دانلود کتاب Nature

فهرست مطالب :

Structures of metabotropic GABAB receptor
Online content
Fig. 1 Cryo-EM map and model of the full-length GABAB receptor heterodimer in inactive state.
Fig. 2 TM3 and TM5 stabilize an inactive-state dimer interface of GABAB 7TM.
Fig. 3 Phospholipid binds within the transmembrane cores of GABAB.
Fig. 4 Inhibitor-bound GABAB1 homodimers adopt a VFT orientation similar to that of active GABAB heterodimer, and a 7TM interface similar to that of active mGlu5.
Extended Data Fig. 1 Sample preparation, cryo-EM processing and reconstruction of GABAB heterodimer.
Extended Data Fig. 2 Agreement between cryo-EM map and model.
Extended Data Fig. 3 Binding of CGP55845 and cation to GABAB1 VFT.
Extended Data Fig. 4 Comparison of structures across GPCR classes.
Extended Data Fig. 5 Atomistic simulations of phospholipid structural stabilization and entry.
Extended Data Fig. 6 Functional analysis of GABAB mutants.
Extended Data Fig. 7 Modelling of phospholipid into GABAB.
Extended Data Fig. 8 Cryo-EM processing workflow of GABAB1b homodimer.
Extended Data Table 1 Cryo-EM data collection, refinement and validation statistics.
s41586-020-2452-0.pdf
Structure of human GABAB receptor in an inactive state
Inactive conformation of GABAB receptor
Inactive transmembrane heterodimer interface
The ‘intersubunit latch’
Endogenous ligands bound to GABAB1b VFT
Discovery of endogenous phospholipid ligands
Comparison of subunits with other GPCRs
Conclusion
Online content
Fig. 1 Cryo-EM structure of human GABAB receptor.
Fig. 2 Transmembrane heterodimer interface of the GABAB receptor.
Fig. 3 Ca2+ binding in GABAB1b.
Fig. 4 Identification of endogenous phospholipid ligands of the GABAB receptor.
Extended Data Fig. 1 Purification and functional analysis of the human GABAB receptor.
Extended Data Fig. 2 Cryo-EM imaging of human GABAB receptor.
Extended Data Fig. 3 Structural model of the GABAB receptor fit within the cryo-EM map.
Extended Data Fig. 4 Architecture of the GABAB receptor.
Extended Data Fig. 5 Heterodimer conformation and interface features of the GABAB receptor.
Extended Data Fig. 6 Extracellular ligand binding in GABAB1b.
Extended Data Fig. 7 Endogenous phospholipid-binding sites of the GABAB receptor.
Extended Data Fig. 8 Endogenous phospholipid interactions with GABAB receptor.
Extended Data Fig. 9 Comparison of the GABAB transmembrane domain with other GPCRs.
Extended Data Fig. 10 Conserved motifs in GABAB, rhodopsin and mGlu receptors.
s41586-020-2408-4.pdf
Structural basis of the activation of a metabotropic GABA receptor
Determining the cryo-EM structure
Overall structure of GABAB heterodimer
Effects of agonist binding
PAM stabilizes the active-state conformation
PAM binding site at the heterodimer interface
Discussion
Online content
Fig. 1 Cryo-EM maps and models of the GABAB heterodimer.
Fig. 2 Structural details of GABAB in the inactive apo state.
Fig. 3 Structure of the active-state GABAB, and details of agonist and PAM binding.
Fig. 4 Activation-related transitions in GABAB.
Extended Data Fig. 1 Expression, characterization and purification of GABAB.
Extended Data Fig. 2 Cryo-EM data processing for SKF97541-bound GABAB.
Extended Data Fig. 3 Cryo-EM map quality.
Extended Data Fig. 4 Cryo-EM data processing for SKF97541- and GS39783-bound GABAB.
Extended Data Fig. 5 Cryo-EM data processing for apo GABAB.
Extended Data Fig. 6 Molecular dynamics simulations of inactive (apo) and active (agonist- and PAM-bound) states.
Extended Data Fig. 7 Comparisons with previous crystal structures and additional details of activation-related transitions in GABAB.
Extended Data Fig. 8 Effects of a PAM on the orthosteric ligand binding in the site-1 and -2 mutants of GABAB.
Extended Data Fig. 9 The effects of a PAM on signalling of the site-1 and -2 mutants of GABAB.
Extended Data Table 1 Cryo-EM data collection, refinement and validation statistics.
Extended Data Table 2 Mutation study of GABAB.
s41586-020-2545-9.pdf
Lysosome-targeting chimaeras for degradation of extracellular proteins
Online content
Fig. 1 LYTACs using CI-M6PR traffic proteins to lysosomes.
Fig. 2 CRISPRi screen identifies key cellular machinery for LYTACs.
Fig. 3 LYTACs target soluble proteins to lysosomes for degradation.
Fig. 4 LYTACs accelerate degradation of membrane proteins.
Extended Data Fig. 1 Synthesis of M6Pn-NCA, poly(mannose-6-phosphate-co-Ala), poly(mannose-co-Ala) and poly(GalNAc-co-Ala).
Extended Data Fig. 2 Biotin-poly(M6Pn) LYTACs direct NA-647 to lysosomes.
Extended Data Fig. 3 EGFR surface levels are unchanged upon EXOC1 and EXOC2 knockdown in HeLa cells.
Extended Data Fig. 4 Ab-1 mediates uptake of soluble proteins to lysosomes.
Extended Data Fig. 5 Optimization of LYTAC-mediated EGFR degradation.
Extended Data Fig. 6 Mixed-cell assay demonstrates that binding specificity is comparable between ctx-M6Pn and ctx.
Extended Data Fig. 7 LYTACs mediate EGFR degradation in multiple cell lines.
Extended Data Fig. 8 Synthesis of anti PD-L1 glycopolypeptide conjugates, PD-L1 degradation, and CD71 degradation depends on M6P binding.
Extended Data Fig. 9 Human IgG in select mouse tissues.
Extended Data Table 1 Selected examples of proteins with differential abundance after treatment of HeLa cells with ctx or Ab-2.
s41586-020-2576-2.pdf
Dichotomous engagement of HDAC3 activity governs inflammatory responses
Online content
Fig. 1 HDAC3 activates LPS-stimulated inflammatory gene expression in a DA-independent manner.
Fig. 2 Differential recruitment and transcriptional functions of HDAC3 at DA-independent and DA-dependent LPS-responsive genes.
Fig. 3 Engagement of HDAC3 enzyme activity is determined by its differential recruitment by ATF2 and ATF3.
Fig. 4 Dichotomous functions of HDAC3 orchestrate the inflammatory response to endotoxin in vivo.
Extended Data Fig. 1 DA-independent and DA-dependent functions of HDAC3 in the inflammatory response to LPS.
Extended Data Fig. 2 Differential recruitment and enhancer activity of HDAC3 at LPS-responsive genes.
Extended Data Fig. 3 ATF2 and ATF3 differentially mediate HDAC3 transcriptional effects at DA-independent and DA-dependent sites, respectively.
Extended Data Fig. 4 ATF2 and ATF3 recruit HDAC3 to sites near DA-independent and DA-dependent genes, respectively.
Extended Data Fig. 5 Loss of HDAC3 protein but not deacetylase activity protects mice from acute endotoxic shock.
Extended Data Fig. 6 Dose-dependent effects of HDAC inhibitor SAHA on endotoxin susceptibility.
s41586-020-2586-0.pdf
Position-specific oxidation of miR-1 encodes cardiac hypertrophy
Oxidation of miRNA in cardiac hypertrophy
Sequencing of o8G in cardiac miRNAs
Oxidized miR-1 silences targets via o8GA
o8G-miR-1 induces cardiac hypertrophy
o8G-miR-1 globally redirects target repression
7o8G-miR-1 in cardiomyopathy and its loss of function
Discussion
Online content
Fig. 1 Redox-dependent cardiac hypertrophy induces miRNA oxidation.
Fig. 2 o8G-miSeq for cardiac miRNAs.
Fig. 3 o8G-miR-1 redirects target repression via o8GA base pairing.
Fig. 4 o8G-miR-1 generates cardiac hypertrophy.
Fig. 5 Transcriptome-wide target repression by o8G-miR-1 in cardiac hypertrophy.
Fig. 6 7o8G-miR-1 is implicated in cardiomyopathy and its loss of function.
Extended Data Fig. 1 Adrenergic cardiac hypertrophy depends on ROS.
Extended Data Fig. 2 Adrenergic cardiac hypertrophy oxidizes miRNAs.
Extended Data Fig. 3 Development of o8G-miSeq to identify oxidized miRNA and o8G position for cardiac hypertrophy.
Extended Data Fig. 4 Oxidized miR-1 silences new target sites via o8GA base pairing.
Extended Data Fig. 5 Oxidized miR-1 elicits hypertrophy of cardiomyocyte through o8GA base pairing.
Extended Data Fig. 6 7o8G-miR-1 induces cardiac hypertrophy in vivo.
Extended Data Fig. 7 Transcriptome-wide analysis of 7o8G-miR-1-delivered mouse hearts.
Extended Data Fig. 8 Transcriptome-wide analysis of o8G-miR-1 transfected H9c2 cells.
Extended Data Fig. 9 Identification of 7o8G-miR-1 targets and their 7oxo sites during adrenergic cardiac hypertrophy and cardiomyopathy.
Extended Data Fig. 10 Specific inhibition of 7o8G-miR-1 by competitive inhibitors, anti-7oxo.
Extended Data Fig. 11 Loss-of-function study of 7o8G-miR-1 in vivo by establishing an anti-7oxo transgenic mouse.
s41586-020-2564-6.pdf
Mucosal or systemic microbiota exposures shape the B cell repertoire
Distinct repertoires depend on exposure site
Priming thresholds differ by exposure route
Exposure route affects B cell targeting
Exposure context shapes IgA or IgG diversity
Oral sensitization of systemic responses
Functional effects of sequential exposures
Online content
Fig. 1 Antibody repertoires in mucosal and systemic tissues after transitory oral or systemic exposure to a commensal microorganism.
Fig. 2 Differences between B cell repertoires after systemic or mucosal exposure.
Fig. 3 Antimicrobial antibody responses after combined mucosal and systemic exposure or exposure to two different microbial taxa.
Extended Data Fig. 1 Mucosal and systemic exposure differentially shape the repertoires of the various immunoglobulin isotypes.
Extended Data Fig. 2 Comparison of computational correction method with UMIs for PCR artefacts and sequencing reproducibility on different occasions.
Extended Data Fig. 3 Threshold differences for shaping systemic or mucosal B cell repertoires and induction of antibody responses.
Extended Data Fig. 4 Differences in processing of microbial antigens, and presentation in the mucosal and systemic compartments.
Extended Data Fig. 5 Network formation of different isotypes depending on transitory microbial treatment, and comparison with strong cholera toxin immunogen.
Extended Data Fig. 6 Characteristics of naive B cell repertoires following systemic or mucosal exposure and sites of B cell activation.
Extended Data Fig. 7 CD4 T cells are required for systemic immune memory following intestinal exposure to reversible E.
Extended Data Fig. 8 Experimental schemes.
Extended Data Table 1 Comparison of B cell receptor CDR3 sequences assessed in this study with previously reported data.
s41586-020-2555-7.pdf
Mechanisms of stretch-mediated skin expansion at single-cell resolution
Hydrogel induces mouse skin expansion
Stretching promotes stem cell renewal
Molecular features related to stretch
scRNA-seq during stretching
Mechanosensing at adherens junctions
MEK–ERK–AP1 regulate expansion
YAP and MAL regulate skin stretching
scRNA-seq after MEK and MAL inhibition
Discussion
Online content
Fig. 1 Inflated hydrogel mediates skin expansion.
Fig. 2 Clonal analysis of epidermal stem cells during stretch-mediated skin expansion.
Fig. 3 Transcriptional and chromatin remodelling associated with stretch-mediated skin expansion.
Fig. 4 Molecular regulation of stretch-mediated skin expansion.
Extended Data Fig. 1 A mouse model of mechanical stretch-mediated skin expansion.
Extended Data Fig. 2 Adhesion remodelling and inflammatory response during stretch-mediated skin expansion.
Extended Data Fig. 3 Clonal analysis of epidermal stem cells during homeostasis, TPA treatment and stretch-mediated skin expansion.
Extended Data Fig. 4 Fit of the data to the two-progenitor model.
Extended Data Fig. 5 Genetic signature of TPA-treated and expanded epidermis.
Extended Data Fig. 6 Single-cell RNA sequencing clustering analysis.
Extended Data Fig. 7 Single-cell RNA sequencing clustering analysis on the IFE cells.
Extended Data Fig. 8 Pseudotime analysis for single-cell RNA sequencing.
Extended Data Fig. 9 Cell contractility in stretch-mediated tissue expansion.
Extended Data Fig. 10 MEK/ERK/AP1, YAP-TAZ and MAL/SRF regulate stretch-mediated proliferation.
Extended Data Fig. 11 Pathways associated with stretch-mediated tissue expansion.
Extended Data Fig. 12 Single-cell data analysis after MEK and MAL inhibition.
s41586-020-2404-8.pdf
The effect of large-scale anti-contagion policies on the COVID-19 pandemic
Online content
Fig. 1 Data on COVID-19 infections and large-scale anti-contagion policies.
Fig. 2 Empirical estimates of unmitigated COVID-19 infection growth rates and the effect of anti-contagion policies.
Fig. 3 Estimated infection growth rates based on actual anti-contagion policies and in a no-policy counterfactual scenario.
Fig. 4 Estimated cumulative confirmed COVID-19 infections with and without anti-contagion policies.
Extended Data Fig. 1 Validating disaggregated epidemiological data against aggregated data from the JHU Center for Systems Science and Engineering.
Extended Data Fig. 2 Estimated trends in case detection over time within each country.
Extended Data Fig. 3 Robustness of the estimated no-policy growth rate of infections and the combined effect of policies to withholding blocks of data from entire regions.
Extended Data Fig. 4 Robustness of the estimated effects of individual policies to withholding blocks of data from entire regions.
Extended Data Fig. 5 Evidence to support models in which policies affect infection growth rates in the days following deployment.
Extended Data Fig. 6 Estimated infection or hospitalization growth rates with actual anti-contagion policies and in a no-policy counterfactual scenario.
Extended Data Fig. 7 Sensitivity of estimated averted/delayed infections to the choice of γ and σ in an SIR/SEIR framework.
Extended Data Fig. 8 Simulating reduced-form estimates for the no-policy growth rate of infections for different population regimes and disease dynamics.
Extended Data Fig. 9 Simulating reduced-form estimates for anti-contagion policy effects for different population regimes and assumed disease dynamics.
Extended Data Fig. 10 Regression residuals for the growth rates of COVID-19 by country.
s41586-020-2405-7.pdf
Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe
Estimated infections, Rt and effect sizes
Estimated effect of interventions on deaths
Discussion
Online content
Fig. 1 Country-level estimates of infections, deaths and Rt for France, Italy, Spain and the UK.
Fig. 2 Effectiveness of interventions on Rt.
Extended Data Fig. 1 Country-level estimates of infections, deaths and Rt for Belgium, Germany, Sweden and Switzerland.
Extended Data Fig. 2 Country-level estimates of infections, deaths and Rt for Austria, Norway and Denmark.
Extended Data Fig. 3 Model summary.
Extended Data Fig. 4 Timings of interventions.
Extended Data Fig. 5 Deaths averted owing to interventions.
Table 1 Total population infected by country.
Extended Data Table 1 Total forecasted deaths since the beginning of the epidemic up to 4 May 2020 in our model and in a counterfactual model that assumes no interventions had taken place.
s41586-020-2563-7.pdf
Rescue of oxytocin response and social behaviour in a mouse model of autism
Online content
Fig. 1 Oxytocin response is altered in VTA DA neurons lacking Nlgn3.
Fig. 2 Disruption of translational regulation in the VTA of Nlgn3KO mice.
Fig. 3 The novel MNK1/2 inhibitor ETC-168 rescues translation in Nlgn3KO VTA.
Fig. 4 MNK inhibition restores social novelty responses in Nlgn3KO mice.
Extended Data Fig. 1 Loss of social recognition in Nlgn3KO mice.
Extended Data Fig. 2 Properties of NAc-projecting VTA DA neurons in wild-type and Nlgn3KO mice.
Extended Data Fig. 3 Oxytocinergic innervation to VTA and Avpr1a mRNA levels are not affected in Nlgn3KO mice.
Extended Data Fig. 4 Ribosomal proteins and translation processes are altered in Nlgn3KO mice.
Extended Data Fig. 5 Pharmacological profile of novel MNK1/2 inhibitor ETC-168.
Extended Data Fig. 6 ETC-168 treatment restores cognitive rigidity in Fmr1KO mice.
Extended Data Fig. 7 Effect of ETC-168 treatment on protein abundance in wild-type and Nlgn3KO mice.
Extended Data Fig. 8 Effect of short-term ETC-168 treatment on social recognition in wild-type and Nlgn3KO mice.
Extended Data Fig. 9 Effect of ETC-168 treatment is dependent on the oxytocin receptor.
Extended Data Fig. 10 Effect of long-term ETC-168 treatment on behaviour in wild-type and Nlgn3KO mice.
s41586-020-2559-3.pdf
Index and biological spectrum of human DNase I hypersensitive sites
Index of consensus human DHSs
Common coordinates for regulatory DNA
Proportion of the genome that encodes DHSs
Cellular patterning of DNA accessibility
A vocabulary for regulatory patterns
Biological annotation of individual DHSs
Dense encoding of regulatory information
Regulatory annotation of human genes
Annotating genes with unknown functions
Connecting DHS actuation to specific TFs
Annotating genetic association signals
Genetic signals span gene body DHSs
Discussion
Online content
Fig. 1 Index of DHSs in the human genome.
Fig. 2 A simple vocabulary captures complex patterning of DHSs.
Fig. 3 Regulatory annotation of human genes.
Fig. 4 DHS components illuminate genetic associations and heritability.
Extended Data Fig. 1 Construction of a DHS index.
Extended Data Fig. 2 Genomic context of DHS index elements.
Extended Data Fig. 3 NMF decomposition of DHS index.
Extended Data Fig. 4 Association of DHS components with cellular conditions and TF motifs.
Extended Data Fig. 5 DHS component robustness.
Extended Data Fig. 6 Clustering of same-component DHSs near genes.
Extended Data Fig. 7 Top labelled genes for selected components.
Extended Data Fig. 8 Annotation of genes with unknown function and pathways.
Extended Data Fig. 9 GWAS trait associations of DHS components.
Extended Data Fig. 10 Extendability of the DHS annotation framework.
s41586-020-2531-2.pdf
Ecosystem decay exacerbates biodiversity loss with habitat loss
Passive sampling versus ecosystem decay
Testing the hypotheses
Variation in the effects
Effects on species composition
Discussion
Online content
Fig. 1 Conceptual illustration of the hypotheses and data structure.
Fig. 2 Ecosystem decay drives patterns of biodiversity loss in habitat fragments.
Fig. 3 Study-level variation in the response of species richness to habitat loss.
Fig. 4 Relationship between the species-richness response and the species compositional turnover and nestedness.
Extended Data Fig. 1 Simulations of the null expectation under the random sampling hypothesis for varying degrees of within-species aggregation.
Extended Data Fig. 2 Different measures of species richness related to the size of habitat fragments.
Extended Data Fig. 3 Incorporation of uncertainty by calculating z-scores of observed versus null-expected outcomes.
Extended Data Fig. 4 Testing of robustness of results to alternative methods.
Extended Data Fig. 5 Study-level variation in the number of individuals and evenness.
Extended Data Fig. 6 Study-level slope estimates with latitude.
Extended Data Fig. 7 Relationship between size of habitat fragment and species composition.
Extended Data Fig. 8 Endemics–area relationships.
Extended Data Table 1 Models of standardized species richness (Sstd).
Extended Data Table 2 Models of the standardized number of individuals (Nstd).
Extended Data Table 3 Models of standardized evenness (SPIE).
s41586-020-2566-4.pdf
Soil carbon loss by experimental warming in a tropical forest
Online content
Fig. 1 Soil temperature and moisture content in control and warmed plots by depth.
Fig. 2 Soil CO2 efflux from control and warmed soils over two years.
Fig. 3 The annual carbon emission partitioned into soil-derived and root-derived components.
Extended Data Fig. 1 Thermal images of a warmed plot.
Extended Data Fig. 2 Soil moisture content and temperature in control and warmed plots.
Extended Data Fig. 3 Relationship between soil CO2 efflux, soil moisture and season, in control and warmed plots.
Extended Data Fig. 4 Contribution of root-derived and soil-derived sources to total CO2 efflux.
Extended Data Fig. 5 Average response of soil properties to warming.
Extended Data Table 1 Soil properties.
Extended Data Table 2 The determinants of soil CO2 efflux variation.
Extended Data Table 3 Treatment effects on root and soil components of CO2 efflux.
Extended Data Table 4 Determinants of soil moisture variation.
s41586-020-2573-5.pdf
Heat and carbon coupling reveals ocean warming due to circulation changes
Heat and carbon storage in GFDL ESM2M
Global heat–carbon coupling
Past and future heat redistribution
Discussion
Online content
Fig. 1 Simulated anthropogenic changes in Cant and H.
Fig. 2 Heat–carbon coupling.
Fig. 3 Error in the redistributed ocean heat storage from ESM2M.
Fig. 4 Redistribution of ocean heat storage in the upper 2,000 m.
Extended Data Fig. 1 Physical changes in ESM2M experiments.
Extended Data Fig. 2 The heat–carbon coupling parameter, α.
Extended Data Fig. 3 ESM2M zonal-mean ocean redistributed warming.
Extended Data Fig. 4 1951–2011 zonal-mean ocean redistributed warming.
Extended Data Fig. 5 CMIP5 ocean redistributed heat.
Extended Data Fig. 6 Latitudinal profiles of ocean carbon and CFCs.
Extended Data Fig. 7 Latitudinal changes.
Extended Data Fig. 8 Fixed-climate Cant.
Extended Data Fig. 9 MITgcm ocean circulation.
Extended Data Fig. 10 MITgcm simulated anthropogenic tracer changes.
s41586-020-2573-5.pdf
Heat and carbon coupling reveals ocean warming due to circulation changes
Heat and carbon storage in GFDL ESM2M
Global heat–carbon coupling
Past and future heat redistribution
Discussion
Online content
Fig. 1 Simulated anthropogenic changes in Cant and H.
Fig. 2 Heat–carbon coupling.
Fig. 3 Error in the redistributed ocean heat storage from ESM2M.
Fig. 4 Redistribution of ocean heat storage in the upper 2,000 m.
Extended Data Fig. 1 Physical changes in ESM2M experiments.
Extended Data Fig. 2 The heat–carbon coupling parameter, α.
Extended Data Fig. 3 ESM2M zonal-mean ocean redistributed warming.
Extended Data Fig. 4 1951–2011 zonal-mean ocean redistributed warming.
Extended Data Fig. 5 CMIP5 ocean redistributed heat.
Extended Data Fig. 6 Latitudinal profiles of ocean carbon and CFCs.
Extended Data Fig. 7 Latitudinal changes.
Extended Data Fig. 8 Fixed-climate Cant.
Extended Data Fig. 9 MITgcm ocean circulation.
Extended Data Fig. 10 MITgcm simulated anthropogenic tracer changes.
s41586-020-2565-5.pdf
Coupling dinitrogen and hydrocarbons through aryl migration
Online content
Fig. 1 Strategy for converting benzene and N2 into silylated aniline without the use of carbon electrophiles.
Fig. 2 Activation of benzene.
Fig. 3 Binding and functionalization of N2.
Fig. 4 Proposed cyclic reaction mechanism for the conversion of N2 and benzene to aniline, mediated by iron β-diketiminate complexes.
Fig. 5 Aniline products from amination of arenes with N2.
s41586-020-2567-3.pdf
Evidence of flat bands and correlated states in buckled graphene superlattices
Online content
Fig. 1 Buckled structures in graphene membranes.
Fig. 2 Pseudo-Landau level quantization and sublattice polarization in buckled graphene.
Fig. 3 Simulated LDOS in buckled graphene.
Fig. 4 Flat bands and LDOS maps.
Fig. 5 Flat bands in buckled G/hBN.
Extended Data Fig. 1 Buckling pattern of graphene.
Extended Data Fig. 2 Topography of unbuckled regions in the G/NbSe2 sample.
Extended Data Fig. 3 Topography of buckled regions in the G/NbSe2 sample.
Extended Data Fig. 4 Transition area in the triangular buckling pattern of the G/NbSe2 sample.
Extended Data Fig. 5 Evolution of the calculated LDOS with PMF amplitude for several superlattice periods.
Extended Data Fig. 6 Calculated PMF in the crest areas of the buckled G/NbSe2 sample.
Extended Data Fig. 7 Calculated low-energy band structure and LDOS in the trough regions of the buckled G/NbSe2 sample.
Extended Data Fig. 8 Tight-binding model for a strained lattice.
Extended Data Fig. 9 PMF for a rectangular buckling pattern in graphene.
Extended Data Fig. 10 DOS versus unit cell size in the presence of lattice disorder.
s41586-020-2568-2.pdf
Electronic phase separation in multilayer rhombohedral graphite
Online content
Fig. 1 Transport characteristics of thin RG films.
Fig. 2 Thickness dependence of the transport characteristics of multilayer RG.
Fig. 3 Quantum Hall effect in RG.
Fig. 4 Hysteretic behaviour of the insulating state in multilayer RG.
Extended Data Fig. 1 Effect of stacking sequence on the displacement-field-induced bandgap.
Extended Data Fig. 2 Band structures of multilayer RG with stacking faults.
Extended Data Fig. 3 The quantum Hall effect in thin RG.
Extended Data Fig. 4 Landau levels from surface states of multilayer RG.
Extended Data Fig. 5 Single-gate (D ≠ 0) Landau fan diagrams highlighting the robust ν = −N quantum Hall state in N-layer-thick RG.
Extended Data Fig. 6 Insulating states and hysteretic behaviour in multilayer RG.
Extended Data Fig. 7 Stacking order of device 6 at different fabrication stages.
Extended Data Fig. 8 Temperature dependence of resistivity.
Extended Data Fig. 9 Bandgap opening by displacement field.
s41586-020-2587-z.pdf
Stabilization and operation of a Kerr-cat qubit
Online content
Fig. 1 Qubit encoding, stabilization and implementation.
Fig. 2 Rabi oscillations of the protected KCQ.
Fig. 3 KCQ gate process tomography.
Fig. 4 Cat-quadrature readout (CR) and coherence times.
s41586-020-2572-6.pdf
A dynamically cold disk galaxy in the early Universe
Online content
Fig. 1 [C ii] emission from the lensed galaxy SPT0418-47 and source plane reconstruction.
Fig. 2 Kinematic and dynamical properties of SPT0418-47.
Fig. 3 Comparison between SPT0418-47 and samples of observed and simulated galaxies.
Fig. 4 Comparison between SPT0418-47 and samples of its plausible descendants.
Extended Data Fig. 1 Reconstruction of the [C ii] emission and kinematic model.
Extended Data Fig. 2 Corner plot showing the posterior distributions of the lens and kinematic parameters.
Extended Data Fig. 3 Corner plot showing the posterior distributions of the dynamical parameters.
Extended Data Table 1 Lens and source kinematic parameters.
Extended Data Table 2 Kinematic properties for SPT0418-47 derived under different assumptions.
Extended Data Table 3 Kinematic measurements for the comparison samples.
Extended Data Table 4 Assumptions for the dynamical fit.
Extended Data Table 5 Physical quantities for SPT0418-47 derived from the kinematic and dynamical modelling.
s41586-020-2510-7.pdf
Heat detection by the TRPM2 ion channel
Acknowledgements
Fig. 1 A fraction of thermally activated somatosensory neurons does not express TRPV1, TRPM3 or TRPA1.
Fig. 2 Pharmacological block of TRPM2 inhibits the heat response of heat-sensitive neurons not expressing TRPV1, TRPM3 or TRPA1.
Extended Data Fig. 1 Changing the source of neurons, the order of application of agonists and the heat stimulus, the culture conditions, the rise time of heat application and the starting temperature do not significantly affect the proportions of heat-sen
Extended Data Fig. 2 Effect of TRPM2 blocker 2-APB on heat responses in neurons expressing only one of TRPA1, TRPV1 or TPRPM3.
Extended Data Fig. 3 A fraction of TRPA1+ neurons from Trpm2−/− mice responds to heat when TRPV1 and TRPM3 are blocked.
2511.pdf
Reply to: Heat detection by the TRPM2 ion channel
Methods
Reporting summary
Acknowledgements
Fig. 1 TRPV1- and TRPM3-independent responses to a 45 °C heat stimulus are not inhibited by the TRPM2 antagonist 2-APB.
Fig. 2 High-threshold 2-APB-sensitive heat responses in TKO sensory neurons.
s41586-020-2542-z.pdf
Author Correction: Structural insights into μ-opioid receptor activation
s41586-020-2583-3.pdf
Author Correction: Reversing a model of Parkinson’s disease with in situ converted nigral neurons
s41586-020-2581-5.pdf
Author Correction: The evolutionary history of lethal metastatic prostate cancer
s41586-020-2580-6.pdf
Author Correction: The dental proteome of Homo antecessor