On the push&pull protocol for rumour spreading

The asynchronous push&pull protocol, a randomized distributed algorithm for spreading a rumour in a graph $G$, works as follows. Independent Poisson clocks of rate 1 are associated with the vertices of $G$. Initially, one vertex of $G$ knows the rumour. Whenever the clock of a vertex $x$ rings, it calls a random neighbour $y$: if $x$ knows the rumour and $y$ does not, then $x$ tells $y$ the rumour (a push operation), and if $x$ does not know the rumour and $y$ knows it, $y$ tells $x$ the rumour (a pull operation). The average spread time of $G$ is the expected time it takes for all vertices to know the rumour, and the guaranteed spread time of $G$ is the smallest time $t$ such that with probability at least $1-1/n$, after time $t$ all vertices know the rumour. The synchronous variant of this protocol, in which each clock rings precisely at times $1,2,\dots$, has been studied extensively. We prove the following results for any $n$-vertex graph: In either version, the average spread time is at most linear even if only the pull operation is used, and the guaranteed spread time is within a logarithmic factor of the average spread time, so it is $O(n\log n)$. In the asynchronous version, both the average and guaranteed spread times are $\Omega(\log n)$. We give examples of graphs illustrating that these bounds are best possible up to constant factors. We also prove theoretical relationships between the guaranteed spread times in the two versions. Firstly, in all graphs the guaranteed spread time in the asynchronous version is within an $O(\log n)$ factor of that in the synchronous version, and this is tight. Next, we find examples of graphs whose asynchronous spread times are logarithmic, but the synchronous versions are polynomially large. Finally, we show for any graph that the ratio of the synchronous spread time to the asynchronous spread time is $O(n^{2/3})$.Comment: 25 page

“What if There's Something Wrong with Her?”‐How Biomedical Technologies Contribute to Epistemic Injustice in Healthcare

While there is a steadily growing literature on epistemic injustice in healthcare, there are few discussions of the role that biomedical technologies play in harming patients in their capacity as knowers. Through an analysis of newborn and pediatric genetic and genomic sequencing technologies (GSTs), I argue that biomedical technologies can lead to epistemic injustice through two primary pathways: epistemic capture and value partitioning. I close by discussing the larger ethical and political context of critical analyses of GSTs and their broader implications for just and equitable healthcare delivery

Analysis of the olive fruit fly Bactrocera oleae transcriptome and phylogenetic classification of the major detoxification gene families

he olive fruit fly Bactrocera oleae has a unique ability to cope with olive flesh, and is the most destructive pest of olives worldwide. Its control has been largely based on the use of chemical insecticides, however, the selection of insecticide resistance against several insecticides has evolved. The study of detoxification mechanisms, which allow the olive fruit fly to defend against insecticides, and/or phytotoxins possibly present in the mesocarp, has been hampered by the lack of genomic information in this species. In the NCBI database less than 1,000 nucleotide sequences have been deposited, with less than 10 detoxification gene homologues in total. We used 454 pyrosequencing to produce, for the first time, a large transcriptome dataset for B. oleae. A total of 482,790 reads were assembled into 14,204 contigs. More than 60% of those contigs (8,630) were larger than 500 base pairs, and almost half of them matched with genes of the order of the Diptera. Analysis of the Gene Ontology (GO) distribution of unique contigs, suggests that, compared to other insects, the assembly is broadly representative for the B. oleae transcriptome. Furthermore, the transcriptome was found to contain 55 P450, 43 GST-, 15 CCE- and 18 ABC transporter-genes. Several of those detoxification genes, may putatively be involved in the ability of the olive fruit fly to deal with xenobiotics, such as plant phytotoxins and insecticides. In summary, our study has generated new data and genomic resources, which will substantially facilitate molecular studies in B. oleae, including elucidation of detoxification mechanisms of xenobiotic, as well as other important aspects of olive fruit fly biology

Crystal structure of a murine α-class glutathione S-transferase involved in cellular defense against oxidative stress

Glutathione S-transferases (GSTs) are ubiquitous multifunctional enzymes which play a key role in cellular detoxification. The enzymes protect the cells against toxicants by conjugating them to glutathione. Recently, a novel subgroup of α-class GSTs has been identified with altered substrate specificity which is particularly important for cellular defense against oxidative stress. Here, we report the crystal structure of murine GSTA4-4, which is the first structure of a prototypical member of this subgroup. The structure was solved by molecular replacement and refined to 2.9 Å resolution. It resembles the structure of other members of the GST superfamily, but reveals a distinct substrate binding site.

Answering Complex Questions by Joining Multi-Document Evidence with Quasi Knowledge Graphs

Direct answering of questions that involve multiple entities and relations is a challenge for text-based QA. This problem is most pronounced when answers can be found only by joining evidence from multiple documents. Curated knowledge graphs (KGs) may yield good answers, but are limited by their inherent incompleteness and potential staleness. This paper presents QUEST, a method that can answer complex questions directly from textual sources on-the-fly, by computing similarity joins over partial results from different documents. Our method is completely unsupervised, avoiding training-data bottlenecks and being able to cope with rapidly evolving ad hoc topics and formulation style in user questions. QUEST builds a noisy quasi KG with node and edge weights, consisting of dynamically retrieved entity names and relational phrases. It augments this graph with types and semantic alignments, and computes the best answers by an algorithm for Group Steiner Trees. We evaluate QUEST on benchmarks of complex questions, and show that it substantially outperforms state-of-the-art baselines

Transcriptome profiling of a spirodiclofen susceptible and resistant strain of the European red mite Panonychus ulmi using strand-specific RNA-seq

Background: The European red mite, Panonychus ulmi, is among the most important mite pests in fruit orchards, where it is controlled primarily by acaricide application. However, the species rapidly develops pesticide resistance, and the elucidation of resistance mechanisms for P. ulmi has not kept pace with insects or with the closely related spider mite Tetranychus urticae. The main reason for this lack of knowledge has been the absence of genomic resources needed to investigate the molecular biology of resistance mechanisms. Results: Here, we provide a comprehensive strand-specific RNA-seq based transcriptome resource for P. ulmi derived from strains susceptible and resistant to the widely used acaricide spirodiclofen. From a de novo assembly of the P. ulmi transcriptome, we manually annotated detoxification enzyme families, target-sites of commonly used acaricides, and horizontally transferred genes implicated in plant-mite interactions and pesticide resistance. In a comparative analysis that incorporated sequences available for Panonychus citri, T. urticae, and insects, we identified radiations for detoxification gene families following the divergence of Panonychus and Tetranychus genera. Finally, we used the replicated RNA-seq data from the spirodiclofen susceptible and resistant strains to describe gene expression changes associated with resistance. A cytochrome P450 monooxygenase, as well as multiple carboxylcholinesterases, were differentially expressed between the susceptible and resistant strains, and provide a molecular entry point for understanding resistance to spirodiclofen, widely used to control P. ulmi populations. Conclusions: The new genomic resources and data that we present in this study for P. ulmi will substantially facilitate molecular studies of underlying mechanisms involved in acaricide resistance