bluuebunny/crossref_metadata_2025 huggingface dataset:
A Hybrid Approach for Biomarker Discovery from Microarray Gene Expression Data for Cancer Classification
Authors: Peng Yanxiong , Li Wenyuan , Liu Ying
Published: October 2017

Microarrays allow researchers to monitor the gene expression patterns for tens of thousands of genes across a wide range of cellular responses, phenotype and conditions. Selecting a small subset of discriminate genes from thousands of genes is important for accurate classification of diseases and phenotypes. Many methods have been proposed to find subsets of genes with maximum relevance and minimum redundancy, which can distinguish accurately between samples with different labels. To find the minimum subset of relevant genes is often referred as biomarker discovery. Two main approaches, filter and wrapper techniques, have been applied to biomarker discovery. In this paper, we conducted a comparative study of different biomarker discovery methods, including six filter methods and three wrapper methods. We then proposed a hybrid approach, FR-Wrapper, for biomarker discovery. The aim of this approach is to find an optimum balance between the precision of the biomarker discovery and the computation cost, by taking advantages of both filter method's efficiency and wrapper method's high accuracy. Our hybrid approach applies Fisher's ratio, a simple method easy to understand and implement, to filter out most of the irrelevant genes, then a wrapper method is employed to reduce the redundancy. The performance of FR-Wrapper approach is evaluated over four widely used microarray datasets. Analysis of experimental results reveals that the hybrid approach can achieve the goal of maximum relevance with minimum redundancy.
Application of a New Probabilistic Model for Mining Implicit Associated Cancer Genes from OMIM and Medline
Authors: Zhu Shanfeng , Okuno Yasushi , Tsujimoto Gozoh , Mamitsuka Hiroshi
Published: October 2017

An important issue in current medical science research is to find the genes that are strongly related to an inherited disease. A particular focus is placed on cancer-gene relations, since some types of cancers are inherited. As bio-medical databases have grown speedily in recent years, an informatics approach to predict such relations from currently available databases should be developed. Our objective is to find implicit associated cancer-genes from biomedical databases including the literature database. Co-occurrence of biological entities has been shown to be a popular and efficient technique in biomedical text mining. We have applied a new probabilistic model, called mixture aspect model (MAM) [ 48 ], to combine different types of co-occurrences of genes and cancer derived from Medline and OMIM (Online Mendelian Inheritance in Man). We trained the probability parameters of MAM using a learning method based on an EM (Expectation and Maximization) algorithm. We examined the performance of MAM by predicting associated cancer gene pairs. Through cross-validation, prediction accuracy was shown to be improved by adding gene-gene co-occurrences from Medline to cancer-gene co-occurrences in OMIM. Further experiments showed that MAM found new cancer-gene relations which are unknown in the literature. Supplementary information can be found at http://www.bic.kyotou.ac.jp/pathway/zhusf/CancerInformatics/Supplemental2006.html
Plasma Protein Profiles Differ between Women Diagnosed with Cervical Intraepithelial Neoplasia (CIN) 1 and 3
Authors: Piyathilake Chandrika J. , Oelschlager Denise K. , Meleth Sreelatha , Partridge Edward E. , Grizzle William E.
Published: October 2017

Early detection of precancerous cells in the cervix and their clinical management is the main purpose of cervical cancer prevention and treatment programs. Cytological findings or testing for high risk (HR)-human papillomavirus (HPV) are inadequately sensitive for use in triage of women at high risk for cervical cancer. The current study is an exploratory study to identify candidate surface-enhanced laser desorption/ionization (SELDI) time of flight (TOF) mass spectrometry (MS) protein profiles in plasma that may distinguish cervical intraepithelial neoplasia (CIN 3) from CIN 1 among women infected with HR-HPV. We evaluated the SELDI-TOF-MS plasma protein profiles of HR-HPV positive 32 women with CIN 3 (cases) and 28 women with CIN1 (controls). Case-control status was kept blinded and triplicates of each sample and quality control plasma samples were randomized and after robotic sample preparations were run on WCX2 chips. After alignment of mass/charge (m-z values), an iterative method was used to develop a classifier on a training data set that had 28 cases and 22 controls. The classifier developed was used to classify the subjects in a test data set that has six cases and six controls. The classifier separated the cases from controls in the test set with 100% sensitivity and 100% specificity suggesting the possibility of using plasma SELDI protein profiles to identify women who are likely to have CIN 3 lesions.
Ovarian Cancer Classification Based on Mass Spectrometry Analysis of Sera
Authors: Wu Baolin , Abbott Tom , Fishman David , Mcmurray Walter , Mor Gil , Stone Kathryn , Ward David , Williams Kenneth , Zhao Hongyu
Published: October 2017

In our previous study [ 1 ], we have compared the performance of a number of widely used discrimination methods for classifying ovarian cancer using Matrix Assisted Laser Desorption Ionization (MALDI) mass spectrometry data on serum samples obtained from Reflectron mode. Our results demonstrate good performance with a random forest classifier. In this follow-up study, to improve the molecular classification power of the MALDI platform for ovarian cancer disease, we expanded the mass range of the MS data by adding data acquired in Linear mode and evaluated the resultant decrease in classification error. A general statistical framework is proposed to obtain unbiased classification error estimates and to analyze the effects of sample size and number of selected m/z features on classification errors. We also emphasize the importance of combining biological knowledge and statistical analysis to obtain both biologically and statistically sound results.

Our study shows improvement in classification accuracy upon expanding the mass range of the analysis. In order to obtain the best classification accuracies possible, we found that a relatively large training sample size is needed to obviate the sample variations. For the ovarian MS dataset that is the focus of the current study, our results show that approximately 20–40 m/z features are needed to achieve the best classification accuracy from MALDI-MS analysis of sera. Supplementary information can be found at http://bioinformatics.med.yale.edu/proteomics/BioSupp2.html .
Overlay Tool© for aCGHViewer©: An Analysis Module Built for aCGHViewer© used to Perform Comparisons of Data Derived from Different Microarray Platforms
Authors: Lo Ken C. , Shankar Ganesh , Turpaz Yaron , Bailey Dione , Rossi Michael R. , Burkhardt Tania , Liang Ping , Cowell John K.
Published: October 2017

The Overlay Tool© has been developed to combine high throughput data derived from various microarray platforms. This tool analyzes high-resolution correlations between gene expression changes and either copy number abnormalities (CNAs) or loss of heterozygosity events detected using array comparative genomic hybridization (aCGH). Using an overlay analysis which is designed to be performed using data from multiple microarray platforms on a single biological sample, the Overlay Tool© identifies potentially important genes whose expression profiles are changed as a result of losses, gains and amplifications in the cancer genome. In addition, the Overlay Tool© will incorporate loss of heterozygosity (LOH) probability data into this overlay procedure. To facilitate this analysis, we developed an application which computationally combines two or more high throughput datasets (e.g. aCGH/expression) into a single categorized dataset for visualization and interrogation using a gene-centric approach. As such, data from virtually any microarray platform can be incorporated without the need to remap entire datasets individually. The resultant categorized (overlay) data set can be conveniently viewed using our in-house visualization tool, aCGHViewer© (Shankar et al. 2006), which serves as a conduit to public databases such as UCSC and NCBI, to rapidly investigate genes of interest.
Identification and Characterization of Renal Cell Carcinoma Gene Markers
Authors: Dalgin Gul S. , Holloway Dustin T. , Liou Louis S. , Delisi Charles
Published: October 2017

Microarray gene expression profiling has been used to distinguish histological subtypes of renal cell carcinoma (RCC), and consequently to identify specific tumor markers. The analytical procedures currently in use find sets of genes whose average differential expression across the two categories differ significantly. In general each of the markers thus identified does not distinguish tumor from normal with 100% accuracy, although the group as a whole might be able to do so. For the purpose of developing a widely used economically viable diagnostic signature, however, large groups of genes are not likely to be useful. Here we use two different methods, one a support vector machine variant, and the other an exhaustive search, to reanalyze data previously generated in our Lab (Lenburg et al. 2003). We identify 158 genes, each having an expression level that is higher (lower) in every tumor sample than in any normal sample, and each having a minimum differential expression across the two categories at a significance of 0.01. The set is highly enriched in cancer related genes (p = 1.6 × 10–12), containing 43 genes previously associated with either RCC or other types of cancer. Many of the biomarkers appear to be associated with the central alterations known to be required for cancer transformation. These include the oncogenes JAZF1, AXL, ABL2; tumor suppressors RASD1, PTPRO, TFAP2A, CDKN1C; and genes involved in proteolysis or cell-adhesion such as WASF2, and PAPPA.
Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data
Authors: Hu Simin , Rao J. Sunil
Published: October 2017

In gene selection for cancer classification using microarray data, we define an eigenvalue-ratio statistic to measure a gene's contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalue-ratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.
Gamma-Normal-Gamma Mixture Model for Detecting Differentially Methylated Loci in Three Breast Cancer Cell Lines
Authors: Khalili Abbas , Potter Dustin , Yan Pearlly , Li Lang , Gray Joe , Huang Tim , Lin Shili
Published: October 2017

With state-of-the-art microarray technologies now available for whole genome CpG island (CGI) methylation profiling, there is a need to develop statistical models that are specifically geared toward the analysis of such data. In this article, we propose a Gamma-Normal-Gamma (GNG) mixture model for describing three groups of CGI loci: hypomethylated, undifferentiated, and hypermethylated, from a single methylation microarray. This model was applied to study the methylation signatures of three breast cancer cell lines: MCF7, T47D, and MDAMB361. Biologically interesting and interpretable results are obtained, which highlights the heterogeneity nature of the three cell lines. This underlies the premise for the need of analyzing each of the microarray slides individually as opposed to pooling them together for a single analysis. Our comparisons with the fitted densities from the Normal-Uniform (NU) mixture model in the literature proposed for gene expression analysis show an improved goodness of fit of the GNG model over the NU model. Although the GNG model was proposed in the context of single-slide methylation analysis, it can be readily adapted to analyze multi-slide methylation data as well as other types of microarray data.
Global Tumor RNA Expression in Early Establishment of Experimental Tumor Growth and Related Angiogenesis following Cox-Inhibition Evaluated by Microarray Analysis
Authors: Axelsson Hans , Lönnroth Christina , Andersson Marianne , Wang Wenhua , Lundholm Kent
Published: October 2017

Altered expression of COX-2 and overproduction of prostaglandins, particularly prostaglandin E2, are common in malignant tumors. Consequently, non-steroidal anti-inflammatory drugs (NSAIDs) attenuate tumor net growth, tumor related cachexia, improve appetite and prolong survival. We have also reported that COX-inhibition (indomethacin) interfered with early onset of tumor endothelial cell growth, tumor cell proliferation and apoptosis. It is however still unclear whether such effects are restricted to metabolic alterations closely related to eicosanoid pathways and corresponding regulators, or whether a whole variety of gene products are involved both up- and downstream effects of eicosanoids. Therefore, present experiments were performed by the use of an in vivo, intravital chamber technique, where micro-tumor growth and related angiogenesis were analyzed by microarray to evaluate for changes in global RNA expression caused by indomethacin treatment.

Indomethacin up-regulated 351 and down-regulated 1852 genes significantly (p < 0.01); 1066 of these genes had unknown biological function. Genes with altered expression occurred on all chromosomes.

Our results demonstrate that indomethacin altered expression of a large number of genes distributed among a variety of processes in the carcinogenic progression involving angiogenesis, apoptosis, cell-cycling, cell adhesion, inflammation as well as fatty acid metabolism and proteolysis. It remains a challenge to distinguish primary key alterations from secondary adaptive changes in transcription of genes altered by cyclooxygenase inhibition.
Data Mining for Gene Networks Relevant to Poor Prognosis in Lung Cancer via Backward-Chaining Rule Induction
Authors: Edgerton Mary E. , Fisher Douglas H. , Tang Lianhong , Frey Lewis J. , Chen Zhihua
Published: October 2017

We use Backward Chaining Rule Induction (BCRI), a novel data mining method for hypothesizing causative mechanisms, to mine lung cancer gene expression array data for mechanisms that could impact survival. Initially, a supervised learning system is used to generate a prediction model in the form of “IF  THEN ” style rules. Next, each antecedent (i.e. an IF condition) of a previously discovered rule becomes the outcome class for subsequent application of supervised rule induction. This step is repeated until a termination condition is satisfied. “Chains” of rules are created by working backward from an initial condition (e.g. survival status). Through this iterative process of “backward chaining,” BCRI searches for rules that describe plausible gene interactions for subsequent validation. Thus, BCRI is a semi-supervised approach that constrains the search through the vast space of plausible causal mechanisms by using a top-level outcome to kick-start the process. We demonstrate the general BCRI task sequence, how to implement it, the validation process, and how BCRI-rules discovered from lung cancer microarray data can be combined with prior knowledge to generate hypotheses about functional genomics.
Systems Level Modeling of the Cell Cycle Using Budding Yeast
Authors: Ingalls B.P. , Duncker B.P. , Kim D.R. , McConkey B.J.
Published: October 2017

Proteins involved in the regulation of the cell cycle are highly conserved across all eukaryotes, and so a relatively simple eukaryote such as yeast can provide insight into a variety of cell cycle perturbations including those that occur in human cancer. To date, the budding yeast Saccharomyces cerevisiae has provided the largest amount of experimental and modeling data on the progression of the cell cycle, making it a logical choice for in-depth studies of this process. Moreover, the advent of methods for collection of high-throughput genome, transcriptome, and proteome data has provided a means to collect and precisely quantify simultaneous cell cycle gene transcript and protein levels, permitting modeling of the cell cycle on the systems level. With the appropriate mathematical framework and sufficient and accurate data on cell cycle components, it should be possible to create a model of the cell cycle that not only effectively describes its operation, but can also predict responses to perturbations such as variation in protein levels and responses to external stimuli including targeted inhibition by drugs. In this review, we summarize existing data on the yeast cell cycle, proteomics technologies for quantifying cell cycle proteins, and the mathematical frameworks that can integrate this data into representative and effective models. Systems level modeling of the cell cycle will require the integration of high-quality data with the appropriate mathematical framework, which can currently be attained through the combination of dynamic modeling based on proteomics data and using yeast as a model organism.
Feature Selection for Predicting Tumor Metastases in Microarray Experiments using Paired Design
Authors: Tan Qihua , Thomassen Mads , Kruse Torben A.
Published: October 2017

Among the major issues in gene expression profile classification, feature selection is an important and necessary step in achieving and creating good classification rules given the high dimensionality of microarray data. Although different feature selection methods have been reported, there has been no method specifically proposed for paired microarray experiments. In this paper, we introduce a simple procedure based on a modified t-statistic for feature selection to microarray experiments using the popular matched case-control design and apply to our recent study on tumor metastasis in a low-malignant group of breast cancer patients for selecting genes that best predict metastases. Gene or feature selection is optimized by thresholding in a leaving one-pair out cross-validation. Model comparison through empirical application has shown that our method manifests improved efficiency with high sensitivity and specificity.
The Roles of β-Tubulin Mutations and Isotype Expression in Acquired Drug Resistance
Authors: Huzil J. Torin , Chen Ke , Kurgan Lukasz , Tuszynski Jack A.
Published: October 2017

The antitumor drug paclitaxel stabilizes microtubules and reduces their dynamicity, promoting mitotic arrest and eventually apoptosis. Upon assembly of the α/β-tubulin heterodimer, GTP becomes bound to both the α and β-tubulin monomers. During microtubule assembly, the GTP bound to β-tubulin is hydrolyzed to GDP, eventually reaching steady-state equilibrium between free tubulin dimers and those polymerized into microtubules. Tubulin-binding drugs such as paclitaxel interact with β-tubulin, resulting in the disruption of this equilibrium. In spite of several crystal structures of tubulin, there is little biochemical insight into the mechanism by which anti-tubulin drugs target microtubules and alter their normal behavior. The mechanism of drug action is further complicated, as the description of altered β-tubulin isotype expression and/or mutations in tubulin genes may lead to drug resistance as has been described in the literature. Because of the relationship between β-tubulin isotype expression and mutations within β-tubulin, both leading to resistance, we examined the properties of altered residues within the taxane, colchicine and Vinca binding sites. The amount of data now available, allows us to investigate common patterns that lead to microtubule disruption and may provide a guide to the rational design of novel compounds that can inhibit microtubule dynamics for specific tubulin isotypes or, indeed resistant cell lines. Because of the vast amount of data published to date, we will only provide a broad overview of the mutational results and how these correlate with differences between tubulin isotypes. We also note that clinical studies describe a number of predictive factors for the response to anti-tubulin drugs and attempt to develop an understanding of the features within tubulin that may help explain how they may affect both microtubule assembly and stability.
Advancing Cancer Systems Biology: Introducing the Center for the Development of a Virtual Tumor, CViT
Authors: Deisboeck Thomas S. , Zhang Le , Martin Sean
Published: October 2017

Integrative cancer biology research relies on a variety of data-driven computational modeling and simulation methods and techniques geared towards gaining new insights into the complexity of biological processes that are of critical importance for cancer research. These include the dynamics of gene-protein interaction networks, the percolation of sub-cellular perturbations across scales and the impact they may have on tumorigenesis in both experiments and clinics. Such innovative ‘systems’ research will greatly benefit from enabling Information Technology that is currently under development, including an online collaborative environment, a Semantic Web based computing platform that hosts data and model repositories as well as high-performance computing access. Here, we present one of the National Cancer Institute's recently established Integrative Cancer Biology Programs, i.e. the Center for the Development of a Virtual Tumor, CViT, which is charged with building a cancer modeling community, developing the aforementioned enabling technologies and fostering multi-scale cancer modeling and simulation.
Application of Gene Shaving and Mixture Models to Cluster Microarray Gene Expression Data
Authors: Do K-A. , McLachlan G.J. , Bean R. , Wen S.
Published: October 2017

Researchers are frequently faced with the analysis of microarray data of a relatively large number of genes using a small number of tissue samples. We examine the application of two statistical methods for clustering such microarray expression data: EMMIX-GENE and GeneClust. EMMIX-GENE is a mixture-model based clustering approach, designed primarily to cluster tissue samples on the basis of the genes. GeneClust is an implementation of the gene shaving methodology, motivated by research to identify distinct sets of genes for which variation in expression could be related to a biological property of the tissue samples. We illustrate the use of these two methods in the analysis of Affymetrix oligonucleotide arrays of well-known data sets from colon tissue samples with and without tumors, and of tumor tissue samples from patients with leukemia. Although the two approaches have been developed from different perspectives, the results demonstrate a clear correspondence between gene clusters produced by GeneClust and EMMIX-GENE for the colon tissue data. It is demonstrated, for the case of ribosomal proteins and smooth muscle genes in the colon data set, that both methods can classify genes into co-regulated families. It is further demonstrated that tissue types (tumor and normal) can be separated on the basis of subtle distributed patterns of genes. Application to the leukemia tissue data produces a division of tissues corresponding closely to the external classification, acute myeloid meukemia (AML) and acute lymphoblastic leukemia (ALL), for both methods. In addition, we also identify genes specific for the subgroup of ALL-Tcell samples. Overall, we find that the gene shaving method produces gene clusters at great speed; allows variable cluster sizes and can incorporate partial or full supervision; and finds clusters of genes in which the gene expression varies greatly over the tissue samples while maintaining a high level of coherence between the gene expression profiles. The intent of the EMMIX-GENE method is to cluster the tissue samples. It performs a filtering step that results in a subset of relevant genes, followed by gene clustering, and then tissue clustering, and is favorable in its accuracy of ranking the clusters produced.
Screening the Single Nucleotide Polymorphisms in Patients with Internal Carotid Artery Stenosis by Oligonucleotide-Based Custom DNA Array
Authors: Nakai Kenji , Oyanagi Mayu , Hitomi Jiro , Ogasawara Kuniaki , Inoue Takashi , Kobayashi Masakazu , Nakai Keiko , suwabe Akira , Habano Wataru , Baba Toshiaki , Yoshida Hiroshi , Ogawa Akira
Published: October 2017

Early screening of individuals considered to be at risk for severe internal carotid artery (ICA) stenosis is an important strategy for preventing ischemic cerebral stroke. The purpose of this study is to screening candidate single nucleotide polymorphisms (SNPs) associated with severe ICA stenosis using a newly developed oligonucleotide-based custom DNA array. The subjects consisted of 47 controls and 46 patients with severe ICA stenosis (≥70%) who underwent carotid endarterectomy (CEA). Subjects gave informed consent and we obtained samples of blood and genomic DNA. We studied 8 candidate genes: renin-angiotensin system [angiotensinogen (AGT), angiotensin II receptor type 1 (AGTR1), nitric oxide synthase 3 (NOS3)]; growth factor [hepatocyte growth factor (HGF)]; transgelin (SM22); cytokine [chemokine receptor 2 (CCR2)]; coagulation-fibrinolysis system [5,10-methylenetetrahydrofolate reductase (MTHFR)]; and plasminogen activator inhibitor 1 (PAI-1). Genotyping of candidate SNPs was done with a line probe assay (LiPA) based on an oligonucleotide-based DNA array. Results: The allele frequency of PAI-1 -1965 delG (odds ratio (OR), 0.3; 95% confidence interval (CI), 0.2–0.6) and MTHFR (OR 1.3, 95% CI, 1.0–1.5) were significantly different between controls and cases with ICA stenosis by Fisher's exact test. Multiple logistic analysis revealed that diabetes mellitus (DM), SNPs in PAI-1 -1965 delG and MTHFR were an independent risk for ICA stenosis. In conclusion, genetic factors of coagulation-fibrinolysis as well as diabetes mellitus (DM) were relevant in ICA stenosis.
Including Functional Annotations and Extending the Collection of Structural Classifications of Protein Loops (ArchDB)
Authors: Hermoso Antoni , Espadaler Jordi , Enrique Querol E , Aviles Francesc X. , Sternberg Michael J.E. , Oliva Baldomero , Fernandez-Fuentes Narcis
Published: October 2017

Loops represent an important part of protein structures. The study of loop is critical for two main reasons: First, loops are often involved in protein function, stability and folding. Second, despite improvements in experimental and computational structure prediction methods, modeling the conformation of loops remains problematic. Here, we present a structural classification of loops, ArchDB, a mine of information with application in both mentioned fields: loop structure prediction and function prediction. ArchDB ( http://sbi.imim.es/archdb ) is a database of classified protein loop motifs. The current database provides four different classification sets tailored for different purposes. ArchDB-40, a loop classification derived from SCOP40, well suited for modeling common loop motifs. Since features relevant to loop structure or function can be more easily determined on well-populated clusters, we have developed ArchDB-95, a loop classification derived from SCOP95. This new classification set shows a ~40% increase in the number of subclasses, and a large 7-fold increase in the number of putative structure/function-related subclasses. We also present ArchDB-EC, a classification of loop motifs from enzymes, and ArchDB-KI, a manually annotated classification of loop motifs from kinases. Information about ligand contacts and PDB sites has been included in all classification sets. Improvements in our classification scheme are described, as well as several new database features, such as the ability to query by conserved annotations, sequence similarity, or uploading 3D coordinates of a protein. The lengths of classified loops range between 0 and 36 residues long. ArchDB offers an exhaustive sampling of loop structures. Functional information about loops and links with related biological databases are also provided. All this information and the possibility to browse/query the database through a web-server outline an useful tool with application in the comparative study of loops, the analysis of loops involved in protein function and to obtain templates for loop modeling.
Nicotinic Receptors: Role in Addiction and Other Disorders of the Brain
Authors: Sharma Geeta , Vijayaraghavan Sukumar
Published: October 2017

Nicotine, the addictive component of cigarette smoke has profound effects on the brain. Activation of its receptors by nicotine has complex consequences for network activity throughout the brain, potentially contributing to the addictive property of the drug. Nicotinic receptors have been implicated in psychiatric illnesses like schizophrenia and are also neuroprotective, potentially beneficial for neurodegenerative diseases. These effects of nicotine serve to emphasize the multifarious roles the drug, acting through multiple nicotinic acetylcholine receptor subtypes. The findings also remind us of the complexity of signaling mechanisms and stress the risks of unintended consequences of drugs designed to combat nicotine addiction.
Assessment of Potable Water Quality in Baghdad City, Iraq
Authors: AL-Dulaimi Ghassan Adham , Younes Mohammad Khairi
Published: October 2017

Safe drinking water is crucial for the well-being of current and future generations. This study aims to evaluate the quality of potable water in Baghdad city. Furthermore, this study compares the quality of tap and bottled water. Baghdad city was divided into 4 districts based on the water source, and 40 water samples were collected from each district. Moreover, the most popular bottled water brands were sampled and compared with the tap water samples. The quality of the analyzed potable water samples varied based on the water source. The total dissolved solid (TDS) levels exceed the palatable (>600 ppm) water levels in some districts. In addition, the concentration of sulfate was relatively high in both tap and bottled water and ranged from 200 to 330 ppm. The bottled water quality was within the acceptable limits set by the World Health Organization, but the TDS levels were relatively high. The hardness, Cl−, Pb2+, and bacteria contents in both tap and bottled water were within the standard limits. Finally, it is important to conduct radiological analyses in the future to investigate the effect of wars on Iraqi water resources.
Efficacy of Continuous Positive Airway Pressure Treatment in Patients with Cardiac Arrhythmia and Obstructive Sleep Apnea: What is the Evidence?
Authors: Abumuamar Asmaa M , Mollayeva Tatyana , Sandor Paul , Newman David , Nanthakumar Kumaraswamy , Shapiro Colin M
Published: October 2017

Numerous studies have been conducted in the past few decades on obstructive sleep apnea (OSA) as an independent risk factor for the development and progression of cardiac arrhythmia. Treatment with continuous positive airway pressure (CPAP) therapy lowers blood pressure, improves ejection fraction in patients with heart failure, and decreases the need of revascularization procedures in patients with coronary artery disease. However, there has been little published discussion regarding the effect of CPAP treatment on cardiac arrhythmia in patients with OSA. We aimed to summarize scientific evidence regarding the utility of CPAP treatment in managing the recurrence and severity of different types of cardiac arrhythmia. We retrieved articles published in English before December 2016, through database search of PubMed, CENTRAL, and Embase. All peer-reviewed experimental, comparative, and other observational studies focused on adults were considered eligible. Several studies documented positive changes in arrhythmia frequency and severity with CPAP application, irrespective of type of arrhythmia, study methodology, or setting. However, the available evidence on the impact of CPAP treatment on the frequency and severity of cardiac arrhythmia is limited by heterogeneity of data. The duration of CPAP application, compliance with treatment, and baseline severity of OSA and cardiac pathology are important confounding factors that influence the effect of CPAP treatment. We emphasize the need for agreement on a core set of relevant predictors of the magnitude of the effect. Future research should carefully address these factors and their influence on the potential therapeutic ability of CPAP treatment to improve cardiac outcomes and reduce the risks of adverse cardiac and noncardiac effects associated with untreated OSA.
Fathers’ experiences of their child’s life-limiting condition: An attachment narrative perspective
Authors: Bailey-Pearce Oliver , Stedmon Jacqui , Dallos Rudi , Davis George
Published: October 2017

When a child has a life-limiting illness, parental involvement is amplified, having to respond to the increased needs of the child. Both parents are affected by the illness, yet research has largely under-represented fathers’ experiences of their child’s illness. Seven fathers were interviewed about their experiences with their child’s life-limiting illness. In addition, fathers’ attachment strategies were assessed using the Adult Attachment Interview. Narrative analysis was implemented to explore the interviews, and indicators of attachment markers employed in the Adult Attachment Interview were also identified. The dominant themes were found to be ‘experience of the diagnosis’, ‘living with the illness’, ‘struggling with emotions’ and ‘relationship with staff’. Within each theme, there were differences which related to the father’s attachment strategies. This was particularly evident in parts of their narratives recounting critical moments of threat and anxiety in the course of discovering and adjusting to their child’s illness. Importantly, the findings also suggested that the experience for the fathers stressed, and in some cases disrupted, their attachment coping strategies. All fathers told stories of trying to get it right for their children and family. Their experiences of, and adjustment to, the illness were related to their attachment strategies. The clinical implications for health professionals are discussed.
Social media and youth political engagement: Preaching to the converted or providing a new voice for youth?
Authors: Keating Avril , Melis Gabriella
Published: October 2017

Amidst concern about declining youth political engagement, it is often suggested that social media can provide a solution to this challenge. In this article, however, we argue that these online tools have not thus far mobilised a new audience to become engaged in either institution-oriented activities or political expression. Instead, we found that some young people are far more engaged in using social media for political purposes than others, and that a substantial proportion of young adults never use social media for this purpose. Using latent class analysis (LCA) of a unique web survey of young Britons aged 22–29, we show that the principal driver of online political engagement is political interest (even after controlling for socio-demographic characteristics). On this basis, we conclude that social media may be providing a new outlet for some young adults; it is not re-engaging the young adults who have already lost interest in politics.
Renovation of existing steel railway bridges: Field test and numerical simulation
Authors: Lin Weiwei , Taniguchi Nozomu , Yoda Teruhiko , Hansaka Masanori , Satake Shinya , Sugino Yusuke
Published: October 2017

Renovation of the aged steel railway structures is of vital importance due to their long service life after completion. A strengthening method for aged steel railway bridges by using rubber-latex mortar, glass fiber–reinforced polymer plates, lightweight rapid hardening concrete, and reinforcing bars was introduced in this article. To confirm the real effect of the present strengthening method, field tests were performed on two aged steel railway bridges that have been in service for 87 and 61 years, respectively. Stress variations on the mid-span section of the railway bridge due to the running trains were measured in the field test, and the stress reduction effects as well as the load redistribution effects of the present strengthening method were also confirmed. Three-dimensional finite-element models were built, and the numerical results were in good agreement with the field test results. Besides, structural vibration and noise levels of both strengthened and un-strengthened railway bridges were measured, and the noise reduction effect of the present method was confirmed in the field tests. In addition, further nonlinear analyses were performed, and the applied load–displacement relationships as well as the load–normal longitudinal strain curves of the aged structural steel, the glass fiber–reinforced polymer plates and the rapid hardening concrete, were given. Both experimental and numerical results indicate that the present renovation method can greatly enhance the stiffness and reduce the stress levels of steel members, resulting in the extension of the residual service life of the aged steel railway bridges.
Use of complementary and alternative medicine in Europe: Health-related and sociodemographic determinants
Authors: Kemppainen Laura M. , Kemppainen Teemu T. , Reippainen Jutta A. , Salmenniemi Suvi T. , Vuolanto Pia H.
Published: October 2017

Aims: The aim of this research was to study health-related and sociodemographic determinants of the use of different complementary and alternative medicine (CAM) treatments in Europe and differences in CAM use in various European countries. Methods: The study was based on a design-based logistic regression analysis of the European Social Survey (ESS), Round 7. We distinguished four CAM modalities: manual therapies, alternative medicinal systems, traditional Asian medical systems and mind-body therapies. Results: In total, 25.9% of the general population had used CAM during the last 12 months. Typically, only one CAM treatment had been used, and it was used more often as complementary rather than alternative treatment. The use of CAM varied greatly by country, from 10% in Hungary to almost 40% in Germany. Compared to those in good health, the use of CAM was two to fourfold greater among those with health problems. The health profiles of users of different CAM modalities varied. For example, back or neck pain was associated with all types of CAM, whereas depression was associated only with the use of mind-body therapies. Individuals with difficult to diagnose health conditions were more inclined to utilize CAM, and CAM use was more common among women and those with a higher education. Lower income was associated with the use of mind-body therapies, whereas the other three CAM modalities were associated with higher income. Conclusions: Help-seeking differed according to the health problem, something that should be acknowledged by clinical professionals to ensure safe care. The findings also point towards possible socioeconomic inequalities in health service use.
Privacy, censorship, data breaches and Internet freedom: The drivers of support and opposition to Dark Web technologies
Authors: Jardine Eric
Published: October 2017

Do heightened privacy perceptions, censorship concerns and exposure to online crime affect people’s level of opposition to dual-use technologies such as the Dark Web? If they do, then how much do these factors actually drive baseline levels of opposition to the Dark Web? Do privacy and censorship concerns get amplified in regimes with significant Internet restrictions? Does Internet freedom itself affect people’s baseline levels of opposition to Tor and other Dark Web technologies? Using new survey data on 17,121 Internet users in 17 different countries, a series of mixed-effect order logit regressions reveal that privacy and censorship concerns are both significant predictors of less opposition to the Dark Web. Past exposure to online crime, in contrast, significantly increases opposition to the Dark Web. Interestingly, restrictions on Internet freedom do not amplify privacy and censorship concerns, but Internet freedom itself is related to baseline levels of opposition to the Dark Web forming an inverted-U-shaped pattern.
Journalism and political affiliation of the media: Influence of ownership on Indonesian newspapers
Authors: Ekayanti Mala , Xiaoming Hao
Published: October 2017

Using the Model of Hierarchy of Influences on Media Content as its conceptual framework, this study examines the impact of political ownership of newspapers on journalists’ practice of professional values in day-to-day news-reporting activities in Indonesia. Through a survey of newspaper journalists in Jakarta, this study aims to find out whether journalists perceive political ownership as a potential threat to their practice of professional values. The findings show that political ownership of newspapers may not directly affect the practice of professional values but it can affect such a practice indirectly through interventional practices in the newsroom.
Book Review: Ziai, Aram. 2016: Development Discourse and Global History: From Colonialism to the Sustainable Development Goals
Authors: Telleria Juan
Published: October 2017

Ziai, Aram. 2016: Development Discourse and Global History: From Colonialism to the Sustainable Development Goals. London: Routledge. 244 pp. £110.00. ISBN: 978113 8803251 (Hardback). £36.99. ISBN: 978113 8735132 (Paperback).
How it makes a moral difference that one is worse off than one could have been
Authors: Otsuka Michael
Published: October 2017

In this article, I argue that it makes a moral difference whether an individual is worse off than she could have been. Here, I part company with consequentialists such as Parfit and side with contractualists such as Scanlon. But, unlike some contractualists, I reject the view that all that matters is whether a principle can be justified to each particular individual, where such a justification is attentive to her interests, complaints and other claims. The anonymous goodness of a distribution also matters. My attempt to reconcile contractualist and consequentialist approaches proceeds via a serious of reflections on cases.
The Use of Willingness to Pay in Determining Customer Preferences for Improved Flame-Based Cookstove Features in Two South African Study Areas
Authors: Maré Marcel , Annegarn Harold J.
Published: October 2017

The continued large-scale use of inefficient flame-based cookstoves directly influences human development levels globally, including in South Africa. It has been demonstrated that the adoption and sustained use of safe, inexpensive, and improved stove designs by households could lead to a significant reduction in household air pollution. From an examination of descriptions of previous improved cookstove dissemination programs, it becomes apparent that a focus on customer preferences was absent in many of the unsuccessful projects. This article investigates the customer preferences for improved flame-based cookstove features in two South African study areas using a willingness-to-pay survey methodology. A key finding indicates that the use of safety awareness campaigns could significantly shift demand for inefficient (kerosene powered) cookstoves to efficient and safer liquefied petroleum gas stoves. Furthermore, a preference for larger stoves (allowing for cooking in two pots simultaneously) was found. The availability of credit did not seem to influence purchasing behavior. The article suggests that the inclusion of safety awareness demonstrations in combination with other appropriate stove features (i.e., fuel types, sizes, durability, and payment options) represents a necessary companion to other strategies for the successful dissemination of improved flame-based stoves in the South African marketplace. This also has implication for large-scale stove interventions advocated by the Global Alliance for Clean Cookstoves and the World Bank.
Advocacy Through Education
Authors: Perry Cheryl , Emory Jan
Published: October 2017

Nurses are one of the largest groups of policy stakeholders in the health-care workforce, yet their influence on policy is not necessarily commensurate with their numbers. Since 2011, grassroots action coalitions have emerged to advance the profession’s impact on health-care policy. In one state, a partnership among professional nursing organizations, policy stakeholders, and academics resulted in educational presentations focused on political advocacy knowledge and skills. The goal of this project was to bring awareness to nurses and nursing students about their potential contributions to the political and advocacy processes that shape health policy. The purpose of this study was to determine the effectiveness of focused educational presentations in correcting misconceptions, increasing awareness, and providing clarification of the roles of advanced practice registered nurses, and identifying related policy implications. This quasi-experiment used a retrospective pre–post intervention self-evaluation tool administered immediately following an educational presentation. The sample ( N = 137) consisted of baccalaureate nursing students and licensed nurses. The results showed ( p < .001) that education could have a significant improvement in political advocacy participation.
Neuronal Dysexcitability May Be a Biomarker of Migraine: A Visual Evoked Potential Study
Authors: Kalita Jayantee , Uniyal Ravi , Misra Usha K. , Bhoi Sanjeev K.
Published: October 2017

We report neuronal sensitization and impaired habituation in migraine using pattern reversal visual evoked potential (PRVEP) and correlate these with clinical characteristics of migraine. Sixty-five migraineurs and 30 healthy controls were included. A detailed clinical examination was done and migraine characteristics, including migraine trigger, photophobia, phonophobia, and allodynia were noted. Consecutive 5 blocks of PRVEP were recorded averaging 100 epochs at 3 Hz stimuli. The amplitude of N75 and P100 were measured. Amplitude of first block was considered for sensitization, and impaired habituation was considered if any subsequent block was not suppressed. Migraineurs had sensitization of P100 (14.01 ± 6.02 vs 11.60 ± 5.17 µV; P = .049), but not of N75 (42.22 ± 4.79 vs 11.08 ± 4.56 µV; P = .27) compared with the controls. Impaired habituation of N75 was more marked and persisted up to fourth block of VEP recoding. Impaired habituation of P100 was significant only in the third block. Baseline N75 and P100 amplitudes were higher in females, and N75 was also higher in those with longer duration of illness. These phenomena did not correlate with visual triggers. Sensitization and impaired habituation were marked during headache. Based on the PRVEP findings, it may be concluded that migraineurs have sensitization of P100 and impaired habituation of N75 especially during headache. These phenomena may be useful for therapeutic monitoring.