DNA damage in mouse organs and in human sperm cells by bisphenol A

Abstract

The in vivo genotoxic potential of bisphenol A using the comet assay in mice and in human sperm cells in vitro without metabolizing enzymes was studied. Male mice were exposed by oral gavage to the following doses of bisphenol A (0 125, 250 and 500?mg/kg body weight). DNA damage was investigated in liver, kidney, testes, urinary bladder, colon and lungs cells. In testicular cells, a significant increase in DNA strand breaks was observed in the lowest, but not in the medium or highest dose groups. Histopathological investigation of the testicular samples did not show any treatment dose-related effects. No DNA strand breaks were observed in any of the other investigated tissues. In human sperm cells in vitro, bisphenol A did not induce DNA strand breaks.     

Accounting for matching uncertainty in two stage capture–recapture experiments using photographic measurements of natural marks

We propose a Bayesian hierarchical modeling approach for estimating the size of a closed population from data obtained by identifying individuals through photographs of natural markings. We assume that noisy measurements of a set of distinctive features are available for each individual present in a photographic catalogue. To estimate the population size from two catalogues obtained during two different sampling occasions, we embed the standard two-stage $M_t$ capture–recapture model for closed population into a multivariate normal data matching model that identifies the common individuals across the catalogues. In addition to estimating the population size while accounting for the matching process uncertainty, this hierarchical modelling approach allows to identify the common individuals by using the information provided by the capture–recapture model. This way, our model also represents a novel and reliable tool able to reduce the amount of effort researchers have to expend in matching individuals. We illustrate and motivate the proposed approach via a real data set of photo-identification of narwhals. Moreover, we compare our method with a set of possible alternative approaches by using both the empirical data set and a simulation study.     

Solvent-free sampling with di-n-butylamine for monitoring of isocyanates in air

The solvent-free sampler for airborne isocyanates consisted of a polypropylene tube with an inner wall coated with a glass fibre filter, coupled in series with a 13 mm glass fibre filter. The filters were impregnated with reagent solution containing equimolar amounts of di-n-butylamine (DBA) and acetic acid. Air sampling was performed with an air flow of 0.2 l min(-1). The formed isocyanate-DBA derivatives were determined using liquid chromatography and tandem mass spectrometry. The sampler was investigated in regard to collection principle and extraction of the formed derivatives with good results. The possibility to store the sampler before sampling and to perform long-term sampling was demonstrated. Field extraction of the sampler was not necessary, as there was no difference between immediately extracted samples and stored ones (2 days). In comparative studies, the sampler was evaluated against a reference method, impinger-filter sampling with DBA as reagent. The ratios between the results obtained with the sampler and the reference in a test chamber at a relative humidity (RH) of 45% was in the range of 83-109% for isocyanates formed during thermal decomposition of PUR. At RH 95%, the range was 72-101% with the exception of isocyanic acid. In two field evaluations, the ratios for fast curing 2,4'- and 4,4'-methylene bisphenyl diisocyanate (MDI) was in the range 81-113% and for the 3-ring MDI the range was 54-70%. For the slower curing 1,6-hexamethylene diisocyanate (HDI) and HDI isocyanurate, the ratios were in the range 78-145%. In conclusion, the solvent-free sampler is a convenient alternative in most applications to the more cumbersome impinger-filter sampler.     

Effect of temperature on biogeochemistry of marine organic-enriched systems: implications in a global warming scenario

Coastal biogeochemical cycles are expected to be affected by global warming. By means of a mesocosm experiment, the effect of increased water temperature on the biogeochemical cycles of coastal sediments affected by organic-matter enrichment was tested, focusing on the carbon, sulfur, and iron cycles. Nereis diversicolor was used as a model species to simulate macrofaunal bioirrigation activity in natural sediments. Although bioirrigation rates of N. diversicolor were not temperature dependent, temperature did have a major effect on the sediment metabolism. Under organic-enrichment conditions, the increase in sediment metabolism was greater than expected and occurred through the enhancement of anaerobic metabolic pathway rates, mainly sulfate reduction. There was a twofold increase in sediment metabolism and the accumulation of reduced sulfur. The increase in the benthic metabolism was maintained by the supply of electron acceptors through bioirrigation and as a result of the availability of iron in the sediment. As long as the sediment buffering capacity toward sulfides is not surpassed, an increase in temperature might promote the recovery of organic-enriched sediments by decreasing the time for mineralization of excess organic matter.     

Plants control the seasonal dynamics of microbial N cycling in a beech forest soil by belowground C allocation

Soil microbes in temperate forest ecosystems are able to cycle several hundreds of kilograms of N per hectare per year and are therefore of paramount importance for N retention. Belowground C allocation by trees is an important driver of seasonal microbial dynamics and may thus directly affect N transformation processes over the course of the year. Our study aimed at unraveling plant controls on soil N cycling in a temperate beech forest at a high temporal resolution over a time period of two years, by investigating the effects of tree girdling on microbial N turnover. In both years of the experiment, we discovered (1) a summer N mineralization phase (between July and August) and (2) a winter N immobilization phase (November-February). The summer mineralization phase was characterized by a high N mineralization activity, low microbial N uptake, and a subsequent high N availability in the soil. During the autumn/winter N immobilization phase, gross N mineralization rates were low, and microbial N uptake exceeded microbial N mineralization, which led to high levels of N in the microbial biomass and low N availability in the soil. The observed immobilization phase during the winter may play a crucial role for ecosystem functioning, since it could protect dissolved N that is produced by autumn litter degradation from being lost from the ecosystem during the phase when plants are mostly inactive. The difference between microbial biomass N levels in winter and spring equals 38 kg N/ha and may thus account for almost one-third of the annual plant N demand. Tree girdling strongly affected annual N cycling: the winter N immobilization phase disappeared in girdled plots (microbial N uptake and microbial biomass N were significantly reduced, while the amount of available N in the soil solution was enhanced). This was correlated to a reduced fungal abundance in autumn in girdled plots. By releasing recently fixed photosynthates to the soil, plants may thus actively control the annual microbial N cycle. Tree belowground C allocation increases N accumulation in microorganisms during the winter which may ultimately feed back on plant N availability in the following growing season.     

Definition and calculation of uncertainty in ecological process models

We present a method of multi-criteria assessment for the analysis of process model uncertainty that combines analysis of model structure, parameters and data requirements. There are three components in calculation and definition of uncertainty.

(1)

Assessment criteria: Uncertainty in a process model is reduced as the model can simultaneously simulate an increased number of assessment criteria selected to test specific aspects of the theory being investigated, and within acceptable limits set for those criteria. This reduces incomplete specification of the model—the characteristic that a model may explain some, but not all, of the observed features of a phenomenon. The calculation required is computation of the Pareto set which provides the list of simultaneously achieved criteria within specified ranges.     

Integrated catchment modeling for nutrient reduction: scenarios showing impacts, potential, and cost of measures

A hydrological-based model (HBV-NP) was applied to a catchment (1900 km2) in the southern part of Sweden. Careful characterization of the present load situation and the potential for improved treatment or reduced soil leaching were analyzed. Several scenarios were modeled to find strategies to reach the Swedish environmental goals of reducing anthropogenic nitrogen load by 30% and phosphorus load by 20%. It was stated that the goals could be reached by different approaches that would affect different polluters and social sectors. However, no single measure was enough by itself. Instead, a combination of measures was necessary to achieve the goals. The nitrogen goal was the most difficult to attain. In order to be cost-effective, these measures should be applied to areas contributing the most to the net loading of the sea. This strategy could reduce the costs by 70%-80% when compared with implementing the measures in the entire catchment. Integrated catchment models may thus be helpful tools for reducing costs in environmental control programs.     

Using multi-objective classification to model communities of soil microarthropods

In agricultural soil, a suite of anthropogenic events shape the ecosystem processes and populations. However, the impact from anthropogenic sources on the soil environment is almost exclusively assessed for chemicals, although other factors like crop and tillage practices have an important impact as well. Thus, the farming system as a whole should be evaluated and ranked according to its environmental benefits and impacts. Our starting point is a data set describing agricultural events and soil biological parameters. Using machine learning methods for inducing regression and model trees, we produce empirical models able to predict the soil quality from agricultural measures in terms of quantities describing the soil microarthropod community. We are also interested in discovering additional higher level knowledge. In particular, we have identified the most important factors influencing the population densities of springtails and mites and their biodiversity. We also identify to which agricultural actions different microarthropods react distinctly. To obtain this higher level knowledge, we employ multi-objective regression trees.     

Future agriculture with minimized phosphorus losses to waters: Research needs and direction

The series of papers in this issue of AMBIO represent technical presentations made at the 7th International Phosphorus Workshop (IPW7), held in September, 2013 in Uppsala, Sweden. At that meeting, the 150 delegates were involved in round table discussions on major, predetermined themes facing the management of agricultural phosphorus (P) for optimum production goals with minimal water quality impairment. The six themes were (1) P management in a changing world; (2) transport pathways of P from soil to water; (3) monitoring, modeling, and communication; (4) importance of manure and agricultural production systems for P management; (5) identification of appropriate mitigation measures for reduction of P loss; and (6) implementation of mitigation strategies to reduce P loss. This paper details the major challenges and research needs that were identified for each theme and identifies a future roadmap for catchment management that cost-effectively minimizes P loss from agricultural activities.