Silencing and Un-silencing of Tetracycline-Controlled Genes in Neurons

To identify the underlying reason for the controversial performance of tetracycline (Tet)-controlled regulated gene expression in mammalian neurons, we investigated each of the three components that comprise the Tet inducible systems, namely tetracyclines as inducers, tetracycline-transactivator (tTA) and reverse tTA (rtTA), and tTA-responsive promoters (Ptets). We have discovered that stably integrated Ptet becomes functionally silenced in the majority of neurons when it is inactive during development. Ptet silencing can be avoided when it is either not integrated in the genome or stably-integrated with basal activity. Moreover, long-term, high transactivator levels in neurons can often overcome integration-induced Ptet gene silencing, possibly by inducing promoter accessibility

Split-Cre Complementation Indicates Coincident Activity of Different Genes In Vivo

Cre/LoxP recombination is the gold standard for conditional gene regulation in mice in vivo. However, promoters driving the expression of Cre recombinase are often active in a wide range of cell types and therefore unsuited to target more specific subsets of cells. To overcome this limitation, we designed inactive “split-Cre” fragments that regain Cre activity when overlapping co-expression is controlled by two different promoters. Using transgenic mice and virus-mediated expression of split-Cre, we show that efficient reporter gene activation is achieved in vivo. In the brain of transgenic mice, we genetically defined a subgroup of glial progenitor cells in which the Plp1- and the Gfap-promoter are simultaneously active, giving rise to both astrocytes and NG2-positive glia. Similarly, a subset of interneurons was labelled after viral transfection using Gad67- and Cck1 promoters to express split-Cre. Thus, split-Cre mediated genomic recombination constitutes a powerful spatial and temporal coincidence detector for in vivo targeting

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

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.Peer reviewe