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Showing papers in "Nature in 2018"


Journal ArticleDOI
05 Mar 2018-Nature
TL;DR: The realization of intrinsic unconventional superconductivity is reported—which cannot be explained by weak electron–phonon interactions—in a two-dimensional superlattice created by stacking two sheets of graphene that are twisted relative to each other by a small angle.
Abstract: The behaviour of strongly correlated materials, and in particular unconventional superconductors, has been studied extensively for decades, but is still not well understood. This lack of theoretical understanding has motivated the development of experimental techniques for studying such behaviour, such as using ultracold atom lattices to simulate quantum materials. Here we report the realization of intrinsic unconventional superconductivity-which cannot be explained by weak electron-phonon interactions-in a two-dimensional superlattice created by stacking two sheets of graphene that are twisted relative to each other by a small angle. For twist angles of about 1.1°-the first 'magic' angle-the electronic band structure of this 'twisted bilayer graphene' exhibits flat bands near zero Fermi energy, resulting in correlated insulating states at half-filling. Upon electrostatic doping of the material away from these correlated insulating states, we observe tunable zero-resistance states with a critical temperature of up to 1.7 kelvin. The temperature-carrier-density phase diagram of twisted bilayer graphene is similar to that of copper oxides (or cuprates), and includes dome-shaped regions that correspond to superconductivity. Moreover, quantum oscillations in the longitudinal resistance of the material indicate the presence of small Fermi surfaces near the correlated insulating states, in analogy with underdoped cuprates. The relatively high superconducting critical temperature of twisted bilayer graphene, given such a small Fermi surface (which corresponds to a carrier density of about 1011 per square centimetre), puts it among the superconductors with the strongest pairing strength between electrons. Twisted bilayer graphene is a precisely tunable, purely carbon-based, two-dimensional superconductor. It is therefore an ideal material for investigations of strongly correlated phenomena, which could lead to insights into the physics of high-critical-temperature superconductors and quantum spin liquids.

5,613 citations


Journal ArticleDOI
11 Oct 2018-Nature
TL;DR: Deep phenotype and genome-wide genetic data from 500,000 individuals from the UK Biobank is described, describing population structure and relatedness in the cohort, and imputation to increase the number of testable variants to 96 million.
Abstract: The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.

4,489 citations


Journal ArticleDOI
05 Mar 2018-Nature
TL;DR: It is shown experimentally that when this angle is close to the ‘magic’ angle the electronic band structure near zero Fermi energy becomes flat, owing to strong interlayer coupling, and these flat bands exhibit insulating states at half-filling, which are not expected in the absence of correlations between electrons.
Abstract: A van der Waals heterostructure is a type of metamaterial that consists of vertically stacked two-dimensional building blocks held together by the van der Waals forces between the layers. This design means that the properties of van der Waals heterostructures can be engineered precisely, even more so than those of two-dimensional materials. One such property is the 'twist' angle between different layers in the heterostructure. This angle has a crucial role in the electronic properties of van der Waals heterostructures, but does not have a direct analogue in other types of heterostructure, such as semiconductors grown using molecular beam epitaxy. For small twist angles, the moire pattern that is produced by the lattice misorientation between the two-dimensional layers creates long-range modulation of the stacking order. So far, studies of the effects of the twist angle in van der Waals heterostructures have concentrated mostly on heterostructures consisting of monolayer graphene on top of hexagonal boron nitride, which exhibit relatively weak interlayer interaction owing to the large bandgap in hexagonal boron nitride. Here we study a heterostructure consisting of bilayer graphene, in which the two graphene layers are twisted relative to each other by a certain angle. We show experimentally that, as predicted theoretically, when this angle is close to the 'magic' angle the electronic band structure near zero Fermi energy becomes flat, owing to strong interlayer coupling. These flat bands exhibit insulating states at half-filling, which are not expected in the absence of correlations between electrons. We show that these correlated states at half-filling are consistent with Mott-like insulator states, which can arise from electrons being localized in the superlattice that is induced by the moire pattern. These properties of magic-angle-twisted bilayer graphene heterostructures suggest that these materials could be used to study other exotic many-body quantum phases in two dimensions in the absence of a magnetic field. The accessibility of the flat bands through electrical tunability and the bandwidth tunability through the twist angle could pave the way towards more exotic correlated systems, such as unconventional superconductors and quantum spin liquids.

3,005 citations


Journal ArticleDOI
22 Feb 2018-Nature
TL;DR: Tumours from a large cohort of patients with metastatic urothelial cancer who were treated with an anti-PD-L1 agent were examined and major determinants of clinical outcome were identified and suggested that TGFβ shapes the tumour microenvironment to restrain anti-tumour immunity by restricting T-cell infiltration.
Abstract: Therapeutic antibodies that block the programmed death-1 (PD-1)-programmed death-ligand 1 (PD-L1) pathway can induce robust and durable responses in patients with various cancers, including metastatic urothelial cancer. However, these responses only occur in a subset of patients. Elucidating the determinants of response and resistance is key to improving outcomes and developing new treatment strategies. Here we examined tumours from a large cohort of patients with metastatic urothelial cancer who were treated with an anti-PD-L1 agent (atezolizumab) and identified major determinants of clinical outcome. Response to treatment was associated with CD8+ T-effector cell phenotype and, to an even greater extent, high neoantigen or tumour mutation burden. Lack of response was associated with a signature of transforming growth factor β (TGFβ) signalling in fibroblasts. This occurred particularly in patients with tumours, which showed exclusion of CD8+ T cells from the tumour parenchyma that were instead found in the fibroblast- and collagen-rich peritumoural stroma; a common phenotype among patients with metastatic urothelial cancer. Using a mouse model that recapitulates this immune-excluded phenotype, we found that therapeutic co-administration of TGFβ-blocking and anti-PD-L1 antibodies reduced TGFβ signalling in stromal cells, facilitated T-cell penetration into the centre of tumours, and provoked vigorous anti-tumour immunity and tumour regression. Integration of these three independent biological features provides the best basis for understanding patient outcome in this setting and suggests that TGFβ shapes the tumour microenvironment to restrain anti-tumour immunity by restricting T-cell infiltration.

2,808 citations


Journal ArticleDOI
24 Jan 2018-Nature
TL;DR: Continued research into new drugs and combination therapies is required to expand the clinical benefit to a broader patient population and to improve outcomes in NSCLC.
Abstract: Important advancements in the treatment of non-small cell lung cancer (NSCLC) have been achieved over the past two decades, increasing our understanding of the disease biology and mechanisms of tumour progression, and advancing early detection and multimodal care. The use of small molecule tyrosine kinase inhibitors and immunotherapy has led to unprecedented survival benefits in selected patients. However, the overall cure and survival rates for NSCLC remain low, particularly in metastatic disease. Therefore, continued research into new drugs and combination therapies is required to expand the clinical benefit to a broader patient population and to improve outcomes in NSCLC.

2,410 citations


Journal ArticleDOI
01 Oct 2018-Nature
TL;DR: In this article, the authors describe visible-light-emitting perovskite LEDs that surpass the quantum efficiency milestone of 20.3 per cent, which is achieved by a new strategy for managing the compositional distribution in the device.
Abstract: Metal halide perovskite materials are an emerging class of solution-processable semiconductors with considerable potential for use in optoelectronic devices1–3. For example, light-emitting diodes (LEDs) based on these materials could see application in flat-panel displays and solid-state lighting, owing to their potential to be made at low cost via facile solution processing, and could provide tunable colours and narrow emission line widths at high photoluminescence quantum yields4–8. However, the highest reported external quantum efficiencies of green- and red-light-emitting perovskite LEDs are around 14 per cent7,9 and 12 per cent8, respectively—still well behind the performance of organic LEDs10–12 and inorganic quantum dot LEDs13. Here we describe visible-light-emitting perovskite LEDs that surpass the quantum efficiency milestone of 20 per cent. This achievement stems from a new strategy for managing the compositional distribution in the device—an approach that simultaneously provides high luminescence and balanced charge injection. Specifically, we mixed a presynthesized CsPbBr3 perovskite with a MABr additive (where MA is CH3NH3), the differing solubilities of which yield sequential crystallization into a CsPbBr3/MABr quasi-core/shell structure. The MABr shell passivates the nonradiative defects that would otherwise be present in CsPbBr3 crystals, boosting the photoluminescence quantum efficiency, while the MABr capping layer enables balanced charge injection. The resulting 20.3 per cent external quantum efficiency represents a substantial step towards the practical application of perovskite LEDs in lighting and display. A strategy for managing the compositional distribution in metal halide perovskite light-emitting diodes enables them to surpass 20% external quantum efficiency—a step towards their practical application in lighting and displays.

2,346 citations


Journal ArticleDOI
26 Jul 2018-Nature
TL;DR: A future in which the design, synthesis, characterization and application of molecules and materials is accelerated by artificial intelligence is envisaged.
Abstract: Here we summarize recent progress in machine learning for the chemical sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future in which the design, synthesis, characterization and application of molecules and materials is accelerated by artificial intelligence.

2,295 citations


Journal ArticleDOI
08 Aug 2018-Nature
TL;DR: It is shown that RNA velocity—the time derivative of the gene expression state—can be directly estimated by distinguishing between unspliced and spliced mRNAs in common single-cell RNA sequencing protocols, and expected to greatly aid the analysis of developmental lineages and cellular dynamics, particularly in humans.
Abstract: RNA abundance is a powerful indicator of the state of individual cells. Single-cell RNA sequencing can reveal RNA abundance with high quantitative accuracy, sensitivity and throughput1. However, this approach captures only a static snapshot at a point in time, posing a challenge for the analysis of time-resolved phenomena such as embryogenesis or tissue regeneration. Here we show that RNA velocity-the time derivative of the gene expression state-can be directly estimated by distinguishing between unspliced and spliced mRNAs in common single-cell RNA sequencing protocols. RNA velocity is a high-dimensional vector that predicts the future state of individual cells on a timescale of hours. We validate its accuracy in the neural crest lineage, demonstrate its use on multiple published datasets and technical platforms, reveal the branching lineage tree of the developing mouse hippocampus, and examine the kinetics of transcription in human embryonic brain. We expect RNA velocity to greatly aid the analysis of developmental lineages and cellular dynamics, particularly in humans.

2,285 citations


Journal ArticleDOI
18 Oct 2018-Nature
TL;DR: A compendium of single-cell transcriptomic data from the model organism Mus musculus that comprises more than 100,000 cells from 20 organs and tissues is presented, representing a new resource for cell biology and enabling the direct and controlled comparison of gene expression in cell types that are shared between tissues.
Abstract: Here we present a compendium of single-cell transcriptomic data from the model organism Mus musculus that comprises more than 100,000 cells from 20 organs and tissues. These data represent a new resource for cell biology, reveal gene expression in poorly characterized cell populations and enable the direct and controlled comparison of gene expression in cell types that are shared between tissues, such as T lymphocytes and endothelial cells from different anatomical locations. Two distinct technical approaches were used for most organs: one approach, microfluidic droplet-based 3'-end counting, enabled the survey of thousands of cells at relatively low coverage, whereas the other, full-length transcript analysis based on fluorescence-activated cell sorting, enabled the characterization of cell types with high sensitivity and coverage. The cumulative data provide the foundation for an atlas of transcriptomic cell biology.

1,757 citations


Journal ArticleDOI
08 Mar 2018-Nature
TL;DR: Genotype and microbiome data from 1,046 healthy individuals with several distinct ancestral origins who share a relatively common environment are examined, and it is demonstrated that the gut microbiome is not significantly associated with genetic ancestry, and that host genetics have a minor role in determining microbiome composition.
Abstract: Human gut microbiome composition is shaped by multiple factors but the relative contribution of host genetics remains elusive. Here we examine genotype and microbiome data from 1,046 healthy individuals with several distinct ancestral origins who share a relatively common environment, and demonstrate that the gut microbiome is not significantly associated with genetic ancestry, and that host genetics have a minor role in determining microbiome composition. We show that, by contrast, there are significant similarities in the compositions of the microbiomes of genetically unrelated individuals who share a household, and that over 20% of the inter-person microbiome variability is associated with factors related to diet, drugs and anthropometric measurements. We further demonstrate that microbiome data significantly improve the prediction accuracy for many human traits, such as glucose and obesity measures, compared to models that use only host genetic and environmental data. These results suggest that microbiome alterations aimed at improving clinical outcomes may be carried out across diverse genetic backgrounds.

1,683 citations


Journal ArticleDOI
David Capper1, David Capper2, David Capper3, David T.W. Jones1  +168 moreInstitutions (54)
22 Mar 2018-Nature
TL;DR: This work presents a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and shows that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods.
Abstract: Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.

Journal ArticleDOI
08 Aug 2018-Nature
TL;DR: It is reported that metastatic melanomas release extracellular vesicles, mostly in the form of exosomes, that carry PD-L1 on their surface, suggesting a mechanism by which tumours could evade the immunesystem, and the potential application ofExosomal PD- L1 to monitor patient responses to checkpoint therapies.
Abstract: Tumour cells evade immune surveillance by upregulating the surface expression of programmed death-ligand 1 (PD-L1), which interacts with programmed death-1 (PD-1) receptor on T cells to elicit the immune checkpoint response1,2. Anti-PD-1 antibodies have shown remarkable promise in treating tumours, including metastatic melanoma2–4. However, the patient response rate is low4,5. A better understanding of PD-L1-mediated immune evasion is needed to predict patient response and improve treatment efficacy. Here we report that metastatic melanomas release extracellular vesicles, mostly in the form of exosomes, that carry PD-L1 on their surface. Stimulation with interferon-γ (IFN-γ) increases the amount of PD-L1 on these vesicles, which suppresses the function of CD8 T cells and facilitates tumour growth. In patients with metastatic melanoma, the level of circulating exosomal PD-L1 positively correlates with that of IFN-γ, and varies during the course of anti-PD-1 therapy. The magnitudes of the increase in circulating exosomal PD-L1 during early stages of treatment, as an indicator of the adaptive response of the tumour cells to T cell reinvigoration, stratifies clinical responders from non-responders. Our study unveils a mechanism by which tumour cells systemically suppress the immune system, and provides a rationale for the application of exosomal PD-L1 as a predictor for anti-PD-1 therapy. Melanoma cells release programmed death-ligand 1 (PD-L1) on the surface of circulating exosomes, suggesting a mechanism by which tumours could evade the immunesystem, and the potential application of exosomal PD-L1 to monitor patient responses to checkpoint therapies.

Journal ArticleDOI
10 Oct 2018-Nature
TL;DR: A global model finds that the environmental impacts of the food system could increase by 60–90% by 2050, and that dietary changes, improvements in technologies and management, and reductions in food loss and waste will all be needed to mitigate these impacts.
Abstract: The food system is a major driver of climate change, changes in land use, depletion of freshwater resources, and pollution of aquatic and terrestrial ecosystems through excessive nitrogen and phosphorus inputs. Here we show that between 2010 and 2050, as a result of expected changes in population and income levels, the environmental effects of the food system could increase by 50–90% in the absence of technological changes and dedicated mitigation measures, reaching levels that are beyond the planetary boundaries that define a safe operating space for humanity. We analyse several options for reducing the environmental effects of the food system, including dietary changes towards healthier, more plant-based diets, improvements in technologies and management, and reductions in food loss and waste. We find that no single measure is enough to keep these effects within all planetary boundaries simultaneously, and that a synergistic combination of measures will be needed to sufficiently mitigate the projected increase in environmental pressures.

Journal ArticleDOI
22 Oct 2018-Nature
TL;DR: It is found that the itinerant ferromagnetism persists in Fe3GeTe2 down to the monolayer with an out-of-plane magnetocrystalline anisotropy, which opens up opportunities for potential voltage-controlled magnetoelectronics based on atomically thin van der Waals crystals.
Abstract: Materials research has driven the development of modern nano-electronic devices. In particular, research in magnetic thin films has revolutionized the development of spintronic devices1,2 because identifying new magnetic materials is key to better device performance and design. Van der Waals crystals retain their chemical stability and structural integrity down to the monolayer and, being atomically thin, are readily tuned by various kinds of gate modulation3,4. Recent experiments have demonstrated that it is possible to obtain two-dimensional ferromagnetic order in insulating Cr2Ge2Te6 (ref. 5) and CrI3 (ref. 6) at low temperatures. Here we develop a device fabrication technique and isolate monolayers from the layered metallic magnet Fe3GeTe2 to study magnetotransport. We find that the itinerant ferromagnetism persists in Fe3GeTe2 down to the monolayer with an out-of-plane magnetocrystalline anisotropy. The ferromagnetic transition temperature, Tc, is suppressed relative to the bulk Tc of 205 kelvin in pristine Fe3GeTe2 thin flakes. An ionic gate, however, raises Tc to room temperature, much higher than the bulk Tc. The gate-tunable room-temperature ferromagnetism in two-dimensional Fe3GeTe2 opens up opportunities for potential voltage-controlled magnetoelectronics7-11 based on atomically thin van der Waals crystals.

Journal ArticleDOI
01 Oct 2018-Nature
TL;DR: The formation of submicrometre-scale structure in perovskite light-emitting diodes can raise their external quantum efficiency beyond 20%, suggesting the possibility of both high efficiency and high brightness.
Abstract: Light-emitting diodes (LEDs), which convert electricity to light, are widely used in modern society—for example, in lighting, flat-panel displays, medical devices and many other situations. Generally, the efficiency of LEDs is limited by nonradiative recombination (whereby charge carriers recombine without releasing photons) and light trapping1–3. In planar LEDs, such as organic LEDs, around 70 to 80 per cent of the light generated from the emitters is trapped in the device4,5, leaving considerable opportunity for improvements in efficiency. Many methods, including the use of diffraction gratings, low-index grids and buckling patterns, have been used to extract the light trapped in LEDs6–9. However, these methods usually involve complicated fabrication processes and can distort the light-output spectrum and directionality6,7. Here we demonstrate efficient and high-brightness electroluminescence from solution-processed perovskites that spontaneously form submicrometre-scale structures, which can efficiently extract light from the device and retain wavelength- and viewing-angle-independent electroluminescence. These perovskites are formed simply by introducing amino-acid additives into the perovskite precursor solutions. Moreover, the additives can effectively passivate perovskite surface defects and reduce nonradiative recombination. Perovskite LEDs with a peak external quantum efficiency of 20.7 per cent (at a current density of 18 milliamperes per square centimetre) and an energy-conversion efficiency of 12 per cent (at a high current density of 100 milliamperes per square centimetre) can be achieved—values that approach those of the best-performing organic LEDs. The formation of submicrometre-scale structure in perovskite light-emitting diodes can raise their external quantum efficiency beyond 20%, suggesting the possibility of both high efficiency and high brightness.

Journal ArticleDOI
19 Feb 2018-Nature
TL;DR: The process offers a general platform for incorporating other intrinsically stretchable polymer materials, enabling the fabrication of next-generation stretchable skin electronic devices, and demonstrates an intrinsicallyStretchable polymer transistor array with an unprecedented device density of 347 transistors per square centimetre.
Abstract: Skin-like electronics that can adhere seamlessly to human skin or within the body are highly desirable for applications such as health monitoring, medical treatment, medical implants and biological studies, and for technologies that include human-machine interfaces, soft robotics and augmented reality. Rendering such electronics soft and stretchable-like human skin-would make them more comfortable to wear, and, through increased contact area, would greatly enhance the fidelity of signals acquired from the skin. Structural engineering of rigid inorganic and organic devices has enabled circuit-level stretchability, but this requires sophisticated fabrication techniques and usually suffers from reduced densities of devices within an array. We reasoned that the desired parameters, such as higher mechanical deformability and robustness, improved skin compatibility and higher device density, could be provided by using intrinsically stretchable polymer materials instead. However, the production of intrinsically stretchable materials and devices is still largely in its infancy: such materials have been reported, but functional, intrinsically stretchable electronics have yet to be demonstrated owing to the lack of a scalable fabrication technology. Here we describe a fabrication process that enables high yield and uniformity from a variety of intrinsically stretchable electronic polymers. We demonstrate an intrinsically stretchable polymer transistor array with an unprecedented device density of 347 transistors per square centimetre. The transistors have an average charge-carrier mobility comparable to that of amorphous silicon, varying only slightly (within one order of magnitude) when subjected to 100 per cent strain for 1,000 cycles, without current-voltage hysteresis. Our transistor arrays thus constitute intrinsically stretchable skin electronics, and include an active matrix for sensory arrays, as well as analogue and digital circuit elements. Our process offers a general platform for incorporating other intrinsically stretchable polymer materials, enabling the fabrication of next-generation stretchable skin electronic devices.

Journal ArticleDOI
21 Mar 2018-Nature
TL;DR: A unified framework for image reconstruction—automated transform by manifold approximation (AUTOMAP)—which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data is presented.
Abstract: Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction-automated transform by manifold approximation (AUTOMAP)-which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Journal ArticleDOI
24 Sep 2018-Nature
TL;DR: Monolithically integrated lithium niobate electro-optic modulators that feature a CMOS-compatible drive voltage, support data rates up to 210 gigabits per second and show an on-chip optical loss of less than 0.5 decibels are demonstrated.
Abstract: Electro-optic modulators translate high-speed electronic signals into the optical domain and are critical components in modern telecommunication networks1,2 and microwave-photonic systems3,4. They are also expected to be building blocks for emerging applications such as quantum photonics5,6 and non-reciprocal optics7,8. All of these applications require chip-scale electro-optic modulators that operate at voltages compatible with complementary metal–oxide–semiconductor (CMOS) technology, have ultra-high electro-optic bandwidths and feature very low optical losses. Integrated modulator platforms based on materials such as silicon, indium phosphide or polymers have not yet been able to meet these requirements simultaneously because of the intrinsic limitations of the materials used. On the other hand, lithium niobate electro-optic modulators, the workhorse of the optoelectronic industry for decades9, have been challenging to integrate on-chip because of difficulties in microstructuring lithium niobate. The current generation of lithium niobate modulators are bulky, expensive, limited in bandwidth and require high drive voltages, and thus are unable to reach the full potential of the material. Here we overcome these limitations and demonstrate monolithically integrated lithium niobate electro-optic modulators that feature a CMOS-compatible drive voltage, support data rates up to 210 gigabits per second and show an on-chip optical loss of less than 0.5 decibels. We achieve this by engineering the microwave and photonic circuits to achieve high electro-optical efficiencies, ultra-low optical losses and group-velocity matching simultaneously. Our scalable modulator devices could provide cost-effective, low-power and ultra-high-speed solutions for next-generation optical communication networks and microwave photonic systems. Furthermore, our approach could lead to large-scale ultra-low-loss photonic circuits that are reconfigurable on a picosecond timescale, enabling a wide range of quantum and classical applications5,10,11 including feed-forward photonic quantum computation. Chip-scale lithium niobate electro-optic modulators that rapidly convert electrical to optical signals and use CMOS-compatible voltages could prove useful in optical communication networks, microwave photonic systems and photonic computation.

Journal ArticleDOI
24 Jan 2018-Nature
TL;DR: In this paper, the authors demonstrate magneto-elastic soft millimetre-scale robots that can swim inside and on the surface of liquids, climb liquid menisci, roll and walk on solid surfaces, jump over obstacles, and crawl within narrow tunnels.
Abstract: Untethered small-scale (from several millimetres down to a few micrometres in all dimensions) robots that can non-invasively access confined, enclosed spaces may enable applications in microfactories such as the construction of tissue scaffolds by robotic assembly, in bioengineering such as single-cell manipulation and biosensing, and in healthcare such as targeted drug delivery and minimally invasive surgery. Existing small-scale robots, however, have very limited mobility because they are unable to negotiate obstacles and changes in texture or material in unstructured environments. Of these small-scale robots, soft robots have greater potential to realize high mobility via multimodal locomotion, because such machines have higher degrees of freedom than their rigid counterparts. Here we demonstrate magneto-elastic soft millimetre-scale robots that can swim inside and on the surface of liquids, climb liquid menisci, roll and walk on solid surfaces, jump over obstacles, and crawl within narrow tunnels. These robots can transit reversibly between different liquid and solid terrains, as well as switch between locomotive modes. They can additionally execute pick-and-place and cargo-release tasks. We also present theoretical models to explain how the robots move. Like the large-scale robots that can be used to study locomotion, these soft small-scale robots could be used to study soft-bodied locomotion produced by small organisms.

Journal ArticleDOI
14 Nov 2018-Nature
TL;DR: A single-cell atlas of the maternal–fetal interface reveals the cellular organization of the decidua and placenta, and the interactions that are critical for placentation and reproductive success, and develops a repository of ligand–receptor complexes and a statistical tool to predict the cell–cell communication via these molecular interactions.
Abstract: During early human pregnancy the uterine mucosa transforms into the decidua, into which the fetal placenta implants and where placental trophoblast cells intermingle and communicate with maternal cells. Trophoblast-decidual interactions underlie common diseases of pregnancy, including pre-eclampsia and stillbirth. Here we profile the transcriptomes of about 70,000 single cells from first-trimester placentas with matched maternal blood and decidual cells. The cellular composition of human decidua reveals subsets of perivascular and stromal cells that are located in distinct decidual layers. There are three major subsets of decidual natural killer cells that have distinctive immunomodulatory and chemokine profiles. We develop a repository of ligand-receptor complexes and a statistical tool to predict the cell-type specificity of cell-cell communication via these molecular interactions. Our data identify many regulatory interactions that prevent harmful innate or adaptive immune responses in this environment. Our single-cell atlas of the maternal-fetal interface reveals the cellular organization of the decidua and placenta, and the interactions that are critical for placentation and reproductive success.

Journal ArticleDOI
01 Jun 2018-Nature
TL;DR: 3D printing of programmed ferromagnetic domains in soft materials that enable fast transformations between complex 3D shapes via magnetic actuation are reported, enabling a set of previously inaccessible modes of transformation, such as remotely controlled auxetic behaviours of mechanical metamaterials with negative Poisson’s ratios.
Abstract: Soft materials capable of transforming between three-dimensional (3D) shapes in response to stimuli such as light, heat, solvent, electric and magnetic fields have applications in diverse areas such as flexible electronics1,2, soft robotics3,4 and biomedicine5–7. In particular, magnetic fields offer a safe and effective manipulation method for biomedical applications, which typically require remote actuation in enclosed and confined spaces8–10. With advances in magnetic field control 11 , magnetically responsive soft materials have also evolved from embedding discrete magnets 12 or incorporating magnetic particles 13 into soft compounds to generating nonuniform magnetization profiles in polymeric sheets14,15. Here we report 3D printing of programmed ferromagnetic domains in soft materials that enable fast transformations between complex 3D shapes via magnetic actuation. Our approach is based on direct ink writing 16 of an elastomer composite containing ferromagnetic microparticles. By applying a magnetic field to the dispensing nozzle while printing 17 , we reorient particles along the applied field to impart patterned magnetic polarity to printed filaments. This method allows us to program ferromagnetic domains in complex 3D-printed soft materials, enabling a set of previously inaccessible modes of transformation, such as remotely controlled auxetic behaviours of mechanical metamaterials with negative Poisson’s ratios. The actuation speed and power density of our printed soft materials with programmed ferromagnetic domains are orders of magnitude greater than existing 3D-printed active materials. We further demonstrate diverse functions derived from complex shape changes, including reconfigurable soft electronics, a mechanical metamaterial that can jump and a soft robot that crawls, rolls, catches fast-moving objects and transports a pharmaceutical dose.

Journal ArticleDOI
21 Mar 2018-Nature
TL;DR: This work demonstrates substantial mitigation of both non-radiative losses and photoinduced ion migration in perovskite films and interfaces by decorating the surfaces and grain boundaries with passivating potassium halide layers, and demonstrates the inhibition of transient photo induced ion-migration processes across a wide range of mixed halide perovSKite bandgaps in materials that exhibit bandgap instabilities when unpassivated.
Abstract: M.A.-J. thanks Nava Technology Limited and Nyak Technology Limited for their funding and technical support. Z.A.-G. acknowledges funding from a Winton Studentship, and ICON Studentship from the Lloyd’s Register Foundation. This project has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement number PIOF-GA-2013-622630, the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement number 756962), and the Royal Society and Tata Group (UF150033). We thank the Engineering and Physical Sciences Research Council (EPSRC) for support. XMaS is a mid-range facility at the European Synchrotron Radiation Facility supported by the EPSRC and we are grateful to the XMaS beamline team staff for their support. We thank Diamond Light Source for access to beamline I09 and staff member T.-L. Lee as well as U. Cappel for assistance during the HAXPES measurements. S.C., C.D. and G.D. acknowledge funding from the ERC under grant number 25961976 PHOTO EM and financial support from the European Union under grant number 77 312483 ESTEEM2. M.A. thanks the president of the UAE’s Distinguished Student Scholarship Program, granted by the Ministry of Presidential Affairs. H.R. and B.P. acknowledge support from the Swedish research council (2014-6019) and the Swedish foundation for strategic research. E.M.H. and T.J.S. were supported by the Netherlands Organization for Scientific Research under the Echo grant number 712.014.007.

Journal ArticleDOI
07 Nov 2018-Nature
TL;DR: After alloying with metal cations, a lead-free halide double perovskite shows stable performance and remarkably efficient white-light emission, with possible applications in lighting and display technologies.
Abstract: Lighting accounts for one-fifth of global electricity consumption1. Single materials with efficient and stable white-light emission are ideal for lighting applications, but photon emission covering the entire visible spectrum is difficult to achieve using a single material. Metal halide perovskites have outstanding emission properties2,3; however, the best-performing materials of this type contain lead and have unsatisfactory stability. Here we report a lead-free double perovskite that exhibits efficient and stable white-light emission via self-trapped excitons that originate from the Jahn–Teller distortion of the AgCl6 octahedron in the excited state. By alloying sodium cations into Cs2AgInCl6, we break the dark transition (the inversion-symmetry-induced parity-forbidden transition) by manipulating the parity of the wavefunction of the self-trapped exciton and reduce the electronic dimensionality of the semiconductor4. This leads to an increase in photoluminescence efficiency by three orders of magnitude compared to pure Cs2AgInCl6. The optimally alloyed Cs2(Ag0.60Na0.40)InCl6 with 0.04 per cent bismuth doping emits warm-white light with 86 ± 5 per cent quantum efficiency and works for over 1,000 hours. We anticipate that these results will stimulate research on single-emitter-based white-light-emitting phosphors and diodes for next-generation lighting and display technologies. After alloying with metal cations, a lead-free halide double perovskite shows stable performance and remarkably efficient white-light emission, with possible applications in lighting and display technologies.

Journal ArticleDOI
31 Oct 2018-Nature
TL;DR: This study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct areas of the adult mouse cortex and identifies 133 transcriptomic types of glutamatergic neurons to their long-range projection specificity.
Abstract: The neocortex contains a multitude of cell types that are segregated into layers and functionally distinct areas. To investigate the diversity of cell types across the mouse neocortex, here we analysed 23,822 cells from two areas at distant poles of the mouse neocortex: the primary visual cortex and the anterior lateral motor cortex. We define 133 transcriptomic cell types by deep, single-cell RNA sequencing. Nearly all types of GABA (γ-aminobutyric acid)-containing neurons are shared across both areas, whereas most types of glutamatergic neurons were found in one of the two areas. By combining single-cell RNA sequencing and retrograde labelling, we match transcriptomic types of glutamatergic neurons to their long-range projection specificity. Our study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct areas of the adult mouse cortex.

Journal ArticleDOI
14 Feb 2018-Nature
TL;DR: Increased TGFβ in the tumour microenvironment represents a primary mechanism of immune evasion that promotes T-cell exclusion and blocks acquisition of the TH1-effector phenotype, and immunotherapies directed against TGF β signalling may have broad applications in treating patients with advanced colorectal cancer.
Abstract: Most patients with colorectal cancer die as a result of the disease spreading to other organs. However, no prevalent mutations have been associated with metastatic colorectal cancers. Instead, particular features of the tumour microenvironment, such as lack of T-cell infiltration, low type 1 T-helper cell (TH1) activity and reduced immune cytotoxicity or increased TGFβ levels predict adverse outcomes in patients with colorectal cancer. Here we analyse the interplay between genetic alterations and the tumour microenvironment by crossing mice bearing conditional alleles of four main colorectal cancer mutations in intestinal stem cells. Quadruple-mutant mice developed metastatic intestinal tumours that display key hallmarks of human microsatellite-stable colorectal cancers, including low mutational burden, T-cell exclusion and TGFβ-activated stroma. Inhibition of the PD-1-PD-L1 immune checkpoint provoked a limited response in this model system. By contrast, inhibition of TGFβ unleashed a potent and enduring cytotoxic T-cell response against tumour cells that prevented metastasis. In mice with progressive liver metastatic disease, blockade of TGFβ signalling rendered tumours susceptible to anti-PD-1-PD-L1 therapy. Our data show that increased TGFβ in the tumour microenvironment represents a primary mechanism of immune evasion that promotes T-cell exclusion and blocks acquisition of the TH1-effector phenotype. Immunotherapies directed against TGFβ signalling may therefore have broad applications in treating patients with advanced colorectal cancer.

Journal ArticleDOI
01 Apr 2018-Nature
TL;DR: Molten-salt-assisted chemical vapour deposition is used to synthesize a wide variety of two-dimensional transition-metal chalcogenides and elaborate how the salt decreases the melting point of the reactants and facilitates the formation of intermediate products, increasing the overall reaction rate.
Abstract: Investigations of two-dimensional transition-metal chalcogenides (TMCs) have recently revealed interesting physical phenomena, including the quantum spin Hall effect1,2, valley polarization3,4 and two-dimensional superconductivity 5 , suggesting potential applications for functional devices6–10. However, of the numerous compounds available, only a handful, such as Mo- and W-based TMCs, have been synthesized, typically via sulfurization11–15, selenization16,17 and tellurization 18 of metals and metal compounds. Many TMCs are difficult to produce because of the high melting points of their metal and metal oxide precursors. Molten-salt-assisted methods have been used to produce ceramic powders at relatively low temperature 19 and this approach 20 was recently employed to facilitate the growth of monolayer WS2 and WSe2. Here we demonstrate that molten-salt-assisted chemical vapour deposition can be broadly applied for the synthesis of a wide variety of two-dimensional (atomically thin) TMCs. We synthesized 47 compounds, including 32 binary compounds (based on the transition metals Ti, Zr, Hf, V, Nb, Ta, Mo, W, Re, Pt, Pd and Fe), 13 alloys (including 11 ternary, one quaternary and one quinary), and two heterostructured compounds. We elaborate how the salt decreases the melting point of the reactants and facilitates the formation of intermediate products, increasing the overall reaction rate. Most of the synthesized materials in our library are useful, as supported by evidence of superconductivity in our monolayer NbSe2 and MoTe2 samples21,22 and of high mobilities in MoS2 and ReS2. Although the quality of some of the materials still requires development, our work opens up opportunities for studying the properties and potential application of a wide variety of two-dimensional TMCs.

Journal ArticleDOI
19 Mar 2018-Nature
TL;DR: For example, this paper screened more than 1,000 marketed drugs against 40 representative gut bacterial strains, and found that 24% of the drugs with human targets, including members of all therapeutic classes, inhibited the growth of at least one strain in vitro.
Abstract: A few commonly used non-antibiotic drugs have recently been associated with changes in gut microbiome composition, but the extent of this phenomenon is unknown. Here, we screened more than 1,000 marketed drugs against 40 representative gut bacterial strains, and found that 24% of the drugs with human targets, including members of all therapeutic classes, inhibited the growth of at least one strain in vitro. Particular classes, such as the chemically diverse antipsychotics, were overrepresented in this group. The effects of human-targeted drugs on gut bacteria are reflected on their antibiotic-like side effects in humans and are concordant with existing human cohort studies. Susceptibility to antibiotics and human-targeted drugs correlates across bacterial species, suggesting common resistance mechanisms, which we verified for some drugs. The potential risk of non-antibiotics promoting antibiotic resistance warrants further exploration. Our results provide a resource for future research on drug-microbiome interactions, opening new paths for side effect control and drug repurposing, and broadening our view of antibiotic resistance.

Journal ArticleDOI
14 Feb 2018-Nature
TL;DR: The transcriptional basis of the gradual phenotypic change along the arteriovenous axis is uncovered and unexpected cell type differences are revealed: a seamless continuum for endothelial cells versus a punctuated continuum for mural cells.
Abstract: Cerebrovascular disease is the third most common cause of death in developed countries, but our understanding of the cells that compose the cerebral vasculature is limited Here, using vascular sin

Journal Article
01 Jan 2018-Nature
TL;DR: An updated classification of cell death subroutines focusing on mechanistic and essential aspects of the process is proposed, and the utility of neologisms that refer to highly specialized instances of these processes are discussed.
Abstract: Over the past decade, the Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives. Since the field continues to expand and novel mechanisms that orchestrate multiple cell death pathways are unveiled, we propose an updated classification of cell death subroutines focusing on mechanistic and essential (as opposed to correlative and dispensable) aspects of the process. As we provide molecularly oriented definitions of terms including intrinsic apoptosis, extrinsic apoptosis, mitochondrial permeability transition (MPT)-driven necrosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entotic cell death, NETotic cell death, lysosome-dependent cell death, autophagy-dependent cell death, immunogenic cell death, cellular senescence, and mitotic catastrophe, we discuss the utility of neologisms that refer to highly specialized instances of these processes. The mission of the NCCD is to provide a widely accepted nomenclature on cell death in support of the continued development of the field.

Journal ArticleDOI
01 Mar 2018-Nature
TL;DR: This work combines Monte Carlo tree search with an expansion policy network that guides the search, and a filter network to pre-select the most promising retrosynthetic steps that solve for almost twice as many molecules, thirty times faster than the traditional computer-aided search method.
Abstract: To plan the syntheses of small organic molecules, chemists use retrosynthesis, a problem-solving technique in which target molecules are recursively transformed into increasingly simpler precursors. Computer-aided retrosynthesis would be a valuable tool but at present it is slow and provides results of unsatisfactory quality. Here we use Monte Carlo tree search and symbolic artificial intelligence (AI) to discover retrosynthetic routes. We combined Monte Carlo tree search with an expansion policy network that guides the search, and a filter network to pre-select the most promising retrosynthetic steps. These deep neural networks were trained on essentially all reactions ever published in organic chemistry. Our system solves for almost twice as many molecules, thirty times faster than the traditional computer-aided search method, which is based on extracted rules and hand-designed heuristics. In a double-blind AB test, chemists on average considered our computer-generated routes to be equivalent to reported literature routes.