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Finite-element models are used to identify a material geometry that achieves the theoretical bounds on isotropic elastic stiffness—a combination closed-cell cubic and octet foam. Know your limits Lattice-like arrangements of trusses are a well-known way of achieving lightweight structures with high stiffness and strength. They are just one example of a broader family of materials—sometimes termed mechanical metamaterials—in which structural geometry is harnessed to achieve enhanced combinations of properties. Yet theory predicts limits on these properties that have yet to be attained. Jonathan Berger and colleagues use a combination of theoretical and optimization techniques to identify a material geometry that reaches the theoretical limits for isotropic elastic stiffness. Such a structure should be achievable, for example, by harnessing recent advances in 3D printing. A wide variety of high-performance applications 1 require materials for which shape control is maintained under substantial stress, and that have minimal density. Bio-inspired hexagonal and square honeycomb structures and lattice materials based on repeating unit cells composed of webs or trusses 2 , when made from materials of high elastic stiffness and low density 3 , represent some of the lightest, stiffest and strongest materials available today 4 . Recent advances in 3D printing and automated assembly have enabled such complicated material geometries to be fabricated at low (and declining) cost. These mechanical metamaterials have properties that are a function of their mesoscale geometry as well as their constituents 3 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , leading to combinations of properties that are unobtainable in solid materials; however, a material geometry that achieves the theoretical upper bounds for isotropic elasticity and strain energy storage (the Hashin–Shtrikman upper bounds) has yet to be identified. Here we evaluate the manner in which strain energy distributes under load in a representative selection of material geometries, to identify the morphological features associated with high elastic performance. Using finite-element models, supported by analytical methods, and a heuristic optimization scheme, we identify a material geometry that achieves the Hashin–Shtrikman upper bounds on isotropic elastic stiffness. Previous work has focused on truss networks and anisotropic honeycombs, neither of which can achieve this theoretical limit 13 . We find that stiff but well distributed networks of plates are required to transfer loads efficiently between neighbouring members. The resulting low-density mechanical metamaterials have many advantageous properties: their mesoscale geometry can facilitate large crushing strains with high energy absorption 2 , 14 , 15 , optical bandgaps 16 , 17 , 18 , 19 and mechanically tunable acoustic bandgaps 20 , high thermal insulation 21 , buoyancy, and fluid storage and transport. Our relatively simple design can be manufactured using origami-like sheet folding 22 and bonding methods.

The activation of certain pattern-recognition receptors by pathogen-associated molecular patterns results in the formation of inflammasome complexes. Inflammasome complexes can initiate both the maturation of inflammatory cytokines and pyroptotic cell death via the caspase-mediated cleavage of gasdermin D (GSDMD). As of now, the only known regulators of GSDMD in macrophages are caspase-1 and caspase-11. Orning et al. report an additional pathway controlling GSDMD processing. YopJ, an effector molecule produced by Yersinia (the causative agent of plague), inhibits TAK1–IκB kinase signaling. This, in turn, results in caspase-8–directed cleavage of GSDMD, pyroptosis, and the release of interleukin 1β (IL-1β) and IL-18. Thus, in the arms race between host and pathogen, the host recognizes signaling disturbances as pathogenic and counters with inflammation and cell death. Science , this issue p. 1064 Bacterial blockade of key host signaling pathways triggers pyroptosis and inflammation. Limited proteolysis of gasdermin D (GSDMD) generates an N-terminal pore-forming fragment that controls pyroptosis in macrophages. GSDMD is processed via inflammasome-activated caspase-1 or -11. It is currently unknown whether macrophage GSDMD can be processed by other mechanisms. Here, we describe an additional pathway controlling GSDMD processing. The inhibition of TAK1 or IκB kinase (IKK) by the Yersinia effector protein YopJ elicits RIPK1- and caspase-8–dependent cleavage of GSDMD, which subsequently results in cell death. GSDMD processing also contributes to the NLRP3 inflammasome–dependent release of interleukin-1β (IL-1β). Thus, caspase-8 acts as a regulator of GSDMD-driven cell death. Furthermore, this study establishes the importance of TAK1 and IKK activity in the control of GSDMD cleavage and cytotoxicity.

Though beam-based lattices have dominated mechanical metamaterials for the past two decades, low structural efficiency limits their performance to fractions of the Hashin-Shtrikman and Suquet upper bounds, i.e. the theoretical stiffness and strength limits of any isotropic cellular topology, respectively. While plate-based designs are predicted to reach the upper bounds, experimental verification has remained elusive due to significant manufacturing challenges. Here, we present a new class of nanolattices, constructed from closed-cell plate-architectures. Carbon plate-nanolattices are fabricated via two-photon lithography and pyrolysis and shown to reach the Hashin-Shtrikman and Suquet upper bounds, via in situ mechanical compression, nano-computed tomography and micro-Raman spectroscopy. Demonstrating specific strengths surpassing those of bulk diamond and average performance improvements up to 639% over the best beam-nanolattices, this study provides detailed experimental evidence of plate architectures as a superior mechanical metamaterial topology. Plate-lattices are predicted to reach the upper bounds of strength and stiffness compared to traditional beam-lattices, but they are difficult to manufacture. Here, the authors use two-photon polymerization 3D-printing and pyrolysis to make carbon plate-nanolattices which reach those theoretical bounds, making them up to 639% stronger than beam-nanolattices.

Objectives. To estimate the proportion of US adults who identify as transgender and to compare the demographics of the transgender and nontransgender populations. Methods. We conducted a secondary analysis of data from states and territories in the 2014 Behavioral Risk Factor Surveillance System that asked about transgender status. The proportion of adults identified as transgender was calculated from affirmative and negative responses (n = 151 456). We analyzed data with a design-adjusted χ 2 test. We also explored differences between male-to-female and nontransgender females and female-to-male and nontransgender males. Results. Transgender individuals made up 0.53% (95% confidence interval = 0.46, 0.61) of the population and were more likely to be non-White (40.0% vs 27.3%) and below the poverty line (26.0% vs 15.5%); as likely to be married (50.5% vs 47.7%), living in a rural area (28.7% vs 22.6%), and employed (54.3% vs 57.7%); and less likely to attend college (35.6% vs 56.6%) compared with nontransgender individuals. Conclusions. Our findings suggest that the transgender population is a racially diverse population present across US communities. Inequalities in the education and socioeconomic status have negative implications for the health of the transgender population.

Transiently storing information and mentally manipulating it is known as working memory. These operations are implemented by a distributed, fronto-parietal cognitive control network in the brain. The neural mechanisms controlling interactions within this network are yet to be determined. Here, we show that during a working memory task the brain uses an oscillatory mechanism for regulating access to prefrontal cognitive resources, dynamically controlling interactions between prefrontal cortex and remote neocortical areas. Combining EEG with non-invasive brain stimulation we show that fast rhythmical brain activity at posterior sites are nested into prefrontal slow brain waves. Depending on cognitive demand this high frequency activity is nested into different phases of the slow wave enabling dynamic coupling or de-coupling of the fronto-parietal control network adjusted to cognitive effort. This mechanism constitutes a basic principle of coordinating higher cognitive functions in the human brain. Working memory involves a fronto-parietal brain network, but how the parts of this network are coordinated is unclear. Here, the authors show that fast brain activity at posterior sites is nested into prefrontal slow brain waves, with cognitive demand determining the slow wave phase involved.

The 100 years since the publication of Albert Einstein’s theory of general relativity saw significant development of the understanding of the theory, the identification of potential astrophysical sources of sufficiently strong gravitational waves and development of key technologies for gravitational-wave detectors. In 2015, the first gravitational-wave signals were detected by the two US Advanced LIGO instruments. In 2017, Advanced LIGO and the European Advanced Virgo detectors pinpointed a binary neutron star coalescence that was also seen across the electromagnetic spectrum. The field of gravitational-wave astronomy is just starting, and this Roadmap of future developments surveys the potential for growth in bandwidth and sensitivity of future gravitational-wave detectors, and discusses the science results anticipated to come from upcoming instruments.In the past few years, gravitational-wave observations provided stunning insights into some of the most cataclysmic events in the Universe, heralding a bright future for gravitational-wave physics and astronomy. This is a Roadmap for the field in the coming two decades.

The use of high-throughput phenotyping systems and non-destructive imaging is widely regarded as a key technology allowing scientists and breeders to develop crops with the ability to perform well under diverse environmental conditions. However, many of these phenotyping studies have been optimized using the model plant Arabidopsis thaliana. In this study, The Plant Accelerator® at The University of Adelaide, Australia, was used to investigate the growth and phenotypic response of the important cereal crop, Sorghum bicolor L. Moench and related hybrids to water-limited conditions and different levels of fertilizer. Imaging in different spectral ranges was used to monitor plant composition, chlorophyll, and moisture content. Phenotypic image analysis accurately measured plant biomass. The data set obtained enabled the responses of the different sorghum varieties to the experimental treatments to be differentiated and modelled. Plant architectural instead of architecture elements were determined using imaging and found to correlate with an improved tolerance to stress, for example diurnal leaf curling and leaf area index. Analysis of colour images revealed that leaf ‘greenness’ correlated with foliar nitrogen and chlorophyll, while near infrared reflectance (NIR) analysis was a good predictor of water content and leaf thickness, and correlated with plant moisture content. It is shown that imaging sorghum using a high-throughput system can accurately identify and differentiate between growth and specific phenotypic traits. R scripts for robust, parsimonious models are provided to allow other users of phenomic imaging systems to extract useful data readily, and thus relieve a bottleneck in phenotypic screening of multiple genotypes of key crop plants.

Drought is a complex stress which elicits a wide variety of plant responses. As such, genetic studies of drought are particularly difficult. Elucidation of the genetic basis of components contributing to drought tolerance is likely to be more tractable than that of overall drought tolerance. Certain of the traits which contribute to drought tolerance in plants and the high-throughput phenotyping techniques available to measure those traits are described in this paper. On the basis of the dynamic nature of drought, plant development, and the resulting stress response, the focus is on non-destructive imaging techniques which allow a temporal resolution and monitoring of the same plants throughout the experiment. Information on the physiological changes in response to drought over time is vital in order to identify and characterize different drought-tolerance mechanisms. High-throughput imaging provides a valuable new tool which allows the dissection of plant responses to drought into a series of component traits.

Cancer-related fatigue (CRF) is common among breast cancer (BC) survivors. In addition to aerobic training, psychoeducation, sleep education/restriction, and mindfulness-based therapies are shown to reduce CRF. This study investigates the predictive effect of hygiogenetic and salutogenetic concepts, such as autonomic regulation (aR), self-regulation (SRS) and internal coherence (ICS) along with sleep quality (PSQI) and quality of life (EORTC QLQ C30, including cognitive, emotional and physical functioning) on the success of CRF therapies. Two studies are analyzed: a pilot (CRF-1) with 36 BC patients and a follow-up study (CRF2) with 126 patients either randomized or assigned to therapy by preference. All parameters were assessed at baseline and 10 weeks post-intervention (T1), and in CRF-2 also six months later (T2), and after four years (T3). Multiple linear regression models were applied. Trait aR and ICS are shown to be significant predictors of CRF when all timepoints of the CRF-2 study are included (β Trait aR = −0.170, df = 70, p  < 0.001; β ICS = −0.210, df = 70, p  < 0.01) as well as when combined with data of the CRF-1 study (β Trait aR = −0.144, df = 101, p  = 0.001; β ICS = −0.211, df = 101, p  < 0.01). Cognitive Function showed a borderline significance only at T3 and when all CRF-2 study time measurements were combined (β CF = −0.073, df = 70, p  < 0.05). Using data from two studies with multimodal, aerobic and combined CRF treatments, this study highlights Trait aR and ICS at baseline as long-term predictors of CRF even four years after intervention. A stable autonomic regulation including rest/activity regulation and internal coherence are predictors for therapy response of a multimodal, combination or aerobic treatment in breast cancer survivors with CRF.

Treatment options are limited for the approximately 40% of postmenopausal women worldwide who suffer from female sexual dysfunction (FSD). Neural stimulation has shown potential as a treatment for genital arousal FSD, however the mechanisms for its improvement are unknown. One potential cause of some cases of genital arousal FSD are changes to the composition of the vaginal microbiota, which is associated with vulvovaginal atrophy. The primary hypothesis of this study was that neural stimulation may induce healthy changes in the vaginal microbiome, thereby improving genital arousal FSD symptoms. In this study we used healthy rats, which are a common animal model for sexual function, however the rat vaginal microbiome is understudied. Thus this study also sought to examine the composition of the rat vaginal microbiota. Treatment rats (n = 5) received 30 minutes of cutaneous electrical stimulation targeting the genital branch of the pudendal nerve, and Control animals (n = 4) had 30-minute sessions without stimulation. Vaginal lavage samples were taken during a 14-day baseline period including multiple estrous periods and after twice-weekly 30-minute sessions across a six-week trial period. Analysis of 16S rRNA gene sequences was used to characterize the rat vaginal microbiota in baseline samples and determine the effect of stimulation. We found that the rat vaginal microbiota is dominated by Proteobacteria, Firmicutes, and Actinobacteria, which changed in relative abundance during the estrous cycle and in relationship to each other. While the overall stimulation effects were unclear in these healthy rats, some Treatment animals had less alteration in microbiota composition between sequential samples than Control animals, suggesting that stimulation may help stabilize the vaginal microbiome. Future studies may consider additional physiological parameters, in addition to the microbiome composition, to further examine vaginal health and the effects of stimulation.