An HR-MAS MR Metabolomics Study on Breast Tissues Obtained with Core Needle Biopsy

BACKGROUND: Much research has been devoted to the development of new breast cancer diagnostic measures, including those involving high-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopic techniques. Previous HR-MAS MR results have been obtained from post-surgery samples, which limits their direct clinical applicability. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we performed HR-MAS MR spectroscopic studies on 31 breast tissue samples (13 cancer and 18 non-cancer) obtained by percutaneous core needle biopsy. We showed that cancer and non-cancer samples can be discriminated very well with Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA) multivariate model on the MR spectra. A subsequent blind test showed 69% sensitivity and 94% specificity in the prediction of the cancer status. A spectral analysis showed that in cancer cells, taurine- and choline-containing compounds are elevated. Our approach, additionally, could predict the progesterone receptor statuses of the cancer patients. CONCLUSIONS/SIGNIFICANCE: HR-MAS MR metabolomics on intact breast tissues obtained by core needle biopsy may have a potential to be used as a complement to the current diagnostic and prognostic measures for breast cancers

Ecological drivers of plant diversity patterns in remnants coastal sand dune ecosystems along the northern Adriatic coastline

Coastal sand dunes represent one of the most fragile ecosystems in the Mediterranean basin. These habitats naturally suffer the action of several limiting factors such as sand burial, marine aerosol and low soil fertility; on the other hand, they often host species of high conservation value. Over the last decades, they have also experienced a high level of biological invasion. In this study, we sampled psammophilous vegetation in two sites in the northern Adriatic coast belonging to the Natura 2000 network to describe diversity patterns and to identify the main ecological drivers of species diversity. Plant species richness and their abundance were assessed in each plot. Differences in species composition for native and alien species were compared via PERMANOVA analysis. Species complementarity was explored by partitioning beta diversity in its spatial components (richness and replacement). A Generalized Linear Model was also computed to assess the main environmental factors that may promote invasiveness in these ecosystems. For the investigated area, our results highlight the strong differentiation in community composition both in alien and native species: in particular alien species showed on average a lower complementarity among habitats compared to native species. Specifically, communities seem to be more diversified when larger spatial scales were considered. Beta diversity in both groups appears to be more dominated by the richness component with respect to the replacement component. Furthermore, in these habitats, the occurrence of alien species was shown to be related to geomorphological predictors more than climatic variables