Fate and transport modelling for evaluating antibiotic resistance in aquatic environments: Current knowledge and research priorities.

Antibiotics have revolutionised medicine in the last century and enabled the prevention of bacterial infections that were previously deemed untreatable. However, in parallel, bacteria have increasingly developed resistance to antibiotics through various mechanisms. When resistant bacteria find their way into terrestrial and aquatic environments, animal and human exposures increase, e.g., via polluted soil, food, and water, and health risks multiply. Understanding the fate and transport of antibiotic resistant bacteria (ARB) and the transfer mechanisms of antibiotic resistance genes (ARGs) in aquatic environments is critical for evaluating and mitigating the risks of resistant-induced infections. The conceptual understanding of sources and pathways of antibiotics, ARB, and ARGs from society to the water environments is essential for setting the scene and developing an appropriate framework for modelling. Various factors and processes associated with hydrology, ecology, and climate change can significantly affect the fate and transport of ARB and ARGs in natural environments. This article reviews current knowledge, research gaps, and priorities for developing water quality models to assess the fate and transport of ARB and ARGs. The paper also provides inputs on future research needs, especially the need for new predictive models to guide risk assessment on AR transmission and spread in aquatic environments.

Modeling transport of antibiotic resistant bacteria in aquatic environment using stochastic differential equations.

Contaminated sites are recognized as the "hotspot" for the development and spread of antibiotic resistance in environmental bacteria. It is very challenging to understand mechanism of development of antibiotic resistance in polluted environment in the presence of different anthropogenic pollutants. Uncertainties in the environmental processes adds complexity to the development of resistance. This study attempts to develop mathematical model by using stochastic partial differential equations for the transport of fluoroquinolone and its resistant bacteria in riverine environment. Poisson's process is assumed for the diffusion approximation in the stochastic partial differential equations (SPDE). Sensitive analysis is performed to evaluate the parameters and variables for their influence over the model outcome. Based on their sensitivity, the model parameters and variables are chosen and classified into environmental, demographic, and anthropogenic categories to investigate the sources of stochasticity. Stochastic partial differential equations are formulated for the state variables in the model. This SPDE model is then applied to the 100 km stretch of river Musi (South India) and simulations are carried out to assess the impact of stochasticity in model variables on the resistant bacteria population in sediments. By employing the stochasticity in model variables and parameters we came to know that environmental and anthropogenic variations are not able to affect the resistance dynamics at all. Demographic variations are able to affect the distribution of resistant bacteria population uniformly with standard deviation between 0.087 and 0.084, however, is not significant to have any biological relevance to it. The outcome of the present study is helpful in simplifying the model for practical applications. This study is an ongoing effort to improve the model for the transport of antibiotics and transport of antibiotic resistant bacteria in polluted river. There is a wide gap between the knowledge of stochastic resistant bacterial growth dynamics and the knowledge of transport of antibiotic resistance in polluted aquatic environment, this study is one step towards filling up that gap.

Mathematical model for the transport of fluoroquinolone and its resistant bacteria in aquatic environment.

Development of antibiotic resistance in environmental bacteria is a direct threat to public health. Therefore, it becomes necessary to understand the fate and transport of antibiotic and its resistant bacteria. This paper presents a mathematical model for spatial and temporal transport of fluoroquinolone and its resistant bacteria in the aquatic environment of the river. The model includes state variables for organic matter, fluoroquinolone, heavy metals, and susceptible and resistant bacteria in the water column and sediment bed. Resistant gene is the factor which makes bacteria resistant to a particular antibiotic and is majorly carried on plasmids. Plasmid-mediated resistance genes are transferable between different bacterial species through conjugation (horizontal resistance transfer). This model includes plasmid dynamics between susceptible and resistant bacteria by considering the rate of horizontal resistance gene transfer among bacteria and the rate of losing resistance (segregation). The model describes processes which comprise of advection, dispersion, degradation, adsorption, diffusion, settling, resuspension, microbial growth, segregation, and transfer of resistance genes. The mathematical equations were solved by using numerical methods (implicit-explicit scheme) with appropriate boundary conditions. The development of the present model was motivated by the fact that the Musi River is heavily impacted by antibiotic pollution which led to the development of antibiotic resistance in its aquatic environment. The model was simulated for hypothetical pollution scenarios to predict the future conditions under various pollution management alternatives. The simulation results of the model for different cases show that the concentration of antibiotic, the concentration of organic matter, segregation rate, and horizontal transfer rate are the governing factors in the variation of population density of resistant bacteria. The treatment of effluents for antibiotics might be costly for the bulk drug manufacturing industries, but the guidelines can be made to reduce the organic matter which can limit the growth rate of microbes and reduce the total microbial population in the river. The reduction in antibiotic concentration can reduce the selection pressure on bacteria and can limit the population of resistant culture and its influence zone in the river stretch; however, complete removal of antibiotics may not result in complete elimination of antibiotic-resistant bacteria.

Prevalence of use of advance directives, health care proxy, legal guardian, and living will in 512 patients hospitalized in a cardiac care unit/intensive care unit in 2 community hospitals.

INTRODUCTION: The prevalence of use of any advance directives was 26% in 112 patients hospitalized in a cardiac care unit (CCU)/intensive care unit (ICU) in an academic medical center. MATERIAL AND METHODS: We investigated in 2 community hospitals the prevalence of use of advance directives (AD), health care proxy (HCP), legal guardian (LG), and living will (LW) in 512 patients hospitalized in a CCU/ ICU approached for AD and HCP. RESULTS: The use of AD was 22%, of HCP was 19%, of LG was 16%, and of LW was 5%. CONCLUSIONS: The use of AD was 22%, of HCP was 19%, of LG was 16%, and of LW was 5% in patients hospitalized in a CCU/ICU. Educational programs on use of AD and of HCP need to be part of cardiovascular training programs and of cardiovascular continuing medical education.

Kounis syndrome secondary to ibuprofen use.

Kounis syndrome is the coincidental occurrence of acute coronary syndromes with allergic or hypersensitivity reactions. Clinicians should be aware that various mediators of allergy can cause coronary spasm and even plaque rupture and thrombus formation, thereby causing a serious impact on the course, prognosis and management of the allergic reaction. We report a case of a 20 year old female who developed acute coronary syndrome after anaphylactic reaction to ibuprofen.