Showing papers in "Nature in 2016"
TL;DR: Using this search algorithm, the program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the human European Go champion by 5 games to 0.5, the first time that a computer program has defeated a human professional player in the full-sized game of Go.
Abstract: The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves. Here we introduce a new approach to computer Go that uses ‘value networks’ to evaluate board positions and ‘policy networks’ to select moves. These deep neural networks are trained by a novel combination of supervised learning from human expert games, and reinforcement learning from games of self-play. Without any lookahead search, the neural networks play Go at the level of stateof-the-art Monte Carlo tree search programs that simulate thousands of random games of self-play. We also introduce a new search algorithm that combines Monte Carlo simulation with value and policy networks. Using this search algorithm, our program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the human European Go champion by 5 games to 0. This is the first time that a computer program has defeated a human professional player in the full-sized game of Go, a feat previously thought to be at least a decade away.
14,377 citations
Broad Institute1, Harvard University2, Boston Children's Hospital3, University of Washington4, University of Arizona5, Cardiff University6, Google7, Icahn School of Medicine at Mount Sinai8, Samsung Medical Center9, Vertex Pharmaceuticals10, University of Michigan11, University of Cambridge12, State University of New York Upstate Medical University13, Karolinska Institutet14, University of Eastern Finland15, University of Oxford16, Wellcome Trust Centre for Human Genetics17, Cedars-Sinai Medical Center18, University of Ottawa19, University of Pennsylvania20, University of North Carolina at Chapel Hill21, University of Helsinki22, University of California, San Diego23, University of Mississippi Medical Center24
TL;DR: The aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC) provides direct evidence for the presence of widespread mutational recurrence.
Abstract: Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.
8,758 citations
TL;DR: Using multi-modal magnetic resonance images from the Human Connectome Project and an objective semi-automated neuroanatomical approach, 180 areas per hemisphere are delineated bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults.
Abstract: Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience. Using multi-modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi-automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post-mortem microscopy or other specialized study-specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine-learning classifier to recognize the multi-modal 'fingerprint' of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.
3,414 citations
TL;DR: E engineered fusions of CRISPR/Cas9 and a cytidine deaminase enzyme that retain the ability to be programmed with a guide RNA, do not induce dsDNA breaks, and mediate the direct conversion of cytidine to uridine, thereby effecting a C→T (or G→A) substitution.
Abstract: Current genome-editing technologies introduce double-stranded (ds) DNA breaks at a target locus as the first step to gene correction. Although most genetic diseases arise from point mutations, current approaches to point mutation correction are inefficient and typically induce an abundance of random insertions and deletions (indels) at the target locus resulting from the cellular response to dsDNA breaks. Here we report the development of 'base editing', a new approach to genome editing that enables the direct, irreversible conversion of one target DNA base into another in a programmable manner, without requiring dsDNA backbone cleavage or a donor template. We engineered fusions of CRISPR/Cas9 and a cytidine deaminase enzyme that retain the ability to be programmed with a guide RNA, do not induce dsDNA breaks, and mediate the direct conversion of cytidine to uridine, thereby effecting a C→T (or G→A) substitution. The resulting 'base editors' convert cytidines within a window of approximately five nucleotides, and can efficiently correct a variety of point mutations relevant to human disease. In four transformed human and murine cell lines, second- and third-generation base editors that fuse uracil glycosylase inhibitor, and that use a Cas9 nickase targeting the non-edited strand, manipulate the cellular DNA repair response to favour desired base-editing outcomes, resulting in permanent correction of ~15-75% of total cellular DNA with minimal (typically ≤1%) indel formation. Base editing expands the scope and efficiency of genome editing of point mutations.
3,384 citations
TL;DR: This work bridges the technological gap between signal transduction, conditioning, processing and wireless transmission in wearable biosensors by merging plastic-based sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing.
Abstract: Wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual's state of health. Sampling human sweat, which is rich in physiological information, could enable non-invasive monitoring. Previously reported sweat-based and other non-invasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanically flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plastic-based sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing. This application could not have been realized using either of these technologies alone owing to their respective inherent limitations. The wearable system is used to measure the detailed sweat profile of human subjects engaged in prolonged indoor and outdoor physical activities, and to make a real-time assessment of the physiological state of the subjects. This platform enables a wide range of personalized diagnostic and physiological monitoring applications.
3,235 citations
2,609 citations
TL;DR: Thin films of near-single-crystalline quality are produced, in which the crystallographic planes of the inorganic perovskite component have a strongly preferential out-of-plane alignment with respect to the contacts in planar solar cells to facilitate efficient charge transport.
Abstract: Three-dimensional organic-inorganic perovskites have emerged as one of the most promising thin-film solar cell materials owing to their remarkable photophysical properties, which have led to power conversion efficiencies exceeding 20 per cent, with the prospect of further improvements towards the Shockley-Queisser limit for a single‐junction solar cell (33.5 per cent). Besides efficiency, another critical factor for photovoltaics and other optoelectronic applications is environmental stability and photostability under operating conditions. In contrast to their three-dimensional counterparts, Ruddlesden-Popper phases--layered two-dimensional perovskite films--have shown promising stability, but poor efficiency at only 4.73 per cent. This relatively poor efficiency is attributed to the inhibition of out-of-plane charge transport by the organic cations, which act like insulating spacing layers between the conducting inorganic slabs. Here we overcome this issue in layered perovskites by producing thin films of near-single-crystalline quality, in which the crystallographic planes of the inorganic perovskite component have a strongly preferential out-of-plane alignment with respect to the contacts in planar solar cells to facilitate efficient charge transport. We report a photovoltaic efficiency of 12.52 per cent with no hysteresis, and the devices exhibit greatly improved stability in comparison to their three-dimensional counterparts when subjected to light, humidity and heat stress tests. Unencapsulated two-dimensional perovskite devices retain over 60 per cent of their efficiency for over 2,250 hours under constant, standard (AM1.5G) illumination, and exhibit greater tolerance to 65 per cent relative humidity than do three-dimensional equivalents. When the devices are encapsulated, the layered devices do not show any degradation under constant AM1.5G illumination or humidity. We anticipate that these results will lead to the growth of single-crystalline, solution-processed, layered, hybrid, perovskite thin films, which are essential for high-performance opto-electronic devices with technologically relevant long-term stability.
2,566 citations
TL;DR: Using three million Landsat satellite images, this globally consistent, validated data set shows that impacts of climate change and climate oscillations on surface water occurrence can be measured and that evidence can be gathered to show how surface water is altered by human activities.
Abstract: A freely available dataset produced from three million Landsat satellite images reveals substantial changes in the distribution of global surface water over the past 32 years and their causes, from climate change to human actions. The distribution of surface water has been mapped globally, and local-to-regional studies have tracked changes over time. But to date, there has been no global and methodologically consistent quantification of changes in surface water over time. Jean-Francois Pekel and colleagues have analysed more than three million Landsat images to quantify month-to-month changes in surface water at a resolution of 30 metres and over a 32-year period. They find that surface waters have declined by almost 90,000 square kilometres—largely in the Middle East and Central Asia—but that surface waters equivalent to about twice that area have been created elsewhere. Drought, reservoir creation and water extraction appear to have driven most of the changes in surface water over the past decades. The location and persistence of surface water (inland and coastal) is both affected by climate and human activity1 and affects climate2,3, biological diversity4 and human wellbeing5,6. Global data sets documenting surface water location and seasonality have been produced from inventories and national descriptions7, statistical extrapolation of regional data8 and satellite imagery9,10,11,12, but measuring long-term changes at high resolution remains a challenge. Here, using three million Landsat satellite images13, we quantify changes in global surface water over the past 32 years at 30-metre resolution. We record the months and years when water was present, where occurrence changed and what form changes took in terms of seasonality and persistence. Between 1984 and 2015 permanent surface water has disappeared from an area of almost 90,000 square kilometres, roughly equivalent to that of Lake Superior, though new permanent bodies of surface water covering 184,000 square kilometres have formed elsewhere. All continental regions show a net increase in permanent water, except Oceania, which has a fractional (one per cent) net loss. Much of the increase is from reservoir filling, although climate change14 is also implicated. Loss is more geographically concentrated than gain. Over 70 per cent of global net permanent water loss occurred in the Middle East and Central Asia, linked to drought and human actions including river diversion or damming and unregulated withdrawal15,16. Losses in Australia17 and the USA18 linked to long-term droughts are also evident. This globally consistent, validated data set shows that impacts of climate change and climate oscillations on surface water occurrence can be measured and that evidence can be gathered to show how surface water is altered by human activities. We anticipate that this freely available data will improve the modelling of surface forcing, provide evidence of state and change in wetland ecotones (the transition areas between biomes), and inform water-management decision-making.
2,469 citations
University of Queensland1, University of Glasgow2, QIMR Berghofer Medical Research Institute3, Garvan Institute of Medical Research4, Baylor College of Medicine5, University of Utah6, University of Adelaide7, South Australia Pathology8, Harvard University9, Campbelltown Hospital10, St. Vincent's Health System11, University of New South Wales12, University of Newcastle13, Royal North Shore Hospital14, University of Sydney15, Royal Prince Alfred Hospital16, Fiona Stanley Hospital17, Royal Adelaide Hospital18, Princess Alexandra Hospital19, University of Western Australia20, Beatson West of Scotland Cancer Centre21, Southern General Hospital22, Dresden University of Technology23, University of Texas MD Anderson Cancer Center24, Memorial Sloan Kettering Cancer Center25, Johns Hopkins University School of Medicine26, University of Verona27, Mayo Clinic28, University of Melbourne29
TL;DR: Detailed genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing.
Abstract: Integrated genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing. Expression analysis defined 4 subtypes: (1) squamous; (2) pancreatic progenitor; (3) immunogenic; and (4) aberrantly differentiated endocrine exocrine (ADEX) that correlate with histopathological characteristics. Squamous tumours are enriched for TP53 and KDM6A mutations, upregulation of the TP63∆N transcriptional network, hypermethylation of pancreatic endodermal cell-fate determining genes and have a poor prognosis. Pancreatic progenitor tumours preferentially express genes involved in early pancreatic development (FOXA2/3, PDX1 and MNX1). ADEX tumours displayed upregulation of genes that regulate networks involved in KRAS activation, exocrine (NR5A2 and RBPJL), and endocrine differentiation (NEUROD1 and NKX2-2). Immunogenic tumours contained upregulated immune networks including pathways involved in acquired immune suppression. These data infer differences in the molecular evolution of pancreatic cancer subtypes and identify opportunities for therapeutic development.
2,443 citations
TL;DR: In this metastability-engineering strategy, a transformation-induced plasticity-assisted, dual-phase high-entropy alloy (TRIP-DP-HEA) is designed, which combines the best of two worlds: extensive hardening due to the decreased phase stability known from advanced steels and massive solid-solution strengthening of high-ENTropy alloys.
Abstract: Metals have been mankind's most essential materials for thousands of years; however, their use is affected by ecological and economical concerns Alloys with higher strength and ductility could alleviate some of these concerns by reducing weight and improving energy efficiency However, most metallurgical mechanisms for increasing strength lead to ductility loss, an effect referred to as the strength-ductility trade-off Here we present a metastability-engineering strategy in which we design nanostructured, bulk high-entropy alloys with multiple compositionally equivalent high-entropy phases High-entropy alloys were originally proposed to benefit from phase stabilization through entropy maximization Yet here, motivated by recent work that relaxes the strict restrictions on high-entropy alloy compositions by demonstrating the weakness of this connection, the concept is overturned We decrease phase stability to achieve two key benefits: interface hardening due to a dual-phase microstructure (resulting from reduced thermal stability of the high-temperature phase); and transformation-induced hardening (resulting from the reduced mechanical stability of the room-temperature phase) This combines the best of two worlds: extensive hardening due to the decreased phase stability known from advanced steels and massive solid-solution strengthening of high-entropy alloys In our transformation-induced plasticity-assisted, dual-phase high-entropy alloy (TRIP-DP-HEA), these two contributions lead respectively to enhanced trans-grain and inter-grain slip resistance, and hence, increased strength Moreover, the increased strain hardening capacity that is enabled by dislocation hardening of the stable phase and transformation-induced hardening of the metastable phase produces increased ductility This combined increase in strength and ductility distinguishes the TRIP-DP-HEA alloy from other recently developed structural materials This metastability-engineering strategy should thus usefully guide design in the near-infinite compositional space of high-entropy alloys
2,403 citations
ETH Zurich1, International Institute for Applied Systems Analysis2, Netherlands Environmental Assessment Agency3, Wageningen University and Research Centre4, World Resources Institute5, University of Cape Town6, Federal University of Rio de Janeiro7, Graz University of Technology8, University of Melbourne9, Potsdam Institute for Climate Impact Research10
TL;DR: Substantial enhancement or over-delivery on current INDCs by additional national, sub-national and non-state actions is required to maintain a reasonable chance of meeting the target of keeping warming well below 2 degrees Celsius.
Abstract: The Paris climate agreement aims at holding global warming to well below 2 degrees Celsius and to "pursue efforts" to limit it to 1.5 degrees Celsius. To accomplish this, countries have submitted Intended Nationally Determined Contributions (INDCs) outlining their post-2020 climate action. Here we assess the effect of current INDCs on reducing aggregate greenhouse gas emissions, its implications for achieving the temperature objective of the Paris climate agreement, and potential options for overachievement. The INDCs collectively lower greenhouse gas emissions compared to where current policies stand, but still imply a median warming of 2.6-3.1 degrees Celsius by 2100. More can be achieved, because the agreement stipulates that targets for reducing greenhouse gas emissions are strengthened over time, both in ambition and scope. Substantial enhancement or over-delivery on current INDCs by additional national, sub-national and non-state actions is required to maintain a reasonable chance of meeting the target of keeping warming well below 2 degrees Celsius.
TL;DR: This list is not exhaustive; almost all commercial chemicals arise from a separation process that could be improved, and here, seven chemical separation processes that, if improved, would reap great global benefits.
Abstract: Purifying mixtures without using heat would lower global energy use, emissions and pollution — and open up new routes to resources, say David S. Sholl and Ryan P. Lively.
TL;DR: With its exceptional precision, SpCas9-HF1 provides an alternative to wild-type Sp Cas9 for research and therapeutic applications and suggests a general strategy for optimizing genome-wide specificities of other CRISPR-RNA-guided nucleases.
Abstract: CRISPR-Cas9 nucleases are widely used for genome editing but can induce unwanted off-target mutations. Existing strategies for reducing genome-wide off-target effects of the widely used Streptococcus pyogenes Cas9 (SpCas9) are imperfect, possessing only partial or unproven efficacies and other limitations that constrain their use. Here we describe SpCas9-HF1, a high-fidelity variant harbouring alterations designed to reduce non-specific DNA contacts. SpCas9-HF1 retains on-target activities comparable to wild-type SpCas9 with >85% of single-guide RNAs (sgRNAs) tested in human cells. Notably, with sgRNAs targeted to standard non-repetitive sequences, SpCas9-HF1 rendered all or nearly all off-target events undetectable by genome-wide break capture and targeted sequencing methods. Even for atypical, repetitive target sites, the vast majority of off-target mutations induced by wild-type SpCas9 were not detected with SpCas9-HF1. With its exceptional precision, SpCas9-HF1 provides an alternative to wild-type SpCas9 for research and therapeutic applications. More broadly, our results suggest a general strategy for optimizing genome-wide specificities of other CRISPR-RNA-guided nucleases.
TL;DR: In patients with prodromal or mild AD, one year of monthly intravenous infusions of aducanumab reduces brain Aβ in a dose- and time-dependent manner, accompanied by a slowing of clinical decline measured by Clinical Dementia Rating—Sum of Boxes and Mini Mental State Examination scores.
Abstract: Alzheimer's disease (AD) is characterized by deposition of amyloid-β (Aβ) plaques and neurofibrillary tangles in the brain, accompanied by synaptic dysfunction and neurodegeneration. Antibody-based immunotherapy against Aβ to trigger its clearance or mitigate its neurotoxicity has so far been unsuccessful. Here we report the generation of aducanumab, a human monoclonal antibody that selectively targets aggregated Aβ. In a transgenic mouse model of AD, aducanumab is shown to enter the brain, bind parenchymal Aβ, and reduce soluble and insoluble Aβ in a dose-dependent manner. In patients with prodromal or mild AD, one year of monthly intravenous infusions of aducanumab reduces brain Aβ in a dose- and time-dependent manner. This is accompanied by a slowing of clinical decline measured by Clinical Dementia Rating-Sum of Boxes and Mini Mental State Examination scores. The main safety and tolerability findings are amyloid-related imaging abnormalities. These results justify further development of aducanumab for the treatment of AD. Should the slowing of clinical decline be confirmed in ongoing phase 3 clinical trials, it would provide compelling support for the amyloid hypothesis.
TL;DR: It is shown that droughts and extreme heat significantly reduced national cereal production by 9–10%, whereas the analysis could not identify an effect from floods and extreme cold in the national data, which may help to guide agricultural priorities in international disaster risk reduction and adaptation efforts.
Abstract: In recent years, several extreme weather disasters have partially or completely damaged regional crop production. While detailed regional accounts of the effects of extreme weather disasters exist, the global scale effects of droughts, floods and extreme temperature on crop production are yet to be quantified. Here we estimate for the first time, to our knowledge, national cereal production losses across the globe resulting from reported extreme weather disasters during 1964-2007. We show that droughts and extreme heat significantly reduced national cereal production by 9-10%, whereas our analysis could not identify an effect from floods and extreme cold in the national data. Analysing the underlying processes, we find that production losses due to droughts were associated with a reduction in both harvested area and yields, whereas extreme heat mainly decreased cereal yields. Furthermore, the results highlight ~7% greater production damage from more recent droughts and 8-11% more damage in developed countries than in developing ones. Our findings may help to guide agricultural priorities in international disaster risk reduction and adaptation efforts.
TL;DR: It is shown that GSDMD-NT oligomerizes in membranes to form pores that are visible by electron microscopy and kills cell-free bacteria in vitro and may have a direct bactericidal effect within the cytosol of host cells, but the importance of direct bacterial killing in controlling in vivo infection remains to be determined.
Abstract: Inflammatory caspases (caspases 1, 4, 5 and 11) are activated in response to microbial infection and danger signals. When activated, they cleave mouse and human gasdermin D (GSDMD) after Asp276 and Asp275, respectively, to generate an N-terminal cleavage product (GSDMD-NT) that triggers inflammatory death (pyroptosis) and release of inflammatory cytokines such as interleukin-1β. Cleavage removes the C-terminal fragment (GSDMD-CT), which is thought to fold back on GSDMD-NT to inhibit its activation. However, how GSDMD-NT causes cell death is unknown. Here we show that GSDMD-NT oligomerizes in membranes to form pores that are visible by electron microscopy. GSDMD-NT binds to phosphatidylinositol phosphates and phosphatidylserine (restricted to the cell membrane inner leaflet) and cardiolipin (present in the inner and outer leaflets of bacterial membranes). Mutation of four evolutionarily conserved basic residues blocks GSDMD-NT oligomerization, membrane binding, pore formation and pyroptosis. Because of its lipid-binding preferences, GSDMD-NT kills from within the cell, but does not harm neighbouring mammalian cells when it is released during pyroptosis. GSDMD-NT also kills cell-free bacteria in vitro and may have a direct bactericidal effect within the cytosol of host cells, but the importance of direct bacterial killing in controlling in vivo infection remains to be determined.
TL;DR: It is shown that compared to vehicle alone, AP20187 treatment extended median lifespan in both male and female mice of two distinct genetic backgrounds and the clearance of p16Ink4a-positive cells delayed tumorigenesis and attenuated age-related deterioration of several organs without apparent side effects.
Abstract: Cellular senescence, a stress-induced irreversible growth arrest often characterized by expression of p16(Ink4a) (encoded by the Ink4a/Arf locus, also known as Cdkn2a) and a distinctive secretory phenotype, prevents the proliferation of preneoplastic cells and has beneficial roles in tissue remodelling during embryogenesis and wound healing. Senescent cells accumulate in various tissues and organs over time, and have been speculated to have a role in ageing. To explore the physiological relevance and consequences of naturally occurring senescent cells, here we use a previously established transgene, INK-ATTAC, to induce apoptosis in p16(Ink4a)-expressing cells of wild-type mice by injection of AP20187 twice a week starting at one year of age. We show that compared to vehicle alone, AP20187 treatment extended median lifespan in both male and female mice of two distinct genetic backgrounds. The clearance of p16(Ink4a)-positive cells delayed tumorigenesis and attenuated age-related deterioration of several organs without apparent side effects, including kidney, heart and fat, where clearance preserved the functionality of glomeruli, cardio-protective KATP channels and adipocytes, respectively. Thus, p16(Ink4a)-positive cells that accumulate during adulthood negatively influence lifespan and promote age-dependent changes in several organs, and their therapeutic removal may be an attractive approach to extend healthy lifespan.
TL;DR: It is found that many structurally diverse alleles of the complement component 4 (C4) genes generated widely varying levels of C4A and C4B expression in the brain, with each common C4 allele associating with schizophrenia in proportion to its tendency to generate greater expression of C 4A.
Abstract: Schizophrenia is a heritable brain illness with unknown pathogenic mechanisms. Schizophrenia's strongest genetic association at a population level involves variation in the major histocompatibility complex (MHC) locus, but the genes and molecular mechanisms accounting for this have been challenging to identify. Here we show that this association arises in part from many structurally diverse alleles of the complement component 4 (C4) genes. We found that these alleles generated widely varying levels of C4A and C4B expression in the brain, with each common C4 allele associating with schizophrenia in proportion to its tendency to generate greater expression of C4A. Human C4 protein localized to neuronal synapses, dendrites, axons, and cell bodies. In mice, C4 mediated synapse elimination during postnatal development. These results implicate excessive complement activity in the development of schizophrenia and may help explain the reduced numbers of synapses in the brains of individuals with schizophrenia.
National University of Cordoba1, Max Planck Society2, VU University Amsterdam3, Macquarie University4, University of Grenoble5, University of Lyon6, Leipzig University7, Industrial University of Santander8, University of Oldenburg9, Imperial College London10, University of Montpellier11, Forschungszentrum Jülich12, University of Western Sydney13, University of Minnesota14, University of New South Wales15, Royal Botanic Gardens16, Missouri Botanical Garden17, George Washington University18, Paul Sabatier University19, Smithsonian Tropical Research Institute20, Komarov Botanical Institute21, Institut national de la recherche agronomique22, University of Bordeaux23, Florida International University24, University of Insubria25, University of Milan26, Université de Sherbrooke27, Centro Agronómico Tropical de Investigación y Enseñanza28
TL;DR: Analysis of worldwide variation in six major traits critical to growth, survival and reproduction within the largest sample of vascular plant species ever compiled found that occupancy of six-dimensional trait space is strongly concentrated, indicating coordination and trade-offs.
Abstract: The authors found that the key elements of plant form and function, analysed at global scale, are largely concentrated into a two-dimensional plane indexed by the size of whole plants and organs on the one hand, and the construction costs for photosynthetic leaf area, on the other.
Cambridge University Hospitals NHS Foundation Trust1, Wellcome Trust Sanger Institute2, Lund University3, Erasmus University Medical Center4, Radboud University Nijmegen5, European Bioinformatics Institute6, University of Oslo7, Oslo University Hospital8, Gachon University9, Netherlands Cancer Institute10, Université libre de Bruxelles11, University of Antwerp12, Harvard University13, University of Amsterdam14, University of Ulsan15, Hanyang University16, Memorial Sloan Kettering Cancer Center17, University of Texas MD Anderson Cancer Center18, French Institute of Health and Medical Research19, Ninewells Hospital20, ICM Partners21, University of Queensland22, University of Iceland23, Curie Institute24, University of Cambridge25, Institute of Cancer Research26, King's College London27, University of Bergen28, Singapore General Hospital29
TL;DR: This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operative, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.
Abstract: We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.
TL;DR: There are opportunities to use such sustainable polymers in both high-value areas and in basic applications such as packaging.
Abstract: Renewable resources are used increasingly in the production of polymers. In particular, monomers such as carbon dioxide, terpenes, vegetable oils and carbohydrates can be used as feedstocks for the manufacture of a variety of sustainable materials and products, including elastomers, plastics, hydrogels, flexible electronics, resins, engineering polymers and composites. Efficient catalysis is required to produce monomers, to facilitate selective polymerizations and to enable recycling or upcycling of waste materials. There are opportunities to use such sustainable polymers in both high-value areas and in basic applications such as packaging. Life-cycle assessment can be used to quantify the environmental benefits of sustainable polymers.
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TL;DR: A new relationship with the authors' goods and materials would save resources and energy and create local jobs, explains Walter R. Stahel.
Abstract: A new relationship with our goods and materials would save resources and energy and create local jobs, explains Walter R. Stahel.
TL;DR: It is demonstrated that the liposome-leakage and pore-forming activities of the gasdermin-N domain are required for pyroptosis and provide insights into the roles of theGasdermin family in necrosis, immunity and diseases.
Abstract: The N-terminal domains of gasdermin proteins cause pyroptotic cell death by oligomerizing to form membrane pores.
TL;DR: The semiconductor industry will soon abandon its pursuit of Moore's law as mentioned in this paper, and things could get a lot more interesting in the next few decades, which is a good thing.
Abstract: The semiconductor industry will soon abandon its pursuit of Moore's law. Now things could get a lot more interesting.
TL;DR: An untethered operation of a robot composed solely of soft materials that autonomously regulates fluid flow and, hence, catalytic decomposition of an on-board monopropellant fuel supply is reported.
Abstract: An untethered, entirely soft robot is designed to operate autonomously by combining microfluidic logic and hydrogen peroxide as an on-board fuel supply. Soft robotics have so far necessarily included some 'hard' or metallic elements, in particular in the form of batteries or wiring, to connect them to an external power source. Additionally, external wiring tethering them to a power source places limits on the autonomy of such robots. Now Jennifer Lewis and colleagues have combined a 3D-printed soft polymeric robot with microfluidic logic and hydrogen peroxide as an onboard fuel to produce an eight-armed robot — an 'octobot' — that actuates its arms, without the incorporation of any hard structures. The hydrogen peroxide decomposes in the presence of a platinum catalyst to produce oxygen and a volumetric expansion that fills bladders embedded within the arms of the octobot. The design of the fuel reservoirs, microfluidic channels and vents to release the gas means that two sets of arms actuate cyclically. Soft robots possess many attributes that are difficult, if not impossible, to achieve with conventional robots composed of rigid materials1,2. Yet, despite recent advances, soft robots must still be tethered to hard robotic control systems and power sources3,4,5,6,7,8,9,10. New strategies for creating completely soft robots, including soft analogues of these crucial components, are needed to realize their full potential. Here we report the untethered operation of a robot composed solely of soft materials. The robot is controlled with microfluidic logic11 that autonomously regulates fluid flow and, hence, catalytic decomposition of an on-board monopropellant fuel supply. Gas generated from the fuel decomposition inflates fluidic networks downstream of the reaction sites, resulting in actuation12. The body and microfluidic logic of the robot are fabricated using moulding and soft lithography, respectively, and the pneumatic actuator networks, on-board fuel reservoirs and catalytic reaction chambers needed for movement are patterned within the body via a multi-material, embedded 3D printing technique13,14. The fluidic and elastomeric architectures required for function span several orders of magnitude from the microscale to the macroscale. Our integrated design and rapid fabrication approach enables the programmable assembly of multiple materials within this architecture, laying the foundation for completely soft, autonomous robots.
TL;DR: The looming antibiotic-resistance crisis has penetrated the consciousness of clinicians, researchers, policymakers, politicians and the public at large as discussed by the authors, and the evolution and widespread distribution of antibiotic-resistant elements in bacterial pathogens has made diseases that were once easily treatable deadly again.
Abstract: The looming antibiotic-resistance crisis has penetrated the consciousness of clinicians, researchers, policymakers, politicians and the public at large. The evolution and widespread distribution of antibiotic-resistance elements in bacterial pathogens has made diseases that were once easily treatable deadly again. Unfortunately, accompanying the rise in global resistance is a failure in antibacterial drug discovery. Lessons from the history of antibiotic discovery and fresh understanding of antibiotic action and the cell biology of microorganisms have the potential to deliver twenty-first century medicines that are able to control infection in the resistance era.
TL;DR: Powerful mass-spectrometry-based technologies now provide unprecedented insights into the composition, structure, function and control of the proteome, shedding light on complex biological processes and phenotypes.
Abstract: Numerous biological processes are concurrently and coordinately active in every living cell. Each of them encompasses synthetic, catalytic and regulatory functions that are, almost always, carried out by proteins organized further into higher-order structures and networks. For decades, the structures and functions of selected proteins have been studied using biochemical and biophysical methods. However, the properties and behaviour of the proteome as an integrated system have largely remained elusive. Powerful mass-spectrometry-based technologies now provide unprecedented insights into the composition, structure, function and control of the proteome, shedding light on complex biological processes and phenotypes.
TL;DR: A model coupling ice sheet and climate dynamics—including previously underappreciated processes linking atmospheric warming with hydrofracturing of buttressing ice shelves and structural collapse of marine-terminating ice cliffs—is calibrated against Pliocene and Last Interglacial sea-level estimates and applied to future greenhouse gas emission scenarios.
Abstract: Polar temperatures over the last several million years have, at times, been slightly warmer than today, yet global mean sea level has been 6-9 metres higher as recently as the Last Interglacial (130,000 to 115,000 years ago) and possibly higher during the Pliocene epoch (about three million years ago). In both cases the Antarctic ice sheet has been implicated as the primary contributor, hinting at its future vulnerability. Here we use a model coupling ice sheet and climate dynamics-including previously underappreciated processes linking atmospheric warming with hydrofracturing of buttressing ice shelves and structural collapse of marine-terminating ice cliffs-that is calibrated against Pliocene and Last Interglacial sea-level estimates and applied to future greenhouse gas emission scenarios. Antarctica has the potential to contribute more than a metre of sea-level rise by 2100 and more than 15 metres by 2500, if emissions continue unabated. In this case atmospheric warming will soon become the dominant driver of ice loss, but prolonged ocean warming will delay its recovery for thousands of years.
TL;DR: A body of knowledge is accumulating that points to the gut microbiota as a mediator of dietary impact on the host metabolic status and the prospect of therapeutic interventions such as personalized nutrition.
Abstract: It is widely accepted that obesity and associated metabolic diseases, including type 2 diabetes, are intimately linked to diet. However, the gut microbiota has also become a focus for research at the intersection of diet and metabolic health. Mechanisms that link the gut microbiota with obesity are coming to light through a powerful combination of translation-focused animal models and studies in humans. A body of knowledge is accumulating that points to the gut microbiota as a mediator of dietary impact on the host metabolic status. Efforts are focusing on the establishment of causal relationships in people and the prospect of therapeutic interventions such as personalized nutrition.
TL;DR: A machine learning model called a differentiable neural computer (DNC), which consists of a neural network that can read from and write to an external memory matrix, analogous to the random-access memory in a conventional computer.
Abstract: Artificial neural networks are remarkably adept at sensory processing, sequence learning and reinforcement learning, but are limited in their ability to represent variables and data structures and to store data over long timescales, owing to the lack of an external memory. Here we introduce a machine learning model called a differentiable neural computer (DNC), which consists of a neural network that can read from and write to an external memory matrix, analogous to the random-access memory in a conventional computer. Like a conventional computer, it can use its memory to represent and manipulate complex data structures, but, like a neural network, it can learn to do so from data. When trained with supervised learning, we demonstrate that a DNC can successfully answer synthetic questions designed to emulate reasoning and inference problems in natural language. We show that it can learn tasks such as finding the shortest path between specified points and inferring the missing links in randomly generated graphs, and then generalize these tasks to specific graphs such as transport networks and family trees. When trained with reinforcement learning, a DNC can complete a moving blocks puzzle in which changing goals are specified by sequences of symbols. Taken together, our results demonstrate that DNCs have the capacity to solve complex, structured tasks that are inaccessible to neural networks without external read-write memory.