Net processes correspond to derivation processes in graph grammars

AbstractThe aim of this paper is to compare the running behaviour of Petri nets, given by firing sequences and processes, with derivations and derivation processes in graph grammars. In a first step, Petri nets are simulated by graph grammars so that each firing in a net corresponds exactly to a direct derivation in the simulating graph grammar. In a second step the non-sequential behaviour of nets described by net processes is related to the non-sequential behaviour of graph grammars given by derivation processes. a one-to-one correppondence can be established between the processes on a Petri net and the complete conflict-free processes in the graph grammar simulating the net. This adds a new piece of evidence substantiating the close relationship between net and graph grammar theory

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

Fluorescence-Based Detection of Natural Transformation in Drug-Resistant Acinetobacter baumannii

International audienceAcinetobacter baumanniiis a nosocomial agent with a high propensityfor developing resistance to antibiotics. This ability relies on horizontal gene transfermechanisms occurring in theAcinetobactergenus, including natural transformation.To study natural transformation in bacteria, the most prevalent method uses selec-tion for the acquisition of an antibiotic resistance marker in a target chromosomallocus by the recipient cell. Most clinical isolates ofA. baumanniiare resistant to mul-tiple antibiotics, limiting the use of such selection-based methods. Here, we reportthe development of a phenotypic and selection-free method based on flow cytom-etry to detect transformation events in multidrug-resistant (MDR) clinicalA. bauman-niiisolates. To this end, we engineered a translational fusion between the abundantand conservedA. baumanniinucleoprotein (HU) and the superfolder green fluores-cent protein (sfGFP). The new method was benchmarked against the conventionalantibiotic selection-based method. Using this new method, we investigated severalparameters affecting transformation efficiencies and identified conditions of trans-formability one hundred times higher than those previously reported. Using opti-mized transformation conditions, we probed natural transformation in a set of MDRclinical and nonclinical animalA. baumanniiisolates. Regardless of their origin, themajority of the isolates displayed natural transformability, indicative of a conservedtrait in the species. Overall, this new method and optimized protocol will greatly fa-cilitate the study of natural transformation in the opportunistic pathogenA. bau-mannii.IMPORTANCEAntibiotic resistance is a pressing global health concern with therise of multiple and panresistant pathogens. The rapid and unfailing resistanceto multiple antibiotics of the nosocomial agentAcinetobacter baumannii, notablyto carbapenems, prompt to understand the mechanisms behind acquisition ofnew antibiotic resistance genes. Natural transformation, one of the horizontalgene transfer mechanisms in bacteria, was only recently described inA. bauman-niiand could explain its ability to acquire resistance genes. We developed a reli-able method to probe and study natural transformation mechanism inA. bau-mannii. More broadly, this new method based on flow cytometry will allowexperimental detection and quantification of horizontal gene transfer events inmultidrug-resistantA. baumannii