The Endosymbiotic Bacterium Wolbachia Induces Resistance to Dengue Virus in Aedes aegypti

Genetic strategies that reduce or block pathogen transmission by mosquitoes have been proposed as a means of augmenting current control measures to reduce the growing burden of vector-borne diseases. The endosymbiotic bacterium Wolbachia has long been promoted as a potential vehicle for introducing disease-resistance genes into mosquitoes, thereby making them refractory to the human pathogens they transmit. Given the large overlap in tissue distribution and intracellular localization between Wolbachia and dengue virus in mosquitoes, we conducted experiments to characterize their interactions. Our results show that Wolbachia inhibits viral replication and dissemination in the main dengue vector, Aedes aegypti. Moreover, the virus transmission potential of Wolbachia-infected Ae. aegypti was significantly diminished when compared to wild-type mosquitoes that did not harbor Wolbachia. At 14 days post-infection, Wolbachia completely blocked dengue transmission in at least 37.5% of Ae. aegypti mosquitoes. We also observed that this Wolbachia-mediated viral interference was associated with an elevated basal immunity and increased longevity in the mosquitoes. These results underscore the potential usefulness of Wolbachia-based control strategies for population replacement

SR4GN: A Species Recognition Software Tool for Gene Normalization

As suggested in recent studies, species recognition and disambiguation is one of the most critical and challenging steps in many downstream text-mining applications such as the gene normalization task and protein-protein interaction extraction. We report SR4GN: an open source tool for species recognition and disambiguation in biomedical text. In addition to the species detection function in existing tools, SR4GN is optimized for the Gene Normalization task. As such it is developed to link detected species with corresponding gene mentions in a document. SR4GN achieves 85.42% in accuracy and compares favorably to the other state-of-the-art techniques in benchmark experiments. Finally, SR4GN is implemented as a standalone software tool, thus making it convenient and robust for use in many text-mining applications. SR4GN can be downloaded at: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/downloads/SR4G

More sustainable electricity generation in hot and dry fuel cells with a novel hybrid membrane of Nafion/nano-silica/hydroxyl ionic liquid

A new hybrid proton exchange membrane (PEM) has been prepared from hydroxyl functionalized imidazolium ionic liquid (IL-OH), Nafion and nano-SiO2. The IL-OH, with a hydroxyl group that acts as both a proton acceptor and donor, forms strong hydrogen bonds with both Nafion and nano-SiO2, resulting in an effective hydrogen bond network in the ternary membrane. Such an anhydrous hydrogen-bond network, which is unknown previously, endows the PEMs with higher proton conductivity, greater thermal stability and surprisingly a more robust mechanical performance than PEMs consisting of conventional ionic liquids. The resulting PEMs have a tensile strength that is more than twice as strong as recast Nafion and an anhydrous ionic conductivity of ∼55 mS cm−1 at temperatures above 160 °C, with a proton transfer number of ∼0.9. A laboratory assembled H2–O2 fuel cell employing this new PEM delivered a power density of 340 and 420 mW cm−2 at 160 and 180 °C, respectively

The gene normalization task in BioCreative III

BACKGROUND: We report the Gene Normalization (GN) challenge in BioCreative III where participating teams were asked to return a ranked list of identifiers of the genes detected in full-text articles. For training, 32 fully and 500 partially annotated articles were prepared. A total of 507 articles were selected as the test set. Due to the high annotation cost, it was not feasible to obtain gold-standard human annotations for all test articles. Instead, we developed an Expectation Maximization (EM) algorithm approach for choosing a small number of test articles for manual annotation that were most capable of differentiating team performance. Moreover, the same algorithm was subsequently used for inferring ground truth based solely on team submissions. We report team performance on both gold standard and inferred ground truth using a newly proposed metric called Threshold Average Precision (TAP-k). RESULTS: We received a total of 37 runs from 14 different teams for the task. When evaluated using the gold-standard annotations of the 50 articles, the highest TAP-k scores were 0.3297 (k=5), 0.3538 (k=10), and 0.3535 (k=20), respectively. Higher TAP-k scores of 0.4916 (k=5, 10, 20) were observed when evaluated using the inferred ground truth over the full test set. When combining team results using machine learning, the best composite system achieved TAP-k scores of 0.3707 (k=5), 0.4311 (k=10), and 0.4477 (k=20) on the gold standard, representing improvements of 12.4%, 21.8%, and 26.6% over the best team results, respectively. CONCLUSIONS: By using full text and being species non-specific, the GN task in BioCreative III has moved closer to a real literature curation task than similar tasks in the past and presents additional challenges for the text mining community, as revealed in the overall team results. By evaluating teams using the gold standard, we show that the EM algorithm allows team submissions to be differentiated while keeping the manual annotation effort feasible. Using the inferred ground truth we show measures of comparative performance between teams. Finally, by comparing team rankings on gold standard vs. inferred ground truth, we further demonstrate that the inferred ground truth is as effective as the gold standard for detecting good team performance

Androgen Regulation of 5α-Reductase Isoenzymes in Prostate Cancer: Implications for Prostate Cancer Prevention

The enzyme 5α-reductase, which converts testosterone to dihydrotestosterone (DHT), performs key functions in the androgen receptor (AR) signaling pathway. The three isoenzymes of 5α-reductase identified to date are encoded by different genes: SRD5A1, SRD5A2, and SRD5A3. In this study, we investigated mechanisms underlying androgen regulation of 5α-reductase isoenzyme expression in human prostate cells. We found that androgen regulates the mRNA level of 5α-reductase isoenzymes in a cell type–specific manner, that such regulation occurs at the transcriptional level, and that AR is necessary for this regulation. In addition, our results suggest that AR is recruited to a negative androgen response element (nARE) on the promoter of SRD5A3 in vivo and directly binds to the nARE in vitro. The different expression levels of 5α-reductase isoenzymes may confer response or resistance to 5α-reductase inhibitors and thus may have importance in prostate cancer prevention

BioCreative III interactive task: an overview

The BioCreative challenge evaluation is a community-wide effort for evaluating text mining and information extraction systems applied to the biological domain. The biocurator community, as an active user of biomedical literature, provides a diverse and engaged end user group for text mining tools. Earlier BioCreative challenges involved many text mining teams in developing basic capabilities relevant to biological curation, but they did not address the issues of system usage, insertion into the workflow and adoption by curators. Thus in BioCreative III (BC-III), the InterActive Task (IAT) was introduced to address the utility and usability of text mining tools for real-life biocuration tasks. To support the aims of the IAT in BC-III, involvement of both developers and end users was solicited, and the development of a user interface to address the tasks interactively was requested