A reactive molecular dynamics model for uranium/hydrogen containing systems.

Uranium-based materials are valuable assets in the energy, medical, and military industries. However, understanding their sensitivity to hydrogen embrittlement is particularly challenging due to the toxicity of uranium and the computationally expensive nature of quantum-based methods generally required to study such processes. In this regard, we have developed a Chebyshev Interaction Model for Efficient Simulation (ChIMES) that can be employed to compute energies and forces of U and UH3 bulk structures with vacancies and hydrogen interstitials with accuracy similar to that of Density Functional Theory (DFT) while yielding linear scaling and orders of magnitude improvement in computational efficiency. We show that the bulk structural parameters, uranium and hydrogen vacancy formation energies, and diffusion barriers predicted by the ChIMES potential are in strong agreement with the reference DFT data. We then use ChIMES to conduct molecular dynamics simulations of the temperature-dependent diffusion of a hydrogen interstitial and determine the corresponding diffusion activation energy. Our model has particular significance in studies of actinides and other high-Z materials, where there is a strong need for computationally efficient methods to bridge length and time scales between experiments and quantum theory.

Reoccurring Escherichia coli O157:H7 Strain Linked to Leafy Greens-Associated Outbreaks, 2016-2019.

Genomic characterization of an Escherichia coli O157:H7 strain linked to leafy greens-associated outbreaks dates its emergence to late 2015. One clade has notable accessory genomic content and a previously described mutation putatively associated with increased arsenic tolerance. This strain is a reoccurring, emerging, or persistent strain causing illness over an extended period.

United atom and coarse grained models for crosslinked polydimethylsiloxane with applications to the rheology of silicone fluids.

Siloxane systems consisting primarily of polydimethylsiloxane (PDMS) are versatile, multifaceted materials that play a key role in diverse applications. However, open questions exist regarding the correlation between their varied atomic-level properties and observed macroscale features. To this effect, we have created a systematic workflow to determine coarse-grained simulation models for crosslinked PDMS in order to further elucidate the effects of network changes on the system's rheological properties below the gel point. Our approach leverages a fine-grained united atom model for linear PDMS, which we extend to include crosslinking terms, and applies iterative Boltzmann inversion to obtain a coarse-grain "bead-spring-type" model. We then perform extensive molecular dynamics simulations to explore the effect of crosslinking on the rheology of silicone fluids, where we compute systematic increases in both density and shear viscosity that compare favorably to experiments that we conduct here. The kinematic viscosity of partially crosslinked fluids follows an empirical linear relationship that is surprisingly consistent with Rouse theory, which was originally derived for systems comprised of a uniform distribution of linear chains. The models developed here serve to enable quantitative bottom-up predictions for curing- and age-induced effects on macroscale rheological properties, allowing for accurate prediction of material properties based on fundamental chemical data.

Enhancing the accuracy of density functional tight binding models through ChIMES many-body interaction potentials.

Semi-empirical quantum models such as Density Functional Tight Binding (DFTB) are attractive methods for obtaining quantum simulation data at longer time and length scales than possible with standard approaches. However, application of these models can require lengthy effort due to the lack of a systematic approach for their development. In this work, we discuss the use of the Chebyshev Interaction Model for Efficient Simulation (ChIMES) to create rapidly parameterized DFTB models, which exhibit strong transferability due to the inclusion of many-body interactions that might otherwise be inaccurate. We apply our modeling approach to silicon polymorphs and review previous work on titanium hydride. We also review the creation of a general purpose DFTB/ChIMES model for organic molecules and compounds that approaches hybrid functional and coupled cluster accuracy with two orders of magnitude fewer parameters than similar neural network approaches. In all cases, DFTB/ChIMES yields similar accuracy to the underlying quantum method with orders of magnitude improvement in computational cost. Our developments provide a way to create computationally efficient and highly accurate simulations over varying extreme thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly, and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.

Chemical evolution in nitrogen shocked beyond the molecular stability limit.

Evolution of nitrogen under shock compression up to 100 GPa is revisited via molecular dynamics simulations using a machine-learned interatomic potential. The model is shown to be capable of recovering the structure, dynamics, speciation, and kinetics in hot compressed liquid nitrogen predicted by first-principles molecular dynamics, as well as the measured principal shock Hugoniot and double shock experimental data, albeit without shock cooling. Our results indicate that a purely molecular dissociation description of nitrogen chemistry under shock compression provides an incomplete picture and that short oligomers form in non-negligible quantities. This suggests that classical models representing the shock dissociation of nitrogen as a transition to an atomic fluid need to be revised to include reversible polymerization effects.

Delayed lactose utilization among Shiga toxin-producing Escherichia coli of serogroup O121.

Two outbreaks of Shiga toxin-producing Escherichia coli O121:H19 associated with wheat flour, in the United States of America and Canada, involved strains with an unusual phenotype, delayed lactose utilization (DLU). These strains do not ferment lactose when initially cultured on MacConkey agar (MAC), but lactose fermentation occurs following subculture to a second plate of MAC. The prevalence of DLU was determined by examining the ß-galactosidase activity of 49 strains of E. coli O121, and of 37 other strains of E. coli. Twenty four of forty three O121:H19 and one O121:NM displayed DLU. Two strains (O121:NM and O145:H34) did not have detectable ß-galactosidase activity. ß-glucuronidase activity of O121 strains was also determined. All but six DLU strains had normal ß-glucuronidase activity. ß-glucuronidase activity was suppressed on MAC for 17 of 23 O121 non-DLU strains. Genomic analysis found that DLU strains possessed an insertion sequence, IS600 (1267 bp), between lacZ (ß-galactosidase) and lacY (ß-galactoside permease), that was not present in strains exhibiting normal lactose utilization. The insert might reduce the expression of ß-galactoside permease, delaying import of lactose, resulting in the DLU phenotype. The high probability of DLU should be considered when using lactose-containing media for the isolation of STEC O121.

Sequencing of Enteric Bacteria: Library Preparation Procedure Matters for Accurate Identification and Characterization.

Enzymatic library preparation kits are increasingly used for bacterial whole genome sequencing. While they offer a rapid workflow, the transposases used in the kits are recognized to be somewhat biased. The aim of this study was to optimize and validate a protocol for the Illumina DNA Prep kit (formerly Nextera DNA Flex) for sequencing enteric pathogens and compare its performance against the Nextera XT kit. One hundred forty-three strains of Campylobacter, Escherichia, Listeria, Salmonella, Shigella, and Vibrio were prepared with both methods and sequenced on the Illumina MiSeq using 300 and/or 500 cycle chemistries. Sequences were compared using core genome multilocus sequence typing (cgMLST), 7-gene multilocus sequence typing (MLST), and detection of markers encoding serotype, virulence, and antimicrobial resistance. Sequences for one Escherichia strain were downsampled to determine the minimum coverage required for the analyses. While organism-specific differences were observed, the Prep libraries generated longer average read lengths and less fragmented assemblies compared to the XT libraries. In downstream analysis, the most notable difference between the kits was observed for Escherichia, particularly for the 300 cycle sequences. The O group was not predicted in 32% and 4% of XT sequences when using blast and kmer algorithms, respectively, while the O group was predicted from all Prep sequences regardless of the algorithm. In addition, the ehxA gene was not detected in 6% of XT sequences and 34% were missing one or more of the type III secretion systems and/or plasmid-associated genes, which were detected in the Prep sequences. The coverage downsampling revealed that acceptable assembly quality and allele detection was achieved at 30 × coverage with the Prep libraries, whereas 40-50 × coverage was required for the XT libraries. The better performance of the Prep libraries was attributed to more even coverage, particularly in genome regions low in GC content.

Investigating 3,4-bis(3-nitrofurazan-4-yl)furoxan detonation with a rapidly tuned density functional tight binding model.

We describe a machine learning approach to rapidly tune density functional tight binding models for the description of detonation chemistry in organic molecular materials. Resulting models enable simulations on the several 10s of ps scales characteristic to these processes, with "quantum-accuracy." We use this approach to investigate early shock chemistry in 3,4-bis(3-nitrofurazan-4-yl)furoxan, a hydrogen-free energetic material known to form onion-like nanocarbon particulates following detonation. We find that the ensuing chemistry is significantly characterized by the formation of large CxNyOz species, which are likely precursors to the experimentally observed carbon condensates. Beyond utility as a means of investigating detonation chemistry, the present approach can be used to generate quantum-based reference data for the development of full machine-learned interatomic potentials capable of simulation on even greater time and length scales, i.e., for applications where characteristic time scales exceed the reach of methods including Kohn-Sham density functional theory, which are commonly used for reference data generation.

Active learning for robust, high-complexity reactive atomistic simulations.

Machine learned reactive force fields based on polynomial expansions have been shown to be highly effective for describing simulations involving reactive materials. Nevertheless, the highly flexible nature of these models can give rise to a large number of candidate parameters for complicated systems. In these cases, reliable parameterization requires a well-formed training set, which can be difficult to achieve through standard iterative fitting methods. Here, we present an active learning approach based on cluster analysis and inspired by Shannon information theory to enable semi-automated generation of informative training sets and robust machine learned force fields. The use of this tool is demonstrated for development of a model based on linear combinations of Chebyshev polynomials explicitly describing up to four-body interactions, for a chemically and structurally diverse system of C/O under extreme conditions. We show that this flexible training database management approach enables development of models exhibiting excellent agreement with Kohn-Sham density functional theory in terms of structure, dynamics, and speciation.

Calculation of the detonation state of HN3 with quantum accuracy.

HN3 is a unique liquid energetic material that exhibits ultrafast detonation chemistry and a transition to metallic states during detonation. We combine the Chebyshev interaction model for efficient simulation (ChIMES) many-body reactive force field and the extended-Lagrangian multiscale shock technique molecular dynamics method to calculate the detonation properties of HN3 with the accuracy of Kohn-Sham density-functional theory. ChIMES is based on a Chebyshev polynomial expansion and can accurately reproduce density-functional theory molecular dynamics (DFT-MD) simulations for a wide range of unreactive and decomposition conditions of liquid HN3. We show that addition of random displacement configurations and the energies of gas-phase equilibrium products in the training set allows ChIMES to efficiently explore the complex potential energy surface. Schemes for selecting force field parameters and the inclusion of stress tensor and energy data in the training set are examined. Structural and dynamical properties and chemistry predictions for the resulting models are benchmarked against DFT-MD. We demonstrate that the inclusion of explicit four-body energy terms is necessary to capture the potential energy surface across a wide range of conditions. Our results generally retain the accuracy of DFT-MD while yielding a high degree of computational efficiency, allowing simulations to approach orders of magnitude larger time and spatial scales. The techniques and recipes for MD model creation we present allow for direct simulation of nanosecond shock compression experiments and calculation of the detonation properties of materials with the accuracy of Kohn-Sham density-functional theory.

Many-body reactive force field development for carbon condensation in C/O systems under extreme conditions.

We describe the development of a reactive force field for C/O systems under extreme temperatures and pressures, based on the many-body Chebyshev Interaction Model for Efficient Simulation (ChIMES). The resulting model, which targets carbon condensation under thermodynamic conditions of 6500 K and 2.5 g cm-3, affords a balance between model accuracy, complexity, and training set generation expense. We show that the model recovers much of the accuracy of density functional theory for the prediction of structure, dynamics, and chemistry when applied to dissociative condensed phase systems at 1:1 and 1:2 C:O ratios, as well as molten carbon. Our C/O modeling approach exhibits a 104 increase in efficiency for the same system size (i.e., 128 atoms) and a linear system size scalability over standard quantum molecular dynamics methods, allowing the simulation of significantly larger systems than previously possible. We find that the model captures the condensed-phase reaction-coupled formation of carbon clusters implied by recent experiments, and that this process is susceptible to strong finite size effects. Overall, we find the present ChIMES model to be well suited for studying chemical processes and cluster formation at pressures and temperatures typical of shock waves. We expect that the present C/O modeling paradigm can serve as a template for the development of a broader high pressure-high temperature force-field for condensed phase chemistry in organic materials.

Novel quinolone resistance determinant, qepA8, in Shigella flexneri isolated in the United States, 2016.

Enterobacteriaceae, quinolone resistance is largely attributed to mutations in the quinolone resistance-determining regions (QRDR) of gyrA, gyrB, parC, and parE, and plasmid-italiciated quinolone resistance (PMQR) genes (e.g., qnr genes, aac(6')-Ib-cr, or qepA).….

Conjugal Transfer, Whole-Genome Sequencing, and Plasmid Analysis of Four mcr-1-Bearing Isolates from U.S. Patients.

Four Enterobacteriaceae clinical isolates bearing mcr-1 gene-harboring plasmids were characterized. All isolates demonstrated the ability to transfer colistin resistance to Escherichia coli; plasmids were stable in conjugants after multiple passages on nonselective media. mcr-1 was located on an IncX4 (n = 3) or IncN (n = 1) plasmid. The IncN plasmid harbored 13 additional antimicrobial resistance genes. Results indicate that the mcr-1-bearing plasmids in this study were highly transferable in vitro and stable in the recipients.

Probing Additive Loading in the Lamellar Phase of a Nonionic Surfactant: Gibbs Ensemble Monte Carlo Simulations Using the SDK Force Field.

Understanding solute uptake into soft microstructured materials, such as bilayers and worm-like and spherical micelles, is of interest in the pharmaceutical, agricultural, and personal care industries. To obtain molecular-level insight on the effects of solutes loading into a lamellar phase, we utilize the Shinoda-Devane-Klein (SDK) coarse-grained force field in conjunction with configurational-bias Monte Carlo simulations in the osmotic Gibbs ensemble. The lamellar phase is comprised of a bilayer formed by triethylene glycol mono- n-decyl ether (C10E3) surfactants surrounded by water with a 50:50 surfactant/water weight ratio. We study both the unary adsorption isotherm and the effects on bilayer structure and stability caused by n-nonane, 1-hexanol, and ethyl butyrate at several different reduced reservoir pressures. The nonpolar n-nonane molecules load near the center of the bilayer. In contrast, the polar 1-hexanol and ethyl butyrate molecules both load with their polar bead close to the surfactant head groups. Near the center of the bilayer, none of the solute molecules exhibits a significant orientational preference. Solute molecules adsorbed near the polar groups of the surfactant chains show a preference for orientations perpendicular to the interface, and this alignment with the long axis of the surfactant molecules is most pronounced for 1-hexanol. Loading of n-nonane leads to an increase of the bilayer thickness, but does not affect the surface area per surfactant. Loading of polar additives leads to both lateral and transverse swelling. The reduced Henry's law constants of adsorption (expressed as a molar ratio of additive to surfactant per reduced pressure) are 0.23, 1.4, and 14 for n-nonane, 1-hexanol, and ethyl butyrate, respectively, and it appears that the SDK force field significantly overestimates the ethyl butyrate-surfactant interactions.

Adolescent social media use and mental health from adolescent and parent perspectives.

This study investigated adolescent and parent reports of adolescent social media use and its relation to adolescent psychosocial adjustment. The sample consisted of 226 participants (113 parent-adolescent dyads) from throughout the United States, with adolescents (55 males, 51 females, 7 unreported) ranging from ages 14 to 17. Parent and adolescent reports of the number of adolescents' social media accounts were moderately correlated with parent-reported DSM-5 symptoms of inattention, hyperactivity/impulsivity, ODD, anxiety, and depressive symptoms, as well as adolescent-reported fear of missing out (FoMO) and loneliness. Lastly, anxiety and depressive symptoms were highest among adolescents with a relatively high number of parent-reported social media accounts and relatively high FoMO. The implications of these findings and need for related longitudinal studies are discussed.

Evaluating the occurrence of Escherichia albertii in chicken carcass rinses by PCR, Vitek analysis, and sequencing of the rpoB gene.

Escherichia albertii is a recently described species that has been associated with gastroenteritis in humans and with healthy and ill birds. Most recently, it has been identified as the causative agent in a food-borne outbreak in Japan. The distribution and clinical importance of E. albertii are not well studied because its importance is unclear. Culture methods for clinical isolation frequently miss E. albertii or incorrectly identify it as Shigella spp., Escherichia coli, or Hafnia alvei. This study was designed to determine if E. albertii could be recovered from chicken carcass rinses collected at slaughter during a 1-year period from November 2009 until October 2010. Colonies were isolated from chicken carcass rinses and tested by PCR for the presence or absence of clpX, lysP, mdh, intimin (eae), Shiga toxins 1 and 2 (stx1, stx2, and stx2f), heat-stable enterotoxin A (staA), and cytolethal distending toxins 1 and 2 (cdtB) genes. Sixty-five isolates were analyzed by sequencing a section of the rpoB gene. Analysis of the rpoB gene sequences revealed 14 fixed differences between E. albertii and other, closely related organisms. The fixed differences found in the rpoB gene could aid in future discrimination of E. albertii from closely related bacteria.

Conditional expression of flagellar motility, curli fimbriae, and biofilms in Shiga toxin- producing Escherichia albertii.

Escherichia albertii is an emerging foodborne pathogen. We previously reported that some avian Shiga toxin-producing E. albertii strains exhibited higher or comparable cytotoxicity in Vero-d2EGFP cells with several enterohemorrhagic E. coli (EHEC) outbreak strains. To better understand the environmental persistence of this pathogen, comparative genomics and phenotypic assays were applied to assess adhesion capability, motility, and biofilm formation in E. albertii. Among the 108 adherence-related genes, those involved in biogenesis of curli fimbriae, hemorrhagic E. coli pilus, type 1 fimbriae, and Sfm fimbriae were conserved in E. albertii. All 20 E. albertii strains carried a complete set of primary flagellar genes that were organized into four gene clusters, while five strains possessed genes related to the secondary flagella, also known as lateral flagella. Compared to EHEC strain EDL933, the eight chemotaxis genes located within the primary flagellar gene clusters were deleted in E. albertii. Additional deletion of motility genes flhABCD and motBC was identified in several E. albertii strains. Swimming motility was detected in three strains when grown in LB medium, however, when grown in 5% TSB or in the pond water-supplemented with 10% pigeon droppings, an additional four strains became motile. Although all E. albertii strains carried curli genes, curli fimbriae were detected only in four, eight, and nine strains following 24, 48, and 120 h incubation, respectively. Type 1 fimbriae were undetectable in any of the strains grown at 37°C or 28°C. Strong biofilms were detected in strains that produced curli fimbriae and in a chicken isolate that was curli fimbriae negative but carried genes encoding adhesive fimbriae K88, a signature of enterotoxigenic E. coli strains causing neonatal diarrhea in piglets. In all phenotypic traits examined, no correlation was revealed between the strains isolated from different sources, or between the strains with and without Shiga toxin genes. The phenotypic variations could not be explained solely by the genetic diversity or the difference in adherence genes repertoire, implying complex regulation in expression of various adhesins. Strains that exhibited a high level of cytotoxicity and were also proficient in biofilm production, may have potential to emerge into high-risk pathogens.

Genetic Diversity in Salmonella enterica in Outbreaks of Foodborne and Zoonotic Origin in the USA in 2006-2017.

Whole genome sequencing is replacing traditional laboratory surveillance methods as the primary tool to track and characterize clusters and outbreaks of the foodborne and zoonotic pathogen Salmonella enterica (S. enterica). In this study, 438 S. enterica isolates representing 35 serovars and 13 broad vehicle categories from one hundred epidemiologically confirmed outbreaks were evaluated for genetic variation to develop epidemiologically relevant interpretation guidelines for Salmonella disease cluster detection. The Illumina sequences were analyzed by core genome multi-locus sequence typing (cgMLST) and screened for antimicrobial resistance (AR) determinants and plasmids. Ninety-three of the one hundred outbreaks exhibited a close allele range (less than 10 allele differences with a subset closer than 5). The remaining seven outbreaks showed increased variation, of which three were considered polyclonal. A total of 16 and 28 outbreaks, respectively, showed variations in the AR and plasmid profiles. The serovars Newport and I 4,[5],12:i:-, as well as the zoonotic and poultry product vehicles, were overrepresented among the outbreaks, showing increased variation. A close allele range in cgMLST profiles can be considered a reliable proxy for epidemiological relatedness for the vast majority of S. enterica outbreak investigations. Variations associated with mobile elements happen relatively frequently during outbreaks and could be reflective of changing selective pressures.

Time-Resolved X-ray Emission Spectroscopy and Resonant Inelastic X-ray Scattering Spectroscopy of Laser Irradiated Carbon.

The existence of liquid carbon as an intermediate phase preceding the formation of novel carbon materials has been a point of contention for several decades. Experimental observation of such a liquid state requires nonthermal melting of solid carbon materials at various laser fluences and pulse properties. Reflectivity experiments performed in the mid-1980s reached opposing conclusions regarding the metallic or insulating properties of the purported liquid state. Time-resolved X-ray absorption studies showed shortening of C-C bonds and increasing diffraction densities, thought to evidence a liquid or glassy carbon state, respectively. Nevertheless, none of these experiments provided information on the electronic structure of the proposed liquid state. Herein, we report the results of time-resolved resonant inelastic X-ray scattering (RIXS) and time-resolved X-ray emission spectroscopy (XES) studies on amorphous carbon (a-C) and ultrananocrystalline diamond (UNCD) as a function of delay time between the irradiating pulse and X-ray probe. For both a-C and UNCD, we attribute decreases in RIXS or XES signals to transition blocking, relaxation, and finally, ablation. Increased signal at 20 ps following the irradiation of the UNCD is attributed to the probable formation of nanoscale structures in the ablation plume. Differences in the amount of signal observed between a-C and UNCD are explained by the difference in sample thickness and, specifically, incomplete melting of the UNCD film. Comparisons to spectral simulations based on MD trajectories at extreme conditions indicate that the carbon state in our experiments is crystalline. Normal mode analysis confirmed that symmetrical bending or stretching of the C-C bonds in the diamond lattice results in XES spectra with small intensity differences. Overall, we observed no evidence of melting to a liquid state, as determined by the lack of changes in the spectral properties for up to 100 ps delays following the melting pulses.

The Relation of Parental Expressed Emotion, Parental Affiliate Stigma, and Typically-developing Sibling Internalizing Behavior in Families with a Child with ASD.

Caregivers of children with autism spectrum disorder (ASD) experience greater stress, expressed emotion (EE), and affiliate stigma than caregivers of children without ASD. Siblings of children with ASD often experience greater negative functioning than siblings of individuals without ASD. The current study found significant interrelations among symptom severity and externalizing behavior in children with ASD; parental stress, affiliate stigma, and EE; and TD sibling internalizing behavior. In addition, certain subcomponents of affiliate stigma predicted unique variance in EE and TD sibling internalizing behavior. Findings may increase understanding of psychosocial functioning in families with children with ASD and allow clinicians to improve outcomes for all family members. Limitations of the study included self-report data, limited sample diversity, and a cross-sectional design.