Polar extracts from (Tunisian) Acacia salicina Lindl. Study of the antimicrobial and antigenotoxic activities

<p>Abstract</p> <p>Background</p> <p>Methanolic, aqueous and Total Oligomer Flavonoids (TOF)-enriched extracts obtained from the leaves of <it>Acacia salicina </it>'Lindl.' were investigated for antibacterial, antimutagenic and antioxidant activities.</p> <p>Methods</p> <p>The antimicrobial activity was tested on the Gram positive and Gram negative reference bacterial strains. The Mutagenic and antimutagenic activities against direct acting mutagens, methylmethane sulfonate (MMS) and 4-nitro-o-phenylenediamine (NOPD), and indirect acting mutagens, 2-aminoanthracene (2-AA) and benzo[a]pyrene (B(a)P) were performed with <it>S. typhimurium </it>TA102 and TA98 assay systems. In addition, the enzymatic and nonenzymatic methods were employed to evaluate the anti-oxidative effects of the tested extracts.</p> <p>Results</p> <p>A significant effect against the Gram positive and Gram negative reference bacterial strains was observed with all the extracts. The mutagenic and antimutagenic studies revealed that all the extracts decreased the mutagenicity induced by B(a)P (7.5 μg/plate), 2-AA (5 μg/plate), MMS (1.3 mg/plate) and NOPD (10 μg/plate). Likewise, all the extracts showed an important free radical scavenging activity towards the superoxide anion generated by the xanthine/xanthine oxidase assay system, as well as high Trolox Equivalent Antioxidant Capacity (TEAC), against the 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS)⁺• radical. TOF-enriched extract exhibited the highest protective effect against free radicals, direct acting-mutagen and metabolically activated S9-dependent mutagens.</p> <p>Conclusions</p> <p>The present study indicates that the extracts from <it>A. salicina </it>leaves are a significant source of compounds with the antimutagenic and antioxidant activities, and this may be useful for developing potential chemopreventive substances.</p

Hierarchical median narrow band for level set segmentation of cervical cell nuclei

This paper presents a novel hierarchical nuclei segmentation algorithm for isolated and overlapping cervical cells based on a narrow band level set implementation. Our method applies a new multiscale analysis algorithm to estimate the number of clusters in each image region containing cells, which turns into the input to a narrow band level set algorithm. We assess the nuclei segmentation results on three public cervical cell image databases. Overall, our segmentation method outperformed six state-of-the-art methods concerning the number of correctly segmented nuclei and the Dice coefficient reached values equal to or higher than 0.90. We also carried out classification experiments using features extracted from our segmentation results and the proposed pipeline achieved the highest average accuracy values equal to 0.89 and 0.77 for two-class and three-class problems, respectively. These results demonstrated the suitability of the proposed segmentation algorithm to integrate decision support systems for cervical cell screening