MeMo: a hybrid SQL/XML approach to metabolomic data management for functional genomics

Background: The genome sequencing projects have shown our limited knowledge regarding gene function, e.g. S. cerevisiae has 5-6,000 genes of which nearly 1,000 have an uncertain function. Their gross influence on the behaviour of the cell can be observed using large-scale metabolomic studies. The metabolomic data produced need to be structured and annotated in a machine-usable form to facilitate the exploration of the hidden links between the genes and their functions. Description: MeMo is a formal model for representing metabolomic data and the associated metadata. Two predominant platforms (SQL and XML) are used to encode the model. MeMo has been implemented as a relational database using a hybrid approach combining the advantages of the two technologies. It represents a practical solution for handling the sheer volume and complexity of the metabolomic data effectively and efficiently. The MeMo model and the associated software are available at http://dbkgroup.org/memo/. Conclusions: The maturity of relational database technology is used to support efficient data processing. The scalability and self-descriptiveness of XML are used to simplify the relational schema and facilitate the extensibility of the model necessitated by the creation of new experimental techniques. Special consideration is given to data integration issues as part of the systems biology agenda. MeMo has been physically integrated and cross-linked to related metabolomic and genomic databases. Semantic integration with other relevant databases has been supported through ontological annotation. Compatibility with other data formats is supported by automatic conversion

Bilingually motivated word segmentation for statistical machine translation

We introduce a bilingually motivated word segmentation approach to languages where word boundaries are not orthographically marked, with application to Phrase-Based Statistical Machine Translation (PB-SMT). Our approach is motivated from the insight that PB-SMT systems can be improved by optimizing the input representation to reduce the predictive power of translation models. We firstly present an approach to optimize the existing segmentation of both source and target languages for PB-SMT and demonstrate the effectiveness of this approach using a Chinese–English MT task, that is, to measure the influence of the segmentation on the performance of PB-SMT systems. We report a 5.44% relative increase in Bleu score and a consistent increase according to other metrics. We then generalize this method for Chinese word segmentation without relying on any segmenters and show that using our segmentation PB-SMT can achieve more consistent state-of-the-art performance across two domains. There are two main advantages of our approach. First of all, it is adapted to the specific translation task at hand by taking the corresponding source (target) language into account. Second, this approach does not rely on manually segmented training data so that it can be automatically adapted for different domains

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

CD169(+) macrophages are critical for osteoblast maintenance and promote intramembranous and endochondral ossification during bone repair

Osteal macrophages (osteomacs) contribute to bone homeostasis and regeneration. To further distinguish their functions from osteoclasts, which share many markers and growth factor requirements, we developed a rapid, enzyme-free osteomac enrichment protocol that permitted characterization of minimally manipulated osteomacs by flow cytometry. Osteomacs differ from osteoclasts in expression of Siglec1 (CD169). This distinction was confirmed using the CD169-diphtheria toxin (DT) receptor (DTR) knock-in model. DT treatment of naïve CD169-DTR mice resulted in selective and striking loss of osteomacs, whilst osteoclasts and trabecular bone area were unaffected. Consistent with a previously-reported trophic interaction, osteomac loss was accompanied by a concomitant and proportionately striking reduction in osteoblasts. The impact of CD169 macrophage depletion was assessed in two models of bone injury that heal via either intramembranous (tibial injury) or endochondral (internally-plated femoral fracture model) ossification. In both models, CD169 macrophage, including osteomac depletion compromised bone repair. Importantly, DT treatment in CD169-DTR mice did not affect osteoclast frequency in either model. In the femoral fracture model, the magnitude of callus formation correlated with the number of F4/80 macrophages that persisted within the callus. Overall these observations provide compelling support that CD169 osteomacs, independent of osteoclasts, provide vital pro-anabolic support to osteoblasts during both bone homeostasis and repair