The impact of a minimal smoking cessation intervention for pregnant women and their partners on perinatal smoking behaviour in primary health care: A real-life controlled study

<p>Abstract</p> <p>Background</p> <p>There is a demand for strategies to promote smoking cessation in high-risk populations like smoking pregnant women and their partners. The objectives of this study were to investigate parental smoking behaviour during pregnancy after introduction of a prenatal, structured, multi-disciplinary smoking cessation programme in primary care, and to compare smoking behaviour among pregnant women in the city of Trondheim with Bergen and Norway.</p> <p>Methods</p> <p>Sequential birth cohorts were established to evaluate the intervention programme from September 2000 to December 2004 in primary care as a part of the Prevention of Allergy among Children in Trondheim study (PACT). The primary outcome variables were self reported smoking behaviour at inclusion and six weeks postnatal. Data from the Medical Birth Registry of Norway (MBR) were used to describe smoking cessation during pregnancy in Trondheim, Bergen and Norway 1999–2004.</p> <p>Results</p> <p>Maternal smoking prevalence at inclusion during pregnancy were 5% (CI 95% 4–6) in the intervention cohort compared to 7% (CI 95% 6–9), p = 0.03, in the control cohort. Of the pre-pregnancy maternal smokers 25% (CI 95% 20–31) and 32% (CI 95% 26–38), p = 0.17, were still smoking at inclusion in the intervention and control cohorts, respectively. Six weeks postnatal 72% (CI 95% 59–83) and 68% (CI 95% 57–77), p = 0.34 of the maternal smokers at inclusion still smoked. No significant difference in paternal smoking between the cohorts was found after the intervention period. Data from the MBR showed a significantly higher proportion of women who stopped smoking during pregnancy in Trondheim than in Bergen in 2003 and 2004, p = 0.03 and < 0.001, respectively.</p> <p>Conclusion</p> <p>No impact on parental smoking behaviour between the cohorts was observed after the smoking intervention programme. Of the women who stopped smoking during pregnancy most of them stopped smoking before the intervention. However, we observed a significantly higher quitting rate in Trondheim than in Bergen in 2003 and 2004 which may have been facilitated by the supplemental attention on smoking behaviour the PACT study initiated.</p

Characterisation and correction of signal fluctuations in successive acquisitions of microarray images

<p>Abstract</p> <p>Background</p> <p>There are many sources of variation in dual labelled microarray experiments, including data acquisition and image processing. The final interpretation of experiments strongly relies on the accuracy of the measurement of the signal intensity. For low intensity spots in particular, accurately estimating gene expression variations remains a challenge as signal measurement is, in this case, highly subject to fluctuations.</p> <p>Results</p> <p>To evaluate the fluctuations in the fluorescence intensities of spots, we used series of successive scans, at the same settings, of whole genome arrays. We measured the decrease in fluorescence and we evaluated the influence of different parameters (PMT gain, resolution and chemistry of the slide) on the signal variability, at the level of the array as a whole and by intensity interval. Moreover, we assessed the effect of averaging scans on the fluctuations. We found that the extent of photo-bleaching was low and we established that 1) the fluorescence fluctuation is linked to the resolution e.g. it depends on the number of pixels in the spot 2) the fluorescence fluctuation increases as the scanner voltage increases and, moreover, is higher for the red as opposed to the green fluorescence which can introduce bias in the analysis 3) the signal variability is linked to the intensity level, it is higher for low intensities 4) the heterogeneity of the spots and the variability of the signal and the intensity ratios decrease when two or three scans are averaged.</p> <p>Conclusion</p> <p>Protocols consisting of two scans, one at low and one at high PMT gains, or multiple scans (ten scans) can introduce bias or be difficult to implement. We found that averaging two, or at most three, acquisitions of microarrays scanned at moderate photomultiplier settings (PMT gain) is sufficient to significantly improve the accuracy (quality) of the data and particularly those for spots having low intensities and we propose this as a general approach. For averaging and precise image alignment at sub-pixel levels we have made a program freely available on our web-site <url>http://bioinfome.cgm.cnrs-gif.fr</url> to facilitate implementation of this approach.</p

Combining active learning and semi-supervised learning techniques to extract protein interaction sentences

Background: Protein-protein interaction (PPI) extraction has been a focal point of many biomedical research and database curation tools. Both Active Learning and Semi-supervised SVMs have recently been applied to extract PPI automatically. In this paper, we explore combining the AL with the SSL to improve the performance of the PPI task. Methods: We propose a novel PPI extraction technique called PPISpotter by combining Deterministic Annealing-based SSL and an AL technique to extract protein-protein interaction. In addition, we extract a comprehensive set of features from MEDLINE records by Natural Language Processing (NLP) techniques, which further improve the SVM classifiers. In our feature selection technique, syntactic, semantic, and lexical properties of text are incorporated into feature selection that boosts the system performance significantly. Results: By conducting experiments with three different PPI corpuses, we show that PPISpotter is superior to the other techniques incorporated into semi-supervised SVMs such as Random Sampling, Clustering, and Transductive SVMs by precision, recall, and F-measure. Conclusions: Our system is a novel, state-of-the-art technique for efficiently extracting protein-protein interaction pairs.X116sciescopu

End-Tagging of Ultra-Short Antimicrobial Peptides by W/F Stretches to Facilitate Bacterial Killing

BACKGROUND: Due to increasing resistance development among bacteria, antimicrobial peptides (AMPs), are receiving increased attention. Ideally, AMP should display high bactericidal potency, but low toxicity against (human) eukaryotic cells. Additionally, short and proteolytically stable AMPs are desired to maximize bioavailability and therapeutic versatility. METHODOLOGY AND PRINCIPAL FINDINGS: A facile approach is demonstrated for reaching high potency of ultra-short antimicrobal peptides through end-tagging with W and F stretches. Focusing on a peptide derived from kininogen, KNKGKKNGKH (KNK10) and truncations thereof, end-tagging resulted in enhanced bactericidal effect against Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus. Through end-tagging, potency and salt resistance could be maintained down to 4-7 amino acids in the hydrophilic template peptide. Although tagging resulted in increased eukaryotic cell permeabilization at low ionic strength, the latter was insignificant at physiological ionic strength and in the presence of serum. Quantitatively, the most potent peptides investigated displayed bactericidal effects comparable to, or in excess of, that of the benchmark antimicrobial peptide LL-37. The higher bactericidal potency of the tagged peptides correlated to a higher degree of binding to bacteria, and resulting bacterial wall rupture. Analogously, tagging enhanced peptide-induced rupture of liposomes, particularly anionic ones. Additionally, end-tagging facilitated binding to bacterial lipopolysaccharide, both effects probably contributing to the selectivity displayed by these peptides between bacteria and eukaryotic cells. Importantly, W-tagging resulted in peptides with maintained stability against proteolytic degradation by human leukocyte elastase, as well as staphylococcal aureolysin and V8 proteinase. The biological relevance of these findings was demonstrated ex vivo for pig skin infected by S. aureus and E. coli. CONCLUSIONS/SIGNIFICANCE: End-tagging by hydrophobic amino acid stretches may be employed to enhance bactericidal potency also of ultra-short AMPs at maintained limited toxicity. The approach is of general applicability, and facilitates straightforward synthesis of hydrophobically modified AMPs without the need for post-peptide synthesis modifications

Anti-HIV-1 Activity of a New Scorpion Venom Peptide Derivative Kn2-7

For over 30 years, HIV/AIDS has wreaked havoc in the world. In the absence of an effective vaccine for HIV, development of new anti-HIV agents is urgently needed. We previously identified the antiviral activities of the scorpion-venom-peptide-derived mucroporin-M1 for three RNA viruses (measles viruses, SARS-CoV, and H5N1). In this investigation, a panel of scorpion venom peptides and their derivatives were designed and chosen for assessment of their anti-HIV activities. A new scorpion venom peptide derivative Kn2-7 was identified as the most potent anti-HIV-1 peptide by screening assays with an EC50 value of 2.76 µg/ml (1.65 µM) and showed low cytotoxicity to host cells with a selective index (SI) of 13.93. Kn2-7 could inhibit all members of a standard reference panel of HIV-1 subtype B pseudotyped virus (PV) with CCR5-tropic and CXCR4-tropic NL4-3 PV strain. Furthermore, it also inhibited a CXCR4-tropic replication-competent strain of HIV-1 subtype B virus. Binding assay of Kn2-7 to HIV-1 PV by Octet Red system suggested the anti-HIV-1 activity was correlated with a direct interaction between Kn2-7 and HIV-1 envelope. These results demonstrated that peptide Kn2-7 could inhibit HIV-1 by direct interaction with viral particle and may become a promising candidate compound for further development of microbicide against HIV-1

Human Antimicrobial Peptide LL-37 Inhibits Adhesion of Candida albicans by Interacting with Yeast Cell-Wall Carbohydrates

Candida albicans is the major fungal pathogen of humans. Fungal adhesion to host cells is the first step of mucosal infiltration. Antimicrobial peptides play important roles in the initial mucosal defense against C. albicans infection. LL-37 is the only member of the human cathelicidin family of antimicrobial peptides and is commonly expressed in various tissues and cells, including epithelial cells of both the oral cavity and urogenital tract. We found that, at sufficiently low concentrations that do not kill the fungus, LL-37 was still able to reduce C. albicans infectivity by inhibiting C. albicans adhesion to plastic surfaces, oral epidermoid OECM-1 cells, and urinary bladders of female BALB/c mice. Moreover, LL-37-treated C. albicans floating cells that did not adhere to the underlying substratum aggregated as a consequence of LL-37 bound to the cell surfaces. According to the results of a competition assay, the inhibitory effects of LL-37 on cell adhesion and aggregation were mediated by its preferential binding to mannan, the main component of the C. albicans cell wall, and partially by its ability to bind chitin or glucan, which underlie the mannan layer. Therefore, targeting of cell-wall carbohydrates by LL-37 provides a new strategy to prevent C. albicans infection, and LL-37 is a useful, new tool to screen for other C. albicans components involved in adhesion

Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions

Abstract Background Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. Methods In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher’s exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. Results INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with ‘INO_’ prefix. A new annotation property, ‘has literature mining keywords’, was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher’s exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these interaction types and their associated gene-gene pairs uncovered many scientific insights. Conclusions INO provides a novel approach for defining hierarchical interaction types and related keywords for literature mining. The ontology-based literature mining, in combination with an INO-based statistical interaction enrichment test, provides a new platform for efficient mining and analysis of topic-specific gene interaction networks.http://deepblue.lib.umich.edu/bitstream/2027.42/110806/1/13326_2014_Article_197.pd