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Aeromonasspecies (spp.) are well-known fish pathogens, several of which have been recognized as emerging human pathogens. The organism is capable of causing a wide spectrum of diseases in humans, ranging from gastroenteritis, wound infections, and septicemia to devastating necrotizing fasciitis. The systemic form of infection is often fatal, particularly in patients with underlying chronic diseases. Indeed, recent trends demonstrate rising numbers of hospital-acquiredAeromonasinfections, especially in immuno-compromised individuals. Additionally,Aeromonas-associated antibiotic resistance is an increasing challenge in combating both fish and human infections. The acquisition of antibiotic resistance is related toAeromonas’ innate transformative properties including its ability to share plasmids and integron-related gene cassettes between species and with the environment. As a result, alternatives to antibiotic treatments are desperately needed. In that vein, many treatments have been proposed and studied extensively in the fish-farming industry, including treatments that targetAeromonasquorum sensing. In this review, we discuss current strategies targeting quorum sensing inhibition and propose that such studies empower the development of novel chemotherapeutic approaches to combat drug-resistantAeromonasspp. infections in humans.

• Aeromonas notoriously acquires and maintains antimicrobial resistance, making treatment options limited.

• Quorum sensing is an essential virulence mechanism in Aeromonas infections.

• Inhibiting quorum sensing can be an effective strategy in combating Aeromonas infections in animals and humans.

 

Edge dislocations are crucial in understanding both mechanical and electrical transport in solid and are modeled as line distributions of dipole moments. The calculation of the electronic spectrum for the two dimensional dipole, represented by the potential energy V(r,θ)=pcosθ/r, has been the topic of several studies that show significant difficulties in obtaining accurate results. In this work, we demonstrate that the source of these difficulties is a logarithmic contribution to the behavior of the wave function at the origin that was neglected by previous authors. By taking into account this non-analytic deviation of the solution of Schrödinger’s equation, superior results, with the expected rate of convergence, are obtained. This goal is accomplished by “adapting” general algorithms for solving partial derivative differential equations to include the desired asymptotic behavior. We illustrate this principle for the variational principle and finite difference methods. Accurate energies and wave functions are obtained not only for the ground state but also for the first eleven excited states and are useful for designing nanoelectronic devices. This paper demonstrates that augmentary knowledge about analytic properties of the solutions leads to the improved convergence and stability of numerical methods.

 

Introduction: Environmental exposure to indoor dust is known to be associated with myriad health conditions, especially among children. Established routes of exposure include inhalation and non-dietary ingestion, which result in the direct exposure of gastrointestinal epithelia to indoor dust. Despite this, little prior research is available on the impacts of indoor dust on the health of human gastrointestinal tissue. Methods: Cultured human colonic (CCD841) cells were exposed for 24 h to standard trace metal dust (TMD) and organic contaminant dust (OD) samples at the following concentrations: 0, 10, 25, 50, 75, 100, 250, and 500 µg/mL. Cell viability was assessed using an MTT assay and protease analysis (glycyl-phenylalanyl-aminofluorocoumarin (GF-AFC)); cytotoxicity was assessed with a lactate dehydrogenase release assay, and apoptosis was assessed using a Caspase-Glo 3/7 activation assay. Results: TMD and OD decreased cellular metabolic and protease activity and increased apoptosis and biomarkers of cell membrane damage (LDH) in CCD841 human colonic epithelial cells. Patterns appeared to be, in general, dose-dependent, with the highest TMD and OD exposures associated with the largest increases in apoptosis and LDH, as well as with the largest decrements in metabolic and protease activities. Conclusions: TMD and OD exposure were associated with markers of reduced viability and increased cytotoxicity and apoptosis in human colonic cells. These findings add important information to the understanding of the physiologic effects of indoor dust exposure on human health. The doses used in our study represent a range of potential exposure levels, and the effects observed at the higher doses may not necessarily occur under typical exposure conditions. The effects of long-term, low-dose exposure to indoor dust are still not fully understood and warrant further investigation. Future research should explore these physiological mechanisms to further our understanding and inform public health interventions. 

A semiclassical model describing the charge transfer collisions of C 60 fullerene with different slow ions has been developed to analyze available observations. These data reveal multiple Breit–Wigner-like peaks in the cross sections, with subsequent peaks of reactive cross sections decreasing in magnitude. Calculations of charge transfer probabilities, quasi-resonant cross sections, and cross sections for reactive collisions have been performed using semiempirical interaction potentials between fullerenes and ion projectiles. All computations have been carried out with realistic wave functions for C 60 ’s valence electrons derived from the simplified jellium model. The quality of these electron wave functions has been successfully verified by comparing theoretical calculations and experimental data on the small angle cross sections of resonant [Formula: see text] collisions. Using the semiempirical potentials to describe resonant scattering phenomena in C 60 collisions with ions and Landau–Zener charge transfer theory, we calculated theoretical cross sections for various C 60 charge transfer and fragmentation reactions which agree with experiments. 

Indoor dust can be a major source of heavy metals, nutrients, and bacterial contamination in residential environments and may cause serious health problems. The goal of this research is to characterize chemical and bacterial contaminants of indoor, settled house dust in the Houston Metropolitan region. To achieve this, a total of 31 indoor dust samples were collected, along with household survey data, which were subsequently analyzed for elemental and bacterial concentrations. Microscopic and geospatial analysis was conducted to characterize and map potential hotspots of contamination. Interestingly Cd, Cr, Cu, Pb, and Zn concentrations of all 31 indoor dust samples were significantly enriched and exceeded soil background concentrations. Furthermore, As, Cd, Pb, and Zn concentrations in the dust samples were significantly correlated to the enteric bacterial load concentrations. Human health assessment revealed that cancer risk values via ingestion for Cd, Cr, and Ni were greater than the acceptable range. Of our 31 dust sample isolates, three Gram-negative and 16 Gram-positive pathogenic bacteria were identified, capable of causing a wide range of diseases. Our results demonstrate that both chemical and bacterial characterization of indoor dust coupled with spatial mapping is essential to assess and monitor human and ecological health risks. 

Scientific Machine Learning (SciML) is a new multidisciplinary methodology that combines the data-driven machine learning models and the principle-based computational models to improve the simulations of scientific phenomenon and uncover new scientific rules from existing measurements. This article reveals the experience of using the SciML method to discover the nonlinear dynamics that may be hard to model or be unknown in the real-world scenario. The SciML method solves the traditional principle-based differential equations by integrating a neural network to accurately model the nonlinear dynamics while respecting the scientific constraints and principles. The paper discusses the latest SciML models and apply them to the oscillator simulations and experiment. Besides better capacity to simulate, and match with the observation, the results also demonstrate a successful discovery of the hidden physics in the pendulum dynamics using SciML.