Nanoscale Zero-Valent Iron Has Minimum Toxicological Risk on the Germination and Early Growth of Two Grass Species with Potential for Phytostabilization

Two Poaceae species, Agrostis capillaris and Festuca rubra, were selected for their potential as phytostabilizing plants in multicontaminated soils. These species are resistant to contamination and maintain high concentrations of contaminants at the root level. Nanoscale zero-valent iron (nZVI) is an engineered nanomaterial with the ability to stabilize metal(loid)s in soils; its potential toxicological effects in the selected species were studied in a germination test using: (i) control variant without soil; (ii) soil contaminated with Pb and Zn; and (iii) contaminated soil amended with 1% nZVI, as well as in an hydroponic experiment with the addition of nZVI 0, 25, 50 and 100 mg L−1. nZVI had no negative effects on seed germination or seedling growth, but was associated with an increase in shoot growth and reduction of the elongation inhibition rate (root-dependent) of F. rubra seedlings. However, applications of nZVI in the hydroponic solution had no effects on F. rubra but A. capillaris developed longer roots and more biomass. Increasing nZVI concentrations in the growing solution increased Mg and Fe uptake and reduced the Fe translocation factor. Our results indicate that nZVI has few toxic effects on the studied species

Cyanobacteria of the thermal spring at Pancharevo, Sofia, Bulgaria

Eight taxa of cyanobacteria were identified in the thermal spring at Pancharevo (in the Sofia basin, Bulgaria). As well as the widespread Lyngbya thermalis, Phormidesmis molle (syn. Phormidium molle), Phormidium papyraceum, Phormidium corium and Mastigocladus laminosus, four species were identified for the first time in Bulgaria: Calothrix thermalis, Gloeocapsa gelatinosa, Leibleinia epiphytica and Symploca thermalis

Semiparametric Multivariate Accelerated Failure Time Model with Generalized Estimating Equations

The semiparametric accelerated failure time model is not as widely used as the Cox relative risk model mainly due to computational difficulties. Recent developments in least squares estimation and induced smoothing estimating equations provide promising tools to make the accelerate failure time models more attractive in practice. For semiparametric multivariate accelerated failure time models, we propose a generalized estimating equation approach to account for the multivariate dependence through working correlation structures. The marginal error distributions can be either identical as in sequential event settings or different as in parallel event settings. Some regression coefficients can be shared across margins as needed. The initial estimator is a rank-based estimator with Gehan's weight, but obtained from an induced smoothing approach with computation ease. The resulting estimator is consistent and asymptotically normal, with a variance estimated through a multiplier resampling method. In a simulation study, our estimator was up to three times as efficient as the initial estimator, especially with stronger multivariate dependence and heavier censoring percentage. Two real examples demonstrate the utility of the proposed method

Spatial divergence in the proportions of genes encoding toxic peptide synthesis among populations of the cyanobacterium Planktothrix in European lakes

It has been frequently reported that seasonal changes in toxin production by cyanobacteria are due to changes in the proportion of toxic/nontoxic genotypes in parallel to increases or decreases in population density during the seasonal cycle of bloom formation. In order to find out whether there is a relationship between the proportion of genes encoding toxic peptide synthesis and population density of Planktothrix spp. we compared the proportion of three gene regions that are indicative of the synthesis of the toxic heptapeptide microcystin (mcyB), and the bioactive peptides aeruginoside (aerB) and anabaenopeptin (apnC) in samples from 23 lakes of five European countries (n=153). The mcyB, aerB, and apnC genes occurred in 99%, 99%, and 97% of the samples, respectively, and on average comprised 60 ± 3%, 22 ± 2%, and 54 ± 4% of the total population, respectively. Although the populations differed widely in abundance (10−3–103 mm3 L−1) no dependence of the proportion of the mcyB, aerB, and apnC genes on the density of the total population was found. In contrast populations differed significantly in their average mcyB, aerB, and apnC gene proportions, with no change between prebloom and bloom conditions. These results emphasize stable population-specific differences in mcyB, aerB, and apnC proportions that are independent from seasonal influences