Development of a new approach using mathematical modeling to predict cocktail effects of micropollutants of diverse origins.

A wide variety of micropollutants (MP) of diverse origins is present in waste and surface waters without knowing the effect of their combination on ecosystems and human. The impact of chemical mixtures is poorly documented and often limited to binary mixtures using MP of the same category. Knowing that it is not realistic to test every possible combination found in mixtures, we aimed to develop a new method helping to predict cocktail effects. Six chemicals of agriculture, industry or pharmaceutical origin were selected: cyproconazole, diuron, terbutryn, bisphenol A, diclofenac and tramadol. Individual MP were first used in vitro to determine the concentration at which 10% (Effective Concentration EC10) or 25% (EC25) of their maximal effect on human cytotoxicity was observed. Using an Orthogonal Array Composite Design (OACD), relevant complex mixtures were then tested. Multiple linear regression was applied for response surface modeling in order to evaluate and visualize the influence of the different MP in mixtures and their potential interactions. The comparison of the predicted values obtained using the response surface model with those obtained with the model of independent effects, evidenced that the hypothesis of independence was unjustified. The cocktail effect was further investigated by considering micropollutant response surfaces pairwise. It was deduced that there was a neutralizing effect between bisphenol A and tramadol. In conclusion, we propose a new method to predict within a complex mixture of MP the combinations likely involved in cocktail effects. The proposed methodology coupling experimental data acquisition and mathematical modeling can be applied to all kind of relevant bioassays using lower concentrations of MP. Situations at high ecological risk and potentially hazardous for humans will then be identified, which will allow to improve legislation and policies.

Analysis of occupational injuries in the sea fishing industry according to the type of fishery and the fishing activity.

BACKGROUND: Sea fishing is one of the most dangerous occupations. Numerous studies have already sought to evaluate the risk level of this occupation through the analysis of the frequency and seriousness of occupational injuries. The purpose of the present study is to analyse these accidents in terms of two main characteristics of the vessels involved: the fishery type (high seas, offshore, coastal, or inshore fishery) and the fishing activity (use of passive or active gears). MATERIALS AND METHODS: Injury rates were calculated for the Brittany region and for the year 2012. A second analysis was carried out on 8,286 reported injuries that occurred in France from 2002 to 2012, while vessels were in the process of fishing. RESULTS: This first analysis shows that the incidence rate is very high (103 per 1,000 full-time equivalent fishermen) and that it depends more on the fishery type than on the fishing activity; the highest rates concern the offshore and the coastal fleets. Results of the second analysis show that the nature of accidents depends more on the fishing activity than on the type of fishery. CONCLUSIONS: These findings lead to a discussion of the causes of the highest incidence rate values and the causes of the observed variations. The discussion also involves the methodological difficulties related to the incidence rate calculations.

Mid-infrared fibre evanescent wave spectroscopy of serum allows fingerprinting of the hepatic metabolic status in mice.

Non-alcoholic fatty liver disease is associated with obesity, diabetes, and metabolic syndrome. The detection of systemic metabolic changes associated with alterations in the liver status during non-alcoholic fatty liver disease could improve patient follow-up. The aim of the present study was to evaluate the potential of mid-infrared fibre evanescent wave spectroscopy as a minimum-invasive method for evaluating the liver status during non-alcoholic fatty liver disease. Seventy-five mice were subjected to a control, high-fat or high-fat-high carbohydrate diets. We analysed the serum biochemical parameters and mRNA levels of hepatic genes by quantitative RT-PCR. Steatosis was quantified by image analysis. The mid-infrared spectra were acquired from serum, and then analysed to develop a predictive model of the steatosis level. Animals subjected to enriched diets were obese. Hepatic steatosis was found in all animals. The relationship between the spectroscopy-predicted and observed levels of steatosis, expressed as percentages of the liver biopsy area, was not linear. A transition around 10% steatosis was observed, leading us to consider two distinct predictive models (<10% and >10%) based on two different sets of discriminative spectral variables. The model performance was evaluated using random cross-validation (10%). The hypothesis that additional metabolic changes occur beyond this transition was supported by the fact that it was associated with increased serum ALT levels, and Col1α1 chain mRNA levels. Our data suggest that mid-infrared spectroscopy combined with statistical analysis allows identifying serum mid-infrared signatures that reflect the liver status during non-alcoholic fatty liver disease.

Human and organisational factors in maritime accidents: analysis of collisions at sea using the HFACS.

Over the last decade, the shipping industry has implemented a number of measures aimed at improving its safety level (such as new regulations or new forms of team training). Despite this evolution, shipping accidents, and particularly collisions, remain a major concern. This paper presents a modified version of the Human Factors Analysis and Classification System, which has been adapted to the maritime context and used to analyse human and organisational factors in collisions reported by the Marine Accident and Investigation Branch (UK) and the Transportation Safety Board (Canada). The analysis shows that most collisions are due to decision errors. At the precondition level, it highlights the importance of the following factors: poor visibility and misuse of instruments (environmental factors), loss of situation awareness or deficit of attention (conditions of operators), deficits in inter-ship communications or Bridge Resource Management (personnel factors). At the leadership level, the analysis reveals the frequent planning of inappropriate operations and non-compliance with the Safety Management System (SMS). The Multiple Accident Analysis provides an important finding concerning three classes of accidents. Inter-ship communications problems and Bridge Resource Management deficiencies are closely linked to collisions occurring in restricted waters and involving pilot-carrying vessels. Another class of collisions is associated with situations of poor visibility, in open sea, and shows deficiencies at every level of the socio-technical system (technical environment, condition of operators, leadership level, and organisational level). The third class is characterised by non-compliance with the SMS. This study shows the importance of Bridge Resource Management for situations of navigation with a pilot on board in restricted waters. It also points out the necessity to investigate, for situations of navigation in open sea, the masters' decisions in critical conditions as well as the causes of non-compliance with SMS.