopolysaccharide endotoxin together stimulate epithelial cells to produce four proinflammatory cytokines (IL-8, IL-6, IL-1β, and TNF-α) that are necessary and sufficient to induce villus injury and compromise intestinal barrier function. Thus, this human gut-on-a-chip can be used to analyze contributions of microbiome to intestinal pathophysiology and dissect disease mechanisms in a controlled manner that is not possible using existing in vitro systems or animal models.

Lasing in robust cesium lead halide perovskite nanowires

Abstract: The rapidly growing field of nanoscale lasers can be advanced through the discovery of new, tunable light sources. The emission wavelength tunability demonstrated in perovskite materials is an attractive property for nanoscale lasers. Whereas organic-inorganic lead halide perovskite materials are known for their instability, cesium lead halides offer a robust alternative without sacrificing emission tunability or ease of synthesis. Here, we report the low-temperature, solution-phase growth of cesium lead halide nanowires exhibiting low-threshold lasing and high stability. The as-grown nanowires are single crystalline with well-formed facets, and act as high-quality laser cavities. The nanowires display excellent stability while stored and handled under ambient conditions over the course of weeks. Upon optical excitation, Fabry-Perot lasing occurs in CsPbBr3 nanowires with an onset of 5 μJ cm(-2) with the nanowire cavity displaying a maximum quality factor of 1,009 ± 5. Lasing under constant, pulsed excitation can be maintained for over 1 h, the equivalent of 10(9) excitation cycles, and lasing persists upon exposure to ambient atmosphere. Wavelength tunability in the green and blue regions of the spectrum in conjunction with excellent stability makes these nanowire lasers attractive for device fabrication.