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The use of antibiotics to treat bacterial infections often imposes strong selection for antibiotic resistance. However, the prevalence of antibiotic resistance varies greatly across different combinations of pathogens and drugs. What underlies this variation? Systematic reviews, meta-analyses, and literature surveys capable of integrating data across many studies have tried to answer this question, but the vast majority of these studies have focused only on cases where resistance is common or problematic. Yet much could presumably be learned from the cases where resistance is infrequent or absent. Here we conducted a literature survey and a systematic review to study the evolution of antibiotic resistance across a wide range of pathogen-by-drug combinations (57 pathogens and 53 antibiotics from 15 drug classes). Using Akaike information criterion-based model selection and model-averaged parameter estimation we explored 14 different factors posited to be associated with resistance evolution. We find that the most robust predictors of high resistance are nosocomial transmission (i.e., hospital-acquired pathogens) and indirect transmission (e.g., vector-, water-, air-, or vehicle-borne pathogens). While the former was to be expected based on prior studies, the positive correlation between high resistance frequencies and indirect transmission is, to our knowledge, a novel insight. The most robust predictor of low resistance is zoonosis from wild animal reservoirs. We also found partial support that resistance was associated with pathogen type, horizontal gene transfer, commensalism, and human-to-human transmission. We did not find support for correlations between resistance and environmental reservoirs, mechanisms of drug action, and global drug use. This work explores the relative explanatory power of various pathogen and drug factors on resistance evolution, which is necessary to identify priority targets of stewardship efforts to slow the spread of drug-resistant pathogens.

 

The contrasting internal luminosity of Uranus and Neptune present a challenge to our understanding of the origin and evolution of these bodies, as well as extra-solar ice giants. The thermal evolution of Neptune is known to be nearly consistent with an entirely fluid interior, but this is not a unique solution, and does not account for the tidal dissipation required by the migration of its moons. We examine a model that has been previously shown to explain the thermal and tidal evolution of Uranus: one that features a growing, frozen core. The core traps heat in the interior, affecting the cooling time scale, and provides a source of tidal dissipation. We review the growing, frozen core model, and the computation of thermal and tidal evolution. We then apply this model to Neptune. We find that the growing frozen core model can account for the observed internal luminosity of Neptune and the migration of its moons, in the form of resonances that were either encountered or avoided in the past. We discuss prospects for observational tests of the growing frozen core model and possible implications for understanding the gas giants.

 

Computing excited-state properties of molecules and solids is considered one of the most important near-term applications of quantum computers. While many of the current excited-state quantum algorithms differ in circuit architecture, specific exploitation of quantum advantage, or result quality, one common feature is their rooting in the Schrödinger equation. However, through contracting (or projecting) the eigenvalue equation, more efficient strategies can be designed for near-term quantum devices. Here we demonstrate that when combined with the Rayleigh–Ritz variational principle for mixed quantum states, the ground-state contracted quantum eigensolver (CQE) can be generalized to compute any number of quantum eigenstates simultaneously. We introduce twoexcited-state(anti-Hermitian) CQEs that perform the excited-state calculation while inheriting many of the remarkable features of the original ground-state version of the algorithm, such as its scalability. To showcase our approach, we study several model and chemical Hamiltonians and investigate the performance of different implementations.

 

When particle dark matter is bound gravitationally around a massive black hole in sufficiently high densities, the dark matter will affect the rate of inspiral of a secondary compact object that forms a binary with the massive black hole. In this paper, we revisit previous estimates of the impact of dark-matter accretion by black-hole secondaries on the emitted gravitational waves. We identify a region of parameter space of binaries for which estimates of the accretion were too large (specifically, because the dark-matter distribution was assumed to be unchanging throughout the process, and the secondary black hole accreted more mass in dark matter than that enclosed within the orbit of the secondary). To restore consistency in these scenarios, we propose and implement a method to remove dark-matter particles from the distribution function when they are accreted by the secondary. This new feedback procedure then satisfies mass conservation, and when evolved with physically reasonable initial data, the mass accreted by the secondary no longer exceeds the mass enclosed within its orbital radius. Comparing the simulations with accretion feedback to those without this feedback, including feedback leads to a smaller gravitational-wave dephasing from binaries in which only the effects of dynamical friction are being modeled. Nevertheless, the dephasing can be hundreds to almost a thousand gravitational-wave cycles, an amount that should allow the effects of accretion to be inferred from gravitational-wave measurements of these systems. 

The suffix array is a crucial data structure for efficient string analysis. Over the course of twenty-six years, sequential suffix array construction algorithms have achieved O(n) time complexity and in-place sorting. In this paper, we present the Tunnel algorithm, the first large-scale parallel suffix array construction algorithm with a time complexity of O(n/p) based on the parallel random access machine (PRAM) model. The Tunnel algorithm is built on three key ideas: dividing the problem of size O(n) into p sub-problems of reduced size O(n/p) by replacing long suffixes with shorter prefixes of size at most a constant D ; introducing a Tunnel mechanism to efficiently induce the order of a set of suffixes with long common prefixes; developing a strategy to transform a partially ordered suffix set into a total order relation by iteratively applying the Tunnel inducing method. We provide a detailed description of the algorithm, along with a thorough analysis of its time and space complexity, to demonstrate its correctness and efficiency. The proposed Tunnel algorithm exhibits scalable performance, making it suitable for large string analytics on large-scale parallel systems. 

In many oceanic regions, anthropogenic warming will coincide with iron (Fe) limitation. Interactive effects between warming and Fe limitation on phytoplankton physiology and biochemical function are likely, as temperature and Fe availability affect many of the same essential cellular pathways. However, we lack a clear understanding of how globally significant phytoplankton such as the picocyanobacteriaSynechococcuswill respond to these co-occurring stressors, and what underlying molecular mechanisms will drive this response. Moreover, ecotype-specific adaptations can lead to nuanced differences in responses between strains. In this study,Synechococcusisolates YX04-1 (oceanic) and XM-24 (coastal) from the South China Sea were acclimated to Fe limitation at two temperatures, and their physiological and proteomic responses were compared. Both strains exhibited reduced growth due to warming and Fe limitation. However, coastal XM-24 maintained relatively higher growth rates in response to warming under replete Fe, while its growth was notably more compromised under Fe limitation at both temperatures compared with YX04-1. In response to concurrent heat and Fe stress, oceanic YX04-1 was better able to adjust its photosynthetic proteins and minimize the generation of reactive oxygen species while reducing proteome Fe demand. Its intricate proteomic response likely enabled oceanic YX04-1 to mitigate some of the negative impact of warming on its growth during Fe limitation. Our study highlights how ecologically-shaped adaptations inSynechococcusstrains even from proximate oceanic regions can lead to differing physiological and proteomic responses to these climate stressors.

 

Using sequences from 2,615 ultraconserved element (UCE) loci and multiple methodologies we inferred phylogenies for the largest genetic data set of New World bats in the genus Myotis to date. The resulting phylogenetic trees were populated with short branch lengths and widespread conflict, hallmarks consistent with rapid adaptive radiations. The degree of conflict observed in Myotis has likely contributed to difficulties disentangling deeper evolutionary relationships. Unlike earlier phylogenies based on 1 to 2 gene sequences, this UCE data set places M. brandtii outside the New World clades. Introgression testing of a small subset of our samples revealed evidence of historical but not contemporary gene flow, suggesting that hybridization occurs less frequently in the Neotropics than the Nearctic. We identified several instances of cryptic lineages within described species as well as several instances of potential taxonomic oversplitting. Evidence from Central and South American localities suggests that diversity in those regions is not fully characterized. In light of the accumulated evidence of the evolutionary complexity in Myotis and our survey of the taxonomic implications from our phylogenies, it is apparent that the definition of species and regime of species delimitation need to be reevaluated for Myotis. This will require substantial collaboration and sample sharing between geneticists and taxonomists to build a system that is both robust and applicable in a genus as diverse as Myotis.

 

We report the formation of minerals from the tochilinite-valleriite group (TVG) during laboratory serpentinization experiments conducted at 300 and 328 °C. Minerals in the TVG are composed of a mixture of sulfide and hydroxide layers that can contain variable proportions of Fe, Mg, Cu, Ni, and other cations in both layers. Members of this group have been observed as accessory minerals in several serpentinites, and have also been observed in association with serpentine minerals in meteorites. To our knowledge, however, TVG minerals have not previously been identified as reaction products during laboratory simulation of serpentinization. The serpentinization experiments reacted olivine with artificial seawater containing 34S-labeled sulfate, with a small amount of solid FeS also added to the 300 °C experiment. In both experiments, the predominant reaction products were chrysotile serpentine, brucite, and magnetite. At 300 °C, these major products were accompanied by trace amounts of the Ni-bearing TVG member haapalaite, Ni,Fe-sulfide (likely pentlandite), and anhydrite. At 328 °C, valleriite occurs rather than haapalaite and the accompanying Ni,Fe-sulfide is proportionally more enriched in Ni. Reduction of sulfate by H2 produced during serpentinization evidently provided a source of reduced S that contributed to formation of the TVG minerals and Ni,Fe-sulfides. The results provide new constraints on the conditions that allow precipitation of tochilinite-valleriite group minerals in natural serpentinites.

 

In exponential population growth, variability in the timing of individual division events and environmental factors (including stochastic inoculation) compound to produce variable growth trajectories. In several stochastic models of exponential growth we show power-law relationships that relate variability in the time required to reach a threshold population size to growth rate and inoculum size. Population-growth experiments inE. coliandS. aureuswith inoculum sizes ranging between 1 and 100 are consistent with these relationships. We quantify how noise accumulates over time, finding that it encodes—and can be used to deduce—information about the early growth rate of a population.

 

The traditional freehand placement of an external ventricular drain (EVD) relies on empirical craniometric landmarks to guide the craniostomy and subsequent passage of the EVD catheter. The diameter and trajectory of the craniostomy physically limit the possible trajectories that can be achieved during the passage of the catheter. In this study, the authors implemented a mixed reality–guided craniostomy procedure to evaluate the benefit of an optimally drilled craniostomy to the accurate placement of the catheter. Optical marker–based tracking using an OptiTrack system was used to register the brain ventricular hologram and drilling guidance for craniostomy using a HoloLens 2 mixed reality headset. A patient-specific 3D-printed skull phantom embedded with intracranial camera sensors was developed to automatically calculate the EVD accuracy for evaluation. User trials consisted of one blind and one mixed reality–assisted craniostomy followed by a routine, unguided EVD catheter placement for each of two different drill bit sizes. A total of 49 participants were included in the study (mean age 23.4 years, 59.2% female). The mean distance from the catheter target improved from 18.6 ± 12.5 mm to 12.7 ± 11.3 mm (p = 0.0008) using mixed reality guidance for trials with a large drill bit and from 19.3 ± 12.7 mm to 10.1 ± 8.4 mm with a small drill bit (p < 0.0001). Accuracy using mixed reality was improved using a smaller diameter drill bit compared with a larger bit (p = 0.039). Overall, the majority of the participants were positive about the helpfulness of mixed reality guidance and the overall mixed reality experience. Appropriate indications and use cases for the application of mixed reality guidance to neurosurgical procedures remain an area of active inquiry. While prior studies have demonstrated the benefit of mixed reality–guided catheter placement using predrilled craniostomies, the authors demonstrate that real-time quantitative and visual feedback of a mixed reality–guided craniostomy procedure can independently improve procedural accuracy and represents an important tool for trainee education and eventual clinical implementation.