Health Behaviours and Its Associated Factors among Undergraduate Students in Kuala Lumpur, Malaysia

University students are asset of any nations for future development. Their current lifestyle practices, diet and physical activity can determine their future health. This study aims to assess health behaviours and its associated factors among undergraduate students from a public university in Malaysia. This cross-sectionalstudy was conducted between July to September 2015 among 1023 students using a structured questionnaire. The mean positive health practice score was 8.72/13 (±1.77). The most common positive health care practised was non-tobacco use while the least common was avoiding eating foods that contain fats and cholesterol. Year of study, self-perceived health status, internet addiction and self-perceived importance of taking health measures were significant predictors of health practice among the students. The odds ratios of 0.68, 0.49, and 0.57 indicate that the odds of students in year 2, 3 and 4, respectively practising positive health behaviours were 32% (1-0.68), 51% and 43% lower than those in Year 1. The odds of students who have self-perceived poor health status and those without Internet addiction were 95% and 25% lower in practising positive health behaviours compared to students who perceived themselves to have excellent health status and students with internet addiction, respectively. Students who perceived high importance of taking health measures were 1.77 times more likely to have positive health practices compared to those who have lower perceived importance of taking health measures. The findings of this study will enable development of targeted interventions to improve health behaviors among university students. Keywords: health behaviours, undergraduate students, lifestyle, Malaysi

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.Peer reviewe

Inferring the evolution of the major histocompatibility complex of wild pigs and peccaries using hybridisation DNA capture-based sequencing

The major histocompatibility complex (MHC) is a key genomic model region for understanding the evolution of gene families and the co-evolution between host and pathogen. To date, MHC studies have mostly focused on species from major vertebrate lineages. The evolution of MHC classical (Ia) and non-classical (Ib) genes in pigs has attracted interest because of their antigen presentation roles as part of the adaptive immune system. The pig family Suidae comprises over 18 extant species (mostly wild), but only the domestic pig has been extensively sequenced and annotated. To address this, we used a DNA-capture approach, with probes designed from the domestic pig genome, to generate MHC data for 11 wild species of pigs and their closest living family, Tayassuidae. The approach showed good efficiency for wild pigs (~80% reads mapped, ~87× coverage), compared to tayassuids (~12% reads mapped, ~4× coverage). We retrieved 145 MHC loci across both families. Phylogenetic analyses show that the class Ia and Ib genes underwent multiple duplications and diversifications before suids and tayassuids diverged from their common ancestor. The histocompatibility genes mostly form orthologous groups and there is genetic differentiation for most of these genes between Eurasian and sub-Saharan African wild pigs. Tests of selection showed that the peptide-binding region of class Ib genes was under positive selection. These findings contribute to better understanding of the evolutionary history of the MHC, specifically, the class I genes, and provide useful data for investigating the immune response of wild populations against pathogens

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 science. © The Author(s) 2019. Published by Oxford University Press