Deep dive into the chronic toxicity of tyre particle mixtures and their leachates.

This is the final version. Available from Elsevier via the DOI in this record. Data Availability: Data will be made available on request.Particles from the tread of vehicle tyres are a global pollutant, which are emitted into the environment at an approximate rate of 1.4 kg.year-1 for an average passenger-car. In this study, popular tyre brands were used to generate a tyre tread microparticle mixture. The chronic toxicity of both particles and chemical leachates were compared on a planktonic test species (Daphnia magna). Over 21 days of exposure, pristine tyre tread microparticles were more toxic (LC50 60 mg.L-1) than chemical lechates alone (LC50 542 mg.L-1). Microparticles and leachates showed distinct effects on reproduction and morphological development at environmentally relevant concentrations, with dose-dependent uptake of particles visible in the digestive tract. Chemical characterization of leachates revealed a metal predominance of zinc, titanium, and strontium. Of the numerous organic chemicals present, at least 54 were shared across all 5 tyre brands, with many classified to be very toxic. Our results provide a critically needed information on the toxicity of tyre tread particles and the associated chemicals that leach from them to inform future mitigation measures. We conclude that tyre particles are hazardous pollutants of particular concern that are close to or possibly above chronic environmental safety limits in some locations.Natural Environment Research Council (NERC

Gamma estimator of Jarzynski equality for recovering binding energies from noisy dynamic data sets

A fundamental problem in thermodynamics is the recovery of macroscopic equilibrated interaction energies from experimentally measured single-molecular interactions. The Jarzynski equality forms a theoretical basis in recovering the free energy difference between two states from exponentially averaged work performed to switch the states. In practice, the exponentially averaged work value is estimated as the mean of finite samples. Numerical simulations have shown that samples having thousands of measurements are not large enough for the mean to converge when the fluctuation of external work is above 4 kBT, which is easily observable in biomolecular interactions. We report the first example of a statistical gamma work distribution applied to single molecule pulling experiments. The Gibbs free energy of surface adsorption can be accurately evaluated even for a small sample size. The values obtained are comparable to those derived from multi-parametric surface plasmon resonance measurements and molecular dynamics simulations

Modeling the Lag Time of Listeria monocytogenes from Viable Count Enumeration and Optical Density Data

The following two factors significantly influence estimates of the maximum specific growth rate (μ(max)) and the lag-phase duration (λ): (i) the technique used to monitor bacterial growth and (ii) the model fitted to estimate parameters. In this study, nine strains of Listeria monocytogenes were monitored simultaneously by optical density (OD) analysis and by viable count enumeration (VCE) analysis. Four usual growth models were fitted to our data, and estimates of growth parameters were compared from one model to another and from one monitoring technique to another. Our results show that growth parameter estimates depended on the model used to fit data, whereas there were no systematic variations in the estimates of μ(max) and λ when the estimates were based on OD data instead of VCE data. By studying the evolution of OD and VCE simultaneously, we found that while log OD/VCE remained constant for some of our experiments, a visible linear increase occurred during the lag phase for other experiments. We developed a global model that fits both OD and VCE data. This model enabled us to detect for some of our strains an increase in OD during the lag phase. If not taken into account, this phenomenon may lead to an underestimate of λ

Application of a temperature-dependent von Bertalanffy growth model to bullhead Cottus gobio

International audienc

Recommendations for the analysis of hemocyte-related immunocompetent oxidative activity in the freshwater snail Lymnaea stagnalis

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Modeling and Predicting the Simultaneous Growth of Escherichia coli O157:H7 and Ground Beef Background Microflora for Various Enrichment Protocols

The simultaneous growth of Escherichia coli O157:H7 (O157) and the ground beef background microflora (BM) was described in order to characterize the effects of enrichment factors on the growth of these organisms. The different enrichment factors studied were basal medium (Trypticase soy broth and E. coli broth), the presence of novobiocin in the broth, and the incubation temperature (37°C or 40°C). BM and O157 kinetics were simultaneously fitted by using a competitive growth model. The simple competition between the two microfloras implied that O157 growth stopped as soon as the maximal bacterial density in the BM was reached. The present study shows that the enrichment protocol factors had little impact on the simultaneous growth of BM and O157. The selective factors (i.e., bile salts and novobiocin) and the higher incubation temperature (40°C) did not inhibit BM growth, and incubation at 40°C only slightly improved O157 growth. The results also emphasize that when the level of O157 contamination in ground beef is low, the 6-h enrichment step recommended in the immunomagnetic separation protocol (ISO EN 16654) is not sufficient to detect O157 by screening methods. In this case, prior enrichment for approximately 10 h appears to be the optimal duration for enrichment. However, more experiments must be carried out with ground beef packaged in different ways in order to confirm the results obtained in the present study for non-vacuum- and non-modified-atmosphere-packed ground beef

Strain- and serotype-dependent affinity of Shiga toxin-producing Escherichia coli for bovine milk fat globules

International audienceShiga toxin-producing Escherichia coli (STEC) are widely detected in raw milk products intended for hu-man consumption. Although STEC are a worldwide public health problem, the pathogenicity of STEC in cheese remains unclear. In fact, bacterial association with compounds in raw milk cheeses could reduce their pathogenicity. A previous study showed the association of 2 STEC strains with raw milk cream in a natural creaming assay. Different concentrations of each strain were required to saturate the cream. In this study, we hypothesized that all STEC strains could be associated with milk fat globules (MFG) in raw milk and that the bacterial load required for saturation of the cream is serotype dependent. We evaluated the affinity of STEC strains belonging to the O157:H7, O26: H11, and O103:H2 serotypes for bovine raw milk cream and ana-lyzed saturation of the cream layer by natural creaming assay. We used 12 STEC strains and 3 strains belonging to another pathotype to assess the effects of serotypes on this phenomenon. We performed sucrose density gra-dient centrifugation assays with 2 STEC model strains to confirm the results obtained by natural creaming. The localization of STEC within MFG-enriched creams was observed by confocal and electron microscopy. We recovered approximately 10 times more STEC from the cream layer after natural creaming than from raw bovine milk. The concentration of STEC required to saturate the cream layer (the saturation concentration) was estimated for each strain by nonlinear regression, highlighting a strain and serotype effect. Moreover, the concentration of STEC in the cream was milk fat level dependent. However, even in nonsaturating conditions, a high level of STEC was still present in the aque-ous phase, after fat separation. Thus, natural creaming should not be used as the sole preventive measure to remove STEC from naturally contaminated raw milk. The results of our study suggest that cream saturation is a complex mechanism, most likely involving specific interactions between STEC and raw MFG