Shallow Dialogue Processing Using Machine Learning Algorithms (or not)

This paper presents a shallow dialogue analysis model, aimed at human-human dialogues in the context of staff or business meetings. Four components of the model are defined, and several machine learning techniques are used to extract features from dialogue transcripts: maximum entropy classifiers for dialogue acts, latent semantic analysis for topic segmentation, or decision tree classifiers for discourse markers. A rule-based approach is proposed for solving cross-modal references to meeting documents. The methods are trained and evaluated thanks to a common data set and annotation format. The integration of the components into an automated shallow dialogue parser opens the way to multimodal meeting processing and retrieval applications.

Doxorubicin Affects Expression of Proteins of Neuronal Pathways in MCF-7 Breast Cancer Cells.

In the present article, we report on the semi-quantitative proteome analysis and related changes in protein expression of the MCF-7 breast cancer cell line following treatment with doxorubicin, using the precursor acquisition independent from ion count (PAcIFIC) mass spectrometry method. PAcIFIC represents a cost-effective and easy-to-use proteomics approach, enabling for deep proteome sequencing with minimal sample handling. The acquired proteomic data sets were searched for regulated Reactome pathways and Gene Ontology annotation terms using a new algorithm (SetRank). Using this approach, we identified pathways with significant changes (≤0.05), such as chromatin organization, DNA binding, embryo development, condensed chromosome, sequence-specific DNA binding, response to oxidative stress and response to toxin, as well as others. These sets of pathways are already well-described as being susceptible to chemotherapeutic drugs. Additionally, we found pathways related to neuron development, such as central nervous system neuron differentiation, neuron projection membrane and SNAP receptor activity. These later pathways might indicate biological mechanisms on the molecular level causing the known side-effect of doxorubicin chemotherapy, characterized as cognitive impairment, also called 'chemo brain'. Mass spectrometry data are available via ProteomeXchange with identifier PXD002998.

Differentiation of IncL and IncM Plasmids Associated with the Spread of Clinically Relevant Antimicrobial Resistance.

INTRODUCTION blaOXA-48, blaNDM-1 and blaCTX-M-3 are clinically relevant resistance genes, frequently associated with the broad-host range plasmids of the IncL/M group. The L and M plasmids belong to two compatible groups, which were incorrectly classified together by molecular methods. In order to understand their evolution, we fully sequenced four IncL/M plasmids, including the reference plasmids R471 and R69, the recently described blaOXA-48-carrying plasmid pKPN-El.Nr7 from a Klebsiella pneumoniae isolated in Bern (Switzerland), and the blaSHV-5 carrying plasmid p202c from a Salmonella enterica from Tirana (Albania). METHODS Sequencing was performed using 454 Junior Genome Sequencer (Roche). Annotation was performed using Sequin and Artemis software. Plasmid sequences were compared with 13 fully sequenced plasmids belonging to the IncL/M group available in GenBank. RESULTS Comparative analysis of plasmid genomes revealed two distinct genetic lineages, each containing one of the R471 (IncL) and R69 (IncM) reference plasmids. Conjugation experiments demonstrated that plasmids representative of the IncL and IncM groups were compatible with each other. The IncL group is constituted by the blaOXA-48-carrying plasmids and R471. The IncM group contains two sub-types of plasmids named IncM1 and IncM2 that are each incompatible. CONCLUSION This work re-defines the structure of the IncL and IncM families and ascribes a definitive designation to the fully sequenced IncL/M plasmids available in GenBank.