Characterisation of an ABC transporter of a resistant Candida glabrata clinical isolate

BACKGROUND Candida glabrata ranks second in epidemiological surveillance studies, and is considered one of the main human yeast pathogens. Treatment of Candida infections represents a contemporary public health problem due to the limited availability of an antifungal arsenal, toxicity effects and increasing cases of resistance. C. glabrata presents intrinsic fluconazole resistance and is a significant concern in clinical practice and in hospital environments. OBJECTIVE The aim of this study was to characterise the azole resistance mechanism presented by a C. glabrata clinical isolate from a Brazilian university hospital. METHODS Azole susceptibility assays, chemosensitisation, flow cytometry and mass spectrometry were performed. FINDINGS Our study demonstrated extremely high resistance to all azoles tested: fluconazole, voriconazole, posaconazole and itraconazole. This isolate was chemosensitised by FK506, a classical inhibitor of ABC transporters related to azole resistance, and Rhodamine 6G extrusion was observed. A mass spectrometry assay confirmed the ABC protein identification suggesting the probable role of efflux pumps in this resistance phenotype. MAIN CONCLUSIONS This study emphasizes the importance of ABC proteins and their relation to the resistance mechanism in hospital environments and they may be an important target for the development of compounds able to unsettle drug extrusion

Biased-corrected richness estimates for the Amazonian tree flora

Amazonian forests are extraordinarily diverse, but the estimated species richness is very much debated. Here, we apply an ensemble of parametric estimators and a novel technique that includes conspecific spatial aggregation to an extended database of forest plots with up-to-date taxonomy. We show that the species abundance distribution of Amazonia is best approximated by a logseries with aggregated individuals, where aggregation increases with rarity. By averaging several methods to estimate total richness, we confirm that over 15,000 tree species are expected to occur in Amazonia. We also show that using ten times the number of plots would result in an increase to just ~50% of those 15,000 estimated species. To get a more complete sample of all tree species, rigorous field campaigns may be needed but the number of trees in Amazonia will remain an estimate for years to come

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research