On Optimal Two-Impulse Earth-Moon Transfers in a Four-Body Model

In this paper two-impulse Earth-Moon transfers are treated in the restricted four-body problem with the Sun, the Earth, and the Moon as primaries. The problem is formulated with mathematical means and solved through direct transcription and multiple shooting strategy. Thousands of solutions are found, which make it possible to frame known cases as special points of a more general picture. Families of solutions are defined and characterized, and their features are discussed. The methodology described in this paper is useful to perform trade-off analyses, where many solutions have to be produced and assessed

T7 RNA Polymerase Functions In Vitro without Clustering

Many nucleic acid polymerases function in clusters known as factories. We investigate whether the RNA polymerase (RNAP) of phage T7 also clusters when active. Using ‘pulldowns’ and fluorescence correlation spectroscopy we find that elongation complexes do not interact in vitro with a Kd<1 µM. Chromosome conformation capture also reveals that genes located 100 kb apart on the E. coli chromosome do not associate more frequently when transcribed by T7 RNAP. We conclude that if clustering does occur in vivo, it must be driven by weak interactions, or mediated by a phage-encoded protein

Inhibition of Notch3 signalling induces rhabdomyosarcoma cell differentiation promoting p38 phosphorylation and p21Cip1 expression and hampers tumour cell growth in vitro and in vivo

Rhabdomyosarcoma (RMS) is a paediatric soft-tissue sarcoma arising from skeletal muscle precursors coexpressing markers of proliferation and differentiation. Inducers of myogenic differentiation suppress RMS tumourigenic phenotype. The Notch target gene HES1 is upregulated in RMS and prevents tumour cell differentiation in a Notch-dependent manner. However, Notch receptors regulating this phenomenon are unknown. In agreement with data in RMS primary tumours, we show here that the Notch3 receptor is overexpressed in RMS cell lines versus normal myoblasts. Notch3-targeted downregulation in RMS cells induces hyper-phosphorylation of p38 and Akt essential for myogenesis, resulting in the differentiation of tumour cells into multinucleated myotubes expressing Myosin Heavy Chain. These phenomena are associated to a marked decrease in HES1 expression, an increase in p21Cip1 level and the accumulation of RMS cells in the G1 phase. HES1-forced overexpression in RMS cells reverses, at least in part, the pro-differentiative effects of Notch3 downregulation. Notch3 depletion also reduces the tumourigenic potential of RMS cells both in vitro and in vivo. These results indicate that downregulation of Notch3 is sufficient to force RMS cells into completing a correct full myogenic program providing evidence that it contributes, partially through HES1 sustained expression, to their malignant phenotype. Moreover, they suggest Notch3 as a novel potential target in human RMS

Metformin strongly affects transcriptome of peripheral blood cells in healthy individuals

Funding Information: The study was supported by the European Regional Development Fund under the project ?Investigation of interplay between multiple determinants influencing response to metformin: search for reliable predictors for efficacy of type 2 diabetes therapy? (Project No.: 1.1.1.1/16/A/091, https://ec.europa.eu/regional_policy/en/funding/ erdf/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors would like to thank all the volunteers for their participation and acknowledge the Genome Database of the Latvian Population for providing biological material and data. Publisher Copyright: © 2019 Ustinova et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Metformin is a commonly used antihyperglycaemic agent for the treatment of type 2 diabetes mellitus. Nevertheless, the exact mechanisms of action, underlying the various therapeutic effects of metformin, remain elusive. The goal of this study was to evaluate the alterations in longitudinal whole-blood transcriptome profiles of healthy individuals after a one-week metformin intervention in order to identify the novel molecular targets and further prompt the discovery of predictive biomarkers of metformin response. Next generation sequencing-based transcriptome analysis revealed metformin-induced differential expression of genes involved in intestinal immune network for IgA production and cytokine-cytokine receptor interaction pathways. Significantly elevated faecal sIgA levels during administration of metformin, and its correlation with the expression of genes associated with immune response (CXCR4, HLA-DQA1, MAP3K14, TNFRSF21, CCL4, ACVR1B, PF4, EPOR, CXCL8) supports a novel hypothesis of strong association between metformin and intestinal immune system, and for the first time provide evidence for altered RNA expression as a contributing mechanism of metformin’s action. In addition to universal effects, 4 clusters of functionally related genes with a subject-specific differential expression were distinguished, including genes relevant to insulin production (HNF1B, HNF1A, HNF4A, GCK, INS, NEUROD1, PAX4, PDX1, ABCC8, KCNJ11) and cholesterol homeostasis (APOB, LDLR, PCSK9). This inter-individual variation of the metformin effect on the transcriptional regulation goes in line with well-known variability of the therapeutic response to the drug.publishersversionPeer reviewe

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

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ(2) meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico-replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases