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Dilute species transport in generalized Newtonian fluids (GNFs) is typically described using explanatory empirical approaches assuming a traditional Fickian form, which is an approach that lacks predictive ability for systems and conditions not specifically investigated. Dilute species transport was investigated for a wide range of Cross and Carreau fluids flowing through a set of monodisperse and polydisperse sphere pack porous media. Both microscale and macroscale simulations were performed to demonstrate that GNF fluid flow can be predicted based upon Newtonian characterization of the media and rheological characterization of the fluid. Dilute species transport was shown to have a Fickian limit with dispersivity dependent on the porous media, fluid properties, and the flow rate in a nonlinear fashion. Dimensionless analysis and symbolic regression was used to deduce an explanatory and predictive function to describe dispersivity in terms of relevant system properties, enabling prediction of dilute species transport for GNFs flowing through porous media that does not require any non‐Newtonian experiments or parameter estimation.

Arsenic (As), chromium (Cr), and vanadium (V) are naturally occurring, redox-active elements that can become human health hazards when they are released from aquifer substrates into groundwater that may be used as domestic or irrigation source. As such, there is a need to develop incisive conceptual and quantitative models of the geochemistry and transport of potentially hazardous elements to assess risk and facilitate interventions. However, understanding the complexity and heterogeneous subsurface environment requires knowledge of solid-phase minerals, hydrologic movement, aerobic and anaerobic environments, microbial interactions, and complicated chemical kinetics. Here, we examine the relevant geochemical and hydrological information about the release and transport of potentially hazardous geogenic contaminants, specifically As, Cr, and V, as well as the potential challenges in developing a robust understanding of their behavior in the subsurface. We explore the development of geochemical models, illustrate how they can be utilized, and describe the gaps in knowledge that exist in translating subsurface conditions into numerical models, as well as provide an outlook on future research needs and developments.

Generalized Newtonian fluids (GNFs), for which the viscosity of the fluid is shear-rate dependent, appear regularly in polymeric, geological, and biological flows, making them important to many porous medium operations. Despite this, the methods used to model flow and transport of GNFs heretofore have been limited, focusing on empirical models that require experimental or simulated data for flow of every fluid of interest, flowing in every porous medium of interest. In this work, new flow and transport models for GNFs have been developed that allow prediction using only a limited number of commonly tabulated system and fluid properties. In particular, observations from one Newtonian fluid flowing through a medium at one flow rate are adequate to model all GNFs of interest flowing through that medium at any laminar flow rate. The new flow and transport models were found to be accurate for a wide variety of GNFs and porous media when compared to data generated from mature computational simulators. These new models operate in an analogous fashion to the way Newtonian flow and transport models do, thus system parameters may be determined in advance and used to model unknown GNFs of interest in the future. This represents a significant improvement in the state of the science of GNF flow and transport modeling, and may lead to inclusion of these models in the next generation of porous medium simulators.

Single fluid porous medium systems are typically modeled at an averaged length scale termed the macroscale using Darcy's law. Standard approaches for modeling macroscale single fluid phase flow of non-Newtonian fluids extend Darcy's law, using an effective viscosity and assuming that the permeability is invariant. This approach results in a need to determine the effective viscosity for every fluid and flow rate. We use the thermodynamically constrained averaging theory (TCAT) to examine the formulation and closure of a macroscale model for non-Newtonian flow that is consistent with microscale conservation principles and the second law of thermodynamics. A connection between microscale and macroscale quantities is used to calculate interphase momentum transfer for non-Newtonian flow in porous medium systems. Darcy's law is shown to approximate momentum transfer from the fluid phase to the solid phase. This momentum transfer is found to depend on the viscosity at the solid surface. As a consequence of the derived equation for momentum transfer, the commonly called intrinsic permeability is not invariant for non-Newtonian flow, which is an assumption that underlies standard effective viscosity approaches. TCAT is used to derive a macroscale equation relating the flow rate and the pressure gradient dependent upon fluid properties and medium characterization, breaking the need to investigate all flow and composition conditions currently required. This new approach is validated for model systems and used to interpret results from the literature, including an evaluation of conditions under which a transition occurs away from the strictly laminar flow conditions. The results from this work form a basis for more rigorous and realistic modeling of non-Newtonian flow in porous medium systems.

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It has been established in recent years that the gut microbiome plays a role in health and disease, potentially via alterations in metabolites that influence host physiology. Although sleep disruption and gut dysbiosis have been associated with many of the same diseases, studies investigating the gut microbiome in the context of sleep disruption have yielded inconsistent results, and have not assessed the fecal metabolome. We exposed mice to five days of sleep disruption followed by four days of ad libitum recovery sleep, and assessed the fecal microbiome and fecal metabolome at multiple timepoints using 16S rRNA gene amplicons and untargeted LC-MS/MS mass spectrometry. We found global shifts in both the microbiome and metabolome in the sleep-disrupted group on the second day of recovery sleep, when most sleep parameters had recovered to baseline levels. We observed an increase in the Firmicutes:Bacteroidetes ratio, along with decreases in the genus Lactobacillus, phylum Actinobacteria, and genus Bifidobacterium in sleep-disrupted mice compared to control mice. The latter two taxa remained low at the fourth day post-sleep disruption. We also identified multiple classes of fecal metabolites that were differentially abundant in sleep-disrupted mice, some of which are physiologically relevant and commonly influenced by the microbiome. This included bile acids, and inference of microbial functional gene content suggested reduced levels of the microbial bile salt hydrolase gene in sleep-disrupted mice. Overall, this study adds to the evidence base linking disrupted sleep to the gut microbiome and expands it to the fecal metabolome, identifying sleep disruption-sensitive bacterial taxa and classes of metabolites that may serve as therapeutic targets to improve health after poor sleep.

Recent advances in next-generation DNA sequencing technologies have made possible the development of high-throughput SNP genotyping platforms that allow for the simultaneous interrogation of thousands of single-nucleotide polymorphisms (SNPs). Such resources have the potential to facilitate the rapid development of high-density genetic maps, and to enable genome-wide association studies as well as molecular breeding approaches in a variety of taxa. Herein, we describe the development of a SNP genotyping resource for use in sunflower (Helianthus annuus L.). This work involved the development of a reference transcriptome assembly for sunflower, the discovery of thousands of high quality SNPs based on the generation and analysis of ca. 6 Gb of transcriptome re-sequencing data derived from multiple genotypes, the selection of 10,640 SNPs for inclusion in the genotyping array, and the use of the resulting array to screen a diverse panel of sunflower accessions as well as related wild species. The results of this work revealed a high frequency of polymorphic SNPs and relatively high level of cross-species transferability. Indeed, greater than 95% of successful SNP assays revealed polymorphism, and more than 90% of these assays could be successfully transferred to related wild species. Analysis of the polymorphism data revealed patterns of genetic differentiation that were largely congruent with the evolutionary history of sunflower, though the large number of markers allowed for finer resolution than has previously been possible.

In this randomized trial in patients hospitalized with alcoholic hepatitis, pentoxifylline did not improve survival. The 28-day survival advantage in patients treated with prednisolone did not reach significance and was not sustained at 90 days or 1 year. Alcoholic hepatitis is a distinct manifestation of alcoholic liver disease that is characterized by jaundice and liver failure. This condition develops in persons with a history of prolonged and heavy alcohol use. 1 The severity of alcoholic hepatitis is conventionally defined by Maddrey’s discriminant function, which is calculated as 4.6×(patient’s prothrombin time in seconds−control’s prothrombin time in seconds)+patient’s serum bilirubin level in milligrams per deciliter; a value of 32 or higher indicates severe alcoholic hepatitis that carries an adverse prognosis, with mortality of 20 to 30% within 1 month after presentation and 30 to 40% within 6 months after presentation. 2 A . . .

The 21-residue PGLa peptide is well known for antimicrobial activity attributed to its ability to compromize bacterial membranes. Using all-atom explicit solvent replica exchange molecular dynamics with solute tempering, we studied PGLa binding to a model anionic DMPC/DMPG bilayer at the high peptide:lipid ratio that promotes PGLa dimerization (a two peptides per leaflet system). As a reference we used our previous simulations at the low peptide:lipid ratio (a one peptide per leaflet system). We found that the increase in the peptide:lipid ratio suppresses PGLa helical propensity, tilts the bound peptide toward the bilayer hydrophobic core, and forces it deeper into the bilayer. Surprisingly, at the high peptide:lipid ratio PGLa binding induces weaker bilayer thinning, but deeper water permeation. We explain these effects by the cross-correlations between lipid shells surrounding PGLa that leads to a much diminished efflux of DMPC lipids from the peptide proximity at the high peptide:lipid ratio. Consistent with the experimental data the propensity for PGLa dimerization was found to be weak resulting in coexistence of monomers and dimers with distinctive properties. PGLa dimers assemble via apolar criss-cross interface and become partially expelled from the bilayer residing at the bilayer-water boundary. We rationalize their properties by the dimer tendency to preserve favorable electrostatic interactions between lysine and phosphate lipid groups as well as to avoid electrostatic repulsion between lysines in the low dielectric environment of the bilayer core. PGLa homedimer interface is predicted to be distinct from that involved in PGLa-magainin heterodimers.

Participants read aloud swear words, euphemisms of the swear words, and neutral stimuli while their autonomic activity was measured by electrodermal activity. The key finding was that autonomic responses to swear words were larger than to euphemisms and neutral stimuli. It is argued that the heightened response to swear words reflects a form of verbal conditioning in which the phonological form of the word is directly associated with an affective response. Euphemisms are effective because they replace the trigger (the offending word form) by another word form that expresses a similar idea. That is, word forms exert some control on affect and cognition in turn. We relate these findings to the linguistic relativity hypothesis, and suggest a simple mechanistic account of how language may influence thinking in this context.