Point process modeling for directed interaction networks

Network data often take the form of repeated interactions between senders and receivers tabulated over time. A primary question to ask of such data is which traits and behaviors are predictive of interaction. To answer this question, a model is introduced for treating directed interactions as a multivariate point process: a Cox multiplicative intensity model using covariates that depend on the history of the process. Consistency and asymptotic normality are proved for the resulting partial-likelihood-based estimators under suitable regularity conditions, and an efficient fitting procedure is described. Multicast interactions--those involving a single sender but multiple receivers--are treated explicitly. The resulting inferential framework is then employed to model message sending behavior in a corporate e-mail network. The analysis gives a precise quantification of which static shared traits and dynamic network effects are predictive of message recipient selection.Comment: 36 pages, 13 figures; includes supplementary materia

The development and validation of the Healthy Computing Questionnaire for Children (HCQC)

BACKGROUND: School children may be at risk of physical health problems associated with desktop, laptop and tablet computer use. There are some interventions designed to educate children about ergonomic practices when using computers. A common limitation of past intervention studies has been the lack of a valid and reliable questionnaire to determine effectiveness of the intervention. OBJECTIVE: The aim of this study was to develop a valid and reliable self-report measure to assess primary school children’s knowledge, attitudes and behaviours related to healthy computer use. METHODS: A mixed methods approach was used to develop the questionnaire and test its psychometric properties. A convenience sample of 440 primary school children in Year 5 (aged 9–11 years) was used in the development and validation of the questionnaire. RESULTS: The final questionnaire comprised 56 items across the three subscales of knowledge, attitudes and behaviour. The questionnaire was shown to have good content validity and adequate test-retest reliability. Internal consistency was adequate for the attitude items, but low for the knowledge items. CONCLUSIONS: This study produced a valid and reliable tool, using a health promotion framework, for measuring primary school children’s knowledge, attitudes and behaviours related to healthy computing

High-risk mammographic parenchymal patterns and anthropometric measures: a case–control study

Mammographic parenchymal patterns are related to breast cancer risk and are also affected by anthropometric measure. We carried out a case–control study comprising 200 cases with high-risk (P2 and DY) mammographic parenchymal pattern and 200 controls with low-risk (N1 and P1) patterns in order to investigate the effect of body size and shape and breast size on mammographic patterns. Women in the highest quartile of body mass index (BMI) distribution were significantly less likely to have a high-risk pattern (odds ratio (OR) = 0.21, 95% confidence interval (CI) 0.08–0.52, P-value for trend = 0.001) compared to those in the lowest quartile. Relative to women with a waist to hip ratio (WHR) of less than 0.75, the OR of having a high-risk pattern in women with a WHR greater than 0.80 was 0.30 (95% CI 0.14–0.63). Breast size as measured by cup size was significantly and negatively related to high-risk pattern. Our study indicates that both BMI and WHR are negatively associated with high-risk patterns. However, both phenomena are associated with increased risk of breast cancer in post-menopausal women. This negative confounding of two positive risk factors means that the effect of parenchymal patterns on risk will tend to be underestimated when not adjusted for BMI and WHR and vice versa. Thus we may have underestimated the importance of BMI and mammographic parenchymal patterns in the past. Further studies are needed to determine a measure of parenchymal density that is independent of anthropometric measures and breast size. © 1999 Cancer Research Campaig

A role for hydrophobicity in a Diels–Alder reaction catalyzed by pyridyl-modified RNA

New classes of RNA enzymes or ribozymes have been obtained by in vitro evolution and selection of RNA molecules. Incorporation of modified nucleotides into the RNA sequence has been proposed to enhance function. DA22 is a modified RNA containing 5-(4-pyridylmethyl) carboxamide uridines, which has been selected for its ability to promote a Diels–Alder cycloaddition reaction. Here, we show that DA_TR96, the most active member of the DA22 RNA sequence family, which was selected with pyridyl-modified nucleotides, accelerates a cycloaddition reaction between anthracene and maleimide derivatives with high turnover. These widely used reactants were not used in the original selection for DA22 and yet here they provide the first demonstration of DA_TR96 as a true multiple-turnover catalyst. In addition, the absence of a structural or essential kinetic role for Cu2+, as initially postulated, and nonsequence-specific hydrophobic interactions with the anthracene substrate have led to a reevaluation of the pyridine modification's role. These findings broaden the catalytic repertoire of the DA22 family of pyridyl-modified RNAs and suggest a key role for the hydrophobic effect in the catalytic mechanism

Spatio-Temporal Patterns of Barmah Forest Virus Disease in Queensland, Australia

Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland

DataSHIELD: taking the analysis to the data, not the data to the analysis

Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK's proposed 'care.data' initiative, and these issues reflect important societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data. Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC. Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach. DataSHIELD facilitates important research in settings where: (i) a co-analysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property-the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis

The epidemiology of coronary heart disease : A review

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31999/1/0000041.pd