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There is a need for large-scale, longitudinal studies to determine the mechanisms by which the gut microbiome and its interactions with the host affect human health and disease. Current methods for profiling the microbiome typically utilize next-generation sequencing applications that are expensive, slow, and complex. Here, we present a synthetic biology platform for affordable, on-demand, and simple analysis of microbiome samples using RNA toehold switch sensors in paper-based, cell-free reactions. We demonstrate species-specific detection of mRNAs from 10 different bacteria that affect human health and four clinically relevant host biomarkers. We develop a method to quantify mRNA using our toehold sensors and validate our platform on clinical stool samples by comparison to RT-qPCR. We further highlight the potential clinical utility of the platform by showing that it can be used to rapidly and inexpensively detect toxin mRNA in the diagnosis of Clostridium difficile infections., National Institutes of Health (U.S.) (Grant T32-DK007191)

Culture contamination, end-product toxicity, and energy efficient product recovery are long-standing bioprocess challenges. To solve these problems, we propose a high-pressure fermentation strategy, coupled with in situ extraction using the abundant and renewable solvent supercritical carbon dioxide (scCO2), which is also known for its broad microbial lethality. Towards this goal, we report the domestication and engineering of a scCO2-tolerant strain of Bacillus megaterium, previously isolated from formation waters from the McElmo Dome CO2 field, to produce branched alcohols that have potential use as biofuels. After establishing induced-expression under scCO2, isobutanol production from 2-ketoisovalerate is observed with greater than 40% yield with co-produced isopentanol. Finally, we present a process model to compare the energy required for our process to other in situ extraction methods, such as gas stripping, finding scCO2 extraction to be potentially competitive, if not superior., End-product toxicity, culture contamination, and energy efficient product recovery are long-standing issues in bioprocessing. Here, the authors address these problems using a fermentation strategy that combines microbial production of branched alcohols with supercritical carbon dioxide extraction.

The temperature scales of screening of local magnetic and orbital moments are important characteristics of strongly correlated substances. In a recent paper X. Deng et al. using dynamic mean-field theory (DMFT) have identified temperature scales of the onset of screening in orbital and spin channels in some correlated metals from the deviation of temperature dependence of local susceptibility from the Curie law. We argue that the scales obtained this way are in fact much larger, than the corresponding Kondo temperatures, and, therefore, do not characterize the screening process. By reanalyzing the results of this paper we find the characteristic (Kondo) temperatures for screening in the spin channel $T_K\approx 100$ K for V$_2$O$_3$ and $T_K\approx 350$ K for Sr$_2$RuO$_4$, which are almost an order of magnitude smaller than those for the onset of the screening estimated in the paper ($1000$ K and $2300$ K, respectively); for V$_2$O$_3$ the obtained temperature scale $T_K$ is therefore comparable to the temperature of completion of the screening, $T^{\rm comp}\sim 25$ K, which shows that the screening in this material can be described in terms of a single temperature scale., This is a post-peer-review, pre-copyedit version of an article published in Matters Arising section of Nature Communications. The final authenticated version is available online at http://dx.doi.org/10.1038/s41467-021-21641-2

Author(s): Cao, Wei; Banerjee, Kaustav | Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Author(s): Daya, Michelle; Rafaels, Nicholas; Brunetti, Tonya M; Chavan, Sameer; Levin, Albert M; Shetty, Aniket; Gignoux, Christopher R; Boorgula, Meher Preethi; Wojcik, Genevieve; Campbell, Monica; Vergara, Candelaria; Torgerson, Dara G; Ortega, Victor E; Doumatey, Ayo; Johnston, Henry Richard; Acevedo, Nathalie; Araujo, Maria Ilma; Avila, Pedro C; Belbin, Gillian; Bleecker, Eugene; Bustamante, Carlos; Caraballo, Luis; Cruz, Alvaro; Dunston, Georgia M; Eng, Celeste; Faruque, Mezbah U; Ferguson, Trevor S; Figueiredo, Camila; Ford, Jean G; Gan, Weiniu; Gourraud, Pierre-Antoine; Hansel, Nadia N; Hernandez, Ryan D; Herrera-Paz, Edwin Francisco; Jimenez, Silvia; Kenny, Eimear E; Knight-Madden, Jennifer; Kumar, Rajesh; Lange, Leslie A; Lange, Ethan M; Lizee, Antoine; Maul, Pissamai; Maul, Trevor; Mayorga, Alvaro; Meyers, Deborah; Nicolae, Dan L; O'Connor, Timothy D; Oliveira, Ricardo Riccio; Olopade, Christopher O; Olopade, Olufunmilayo; Qin, Zhaohui S; Rotimi, Charles; Vince, Nicolas; Watson, Harold; Wilks, Rainford J; Wilson, James G; Salzberg, Steven; Ober, Carole; Burchard, Esteban G; Williams, L Keoki; Beaty, Terri H; Taub, Margaret A; Ruczinski, Ingo; Mathias, Rasika A; Barnes, Kathleen C; CAAPA | Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Inspired by the social and economic benefits of diversity, we analyze over 9 million papers and 6 million scientists to study the relationship between research impact and five classes of diversity: ethnicity, discipline, gender, affiliation, and academic age. Using randomized baseline models, we establish the presence of homophily in ethnicity, gender and affiliation. We then study the effect of diversity on scientific impact, as reflected in citations. Remarkably, of the classes considered, ethnic diversity had the strongest correlation with scientific impact. To further isolate the effects of ethnic diversity, we used randomized baseline models and again found a clear link between diversity and impact. To further support these findings, we use coarsened exact matching to compare the scientific impact of ethnically diverse papers and scientists with closely-matched control groups. Here, we find that ethnic diversity resulted in an impact gain of 10.63% for papers, and 47.67% for scientists., Diversity is believed to raise effectiveness and performance but it contains many aspects. Here the authors studied the relationship between research impact and five classes of diversity and found that ethnic diversity had the strongest correlation with scientific impact.

Complex dynamical fluctuations, from intracellular noise, brain dynamics or computer traffic display bursting dynamics consistent with a critical state between order and disorder. Living close to the critical point has adaptive advantages and it has been conjectured that evolution could select these critical states. Is this the case of living cells? A system can poise itself close to the critical point by means of the so-called self-organized criticality (SOC). In this paper we present an engineered gene network displaying SOC behaviour. This is achieved by exploiting the saturation of the proteolytic degradation machinery in E. coli cells by means of a negative feedback loop that reduces congestion. Our critical motif is built from a two-gene circuit, where SOC can be successfully implemented. The potential implications for both cellular dynamics and behaviour are discussed., This work was supported by the Botin Foundation by Banco Santander through its Santander Universities Global Division, the Spanish Ministry of Economy and Competitiveness, grant AEI-PID2019-111680GB-I00/AEI/10.13039/501100011033, an AGAUR FI 2018 grant, and the Santa Fe Institute (where the key idea was conceived). J.S. and A.G. have been partially funded by the CERCA Programme of the Generalitat de Catalunya. J.S. acknowledges support from Agencia Estatal de Investigación grant RTI2018-098322-B-I00 and Ramón y Cajal contract RYC-2017-22243. A.G. has been funded by the AGAUR grant 2017-SGR-1049 and by the MINECO-FEDER-UE grants PGC-2018-098676-B-100 and RTI2018-093860-B-C21.

Neuronal activity in sensory cortex fluctuates over time and across repetitions of the same input. This variability is often considered detrimental to neural coding. The theory of neural sampling proposes instead that variability encodes the uncertainty of perceptual inferences. In primary visual cortex (V1), modulation of variability by sensory and non-sensory factors supports this view. However, it is unknown whether V1 variability reflects the statistical structure of visual inputs, as would be required for inferences correctly tuned to the statistics of the natural environment. Here we combine analysis of image statistics and recordings in macaque V1 to show that probabilistic inference tuned to natural image statistics explains the widely observed dependence between spike count variance and mean, and the modulation of V1 activity and variability by spatial context in images. Our results show that the properties of a basic aspect of cortical responses—their variability—can be explained by a probabilistic representation tuned to naturalistic inputs., The neural sampling theory suggests that neuronal variability encodes the uncertainty of probabilistic inferences. This paper shows that response variability in primary visual cortex reflects the statistical structure of visual inputs, as required for inferences correctly tuned to the statistics of the natural environment.

Author(s): Coignard, Juliette; Lush, Michael; Beesley, Jonathan; O'Mara, Tracy A; Dennis, Joe; Tyrer, Jonathan P; Barnes, Daniel R; McGuffog, Lesley; Leslie, Goska; Bolla, Manjeet K; Adank, Muriel A; Agata, Simona; Ahearn, Thomas; Aittomaki, Kristiina; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Arnold, Norbert; Aronson, Kristan J; Arun, Banu K; Augustinsson, Annelie; Azzollini, Jacopo; Barrowdale, Daniel; Baynes, Caroline; Becher, Heko; Bermisheva, Marina; Bernstein, Leslie; Bialkowska, Katarzyna; Blomqvist, Carl; Bojesen, Stig E; Bonanni, Bernardo; Borg, Ake; Brauch, Hiltrud; Brenner, Hermann; Burwinkel, Barbara; Buys, Saundra S; Caldes, Trinidad; Caligo, Maria A; Campa, Daniele; Carter, Brian D; Castelao, Jose E; Chang-Claude, Jenny; Chanock, Stephen J; Chung, Wendy K; Claes, Kathleen BM; Clarke, Christine L; GEMO Study Collaborators; EMBRACE Collaborators; Collee, J Margriet; Conroy, Don M; Czene, Kamila; Daly, Mary B; Devilee, Peter; Diez, Orland; Ding, Yuan Chun; Domchek, Susan M; Dork, Thilo; Dos-Santos-Silva, Isabel; Dunning, Alison M; Dwek, Miriam; Eccles, Diana M; Eliassen, A Heather; Engel, Christoph; Eriksson, Mikael; Evans, D Gareth; Fasching, Peter A; Flyger, Henrik; Fostira, Florentia; Friedman, Eitan; Fritschi, Lin; Frost, Debra; Gago-Dominguez, Manuela; Gapstur, Susan M; Garber, Judy; Garcia-Barberan, Vanesa; Garcia-Closas, Montserrat; Garcia-Saenz, Jose A; Gaudet, Mia M; Gayther, Simon A; Gehrig, Andrea; Georgoulias, Vassilios; Giles, Graham G; Godwin, Andrew K; Goldberg, Mark S; Goldgar, David E | Abstract: A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-23162-4.

We study mentorship in scientific collaborations, where a junior scientist is supported by potentially multiple senior collaborators, without them necessarily having formal supervisory roles. We identify 3 million mentor–protege pairs and survey a random sample, verifying that their relationship involved some form of mentorship. We find that mentorship quality predicts the scientific impact of the papers written by proteges post mentorship without their mentors. We also find that increasing the proportion of female mentors is associated not only with a reduction in post-mentorship impact of female proteges, but also a reduction in the gain of female mentors. While current diversity policies encourage same-gender mentorships to retain women in academia, our findings raise the possibility that opposite-gender mentorship may actually increase the impact of women who pursue a scientific career. These findings add a new perspective to the policy debate on how to best elevate the status of women in science. Here, the authors study mentorship in scientific collaborations, and find that mentorship quality predicts the scientific impact of proteges post mentorship. Moreover, female proteges collaborating with male mentors become more impactful post mentorship than those who collaborate with female mentors.

The self-organization of strongly interacting electrons into superlattice structures underlies the properties of many quantum materials. How these electrons arrange within the superlattice dictates what symmetries are broken and what ground states are stabilized. Here we show that cryogenic scanning transmission electron microscopy (cryo-STEM) enables direct mapping of local symmetries and order at the intra-unit-cell level in the model charge-ordered system Nd1/2Sr1/2MnO3. In addition to imaging the prototypical site-centered charge order, we discover the nanoscale coexistence of an exotic intermediate state which mixes site and bond order and breaks inversion symmetry. We further show that nonlinear coupling of distinct lattice modes controls the selection between competing ground states. The results demonstrate the importance of lattice coupling for understanding and manipulating the character of electronic self-organization and that cryo-STEM can reveal local order in strongly correlated systems at the atomic scale., In this paper, the authors demonstrate that cryogenic scanning transmission electron microscopy allows for the direct mapping of the local arrangements and symmetries of electronic order, providing a useful method for studying strongly correlated systems. They show this using the example of Nd1/2Sr1/2MnO3, a model charge ordered material.

The α-type ADP-ribosylated peptides represent a class of important molecular tools in the field of protein ADP-ribosylation, however, they are difficult to access because of their inherent complicated structures and the lack of effective synthetic tools. In this paper, we present a biomimetic α-selective ribosylation reaction to synthesize a key intermediate, α-ADP-ribosyl azide, directly from native β-nicotinamide adenine dinucleotide in a clean ionic liquid system. This reaction in tandem with click chemistry then offers a two-step modular synthesis of α-ADP-ribosylated peptides. These syntheses can be performed open air in eppendorf tubes, without the need for specialized instruments or training. Importantly, we demonstrate that the synthesized α-ADP-ribosylated peptides show high binding affinity and desirable stability for enriching protein partners, and reactivity in post-stage poly ADP-ribosylations. Owing to their simple chemistry and multidimensional bio-applications, the presented methods may provide a powerful platform to produce general molecular tools for the study of protein ADP-ribosylation., ADP-ribosylated peptides are important molecular tools, however, the lack of effective synthetic methods hinders the access to their complex structures. Here, the authors present a biomimetic α-selective ribosylation reaction coupled with click chemistry ultimately providing a two-step modular synthesis of α-ADP-ribosylated peptides.

Electrical pumping of organic semiconductor devices involves charge injection, transport, device on/off dynamics, exciton formation and annihilation processes. A comprehensive model analysing those entwined processes together is most helpful in determining the dominating loss pathways. In this paper, we report experimental and theoretical results of Super Yellow (Poly(p-phenylene vinylene) co-polymer) organic light emitting diodes operating at high current density under high voltage nanosecond pulses. We demonstrate complete exciton and charge carrier dynamics of devices, starting from charge injection to light emission, in a time scale spanning from the sub-ns to microsecond region, and compare results with optical pumping. The experimental data is accurately replicated by simulation, which provides a robust test platform for any organic materials. The universality of our model is successfully demonstrated by its application to three other laser active materials. The findings provide a tool to narrow the search for material and device designs for injection lasing., Though efforts toward electrically-pumped lasers based on simple organic light-emitting diode (OLED) structures have been reported, a comprehensive model is needed to elucidate key optoelectronic processes. Here, the authors report a model describing OLED operation under high current densities.

Power laws are omnipresent and actively studied in many scientific fields, including plasticity of materials. Here, we report the power-law statistics in the second and subsequent pop-in magnitudes during load-controlled nanoindentation testing, whereas the first pop-in is characterized by Gaussian-like statistics with a well-defined average value. The transition from Gaussian-like to power-law is due to the change in the deformation mechanism from dislocation nucleation to dislocation network evolution in the sharp-indenter induced abruptly decaying stress and dislocation density fields. Based on nanoindentation testing on the (100) and (111) surfaces of body-centered cubic (BCC) iron and the (100) surface of face-centered cubic (FCC) copper, the scaling exponents of the power laws were determined to be 5.6, 3.9, and 6.4, respectively. These power-law exponents are much higher than those typically observed in micro-pillar plasticity (1.0–1.8), suggesting that the nanoindentation plasticity belongs to a different universality class than the micro-pillar plasticity., Although power laws are observed during nanoindentation and the power-law exponents are estimated to be approximately 1.5-1.6 for face-centered cubic metals, the origin of the exponent remains unclear. In this paper, we show the power-law statistics in pop-in magnitudes and unveil the nature of the exponent.

Graphene oxide (GO) sheets have been used as a model system to study how the mechanical properties of two-dimensional building blocks scale to their bulk form, such as paper-like, lamellar-structured thin films. Here, we report that the modulus of multilayer GO films can be significantly enhanced if some of the sheets are drastically weakened by introducing in-plane porosity. Nanometer-sized pores are introduced in GO sheets by chemical etching. Membrane-deflection measurements at the single-layer level show that the sheets are drastically weakened as the in-plane porosity increases. However, the mechanical properties of the corresponding multilayer films are much less sensitive to porosity. Surprisingly, the co-assembly of pristine and etched GO sheets yields even stiffer films than those made from pristine sheets alone. This is attributed to the more compliant nature of the soft porous sheets, which act as a binder to improve interlayer packing and load transfer in the multilayer films., Graphene oxide sheets have been used as a model system to study how the mechanical properties of individual 2D building blocks scale to their bulk form. Here the authors show that the modulus of multilayer graphene oxide films can be enhanced if some of the sheets are weakened by introducing in-plane porosity.

The development of new catalysts for oxidation reactions is of central importance for many industrial processes. Plasmonic catalysis involves photoexcitation of templates/chips to drive and enhance oxidation of target molecules. Raman-based sensing of target molecules can also be enhanced by these templates. This provides motivation for the rational design, characterization, and experimental demonstration of effective template nanostructures. In this paper, we report on a template comprising silver nanoparticles on aligned peptide nanotubes, contacted with a microfabricated chip in a dry environment. Efficient plasmonic catalysis for oxidation of molecules such as p-aminothiophenol results from facile trans-template charge transfer, activated and controlled by application of an electric field. Raman detection of biomolecules such as glucose and nucleobases are also dramatically enhanced by the template. A reduced quantum mechanical model is formulated, comprising a minimum description of key components. Calculated nanotube-metal-molecule charge transfer is used to understand the catalytic mechanism and shows this system is well-optimized., Plasmonic nanomaterials offer new frontiers as photocatalysis and sensor materials, yet elucidating factors controlling each is a challenge. Here, authors examine the role of electric fields in photocatalysis and biomolecule sensing abilities of peptide-nanotubesupported silver nanoparticles.

This paper reports our experimental studies on the underlying mechanism responsible for electroluminescence spectral narrowing phenomenon in the cavity-based organic light-emitting diodes. It is found that the microcavity generates an emerging phenomenon: a magneto-photoluminescence signal in Poly(9,9-dioctylfluorene-alt-benzothiadiazole) polymer under photoexcitation, which is completely absent when microcavity is not used. This provides an evidence that microcavity leads to the formation of spatially extended states, functioning as the intermediate states prior to the formation of Frenkel excitons in organic materials. This is confirmed by the magneto-electroluminescence solely observed from the cavity-based light-emitting diodes under electrical injection. Furthermore, the narrowed electroluminescence output shows a linear polarization, concurrently occurred with magneto-electroluminescence. This indicates that the spatially extended sates become aligned towards forming coherent light-emitting excitons within the microcavity through optical resonance. Clearly, the spatially extended states present the necessary condition to realize electroluminescence spectral narrowing phenomenon towards lasing actions in cavity-based organic light-emitting diodes., Realizing electrically-pumped lasing actions in microcavity organic light-emitting diodes requires elucidating the origin of spectrally-narrowed electroluminescence amplification. Here, the authors show that the microcavity induces spatially extended states with polaron-pair like characteristics.

Awareness of the human health impacts of exposure to air pollution is growing rapidly. For example, it has become evident that the adverse health effects of air pollution are more pronounced in disadvantaged populations. Policymakers in many jurisdictions have responded to this evidence by enacting initiatives that lead to lower concentrations of air pollutants, such as urban traffic restrictions. In this review, we focus on the interplay between advances in environmental exposure assessment and developments in policy. We highlight recent progress in the granular measurement of air pollutants and individual-level exposures, and how this has enabled focused local policy actions. Finally, we detail an illustrative study designed to link individual-level health-relevant exposures with economic, behavioral, biological, familial, and environmental variables., How can scientists and policymakers work together to reduce the health impacts of air pollution? In this review paper, the authors discuss the interplay between advances in environmental exposure assessment and policy advances to tackle pollution in a focused way.

The original version of this article incorrectly listed the present address of Bo Wu as ‘Present address: Institute of Electronic Paper Displays, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, Guangdong Province 510006, China’. This is the author’s primary affiliation. This has been corrected in both the PDF and HTML versions of the article.

Long-read sequencing technologies have greatly facilitated assemblies of large eukaryotic genomes. In this paper, Oxford Nanopore sequences generated on a MinION sequencer are combined with Bionano Genomics Direct Label and Stain (DLS) optical maps to generate a chromosome-scale de novo assembly of the repeat-rich Sorghum bicolor Tx430 genome. The final assembly consists of 29 scaffolds, encompassing in most cases entire chromosome arms. It has a scaffold N50 of 33.28 Mbps and covers 90% of the expected genome length. A sequence accuracy of 99.85% is obtained after aligning the assembly against Illumina Tx430 data and 99.6% of the 34,211 public gene models align to the assembly. Comparisons of Tx430 and BTx623 DLS maps against the public BTx623 v3.0.1 genome assembly suggest substantial discrepancies whose origin remains to be determined. In summary, this study demonstrates that informative assemblies of complex plant genomes can be generated by combining nanopore sequencing with DLS optical maps., Assembly of large, repeat-rich eukaryotic genomes remains challenging. Here, the authors use BioNano Genomics DLS optical mapping and single-molecule nanopore sequencing to generate a chromosome-scale assembly of a new Sorghum bicolor accession and identify variation compared to the publicly available S. bicolor genome.

Dissecting cellular differentiation hierarchies in the mammary gland is a prerequisite for understanding both normal development and malignant transformation during tumorigenesis and tumor cell-of-origin. To achieve these goals, several recent papers utilized single cell RNA-seq and lineage tracing to improve our understanding of the composition of the mammary epithelium at different developmental stages.

The discovery of peptide substrates for enzymes with exclusive, selective activities is a central goal in chemical biology. In this paper, we develop a hybrid computational and biochemical method to rapidly optimize peptides for specific, orthogonal biochemical functions. The method is an iterative machine learning process by which experimental data is deposited into a mathematical algorithm that selects potential peptide substrates to be tested experimentally. Once tested, the algorithm uses the experimental data to refine future selections. This process is repeated until a suitable set of de novo peptide substrates are discovered. We employed this technology to discover orthogonal peptide substrates for 4’-phosphopantetheinyl transferase, an enzyme class that covalently modifies proteins. In this manner, we have demonstrated that machine learning can be leveraged to guide peptide optimization for specific biochemical functions not immediately accessible by biological screening techniques, such as phage display and random mutagenesis., The discovery of peptide substrates for enzymes with selective activities is a central goal in chemical biology. Here, the authors develop a hybrid method combining machine learning and experimental testing for fast optimization of peptides for specific, orthogononal functions.

Correction to: Nature Communications https://doi.org/10.1038/s41467-017-01045-x, published online 31 October 2017 It has come to our attention that we did not specify whether the stimulation magnitudes we report in this Article are peak amplitudes or peak-to-peak. All references to intensity given in mA in the manuscript refer to peak-to-peak amplitudes, except in Fig. 2, where the model is calibrated to 1 mA peak amplitude, as stated. In the original version of the paper we incorrectly calibrated the computational models to 1 mA peak-to-peak, rather than 1 mA peak amplitude. This means that we divided by a value twice as large as we should have. The correct estimated fields are therefore twice as large as shown in the original Fig. 2 and Supplementary Fig. 11. The corrected figures are now properly calibrated to 1mA peak amplitude. Furthermore, the sentence in the first paragraph of the Results section ‘Intensity ranged from 0.5 to 2.5 mA (current density 0.125–0.625 mA mA/cm2), which is stronger than in previous reports’, should have read ‘Intensity ranged from 0.5 to 2.5 mA peak to peak (peak current density 0.0625–0.3125 mA/cm2), which is stronger than in previous reports.’ These errors do not affect any of the Article’s conclusions. Correct versions of Fig. 2 and Supplementary Fig. 11 are presented below as Figs. 1, 2.

Several recent papers report spectacular, and unexpected, order of magnitude improvement in creep life of alloys upon adding small amounts of elements like zinc. This microalloying effect raises fundamental questions regarding creep deformation mechanisms. Here, using atomic-scale characterization and first principles calculations, we attribute the 600% increase in creep life in a prototypical Mg–rare earth (RE)–Zn alloy to multiple mechanisms caused by RE–Zn bonding—stabilization of a large volume fraction of strengthening precipitates on slip planes, increase in vacancy diffusion barrier, reduction in activated cross-slip, and enhancement of covalent character and bond strength around Zn solutes along the c-axis of Mg. We report that increased vacancy diffusion barrier, which correlates with the observed 25% increase in interplanar bond stiffness, primarily enhances the high-temperature creep life. Thus, we demonstrate that an approach of local, randomized tailoring of bond stiffness via microalloying enhances creep performance of alloys., Adding very small amounts of zinc to magnesium alloys containing rare earth elements dramatically improves their creep life. Here, the authors use first principles calculations and atomic-scale characterization to show that this is due to stiff covalent bonding of zinc and rare earth elements such as neodymium.

Nature Communications 8: Article number: 15840 (2017); Published 15 June 2017; Updated 29 November 2017 In this Article, two papers are mistakenly listed as having made use of the antibody 14C8 instead of the antibody PPG5/10. In the Discussion section, ref. 45 is incorrectly cited as having shown that the antibody 14C8 works well, and in Fig.

Nature Communications 7: Article number: 11520 10.1038/ncomms11520 (2016); Published: May92016; Updated: June072016 The HTML version of this Correspondence was previously published with an incomplete title and incorrect Article number. This has now been corrected in the HTML; the PDF version of the paper was correct from the time of publication.

Biological market theory is potentially useful for understanding helping behaviour in animal societies. It predicts that competition for trading partners will affect the value of commodities exchanged. It has gained empirical support in cooperative breeders, where subordinates help dominant breeders in exchange for group membership, but so far without considering one crucial aspect: outside options. We find support for a biological market in paper wasps, Polistes dominula. We first show that females have a choice of cooperative partners. Second, by manipulating entire subpopulations in the field, we increase the supply of outside options for subordinates, freeing up suitable nesting spots and providing additional nesting partners. We predicted that by intensifying competition for help, our manipulation would force dominants to accept a lower price for group membership. As expected, subordinates reduce their foraging effort following our treatments. We conclude that to accurately predict the amount of help provided, social units cannot be viewed in isolation: the surrounding market must also be considered. In cooperatively breeding species, subordinates help to raise the dominant breeders’ offspring in return for benefits associated with group membership. Here, Grinsted and Field show that the amount of help provided by subordinate paper wasps depends on the availability of alternative nesting options, as predicted by biological market theory.

γ-Secretase generates the peptides of Alzheimer's disease, Aβ40 and Aβ42, by cleaving the amyloid precursor protein within its transmembrane domain. γ-Secretase also cleaves numerous other substrates, raising concerns about γ-secretase inhibitor off-target effects. Another important class of drugs, γ-secretase modulators, alter the cleavage site of γ-secretase on amyloid precursor protein, changing the Aβ42/Aβ40 ratio, and are thus a promising therapeutic approach for Alzheimer's disease. However, the target for γ-secretase modulators is uncertain, with some data suggesting that they function on γ-secretase, whereas others support their binding to the amyloid precursor. In this paper we address this controversy by using a fluorescence resonance energy transfer-based assay to examine whether γ-secretase modulators alter Presenilin-1/γ-secretase conformation in intact cells in the absence of its natural substrates such as amyloid precursor protein and Notch. We report that the γ-secretase allosteric site is located within the γ-secretase complex, but substrate docking is needed for γ-secretase modulators to access this site., γ-Secretase modulators have promise in the treatment of Alzheimer's disease, but their molecular target is uncertain. Here, fluorescence resonance energy transfer is used to determine that the γ-secretase allosteric site is within the γ-secretase complex and that substrate docking is required for modulators to access the site.

Limbs develop using a common genetic programme despite widely differing morphologies. This programme is modulated by limb-restricted regulators such as hindlimb (HL) transcription factors Pitx1 and Tbx4 and the forelimb (FL) Tbx5. Both Tbx factors have been implicated in limb patterning and growth, but their relative activities and underlying mechanisms remain unclear. In this paper, we show that Tbx4 and Tbx5 harbour conserved and divergent transcriptional regulatory domains that account for their roles in limb development. In particular, both factors share an activator domain and the ability to stimulate limb growth. However, we find that Tbx4 is the primary effector of HL identity for both skeletal and muscle development; this activity relies on a repressor domain that is inactivated by a human TBX4 small-patella syndrome mutation. We propose that limb identity is largely achieved by default in FL, whereas a specific repressor activity unique to Tbx4 determines HL identity., The embryonic development of forelimbs and hindlimbs is regulated by transcription factors, including Pitx1, Tbx4 and Tbx5. In this study, the contributions of Tbx4 and Tbx5 to limb identity are further delineated, resulting in the demonstration of a role for Tbx4 in hindlimb skeletal and muscle patterning.

The genome of the microsporidia Encephalitozoon cuniculi is widely recognized as a model for extreme reduction and compaction. At only 2.9 Mbp, the genome encodes approximately 2,000 densely packed genes and little else. However, the nuclear genome of its sister, Encephalitozoon intestinalis, is even more reduced; at 2.3 Mbp, it represents a 20% reduction from an already severely compacted genome, raising the question, what else can be lost? In this paper, we describe the complete sequence of the E. intestinalis genome and its comparison with that of E. cuniculi. The two species share a conserved gene content, order and density over most of their genomes. The exceptions are the subtelomeric regions, where E. intestinalis chromosomes are missing large gene blocks of sequence found in E. cuniculi. In the remaining gene-dense chromosome 'cores', the diminutive intergenic sequences and introns are actually more highly conserved than the genes themselves, suggesting that they have reached the limits of reduction for a fully functional genome., A comparison of related genomes provides valuable information about how they evolve. Here, the complete sequence of the smallest known nuclear genome from the microsporidia E. intestinalis is described and compared with its larger sister E. cuniculi, revealing what parts are indispensable in even the most reduced genomes.

Biodiversity is of crucial importance for ecosystem functioning, sustainability and resilience, but the magnitude and organization of marine diversity at a range of spatial and taxonomic scales are undefined. In this paper, we use second-generation sequencing to unmask putatively diverse marine metazoan biodiversity in a Scottish temperate benthic ecosystem. We show that remarkable differences in diversity occurred at microgeographical scales and refute currently accepted ecological and taxonomic paradigms of meiofaunal identity, rank abundance and concomitant understanding of trophic dynamics. Richness estimates from the current benchmarked Operational Clustering of Taxonomic Units from Parallel UltraSequencing analyses are broadly aligned with those derived from morphological assessments. However, the slope of taxon rarefaction curves for many phyla remains incomplete, suggesting that the true alpha diversity is likely to exceed current perceptions. The approaches provide a rapid, objective and cost-effective taxonomic framework for exploring links between ecosystem structure and function of all hitherto intractable, but ecologically important, communities., Recent developments in sequencing technologies have provided the opportunity to investigate the biodiversity of ecosystems. Such a metagenomic approach, combined with taxon clustering, is used here to demonstrate that the species richness of a marine community in Scotland is much greater than anticipated.

Probing the local transport properties of two-dimensional electron systems (2DES) confined at buried interfaces requires a non-invasive technique with a high spatial resolution operating in a broad temperature range. In this paper, we investigate the scattering-type scanning near field optical microscopy as a tool for studying the conducting LaAlO3/SrTiO3 interface from room temperature down to 6 K. We show that the near-field optical signal, in particular its phase component, is highly sensitive to the transport properties of the electron system present at the interface. Our modeling reveals that such sensitivity originates from the interaction of the AFM tip with coupled plasmon–phonon modes with a small penetration depth. The model allows us to quantitatively correlate changes in the optical signal with the variation of the 2DES transport properties induced by cooling and by electrostatic gating. To probe the spatial resolution of the technique, we image conducting nano-channels written in insulating heterostructures with a voltage-biased tip of an atomic force microscope.