Antibacterial activity of Thymoquinone, an active principle of Nigella sativa and its potency to prevent bacterial biofilm formation

<p>Abstract</p> <p>Background</p> <p>Thymoquinone is an active principle of <it>Nigella sativa </it>seed known as "Habbah Al-Sauda" in Arabic countries and "Sinouj" in Tunisia. Bacterial biofilms tend to exhibit significant tolerance to antimicrobials drugs during infections.</p> <p>Methods</p> <p>The antibacterial activity of Thymoquinone (TQ) and its biofilm inhibition potencies were investigated on 11 human pathogenic bacteria. The growth and development of the biofilm were assessed using the crystal violet (CV) and the 2, 3-bis [2-methyloxy-4-nitro-5-sulfophenyl]-2H-tetrazolium-5-carboxanilide (XTT) reduction assay.</p> <p>Results</p> <p>TQ exhibited a significant bactericidal activity against the majority of the tested bacteria (MICs values ranged from 8 to 32 μg/ml) especially Gram positive cocci (<it>Staphylococcus aureus </it>ATCC 25923 and <it>Staphylococcus epidermidis </it>CIP 106510). Crystal violet assay demonstrated that the minimum biofilm inhibition concentration (BIC50) was reached with 22 and 60 μg/ml for <it>Staphylococcus aureus </it>ATCC 25923 and <it>Staphylococcus epidermidis </it>CIP 106510 respectively. In addition our data revealed that cells oxidative activity was influenced by TQ supplementation. In the same way, TQ prevented cell adhesion to glass slides surface.</p> <p>Conclusion</p> <p>The ability of TQ to prevent biofilm formation warrants further investigation to explore its use as bioactive substances with antibiofilm potential.</p

Computing Vertex-Vertex Dissimilarities Using Random Trees: Application to Clustering in Graphs

International audienceA current challenge in graph clustering is to tackle the issue of complex networks, i.e, graphs with attributed vertices and/or edges. In this paper, we present GraphTrees, a novel method that relies on random decision trees to compute pairwise dissimilarities between vertices in a graph. We show that using different types of trees, it is possible to extend this framework to graphs where the vertices have attributes. While many existing methods that tackle the problem of clustering vertices in an attributed graph are limited to categorical attributes, GraphTrees can handle heterogeneous types of vertex attributes. Moreover, unlike other approaches, the attributes do not need to be preprocessed. We also show that our approach is competitive with well-known methods in the case of non-attributed graphs in terms of quality of clustering, and provides promising results in the case of vertex-attributed graphs. By extending the use of an already well established approach-the random trees-to graphs, our proposed approach opens new research directions, by lever-aging decades of research on this topic

Predicting Coral Species Richness: The Effect of Input Variables, Diversity and Scale

Coral reefs are facing a biodiversity crisis due to increasing human impacts, consequently, one third of reef-building corals have an elevated risk of extinction. Logistic challenges prevent broad-scale species-level monitoring of hard corals; hence it has become critical that effective proxy indicators of species richness are established. This study tests how accurately three potential proxy indicators (generic richness on belt transects, generic richness on point-intercept transects and percent live hard coral cover on point-intercept transects) predict coral species richness at three different locations and two analytical scales. Generic richness (measured on a belt transect) was found to be the most effective predictor variable, with significant positive linear relationships across locations and scales. Percent live hard coral cover consistently performed poorly as anindicator of coral species richness. This study advances the practical framework for optimizing coral reef monitoring programs and empirically demonstrates that generic richness offers an effective way to predict coral species richness with a moderate level of precision. While the accuracy of species richness estimates will decrease in communities dominated byspecies-rich genera (e.g. Acropora), generic richness provides a useful measure of phylogenetic diversity and incorporating this metric into monitoring programs will increase the likelihood that changes in coral species diversity can be detected

Seasonality, abundance, and fifteen-year trend in green turtle nesting activity at Itsamia, Moheli, Comoros

International audienceNesting green turtles Chelonia mydas were studied at Moheli Island, Union of Comoros, southwestern Indian Ocean (SWIO). Five contiguous beaches near Itsamia village, in the southeastern part of the island, were monitored daily for nesting activity from January 1999 to June 2007 and irregularly between August 2009 and December 2014; nesting success was recorded from 2000 to 2006. Nesting occurred year-round and peaked in the austral winter, from March through August, with the highest values in May. During the 7 yr period when nesting success was recorded, 63 164 successful nestings were reported, and the total was 69 630 when estimates of missing data were included. The average rate of nesting success was 0.49 (SD = 0.04, n =7). Using the estimate of 3.03 successful nestings per female per season, the estimated number of nesting females per year varied from 924 in 2000 to 5827 in 2005. There was marked growth in nesting activity over the beginning of the study period, as indicated by seasonal decomposition of time series by loess and generalized additive mixed model analyses, with an increase of 226% from 1999 to 2006 and evidently a leveling off of nesters between 2007 and 2014. The Itsamia beaches have one of the largest nesting populations, with a higher rate of increase than any other site in the SWIO. Long-term protection of the beaches and offshore waters by the Itsamia community, despite several years of intense exploitation by outsiders, is reasoned to be the primary explanation for these remarkable figures