The development of antibiotic resistance of bacteria is one of the most pressing problems in world health care. One of the promising ways to overcome microbial resistance to antibiotics is the use of metal nanoparticles and their oxides. In particular, numerous studies have shown the high antibacterial potential of zinc oxide nanoparticles (ZnO-NP) in relation to gram-positive and gram-negative bacteria. This mini-review includes an analysis of the results of studies in recent years aimed at studying the antibacterial activity of nanoparticles based on zinc oxide. The dependence of the antibacterial effect on the size of the applied nanoparticles in relation to E. coli and S. aureus is given. The influence of various ways of synthesis of zinc oxide nanoparticles and the main types of modifications of NP-ZnO to increase the antibacterial efficiency are also considered.

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The use of metal oxide nanoparticles is one of the promising ways for overcoming antibiotic resistance in bacteria. Iron oxide nanoparticles (IONPs) have found wide applications in different fields of biomedicine. Several studies have suggested using the antimicrobial potential of IONPs. Iron is one of the key microelements and plays an important role in the function of living systems of different hierarchies. Iron abundance and its physiological functions bring into question the ability of iron compounds at the same concentrations, on the one hand, to inhibit the microbial growth and, on the other hand, to positively affect mammalian cells. At present, multiple studies have been published that show the antimicrobial effect of IONPs against Gram-negative and Gram-positive bacteria and fungi. Several studies have established that IONPs have a low toxicity to eukaryotic cells. It gives hope that IONPs can be considered potential antimicrobial agents of the new generation that combine antimicrobial action and high biocompatibility with the human body. This review is intended to inform readers about the available data on the antimicrobial properties of IONPs, a range of susceptible bacteria, mechanisms of the antibacterial action, dependence of the antibacterial action of IONPs on the method for synthesis, and the biocompatibility of IONPs with eukaryotic cells and tissues.

This paper addresses interactions among foraging behavior, habitat preferences, site characteristics, and spatial distribution of contaminants in developing PCB exposure estimates for winter flounder at a hypothetical open water dredged material disposal site in the coastal waters of New York and New Jersey (NY-NJ). The implications of these interactions for human health risk estimates for local recreational anglers who fish for and eat flounder are described. The models implemented in this study include a spatial submodel to account for spatial and temporal characteristics of fish exposures and a probabilistic adaptation of the Gobas bioaccumulation model that accounts for temporal variation in concentrations of hydrophobic contaminants in sediment and water. We estimated the geographic distribution of a winter flounder subpopulation offshore of NY-NJ based on species biology and its vulnerability to local recreational fishing, the foraging area of individual fish, and their migration patterns. We incorporated these parameters and an estimate of differential attraction to a management site into a spatially explicit model to assess the range of exposures within the population. The output of this modeling effort, flounder PCB tissue concentrations, provided exposure point concentrations for an estimate of human health risk through ingestion of locally caught flounder. The risks obtained for the spatially nonexplicit case are as much as 1 order of magnitude higher than those obtained with explicit consideration of spatial and temporal characteristics of winter flounder foraging and seasonal migration. This practice of "defaulting" to extremely conservative estimates for exposure parameters in the face of uncertainty ill serves the decision-making process for management of contaminated sediments in general and specifically for disposal of dredged materials. Consideration of realistic spatial and temporal scales in food chain models can help support sediment management decisions by providing a quantitative expression of the confidence in risk estimates.

The treatment of uncertainties associated with modeling and risk assessment has recently attracted significant attention. The methodology and guidance for dealing with parameter uncertainty have been fairly well developed and quantitative tools such as Monte Carlo modeling are often recommended. However, the issue of model uncertainty is still rarely addressed in practical applications of risk assessment. The use of several alternative models to derive a range of model outputs or risks is one of a few available techniques. This article addresses the often-overlooked issue of what we call "modeler uncertainty," i.e., difference in problem formulation, model implementation, and parameter selection originating from subjective interpretation of the problem at hand. This study uses results from the Fruit Working Group, which was created under the International Atomic Energy Agency (IAEA) BIOMASS program (BIOsphere Modeling and ASSessment). Model-model and model-data intercomparisons reviewed in this study were conducted by the working group for a total of three different scenarios. The greatest uncertainty was found to result from modelers' interpretation of scenarios and approximations made by modelers. In scenarios that were unclear for modelers, the initial differences in model predictions were as high as seven orders of magnitude. Only after several meetings and discussions about specific assumptions did the differences in predictions by various models merge. Our study shows that parameter uncertainty (as evaluated by a probabilistic Monte Carlo assessment) may have contributed over one order of magnitude to the overall modeling uncertainty. The final model predictions ranged between one and three orders of magnitude, depending on the specific scenario. This study illustrates the importance of problem formulation and implementation of an analytic-deliberative process in risk characterization.