In vitro effects of tyre debris organic extract on the kinetic and morphologic traits of rabbit spermatozoa

[EN] The present study aims at evaluating the effects of the organic extract of tyre debris (TDOE) from tyre wear on the kinetic and morphologic features of rabbit spermatozoa. Rabbit sperm were incubated for 4 h with 0, 5, 10, 50 and 75 ¿g/mL of TDOE. Sperm motility was evaluated by computer-assisted semen analysis. Phosphatidilcholine (PS) externalization (apoptosis) and plasma membrane breakage (necrosis) were assessed using the annexinV/propidium iodide assay. The sperm ultrastructure was observed by scanning (SEM) and transmission electron microscopy (TEM). A relevant decrease in the motility rate, PS externalization, and in plasma membrane breakage of spermatozoa were observed after incubation with TDOE at concentrations higher than 50 ¿g/mL. The most frequent ultrastructural anomalies detected in the analysed specimens were: plasma and/or acrosomal membrane breakage, swollen and disorganized mitochondria, and altered axonemal patterns. Taken together, these results suggest that the organic extract of tyre debris can be toxic to rabbit spermatozoa ¿ affecting their movement and structural integrity ¿ when present in seminal plasma at a concentrations higher than 50 ¿g/mL. Although rabbit sperm has been proven to be a suitable model for testing the in vitro effects of many chemical compounds, including TDOE, the obtained results must be considered preliminary and cannot be extrapolated yet to the in vivo outcomes because of scanty data. The results encourage, however, further research in this field.Supported by the PROLIFE Flagship project, city of Milan, ItalyMoretti, E.; Dal Bosco, A.; Mourvaki, E.; Cardinali, R.; Collodel, G.; Geminiani, M.; Cetta, F.... (2009). In vitro effects of tyre debris organic extract on the kinetic and morphologic traits of rabbit spermatozoa. World Rabbit Science. 17(4):213-220. doi:10.4995/wrs.2009.64621322017

Evidence of Deterministic Components in the Apparent Randomness of GRBs: Clues of a Chaotic Dynamic

Prompt γ-ray emissions from gamma-ray bursts (GRBs) exhibit a vast range of extremely complex temporal structures with a typical variability time-scale significantly short – as fast as milliseconds. This work aims to investigate the apparent randomness of the GRB time profiles making extensive use of nonlinear techniques combining the advanced spectral method of the Singular Spectrum Analysis (SSA) with the classical tools provided by the Chaos Theory. Despite their morphological complexity, we detect evidence of a non stochastic short-term variability during the overall burst duration – seemingly consistent with a chaotic behavior. The phase space portrait of such variability shows the existence of a well-defined strange attractor underlying the erratic prompt emission structures. This scenario can shed new light on the ultra-relativistic processes believed to take place in GRB explosions and usually associated with the birth of a fast-spinning magnetar or accretion of matter onto a newly formed black hole

Current situation on data exchange in agriculture in the EU27 & Switzerland

AgriXchange network for data exchange in agriculture -hankkeen julkaisuvokKV

tseriesChaos: R package for the analysis of nonlinear time series motivated by chaos theory

R package for the analysis of nonlinear time series motivated by chaos theor

Clustering dependent observations with copula functions

This paper deals with the problem of clustering dependent observations according to their underlying complex generating process. Di Lascio and Giannerini (Journal of Classification 29(1):50\u201375, 2012) introduced the CoClust, a clustering algorithm based on copula function that achieves the task but has a high computational burden. Moreover, the CoClust automatically allocates all the observations to the clusters; thus, it cannot discard potentially irrelevant observations. In this paper we introduce an improved version of the CoClust that both overcomes these issues and performs better in many respects. By means of a Monte Carlo study we investigate the features of the algorithm and show that it improves consistently with respect to the old CoClust. The validity of our proposal is also supported by applications to real data sets of human breast tumor samples for which the algorithm provides a meaningful biological interpretation. The new algorithm is implemented and made available through an updated version of the R package CoClust

Clustering Microarray Data: Theoretical and Practical Issues

The analysis of microarray data is a widespread functional genomics approach that allows for the monitoring of the expression of thousands of genes at once. The analysis of the great amount of data generated in a microarray experiment requires powerful statistical techniques. One of the first tasks of the analysis of microarray data is to cluster data into biologically meaningful groups according to their expression patterns. In this article, we discuss classical as well as recent clustering techniques for microarray data. We pay particular attention to both theoretical and practical issues and give some general indications that might be useful to practitioners

Exploring copulas for the imputation of complex dependent data

In this work we introduce a copula-based method for imputing missing data by using conditional density functions of the missing variables given the observed ones. In theory, such functions can be derived from the multivariate distribution of the variables of interest. In practice, it is very difficult to model joint distributions and derive conditional distributions, especially when the margins are different. We propose a natural solution to the problem by exploiting copulas so that we derive conditional density functions through the corresponding conditional copulas. The approach is appealing since copula functions enable us (1) to fit any combination of marginal distribution functions, (2) to take into account complex multivariate dependence relationships and (3) to model the marginal distributions and the dependence structure separately. We describe the method and perform a Monte Carlo study in order to compare it with two well-known imputation techniques: the nearest neighbour donor imputation and the regression imputation by EM algorithm. Our results indicate that the proposal compares favourably with classical methods in terms of preservation of microdata, margins and dependence structure

Changes in hepatic and renal glutathione-dependent enzyme activities in rabbits and lambs subchronically tretated with triphenyltin acetate

To gain insight into the biochemical mechanisms of organotin toxicity the effects of oral subchronic exposure (70 d) to triphenyltin acetate (TPTA) on hepatic and renal enzymes involved in glutathione metabolism were investigated in rabbits and lambs. Rabbits were offered a diet fortified with 15, 75 or 150 ppm TPTA, whereas lambs were daily given 1 or 7.5 mg/kg TPTA. On the whole, rabbits were more susceptible than lambs and in both species hepatic enzymes were affected to a greater extent than renal enzymes. In rabbit liver, glutathione S-transferase activity toward 1.2-dichloro-4-nitrobenzene (DCNB) was enhanced at 15 ppm and depressed at 150 ppm TPTA, whereas selenium-dependent glutathione peroxidase (Se-GPX) decreased in a dose-related manner; glyoxalase II (GII) activity increased to the same extent at 15 or 75 ppm TPTA but was unaffected at 150 ppm TPTA. For renal enzyme activities in rabbits, only GPX activity was significantly inhibited at 150 ppm TPTA. The only statistically significant changes in lambs were a fall in both hepatic GST accepting DCNB as substrate at 7.5 mg/kg and Se-GPX at I or 7.5 mg/kg TPTA, and an increase in renal GII activity at 7.5 mg/kg TPTA. These results suggest that depression of important antioxidant enzymes such as GST and GPX are part of the complex mechanism of organotin toxicit

L'impatto dell'offerta culturale contemporanea sui flussi turistici. Un'analisi empirica per le province italiane

The main objective of this work is to analyze the link between tourism and the presence of temporary art exhibitions. In fact, the ability of cultural attractions to increase the tourist flow is an issue that has received little attention until now. This paper aims to begin to fill this gap. The database allows to take into account both the temporal and the geographical dimension. The empirical analysis is carried out on 52 Italian provinces during the period 2003-2007