Introduction Concurrent opioid and benzodiazepine use („double-threat”) and double-threat and muscle relaxant use („triple-threat”) are postulated to increase morbidity versus opioids alone. Study objectives were to measure association between double- and triple-threat exposure and hospitalizations in a validated, nationally representative database of the United States. Methods A retrospective cohort study was conducted using the 2013 and 2014 Medical Expenditure Panel Survey (MEPS) longitudinal dataset and affiliated Prescribed Medicines Files. Association between 2013 and 2014 double- and triple-threat exposures and outcome of hospitalizations compared to nonusers, opioid users, and all combinations were assessed via logistic regression. The cohort surveyed in MEPS has been weighted to be reflective of the actual US population in the years 2013 and 2014. Logistic regression applying the subject-level MEPS survey weights was performed to measure association via odds ratios (ORs) of medication exposures with f 5.71 (95% CI 5.69-5.72) in 2013, 11.47 (95% CI 11.44-11.49) in 2014, and 5.59 (95% CI 5.57-5.60) in the longitudinal analysis. Conclusion Concurrent opioid and benzodiazepine use and opioid, benzodiazepine, and muscle relaxant use were associated with increased hospitalization likelihood. Amplified efforts in surveillance, prescribing, monitoring, and deprescribing for concurrent opioid, benzodiazepine, and muscle relaxant use are needed to reduce this public health concern.Striga hermonthica (Del.) Benth parasitism, low soil N, and nutritional deficiencies of normal-endosperm maize (Zea mays L.) threaten maize yield and exacerbate nutritional problems in sub-Sahara Africa (SSA). This study was conducted (a) to evaluate genetic variation among extra-early maturing maize hybrids with provitamin A and quality protein characteristics, (b) to investigate gene action governing the inheritance of Striga resistance, grain yield, low N tolerance, and other measured traits under low-N, high-N, and Striga-infested environments, and (c) to identify hybrids with high yield and stability across environments. One hundred and fifty hybrids developed using North Carolina Design II were evaluated with six checks under low-N, high-N, and Striga-infested environments in Nigeria. Mean squares for hybrids were highly significant (P less then .01) for grain yield and other traits across environments. Only general combining ability (GCA) for female and/or male mean squares were significant for measured traits under low N. In addition to significant GCA effects for most traits, specific combining ability was significant (P less then .05) for Striga emergence count under Striga infestation, and ear height and ears per plant under high N, indicating that additive and nonadditive genetic effects controlled the inheritance of few traits under Striga and high N, whereas additive genetic effect governed the inheritance of the traits under low N. Hybrids TZEEIORQ 55 × TZEEIORQ 26, TZEEIORQ 49 × TZEEIORQ 75, and TZEEIORQ 52 × TZEEIORQ 43 were high yielding and stable across environments and have potential for improving nutrition and maize yields in SSA.The face, just like DNA, is taken to represent a unique individual. This article proposes to move beyond this representational model and to attend to the work that a face can do. I introduce the concept of tentacularity to capture the multiple works accomplished by the face. Drawing on the example of DNA phenotyping, which is used to produce a composite face of an unknown suspect, I first show that this novel technology does not so much produce the face of an individual suspect but that of a suspect population. Second, I demonstrate how the face draws the interest of diverse publics, who with their gaze flesh out its content and contours; the face engages and yields an affective response. I argue that the biologization of appearance by way of the face contributes to the racialization of populations. [race, phenotype, material-semiotics, facial typologies, forensics genetics, DNA phenotyping].Biological cells generate intricate structures by sculpting their membrane from within to actively sense and respond to external stimuli or to explore their environment1-4. Several pathogenic bacteria also provide examples of how localized forces strongly deform cell membranes from inside, leading to the invasion of neighbouring healthy mammalian cells5. Giant unilamellar vesicles have been successfully used as a minimal model system with which to mimic biological cells6-11, but the realization of a minimal system with localized active internal forces that can strongly deform lipid membranes from within and lead to dramatic shape changes remains challenging. Here we present a combined experimental and simulation study that demonstrates how self-propelled particles enclosed in giant unilamellar vesicles can induce a plethora of non-equilibrium shapes and active membrane fluctuations. Using confocal microscopy, in the experiments we explore the membrane response to local forces exerted by self-phoretic Janus microswimmers. To quantify dynamic membrane changes, we perform Langevin dynamics simulations of active Brownian particles enclosed in thin membrane shells modelled by dynamically triangulated surfaces. The most pronounced shape changes are observed at low and moderate particle loadings, with the formation of tether-like protrusions and highly branched, dendritic structures, whereas at high volume fractions globally deformed vesicle shapes are observed. The resulting state diagram predicts the conditions under which local internal forces generate various membrane shapes. A controlled realization of such distorted vesicle morphologies could improve the design of artificial systems such as small-scale soft robots and synthetic cells.Radiation sensors based on the heating effect of absorbed radiation are typically simple to operate and flexible in terms of input frequency, so they are widely used in gas detection1, security2, terahertz imaging3, astrophysical observations4 and medical applications5. Several important applications are currently emerging from quantum technology and especially from electrical circuits that behave quantum mechanically, that is, circuit quantum electrodynamics6. This field has given rise to single-photon microwave detectors7-9 and a quantum computer that is superior to classical supercomputers for certain tasks10. Thermal sensors hold potential for enhancing such devices because they do not add quantum noise and they are smaller, simpler and consume about six orders of magnitude less power than the frequently used travelling-wave parametric amplifiers11. However, despite great progress in the speed12 and noise levels13 of thermal sensors, no bolometer has previously met the threshold for circuit quantum electrodynamics, which lies at a time constant of a few hundred nanoseconds and a simultaneous energy resolution of the order of 10h gigahertz (where h is the Planck constant). Here we experimentally demonstrate a bolometer that operates at this threshold, with a noise-equivalent power of 30 zeptowatts per square-root hertz, comparable to the lowest value reported so far13, at a thermal time constant two orders of magnitude shorter, at 500 nanoseconds. Both of these values are measured directly on the same device, giving an accurate estimation of 30h gigahertz for the calorimetric energy resolution. These improvements stem from the use of a graphene monolayer with extremely low specific heat14 as the active material. The minimum observed time constant of 200 nanoseconds is well below the dephasing times of roughly 100 microseconds reported for superconducting qubits15 and matches the timescales of currently used readout schemes16,17, thus enabling circuit quantum electrodynamics applications for bolometers.Recent years have witnessed increased interest in systems that are capable of supporting multistep chemical processes without the need for manual handling of intermediates. These systems have been based either on collections of batch reactors1 or on flow-chemistry designs2-4, both of which require considerable engineering effort to set up and control. Here we develop an out-of-equilibrium system in which different reaction zones self-organize into a geometry that can dictate the progress of an entire process sequence. Multiple (routinely around 10, and in some cases more than 20) immiscible or pairwise-immiscible liquids of different densities are placed into a rotating container, in which they experience a centrifugal force that dominates over surface tension. As a result, the liquids organize into concentric layers, with thicknesses as low as 150 micrometres and theoretically reaching tens of micrometres. The layers are robust, yet can be internally mixed by accelerating or decelerating the rotation, and each layer can be individually addressed, enabling the addition, sampling or even withdrawal of entire layers during rotation. These features are combined in proof-of-concept experiments that demonstrate, for example, multistep syntheses of small molecules of medicinal interest, simultaneous acid-base extractions, and selective separations from complex mixtures mediated by chemical shuttles. We propose that 'wall-less’ concentric liquid reactors could become a useful addition to the toolbox of process chemistry at small to medium scales and, in a broader context, illustrate the advantages of transplanting material and/or chemical systems from traditional, static settings into a rotating frame of reference.Sensitive microwave detectors are essential in radioastronomy1, dark-matter axion searches2 and superconducting quantum information science3,4. The conventional strategy to obtain higher-sensitivity bolometry is the nanofabrication of ever smaller devices to augment the thermal response5-7. However, it is difficult to obtain efficient photon coupling and to maintain the material properties in a device with a large surface-to-volume ratio owing to surface contamination. Here we present an ultimately thin bolometric sensor based on monolayer graphene. To utilize the minute electronic specific heat and thermal conductivity of graphene, we develop a superconductor-graphene-superconductor Josephson junction8-13 bolometer embedded in a microwave resonator with a resonance frequency of 7.9 gigahertz and over 99 per cent coupling efficiency. The dependence of the Josephson switching current on the operating temperature, charge density, input power and frequency shows a noise-equivalent power of 7 × 10-19 watts per square-root hertz, which corresponds to an energy resolution of a single 32-gigahertz photon14, reaching the fundamental limit imposed by intrinsic thermal fluctuations at 0.19 kelvin. Our results establish that two-dimensional materials could enable the development of bolometers with the highest sensitivity allowed by the laws of thermodynamics.The Greenland Ice Sheet (GIS) is losing mass at a high rate1. Given the short-term nature of the observational record, it is difficult to assess the historical importance of this mass-loss trend. Unlike records of greenhouse gas concentrations and global temperature, in which observations have been merged with palaeoclimate datasets, there are no comparably long records for rates of GIS mass change. Here we reveal unprecedented mass loss from the GIS this century, by placing contemporary and future rates of GIS mass loss within the context of the natural variability over the past 12,000 years. We force a high-resolution ice-sheet model with an ensemble of climate histories constrained by ice-core data2. Our simulation domain covers southwestern Greenland, the mass change of which is dominated by surface mass balance. The results agree favourably with an independent chronology of the history of the GIS margin3,4. The largest pre-industrial rates of mass loss (up to 6,000 billion tonnes per century) occurred in the early Holocene, and were similar to the contemporary (AD 2000-2018) rate of around 6,100 billion tonnes per century5.