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We study a system of ultra-cold dipolar Bose gas atoms confined in a two-dimensional (2D) harmonic trap with a dipolar impurity implanted at the center of the trap. Due to recent experimental progress in dipolar condensates, we focused on calculating properties of dipolar impurity systems that might guide experimentalists if they choose to study impurities in dipolar gases. We used the Gross–Pitaevskii formalism solved numerically via the split-step Crank–Nicolson method. We chose parameters of the background gas to be consistent with dysprosium (Dy), one of the strongest magnetic dipoles and of current experimental interest, and used chromium (Cr), erbium (Er), terbium (Tb), and Dy for the impurity. The dipole moments were aligned by an external field along what was chosen to be the z-axis, and we studied 2D confinements that were perpendicular or parallel to the external field. We show density contour plots for the two confinements, 1D cross-sections of the densities, calculated self-energies of the impurities while varying both number of atoms in the condensate and the symmetry of the trap. We also calculated the time evolution of the density of an initially pure system where an impurity is introduced. Our results show that while the self-energy increases in magnitude with increasing number of particles, it is reduced when the trap anisotropy follows the natural anisotropy of the gas, i.e., elongated along the z-axis in the case of parallel confinement. This work builds upon work conducted in Bose gases with zero-range interactions and demonstrates some of the features that could be found when exploring dipolar impurities in 2D Bose gases. 

Background:It is a major clinical challenge to ensure the long-term function of transplanted kidneys. Specifically, the injury associated with cold storage of kidneys compromises the long-term function of the grafts after transplantation. Therefore, the molecular mechanisms underlying cold-storage–related kidney injury are attractive therapeutic targets to prevent injury and improve long-term graft function. Previously, we found that constitutive proteasome function was compromised in rat kidneys after cold storage followed by transplantation. Here, we evaluated the role of the immunoproteasome (iproteasome), a proteasome variant, during cold storage (CS) followed by transplantation. Methods:Established in vivo rat kidney transplant model with or without CS containing vehicle or iproteasome inhibitor (ONX 0914) was used in this study. Theiproteasome function was performed using rat kidney homogenates and fluorescent-based peptide substrate specific to β5i subunit. Western blotting and quantitative RT-PCR were used to assess the subunit expression/level of theiproteasome (β5i) subunit. Results:We demonstrated a decrease in the abundance of the β5i subunit of theiproteasome in kidneys during CS, but β5i levels increased in kidneys after CS and transplant. Despite the increase in β5i levels and its peptidase activity within kidneys, inhibiting β5i during CS did not improve graft function after transplantation. Summary:These results suggest that the pharmacological inhibition of immunoproteasome function during CS does not improve graft function or outcome. In light of these findings, future studies targeting immunoproteasomes during both CS and transplantation may define the role of immunoproteasomes on short- and long-term kidney transplant outcomes. 

Plant-microbe interactions are critical for ecosystem functioning and driving rhizosphere processes. To fully understand the communication pathways between plants and rhizosphere microbes, it is crucial to measure the numerous processes that occur in the plant and the rhizosphere. The present review first provides an overview of how plants interact with their surrounding microbial communities, and in turn, are affected by them. Next, different optical biosensing technologies that elucidate the plant-microbe interactions and provide pathogenic detection are summarized. Currently, most of the biosensors used for detecting plant parameters or microbial communities in soil are centered around genetically encoded optical and electrochemical biosensors that are often not suitable for field applications. Such sensors require substantial effort and cost to develop and have their limitations. With a particular focus on the detection of root exudates and phytohormones under biotic and abiotic stress conditions, novel low-cost and in-situ biosensors must become available to plant scientists. 

Summary The anthropogenic spread of disease from captive to wild amphibian populations (referred to as spillover) is linked to global amphibian declines. Disinfecting procedures and protocols exist to mitigate pathogen transmission to and within natural areas, but understanding of visitor attitudes and behaviour regarding their adoption is limited. We surveyed visitors in two natural areas in a global amphibian biodiversity hotspot to assess their attitudes regarding pathogen spread in such areas and analysed the factors influencing their behavioural intentions to take specific actions to prevent pathogen spillover. Visitors’ willingness to take action was influenced by their attitudes, behavioural control and trust in wildlife/land managers, whereas socio-demographic characteristics were less influential. These findings help us to understand visitor behaviour with respect to amphibian biosecurity in natural areas and inform enhanced biosecurity measures and strategic messaging to reduce pathogen spillover. 

In the 1980’s, Greene defined hypergeometric functions over finite fields using Jacobi sums. The framework of his theory establishes that these functions possess many properties that are analogous to those of the classical hypergeometric series studied by Gauss and Kummer. These functions have played important roles in the study of Ap ́ery-style supercongruences, the Eichler-Selberg trace formula, Galois representations, and zeta-functions of arithmetic varieties. We study the value distribution (over large finite fields) of natural families of these functions. For the 2F1 functions, the limiting distribution is semicircular (i.e. SU(2)), whereas the distribution for the 3F2 functions is the Batman distribution for the traces of the real orthogonal group O3.