A literature review on the safety assessment of genetically modified plants

In recent years, there has been a notable concern on the safety of genetically modified (GM) foods/plants, an important and complex area of research, which demands rigorous standards. Diverse groups including consumers and environmental Non Governmental Organizations (NGO) have suggested that all GM foods/plants should be subjected to long-term animal feeding studies before approval for human consumption. In 2000 and 2006, we reviewed the information published in international scientific journals, noting that the number of references concerning human and animal toxicological/health risks studies on GM foods/plants was very limited. The main goal of the present review was to assess the current state-of-the-art regarding the potential adverse effects/safety assessment of GM plants for human consumption. The number of citations found in databases (PubMed and Scopus) has dramatically increased since 2006. However, new information on products such as potatoes, cucumber, peas or tomatoes, among others was not available. Corn/maize, rice, and soybeans were included in the present review. An equilibrium in the number research groups suggesting, on the basis of their studies, that a number of varieties of GM products (mainly maize and soybeans) are as safe and nutritious as the respective conventional non-GM plant, and those raising still serious concerns, was currently observed. Nevertheless, it should be noted that most of these studies have been conducted by biotechnology companies responsible of commercializing these GM plants. These findings suggest a notable advance in comparison with the lack of studies published in recent years in scientific journals by those companies. All this recent information is herein critically reviewed.     

Phospholipid fatty acid biomarkers in a freshwater periphyton community exposed to uranium: discovery by non-linear statistical learning

Phospholipid fatty acids (PLFA) have been widely used to characterize environmental microbial communities, generating community profiles that can distinguish phylogenetic or functional groups within the community. The poor specificity of organism groups with fatty acid biomarkers in the classic PLFA-microorganism associations is a confounding factor in many of the statistical classification/clustering approaches traditionally used to interpret PLFA profiles. In this paper we demonstrate that non-linear statistical learning methods, such as a support vector machine (SVM), can more accurately find patterns related to uranyl nitrate exposure in a freshwater periphyton community than linear methods, such as partial least squares discriminant analysis. In addition, probabilistic models of exposure can be derived from the identified lipid biomarkers to demonstrate the potential model-based approach that could be used in remediation. The SVM probability model separates dose groups at accuracies of ∼87.0%, ∼71.4%, ∼87.5%, and 100% for the four groups; Control (non-amended system), low dose (amended at 10 μg U L⁻¹), medium dose (amended at 100 μg U L⁻¹), and high dose (500 μg U L⁻¹). The SVM model achieved an overall cross-validated classification accuracy of ∼87% in contrast to ∼59% for the best linear classifier.     

Inventory and vertical migration of 90Sr fallout and 137Cs/90Sr ratio in Spanish mainland soils

In this paper the inventory of ⁹⁰Sr in 34 points distributed along the Spanish peninsular territory is presented. Obtained values range between 173 Bq/m² and 2047 Bq/m². From these data set and those ¹³⁷Cs data obtained in a previous work the ¹³⁷Cs/⁹⁰Sr activity ratio has been established, laying this value between 0.9 and 3.6. Also the migration depth of both radionuclides has been analysed obtaining for ¹³⁷Cs an average value 57% lower than that obtained for ⁹⁰Sr.Additionally, this paper presents the results obtained in 11 sampling points in which the activity vertical profile has been measured. These profiles have been analysed to state the behaviour of strontium in soils and after, by using a convective-diffusive model, the parameters of the model which governs the vertical migration of ⁹⁰Sr in the soil, v (apparent convection velocity) and D (apparent diffusion coefficient) have been evaluated. Mean values obtained are 0.20 cm/year and 3.67 cm²/year, respectively.     

Geomorphometric study of the spatial organization of forest ecosystems

The use of an extended set of basic characteristics of the terrain topography for studying the spatial variation of a forest ecosystem has shown that it is significantly related to the terrain topography. The relationships with the topographic attributes determining the local hydrological and thermal conditions in the ecosystem has been paid special attention. Maps of ecosystem characteristics based on the observed relationships with topography have been calculated and drawn.     

Interaction of ant species in associations: An attempt to formalize behavioral characters

Behavioral adaptations of ant species were studied in associations of different biotopes in the Crimean Mountains. The pattern of an association was found to depend on the mode of the territorial behavior of dominant species, irrespective of their number. The dominance hierarchy was more strict in monodominant than in bidominant associations. Ant species demonstrated different behavioral strategies, plasticity of foraging, and avoidance of aggressive encounters. A method for formalizing interspecies relationships and a model describing stochastic properties of the biological system are proposed, which can be useful in solving various ethological and ecological problems.     

Assessment of Uncertainty in Long-Term Mass Balances for Acidification Assessments: A MAGIC Model Exercise

Long-term (1860–2010) catchment mass balance calculations rely on models and assumptions which are sources of uncertainty in acidification assessments. In this article, we report on an application of MAGIC to model acidification at the four Swedish IM forested catchments that have been subject to differing degrees of acidification stress. Uncertainties in the modeled mass balances were mainly associated with the deposition scenario and assumptions about sulfate adsorption and soil mass. Estimated base cation (BC) release rates (weathering) varied in a relatively narrow range of 47–62 or 42–47 meq m⁻² year⁻¹, depending on assumptions made about soil cation exchange capacity and base saturation. By varying aluminum solubility or introducing a dynamic weathering feedback that allowed BC release to increase at more acidic pHs, a systematic effect on predicted changes in acid neutralizing capacity (ΔANC ca. 10–41 μeq l⁻¹) and pH (ca. ΔpH = 0.1–0.6) at all sites was observed. More robust projections of future changes in pH and ANC are dependent on reducing uncertainties in BC release rates, the timing, and extent of natural acidification through BC uptake by plants, temporal changes in soil element pools, and fluxes of Al between compartments.     

Integrated biological responses of zebrafish (Danio rerio) to analyze water quality in regions under anthropogenic influence

This study analyzed water quality in regions around Patos lagoon (Southern Brazil) that are under anthropogenic pressure. Water samples were collected from five different sites, including one used as a source for human consumption (COR) and others known to be influenced by human activities (IP). Danio rerio (Teleostei, Cyprinidae) organisms were exposed for 24 h to these water samples, plus a control group. It was observed that: (1) reactive oxygen species levels were lower in COR and IP than in the control group; (2) glutamate-cysteine ligase (catalytic subunit) expression was higher in COR than in other sites; (3) exposure to all water samples affected long-term memory (LTM) when compared to control group. Thus, some water samples possess the ability to modulate the antioxidant system and to induce a decline in cognitive functions, as measured by LTM. The obtained results indicate that a combination of variables of different organization level (molecular, biochemical and behavioral) can be employed to analyze water quality in impacted regions.