Validation of the dynamic direct exposure method for toxicity testing of diesel exhaust in vitro

Finding a Direct Method for a Dynamic Process: The DD (Direct and Dynamic) Cell-Tox Method

The main focus of in vitro toxicity assessment methods is to assess the viability of the cells, which is usually based on metabolism changes. Yet, when exposed to toxic substances, the cell triggers multiple signals in response. With this in mind, we have developed a promising cell-based toxicity method that observes various cell responses when exposed to toxic substances (either death, division, or remain viable). Based on the collective cell response, we observed and predicted the dynamics of the cell population to determine the toxicity of the toxicant. The method was tested with two different conformations: In the first conformation, we exposed a monoculture model of blood macrophages to UV light, hydrogen peroxide, nutrient deprivation, tetrabromobisphenol A, fatty acids, and 5-fluorouracil. In the second, we exposed a coculture liver model consisting of hepatocytes, hepatic stellate cells, Kupffer cells, and liver sinusoidal endothelial cells to rifampicin, ibuprofen, and 5-fluorouracil. The method showed good accuracy compared to established toxicity assessment methods. In addition, this approach provided more representative information on the toxic effects of the compounds, as it considers the different cellular responses induced by toxic agents.

In vitro exposure to complete engine emissions - a mini-review

Outdoor air pollution is classified as carcinogenic to humans and exposure to it contributes to increased incidence of various diseases, including cardiovascular, neurological or pulmonary disorders. Vehicle engine emissions represent a significant part of outdoor air pollutants, particularly in large cities with high population density. Considering the potentially negative health impacts of engine emissions exposure, the application of reliable test systems allowing assessment of the biological effects of these pollutants is crucial. The exposure systems should use relevant, preferably multicellular, cell models that are treated with the complete engine exhaust (i.e. a realistic mixture of particles, chemical compounds bound to them and gaseous phase) at the air-liquid interface. The controlled delivery and characterization of chemical and/or particle composition of the exhaust should be possible. In this mini-review we report on such exposure systems that have been developed to date. We focus on a brief description and technical characterization of the systems, and discuss the biological parameters detected following exposure to a gasoline/diesel exhaust. Finally, we summarize and compare findings from the individual systems, including their advantages/limitations.

E-cigarette aerosol induced cytotoxicity, DNA damages and late apoptosis in dynamically exposed A549 cells

In this study, the acute toxicological impacts associated with electronic cigarettes consumption were determined using a novel dynamic exposure methodology. The methodology was deployed to test various e-cigarette generated aerosols in A549 cell cultures. The e-liquid chemical profiling was achieved using GC-MS analysis while toxicity of diluted e-liquids aerosols was reported using numerous cytotoxicity assays. The presented findings pointed to acute aerosol exposure (thirty puffs at 40 W of power and higher) inducing significant cytotoxic, genotoxic, and apoptotic induction in exposed cells. These findings highlighted the significant risks posed by e-cigarette usage. The proposed methodology proved to be a useful tool for future screening of e-liquids generated aerosols toxicity. Future research is needed to establish the chronic toxicity resulting from long-term e-cigarette consumption.

Develop dynamic model for predicting traffic CO emissions in urban areas

The greater the use of energy in the transportation sectors, the higher the emission of carbon monoxide (CO), and hence inevitable harm to environment and human health. In this concern, measuring and predicting of CO emission from transportation sector-especially large cities-is important as it constitute 90 % of all CO emission. Many urban cities in developing world have not properly experienced such measurements or predictions. In this paper, for the first time, field measurements of traffic characteristics data and corresponding CO concentration have been performed for developing a model for predicting CO emissions from transportation sector for New Borg El Arab (NBC), Egypt. The performance of Swiss-German Handbook Emission Factors for Road Transport (HBEFA v3.1) model has been assessed for predicting the CO concentration at roadside in the study area. Results indicated that HBEFA v3.1 underestimate emission figures. The developed CO dynamic emission model involves the traffic flow characteristics with roadside CO concentrations. Acceptable representation of measured CO concentration has been shown by the developed dynamic CO emission model which introduces R (2) = 0.77, mean biases and frictional biases of -0.27 mg m(-3) and 0.09, respectively. A comparison between predicted CO concentrations using HBEFA v3.1 and the promoted dynamic model indicate that HBEFA v3.1 estimates CO emission concentrations in the study area with a mean error and frictional biases 159.26 and 233.33 %, respectively, higher than those of the developed model.

Toxicological perspectives of inhaled therapeutics and nanoparticles

INTRODUCTION

The human respiratory system is an important route for the entry of inhaled therapeutics into the body to treat diseases. Inhaled materials may consist of gases, vapours, aerosols and particulates. In all cases, assessing the toxicological effect of inhaled therapeutics has many challenges.

AREAS COVERED

This article provides an overview of in vivo and in vitro models for testing the toxicity of inhaled therapeutics and nanoparticles implemented in drug delivery. Traditionally, inhalation toxicity has been performed on test animals to identify the median lethal concentration of airborne materials. Later maximum tolerable concentration denoted by LC0 has been introduced as a more ethically acceptable end point. More recently, in vitro methods have been developed, allowing the direct exposure of airborne material to cultured human target cells on permeable porous membranes at the air-liquid interface.

EXPERT OPINION

Modifications of current inhalation therapies, new pulmonary medications for respiratory diseases and implementation of the respiratory tract for systemic drug delivery are providing new challenges when conducting well-designed inhalation toxicology studies. In particular, the area of nanoparticles and nanocarriers is of critical toxicological concern. There is a need to develop toxicological test models, which characterise the toxic response and cellular interaction between inhaled particles and the respiratory system.

Toxicological assessment of inhaled nanoparticles: role of in vivo, ex vivo, in vitro, and in silico studies

The alveolar epithelium of the lung is by far the most permeable epithelial barrier of the human body. The risk for adverse effects by inhaled nanoparticles (NPs) depends on their hazard (negative action on cells and organism) and on exposure (concentration in the inhaled air and pattern of deposition in the lung). With the development of advanced in vitro models, not only in vivo, but also cellular studies can be used for toxicological testing. Advanced in vitro studies use combinations of cells cultured in the air-liquid interface. These cultures are useful for particle uptake and mechanistic studies. Whole-body, nose-only, and lung-only exposures of animals could help to determine retention of NPs in the body. Both approaches also have their limitations; cellular studies cannot mimic the entire organism and data obtained by inhalation exposure of rodents have limitations due to differences in the respiratory system from that of humans. Simulation programs for lung deposition in humans could help to determine the relevance of the biological findings. Combination of biological data generated in different biological models and in silico modeling appears suitable for a realistic estimation of potential risks by inhalation exposure to NPs.