Local multiresolution order in community detection

Community detection algorithms attempt to find the best clusters of nodes in an arbitrary complex network. Multi-scale ("multiresolution") community detection extends the problem to identify the best network scale(s) for these clusters. The latter task is generally accomplished by analyzing community stability simultaneously for all clusters in the network. In the current work, we extend this general approach to define local multiresolution methods, which enable the extraction of well-defined local communities even if the global community structure is vaguely defined in an average sense. Toward this end, we propose measures analogous to variation of information and normalized mutual information that are used to quantitatively identify the best resolution(s) at the community level based on correlations between clusters in independently-solved systems. We demonstrate our method on two constructed networks as well as a real network and draw inferences about local community strength. Our approach is independent of the applied community detection algorithm save for the inherent requirement that the method be able to identify communities across different network scales, with appropriate changes to account for how different resolutions are evaluated or defined in a particular community detection method. It should, in principle, easily adapt to alternative community comparison measures.Comment: 19 pages, 11 figure

Association between dietary inflammatory potential and breast cancer incidence and death: results from the Women\u27s Health Initiative

BACKGROUND: Diet modulates inflammation and inflammatory markers have been associated with cancer outcomes. In the Women\u27s Health Initiative, we investigated associations between a dietary inflammatory index (DII) and invasive breast cancer incidence and death. METHODS: The DII was calculated from a baseline food frequency questionnaire in 122 788 postmenopausal women, enrolled from 1993 to 1998 with no prior cancer, and followed until 29 August 2014. With median follow-up of 16.02 years, there were 7495 breast cancer cases and 667 breast cancer deaths. We used Cox regression to estimate multivariable-adjusted hazards ratios (HRs) and 95% confidence intervals (95% CIs) by DII quintiles (Q) for incidence of overall breast cancer, breast cancer subtypes, and deaths from breast cancer. The lowest quintile (representing the most anti-inflammatory diet) was the reference. RESULTS: The DII was not associated with incidence of overall breast cancer (HRQ5vsQ1, 0.99; 95% CI, 0.91-1.07; Ptrend=0.83 for overall breast cancer). In a full cohort analysis, a higher risk of death from breast cancer was associated with consumption of more pro-inflammatory diets at baseline, after controlling for multiple potential confounders (HRQ5vsQ1, 1.33; 95% CI, 1.01-1.76; Ptrend=0.03). CONCLUSIONS: Future studies are needed to examine the inflammatory potential of post-diagnosis diet given the suggestion from the current study that dietary inflammatory potential before diagnosis is related to breast cancer death

MOS11: A New Component in the mRNA Export Pathway

Nucleocytoplasmic trafficking is emerging as an important aspect of plant immunity. The three related pathways affecting plant immunity include Nuclear Localization Signal (NLS)–mediated nuclear protein import, Nuclear Export Signal (NES)–dependent nuclear protein export, and mRNA export relying on MOS3, a nucleoporin belonging to the Nup107–160 complex. Here we report the characterization, identification, and detailed analysis of Arabidopsis modifier of snc1, 11 (mos11). Mutations in MOS11 can partially suppress the dwarfism and enhanced disease resistance phenotypes of snc1, which carries a gain-of-function mutation in a TIR-NB-LRR type Resistance gene. MOS11 encodes a conserved eukaryotic protein with homology to the human RNA binding protein CIP29. Further functional analysis shows that MOS11 localizes to the nucleus and that the mos11 mutants accumulate more poly(A) mRNAs in the nucleus, likely resulting from reduced mRNA export activity. Epistasis analysis between mos3-1 and mos11-1 revealed that MOS11 probably functions in the same mRNA export pathway as MOS3, in a partially overlapping fashion, before the mRNA molecules pass through the nuclear pores. Taken together, MOS11 is identified as a new protein contributing to the transfer of mature mRNA from the nucleus to the cytosol

The pituitary tumor transforming gene 1 (PTTG-1): An immunological target for multiple myeloma

<p>Abstract</p> <p>Background</p> <p>Multiple Myeloma is a cancer of B plasma cells, which produce non-specific antibodies and proliferate uncontrolled. Due to the potential relapse and non-specificity of current treatments, immunotherapy promises to be more specific and may induce long-term immunity in patients. The pituitary tumor transforming gene 1 (PTTG-1) has been shown to be a novel oncogene, expressed in the testis, thymus, colon, lung and placenta (undetectable in most other tissues). Furthermore, it is over expressed in many tumors such as the pituitary adenoma, breast, gastrointestinal cancers, leukemia, lymphoma, and lung cancer and it seems to be associated with tumorigenesis, angiogenesis and cancer progression. The purpose was to investigate the presence/rate of expression of PTTG-1 in multiple myeloma patients.</p> <p>Methods</p> <p>We analyzed the PTTG-1 expression at the transcriptional and the protein level, by PCR, immunocytochemical methods, Dot-blot and ELISA performed on patient's sera in 19 multiple myeloma patients, 6 different multiple myeloma cell lines and in normal human tissue.</p> <p>Results</p> <p>We did not find PTTG-1 presence in the normal human tissue panel, but PTTG-1 mRNA was detectable in 12 of the 19 patients, giving evidence of a 63% rate of expression (data confirmed by ELISA). Four of the 6 investigated cell lines (66.6%) were positive for PTTG-1. Investigations of protein expression gave evidence of 26.3% cytoplasmic expression and 16% surface expression in the plasma cells of multiple myeloma patients. Protein presence was also confirmed by Dot-blot in both cell lines and patients.</p> <p>Conclusion</p> <p>We established PTTG-1's presence at both the transcriptional and protein levels. These data suggest that PTTG-1 is aberrantly expressed in multiple myeloma plasma cells, is highly immunogenic and is a suitable target for immunotherapy of multiple myeloma.</p

Non-Coding RNA Prediction and Verification in Saccharomyces cerevisiae

Non-coding RNA (ncRNA) play an important and varied role in cellular function. A significant amount of research has been devoted to computational prediction of these genes from genomic sequence, but the ability to do so has remained elusive due to a lack of apparent genomic features. In this work, thermodynamic stability of ncRNA structural elements, as summarized in a Z-score, is used to predict ncRNA in the yeast Saccharomyces cerevisiae. This analysis was coupled with comparative genomics to search for ncRNA genes on chromosome six of S. cerevisiae and S. bayanus. Sets of positive and negative control genes were evaluated to determine the efficacy of thermodynamic stability for discriminating ncRNA from background sequence. The effect of window sizes and step sizes on the sensitivity of ncRNA identification was also explored. Non-coding RNA gene candidates, common to both S. cerevisiae and S. bayanus, were verified using northern blot analysis, rapid amplification of cDNA ends (RACE), and publicly available cDNA library data. Four ncRNA transcripts are well supported by experimental data (RUF10, RUF11, RUF12, RUF13), while one additional putative ncRNA transcript is well supported but the data are not entirely conclusive. Six candidates appear to be structural elements in 5′ or 3′ untranslated regions of annotated protein-coding genes. This work shows that thermodynamic stability, coupled with comparative genomics, can be used to predict ncRNA with significant structural elements

Nucleolin Inhibits G4 Oligonucleotide Unwinding by Werner Helicase

The Werner protein (WRNp), a member of the RecQ helicase family, is strongly associated with the nucleolus, as is nucleolin (NCL), an important nucleolar constituent protein. Both WRNp and NCL respond to the effects of DNA damaging agents. Therefore, we have investigated if these nuclear proteins interact and if this interaction has a possible functional significance in DNA damage repair.Here we report that WRNp interacts with the RNA-binding protein, NCL, based on immunoprecipitation, immunofluorescent co-localization in live and fixed cells, and direct binding of purified WRNp to nucleolin. We also map the binding region to the C-terminal domains of both proteins. Furthermore, treatment of U2OS cells with 15 µM of the Topoisomerase I inhibitor, camptothecin, causes the dissociation of the nucleolin-Werner complex in the nucleolus, followed by partial re-association in the nucleoplasm. Other DNA damaging agents, such as hydroxyurea, Mitomycin C, and aphidicolin do not have these effects. Nucleolin or its C-terminal fragment affected the helicase, but not the exonuclease activity of WRNp, by inhibiting WRN unwinding of G4 tetraplex DNA structures, as seen in activity assays and electrophoretic mobility shift assays (EMSA).These data suggest that nucleolin may regulate G4 DNA unwinding by WRNp, possibly in response to certain DNA damaging agents. We postulate that the NCL-WRNp complex may contain an inactive form of WRNp, which is released from the nucleolus upon DNA damage. Then, when required, WRNp is released from inhibition and can participate in the DNA repair processes

Reduced Levels of Membrane-Bound Alkaline Phosphatase Are Common to Lepidopteran Strains Resistant to Cry Toxins from Bacillus thuringiensis

Development of insect resistance is one of the main concerns with the use of transgenic crops expressing Cry toxins from the bacterium Bacillus thuringiensis. Identification of biomarkers would assist in the development of sensitive DNA-based methods to monitor evolution of resistance to Bt toxins in natural populations. We report on the proteomic and genomic detection of reduced levels of midgut membrane-bound alkaline phosphatase (mALP) as a common feature in strains of Cry-resistant Heliothis virescens, Helicoverpa armigera and Spodoptera frugiperda when compared to susceptible larvae. Reduced levels of H. virescens mALP protein (HvmALP) were detected by two dimensional differential in-gel electrophoresis (2D-DIGE) analysis in Cry-resistant compared to susceptible larvae, further supported by alkaline phosphatase activity assays and Western blotting. Through quantitative real-time polymerase chain reaction (qRT-PCR) we demonstrate that the reduction in HvmALP protein levels in resistant larvae are the result of reduced transcript amounts. Similar reductions in ALP activity and mALP transcript levels were also detected for a Cry1Ac-resistant strain of H. armigera and field-derived strains of S. frugiperda resistant to Cry1Fa. Considering the unique resistance and cross-resistance phenotypes of the insect strains used in this work, our data suggest that reduced mALP expression should be targeted for development of effective biomarkers for resistance to Cry toxins in lepidopteran pests

The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

BACKGROUND: Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them.RESULTS:A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthew's Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89 and the best AUC iP/R was 68. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were evaluated by comparing systems against manually generated annotations done by curators from the BioGRID and MINT databases. The highest AUC iP/R achieved by any run was 53, the best MCC score 0.55. In case of competitive systems with an acceptable recall (above 35) the macro-averaged precision ranged between 50 and 80, with a maximum F-Score of 55. CONCLUSIONS: The results of the ACT task of BioCreative III indicate that classification of large unbalanced article collections reflecting the real class imbalance is still challenging. Nevertheless, text-mining tools that report ranked lists of relevant articles for manual selection can potentially reduce the time needed to identify half of the relevant articles to less than 1/4 of the time when compared to unranked results. Detecting associations between full text articles and interaction detection method PSI-MI terms (IMT) is more difficult than might be anticipated. This is due to the variability of method term mentions, errors resulting from pre-processing of articles provided as PDF files, and the heterogeneity and different granularity of method term concepts encountered in the ontology. However, combining the sophisticated techniques developed by the participants with supporting evidence strings derived from the articles for human interpretation could result in practical modules for biological annotation workflows

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas