Activity

Because oceanographic changes predicted to occur due to climate change may result in reduced coastal krill availability, adversely affecting these seabird predators, further information on foraging zones and feeding behaviour of small procellariform species is needed to elucidate more fully the segregation of foraging niches, the capacity of seabirds to adapt to climate change and the potential for interspecific competition in the region. ©2020 Fromant et al.With the purpose of discovering new anticancer molecules that might have fewer side effects or reduce resistance to current antitumor drugs, a bioprospecting study of the microalgae of the Cuatro Cienegas Basin (CCB), an oasis in the Chihuahuan desert in Mexico was conducted. A microalgae was identified as Granulocystopsis sp. through sequencing the rbcL gene and reconstruction of a phylogenetic tree, and its anticancer activities were assessed using various in vitro assays and different cell lines of human cancers, including lung, skin melanoma, colorectal, breast and prostatic cancers, as well as a normal cell line. The values of IC50 of the microalgae methanolic extract using the MTT assay were lower than 20 μg/ml, except that in the lung cancer line and the normal cell line. In vitro, the microalgae extract caused the loss of membrane integrity, monitored by the trypan blue exclusion test and exhibited marked inhibition of adhesion and cell proliferation in cancer cell lines, through the evaluation of the clonogenic assay. Also, typical nuclear changes of apoptotic processes were observed under the microscope, using the dual acridine orange/ethidium bromide fluorescent staining. Finally, the microalgae extract increased the activity of caspases 3 and 7 in skin melanoma, colon, breast and prostate cancer cells, in the same way as the apoptotic inductor and powerful antitumoral drug, doxorubicin. This study shows the anticancer activity from Granulocystopsis sp., a microalgae isolated from the CCB. © 2020 Tavares-Carreón et al.We studied the secondary succession in semi-natural grasslands (dry grasslands and hay meadows) located in the eastern side of the Tuscan Apennines (Tuscany, Central Italy). We compared these habitats, investigating (i) the changes in species richness, composition and phylogenetic diversity during the succession; (ii) whether the trends in species loss and species turnover in taxonomic diversity matched those in phylogenetic diversity. We performed a stratified random sampling, in a full factorial design between habitat type and succession stage (60 sampled plots, 10 × 2 types of habitat × 3 stages of succession). P62-mediated mitophagy inducer price We constructed a phylogenetic tree of the plant communities and compared the differences in taxonomic/phylogenetic α- and β-diversity between these two habitats and during their succession. We identified indicator species for each succession stage and habitat. Looking at α-diversity, both habitats displayed a decrease in species richness, with a random process of species selection in the earlier succession stages from the species regional pool. Nevertheless, in the latter stage of dry grasslands we recorded a shift towards phylogenetic overdispersion at the higher-level groups in the phylogenetic tree. In both habitats, while the richness decreased with succession stage, most species were replaced during the succession. However, the hay meadows were characterized by a higher rate of new species’ ingression whereas the dry grasslands became dominated with Juniperus communis. Accordingly, the two habitats showed similar features in phylogenetic β-diversity. The main component was true phylogenetic turnover, due to replacement of unique lineages along the succession. Nevertheless, in dry grasslands this trend is slightly higher than expected considering the major importance of difference in species richness of dry grasslands sites and this is due to the presence of a phylogenetically very distant species (J. communis). © 2020 Lazzaro et al.Histopathological images contain rich phenotypic descriptions of the molecular processes underlying disease progression. Convolutional neural networks, state-of-the-art image analysis techniques in computer vision, automatically learn representative features from such images which can be useful for disease diagnosis, prognosis, and subtyping. Hepatocellular carcinoma (HCC) is the sixth most common type of primary liver malignancy. Despite the high mortality rate of HCC, little previous work has made use of CNN models to explore the use of histopathological images for prognosis and clinical survival prediction of HCC. We applied three pre-trained CNN models-VGG 16, Inception V3 and ResNet 50-to extract features from HCC histopathological images. Sample visualization and classification analyses based on these features showed a very clear separation between cancer and normal samples. In a univariate Cox regression analysis, 21.4% and 16% of image features on average were significantly associated with overall surthological images using the pre-trained CNN models VGG 16, Inception V3 and ResNet 50 can accurately distinguish normal and cancer samples. Furthermore, these image features are significantly correlated with survival and relevant biological pathways. © 2020 Lu and Daigle, Jr.Background Both angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) are blood pressure-lowering agents, but they are also being used to control proteinuria in early chronic kidney disease (CKD) patients. However, clinically, some patients present merely proteinuria without hypertension. No guidelines pointed out how to select treatments for proteinuria in normotensive patients. Thus, we conducted a Bayesian network analysis to evaluate the relative effects of different kinds of ACEI or ARB or their combination on proteinuria and blood pressure reduction. Methods The protocol was registered in PROSPERO with ID CRD42017073721. A comprehensive literature database query was carried out systematically according to PICOS strategies. The primary outcome was reduction in proteinuria, and the secondary outcomes were eGFR reduction and blood pressure reduction. Random-effects pairwise and Bayesian network meta-analyses were used to estimate the effect of different regimens. Results A total of 14 RCTs with 1,098 patients were included in the analysis.