Epigenome-wide association study reveals decreased average methylation levels years before breast cancer diagnosis

Interest in the potential of DNA methylation in peripheral blood as a biomarker of cancer risk is increasing. We aimed to assess whether epigenome-wide DNA methylation measured in peripheral blood samples obtained before onset of the disease is associated with increased risk of breast cancer. We report on three independent prospective nested case-control studies from the European Prospective Investigation into Cancer and Nutrition (EPIC-Italy; n = 162 matched case-control pairs), the Norwegian Women and Cancer study (NOWAC; n = 168 matched pairs), and the Breakthrough Generations Study (BGS; n = 548 matched pairs). We used the Illumina 450k array to measure methylation in the EPIC and NOWAC cohorts. Whole-genome bisulphite sequencing (WGBS) was performed on the BGS cohort using pooled DNA samples, combined to reach 50× coverage across ~16 million CpG sites in the genome including 450k array CpG sites. Mean β values over all probes were calculated as a measurement for epigenome-wide methylation

Thinking together: What makes Communities of Practice work?

In this article, we develop the founding elements of the concept of Communities of Practice by elaborating on the learning processes happening at the heart of such communities. In particular, we provide a consistent perspective on the notions of knowledge, knowing and knowledge sharing that is compatible with the essence of this concept – that learning entails an investment of identity and a social formation of a person. We do so by drawing richly from the work of Michael Polanyi and his conception of personal knowledge, and thereby we clarify the scope of Communities of Practice and offer a number of new insights into how to make such social structures perform well in professional settings. The conceptual discussion is substantiated by findings of a qualitative empirical study in the UK National Health Service. As a result, the process of ‘thinking together’ is conceptualized as a key part of meaningful Communities of Practice where people mutually guide each other through their understandings of the same problems in their area of mutual interest, and this way indirectly share tacit knowledge. The collaborative learning process of ‘thinking together’, we argue, is what essentially brings Communities of Practice to life and not the other way round

Genomic-Bioinformatic Analysis of Transcripts Enriched in the Third-Stage Larva of the Parasitic Nematode Ascaris suum

Differential transcription in Ascaris suum was investigated using a genomic-bioinformatic approach. A cDNA archive enriched for molecules in the infective third-stage larva (L3) of A. suum was constructed by suppressive-subtractive hybridization (SSH), and a subset of cDNAs from 3075 clones subjected to microarray analysis using cDNA probes derived from RNA from different developmental stages of A. suum. The cDNAs (n = 498) shown by microarray analysis to be enriched in the L3 were sequenced and subjected to bioinformatic analyses using a semi-automated pipeline (ESTExplorer). Using gene ontology (GO), 235 of these molecules were assigned to ‘biological process’ (n = 68), ‘cellular component’ (n = 50), or ‘molecular function’ (n = 117). Of the 91 clusters assembled, 56 molecules (61.5%) had homologues/orthologues in the free-living nematodes Caenorhabditis elegans and C. briggsae and/or other organisms, whereas 35 (38.5%) had no significant similarity to any sequences available in current gene databases. Transcripts encoding protein kinases, protein phosphatases (and their precursors), and enolases were abundantly represented in the L3 of A. suum, as were molecules involved in cellular processes, such as ubiquitination and proteasome function, gene transcription, protein–protein interactions, and function. In silico analyses inferred the C. elegans orthologues/homologues (n = 50) to be involved in apoptosis and insulin signaling (2%), ATP synthesis (2%), carbon metabolism (6%), fatty acid biosynthesis (2%), gap junction (2%), glucose metabolism (6%), or porphyrin metabolism (2%), although 34 (68%) of them could not be mapped to a specific metabolic pathway. Small numbers of these 50 molecules were predicted to be secreted (10%), anchored (2%), and/or transmembrane (12%) proteins. Functionally, 17 (34%) of them were predicted to be associated with (non-wild-type) RNAi phenotypes in C. elegans, the majority being embryonic lethality (Emb) (13 types; 58.8%), larval arrest (Lva) (23.5%) and larval lethality (Lvl) (47%). A genetic interaction network was predicted for these 17 C. elegans orthologues, revealing highly significant interactions for nine molecules associated with embryonic and larval development (66.9%), information storage and processing (5.1%), cellular processing and signaling (15.2%), metabolism (6.1%), and unknown function (6.7%). The potential roles of these molecules in development are discussed in relation to the known roles of their homologues/orthologues in C. elegans and some other nematodes. The results of the present study provide a basis for future functional genomic studies to elucidate molecular aspects governing larval developmental processes in A. suum and/or the transition to parasitism

A molecular insight into algal-oomycete warfare : cDNA analysis of Ectocarpus siliculosus infected with the basal oomycete Eurychasma dicksonii

Peer reviewedPublisher PD

Carbohydrate mouth rinse: does it improve endurance exercise performance?

It is well known that carbohydrate (CHO) supplementation can improve performance in endurance exercises through several mechanisms such as maintenance of glycemia and sparing endogenous glycogen as well as the possibility of a central nervous-system action. Some studies have emerged in recent years in order to test the hypothesis of ergogenic action via central nervous system. Recent studies have demonstrated that CHO mouth rinse can lead to improved performance of cyclists, and this may be associated with the activation of brain areas linked to motivation and reward. These findings have already been replicated in other endurance modalities, such as running. This alternative seems to be an attractive nutritional tool to improve endurance exercise performance

Impact of HPV vaccination : health gains in the Italian female population

Abstract Background Human papillomavirus (HPV) is the leading cause of cervical cancer and other malignant and benign neoplastic lesions. HPV vaccination has three potential goals: to prevent transmission, infection, and disease. At present, there are no available data about health consequences of HPV immunization in Italy. The aim of this study is to evaluate the effect of current HPV vaccination strategy in Italy. Methods A multistate morbidity-mortality model was developed to estimate the infection process in a theoretical cohort of Italian women. The Markov process considered nine health states (health, anogenital warts, grade 1 and grade 2/3 cervical intraepithelial neoplasia, cervical cancer, anal cancer, death due to cervical cancer, anal cancer and other causes), and 26 transition probabilities for each age group. The model was informed with the available data in national and international literature. Effectiveness of immunization was assumed considering a literature review pertaining to models and vaccination coverage rates observed in Italy. Life expectancy (ex), Quality-Adjusted Life Years (QALYs), Disability-Adjusted Life Years (DALYs), and attributable risk (AR) were estimated for no intervention (cervical cancer screening) and vaccination strategies scenarios. Results The model showed that in a cohort of 100,000 Italian women the e0 is equal to 83.1 years. With current HPV vaccination strategy the e0 achieves 83.2 (+0.1) years. When HPV-related diseases are considered altogether, the QALYs increase from 82.7 to 82.9 (+0.2 QALYs) with no intervention and vaccination strategies respectively. DALYs decrease by 0.6 due to vaccination. Finally, AR is equal to 93 and 265 cases per 100,000 women in population and not vaccinated, respectively. Conclusion When mortality due to cervical cancer is considered, HPV vaccination seems to have a low impact on health unit gains in the Italian female population. Conversely, when several HPV-related and cancer morbidity conditions are included, the effect of vaccination becomes quite remarkable

Flaws in design, analysis and interpretation of Pfizer's antifungal trials of voriconazole and uncritical subsequent quotations

We have previously described how a series of trials sponsored by Pfizer of its antifungal drug, fluconazole, in cancer patients with neutropenia handicapped the control drug, amphotericin B, by flaws in design and analysis. We describe similar problems in two pivotal trials of Pfizer's new antifungal agent, voriconazole, published in a prestigious journal. In a non-inferiority trial, voriconazole was significantly inferior to liposomal amphothericin B, but the authors concluded that voriconazole was a suitable alternative. The second trial used amphothericin B deoxycholate as comparator, but handicapped the drug by not requiring pre-medication to reduce infusion-related toxicity or substitution with electrolytes and fluid to reduce nephrotoxicity, although the planned duration of treatment was 84 days. Voriconazole was given for 77 days on average, but the comparator for only 10 days, which precludes a meaningful comparison. In a random sample of 50 references to these trials, we found that the unwarranted conclusions were mostly uncritically propagated. It was particularly surprising that relevant criticism raised by the FDA related to the first trial was only quoted once, and that none of the articles noted the obvious flaws in the design of the second trial. We suggest that editors ensure that the abstract reflects fairly on the remainder of the paper, and that journals do not impose any time limit for accepting letters that point out serious weaknesses in a study that have not been noted before

MemBrain: Improving the Accuracy of Predicting Transmembrane Helices

Prediction of transmembrane helices (TMH) in α helical membrane proteins provides valuable information about the protein topology when the high resolution structures are not available. Many predictors have been developed based on either amino acid hydrophobicity scale or pure statistical approaches. While these predictors perform reasonably well in identifying the number of TMHs in a protein, they are generally inaccurate in predicting the ends of TMHs, or TMHs of unusual length. To improve the accuracy of TMH detection, we developed a machine-learning based predictor, MemBrain, which integrates a number of modern bioinformatics approaches including sequence representation by multiple sequence alignment matrix, the optimized evidence-theoretic K-nearest neighbor prediction algorithm, fusion of multiple prediction window sizes, and classification by dynamic threshold. MemBrain demonstrates an overall improvement of about 20% in prediction accuracy, particularly, in predicting the ends of TMHs and TMHs that are shorter than 15 residues. It also has the capability to detect N-terminal signal peptides. The MemBrain predictor is a useful sequence-based analysis tool for functional and structural characterization of helical membrane proteins; it is freely available at http://chou.med.harvard.edu/bioinf/MemBrain/

Model based dynamics analysis in live cell microtubule images

Background: The dynamic growing and shortening behaviors of microtubules are central to the fundamental roles played by microtubules in essentially all eukaryotic cells. Traditionally, microtubule behavior is quantified by manually tracking individual microtubules in time-lapse images under various experimental conditions. Manual analysis is laborious, approximate, and often offers limited analytical capability in extracting potentially valuable information from the data. Results: In this work, we present computer vision and machine-learning based methods for extracting novel dynamics information from time-lapse images. Using actual microtubule data, we estimate statistical models of microtubule behavior that are highly effective in identifying common and distinct characteristics of microtubule dynamic behavior. Conclusion: Computational methods provide powerful analytical capabilities in addition to traditional analysis methods for studying microtubule dynamic behavior. Novel capabilities, such as building and querying microtubule image databases, are introduced to quantify and analyze microtubule dynamic behavior