Risk prediction models with incomplete data with application to prediction of estrogen receptor-positive breast cancer: prospective data from the Nurses' Health Study

Introduction A number of breast cancer risk prediction models have been developed to provide insight into a woman\u27s individual breast cancer risk. Although circulating levels of estradiol in postmenopausal women predict subsequent breast cancer risk, whether the addition of estradiol levels adds significantly to a model\u27s predictive power has not previously been evaluated. Methods Using linear regression, the authors developed an imputed estradiol score using measured estradiol levels (the outcome) and both case status and risk factor data (for example, body mass index) from a nested case-control study conducted within a large prospective cohort study and used multiple imputation methods to develop an overall risk model including both risk factor data from the main cohort and estradiol levels from the nested case-control study. Results The authors evaluated the addition of imputed estradiol level to the previously published Rosner and Colditz log-incidence model for breast cancer risk prediction within the larger Nurses\u27 Health Study cohort. The follow-up was from 1980 to 2000; during this time, 1,559 invasive estrogen receptor-positive breast cancer cases were confirmed. The addition of imputed estradiol levels significantly improved risk prediction; the age-specific concordance statistic increased from 0.635 ± 0.007 to 0.645 ± 0.007 (P \u3c 0.001) after the addition of imputed estradiol. Conclusion Circulating estradiol levels in postmenopausal women appear to add to other lifestyle factors in predicting a woman\u27s individual risk of breast cancer

A hypothetico-deductive approach to assessing the social function of chemical signalling in a non-territorial solitary carnivore

The function of chemical signalling in non-territorial solitary carnivores is still relatively unclear. Studies on territorial solitary and social carnivores have highlighted odour capability and utility, however the social function of chemical signalling in wild carnivore populations operating dominance hierarchy social systems has received little attention. We monitored scent marking and investigatory behaviour of wild brown bears Ursus arctos, to test multiple hypotheses relating to the social function of chemical signalling. Camera traps were stationed facing bear ‘marking trees’ to document behaviour by different age sex classes in different seasons. We found evidence to support the hypothesis that adult males utilise chemical signalling to communicate dominance to other males throughout the non-denning period. Adult females did not appear to utilise marking trees to advertise oestrous state during the breeding season. The function of marking by subadult bears is somewhat unclear, but may be related to the behaviour of adult males. Subadults investigated trees more often than they scent marked during the breeding season, which could be a result of an increased risk from adult males. Females with young showed an increase in marking and investigation of trees outside of the breeding season. We propose the hypothesis that females engage their dependent young with marking trees from a young age, at a relatively ‘safe’ time of year. Memory, experience, and learning at a young age, may all contribute towards odour capabilities in adult bears

Artificial Lighting as a Vector Attractant and Cause of Disease Diffusion

BACKGROUND: Traditionally, epidemiologists have considered electrification to be a positive factor. In fact, electrification and plumbing are typical initiatives that represent the integration of an isolated population into modern society, ensuring the control of pathogens and promoting public health. Nonetheless, electrification is always accompanied by night lighting that attracts insect vectors and changes people's behavior. Although this may lead to new modes of infection and increased transmission of insect-borne diseases, epidemiologists rarely consider the role of night lighting in their surveys. OBJECTIVE: We reviewed the epidemiological evidence concerning the role of lighting in the spread of vector-borne diseases to encourage other researchers to consider it in future studies. DISCUSSION: We present three infectious vector-borne diseases-Chagas, leishmaniasis, and malaria-and discuss evidence that suggests that the use of artificial lighting results in behavioral changes among human populations and changes in the prevalence of vector species and in the modes of transmission. CONCLUSION: Despite a surprising lack of studies, existing evidence supports our hypothesis that artificial lighting leads to a higher risk of infection from vector-borne diseases. We believe that this is related not only to the simple attraction of traditional vectors to light sources but also to changes in the behavior of both humans and insects that result in new modes of disease transmission. Considering the ongoing expansion of night lighting in developing countries, additional research on this subject is urgently needed.National Council for Scientific and Technological Development (CNPq), Brasilia, Brazi

NirK and nirS Nitrite reductase genes from non-agricultural forest soil bacteria in Thailand

The genetic heterogeneity of the nitrite reductase gene (nirK and nirS) fragments from denitrifying prokaryotes in a non-agricultural forest soil in Thailand was investigated using soil samples from the Plant Germplasm-Royal Initiation Project area in Kanchanaburi Province, Thailand. Soil bacteria were screened for denitrification activity and 13 (from 211) positive isolates were obtained and further evaluated for their ability to reduce nitrate and to accumulate or reduce nitrite. Three species with potentially previously unreported denitrifying activities were recorded. Analysis of the partial nirK and nirS sequences of these 13 strains revealed a diverse sequence heterogeneity in these two genes within the same environment and even potentially within the same host species, the potential existence of lateral gene transfer and the first record of both nirK and nirS homologues in one bacterial species. Finally, isolates of two species of bacteria (Corynebacterium propinquum and Micrococcus lylae) are recorded as denitrifiers for the first time

Effects of ambient air pollution on functional status in patients with chronic congestive heart failure: a repeated-measures study

<p>Abstract</p> <p>Background</p> <p>Studies using administrative data report a positive association between ambient air pollution and the risk of hospitalization for congestive heart failure (HF). Circulating levels of B-type natriuretic peptide (BNP) are directly associated with cardiac hemodynamics and symptom severity in patients with HF and, therefore, serves as a marker of functional status. We tested the hypothesis that BNP levels would be positively associated with short-term changes in ambient pollution levels among 28 patients with chronic stable HF and impaired systolic function.</p> <p>Methods</p> <p>BNP was measured in whole blood at 0, 6, and 12 weeks. We used linear mixed models to evaluate the association between fine particulate matter (PM_2.5), carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, and black carbon and log(BNP). Lags of 0 to 3 days were considered in separate models. We calculated the intraclass correlation coefficient and within-subject coefficient of variation as measures of reproducibility.</p> <p>Results</p> <p>We found no association between any pollutant and measures of BNP at any lag. For example, a 10 μg/m³increase in PM_2.5was associated with a 0.8% (95% CI: -16.4, 21.5; p = 0.94) increase in BNP on the same day. The within-subject coefficient of variation was 45% on the natural scale and 9% on the log scale.</p> <p>Conclusion</p> <p>These results suggest that serial BNP measurements are unlikely to be useful in a longitudinal study of air pollution-related acute health effects. The magnitude of expected ambient air pollution health effects appears small in relation to the considerable within-person variability in BNP levels in this population.</p

Geodesically smoothed tensor features for pulmonary hypertension prognosis using the heart and surrounding tissues

Cardiac magnetic resonance imaging (CMRI) provides non-invasive characterization of the heart and surrounding tissues. It is an important tool for the prognosis of pulmonary arterial hypertension (PAH), a disease with heterogeneous presentation that makes survival likelihood prediction a challenging task. In this paper, we propose a Geodesically Smooothed Tensor feature learning method (GST) that utilizes not only the heart but also its surrounding tissues to characterize disease severity for improving prognosis. Specifically, GST includes structures surrounding the heart by geodesic rings which were incrementally smoothed with Gaussian filters. This provides additive insight while modulating for patient positional differences for a subsequent tensor-based feature learning pipeline. We performed evaluation on Four Chamber and Short Axis CMRI from 150 individuals with confirmed PAH and 1-year mortality census (27 deceased, 123 alive). The proposed GST method improved AUC and Cox difference at 4-years post-imaging (Cox4YD) over the standardized measurement of right ventricular end systolic volume index (RVESVi: AUC: 0.58; Cox4YD: 0.18) on the Four Chamber protocol (AUC: 0.77; Cox4YD: 0.35). Only AUC was improved over RVESVi in the Short Axis scans (AUC: 0.77; Cox4YD: 0.16)

Identification of the Transgenic Integration Site in Immunodeficient tgε26 Human CD3ε Transgenic Mice

A strain of human CD3ε transgenic mice, tgε26, exhibits severe immunodeficiency associated with early arrest of T cell development. Complete loss of T cells is observed in homozygous tgε26 mice, but not in heterozygotes, suggesting that genomic disruption due to transgenic integration may contribute to the arrest of T cell development. Here we report the identification of the transgenic integration site in tgε26 mice. We found that multiple copies of the human CD3ε transgene are inserted between the Sstr5 and Metrn loci on chromosome 17, and that this is accompanied by duplication of the neighboring genomic region spanning 323 kb. However, none of the genes in this region were abrogated. These results suggest that the severe immunodeficiency seen in tgε26 mice is not due to gene disruption resulting from transgenic integration

Estimation of Short-Term Effects of Air Pollution on Stroke Hospital Admissions in Wuhan, China

Background and Objective:High concentrations of air pollutants have been linked to increased incidence of stroke in North America and Europe but not yet assessed in mainland China. The aim of this study is to evaluate the association between stroke hospitalization and short-term elevation of air pollutants in Wuhan, China.Methods:Daily mean NO2, SO2 and PM10 levels, temperature and humidity were obtained from 2006 through 2008. Data on stroke hospitalizations (ICD 10: I60-I69) at four hospitals in Wuhan were obtained for the same period. A time-stratified case-crossover design was performed by season (April-September and October-March) to assess effects of pollutants on stroke hospital admissions.Results:Pollution levels were higher in October-March with averages of 136.1 μg/m3 for PM10, 63.6 μg/m3 for NO2 and 71.0 μg/m3 for SO2 than in April-September when averages were 102.0 μg/m3, 41.7 μg/m3 and 41.7 μg/m3, respectively (p<.001). During the cold season, every 10 μg/m3 increase in NO2 was associated with a 2.9% (95%C.I. 1.2%-4.6%) increase in stroke admissions on the same day. Every 10 ug/m3 increase in PM10 daily concentration was significantly associated with an approximate 1% (95% C.I. 0.1%-1.4%) increase in stroke hospitalization. A two-pollutant model indicated that NO2 was associated with stroke admissions when controlling for PM10. During the warm season, no significant associations were noted for any of the pollutants.Conclusions:Exposure to NO2 is significantly associated with stroke hospitalizations during the cold season in Wuhan, China when pollution levels are 50% greater than in the warm season. Larger and multi-center studies in Chinese cities are warranted to validate our findings. © 2013 Xiang et al

Mathematical model insights into arsenic detoxification

<p>Abstract</p> <p>Background</p> <p>Arsenic in drinking water, a major health hazard to millions of people in South and East Asia and in other parts of the world, is ingested primarily as trivalent inorganic arsenic (iAs), which then undergoes hepatic methylation to methylarsonic acid (MMAs) and a second methylation to dimethylarsinic acid (DMAs). Although MMAs and DMAs are also known to be toxic, DMAs is more easily excreted in the urine and therefore methylation has generally been considered a detoxification pathway. A collaborative modeling project between epidemiologists, biologists, and mathematicians has the purpose of explaining existing data on methylation in human studies in Bangladesh and also testing, by mathematical modeling, effects of nutritional supplements that could increase As methylation.</p> <p>Methods</p> <p>We develop a whole body mathematical model of arsenic metabolism including arsenic absorption, storage, methylation, and excretion. The parameters for arsenic methylation in the liver were taken from the biochemical literature. The transport parameters between compartments are largely unknown, so we adjust them so that the model accurately predicts the urine excretion rates of time for the iAs, MMAs, and DMAs in single dose experiments on human subjects.</p> <p>Results</p> <p>We test the model by showing that, with no changes in parameters, it predicts accurately the time courses of urinary excretion in mutiple dose experiments conducted on human subjects. Our main purpose is to use the model to study and interpret the data on the effects of folate supplementation on arsenic methylation and excretion in clinical trials in Bangladesh. Folate supplementation of folate-deficient individuals resulted in a 14% decrease in arsenicals in the blood. This is confirmed by the model and the model predicts that arsenicals in the liver will decrease by 19% and arsenicals in other body stores by 26% in these same individuals. In addition, the model predicts that arsenic methyltransferase has been upregulated by a factor of two in this population. Finally, we also show that a modification of the model gives excellent fits to the data on arsenic metabolism in human cultured hepatocytes.</p> <p>Conclusions</p> <p>The analysis of the Bangladesh data using the model suggests that folate supplementation may be more effective at reducing whole body arsenic than previously expected. There is almost no data on the upregulation of arsenic methyltransferase in populations chronically exposed to arsenic. Our model predicts upregulation by a factor of two in the Bangladesh population studied. This prediction should be verified since it could have important public health consequences both for treatment strategies and for setting appropriate limits on arsenic in drinking water. Our model has compartments for the binding of arsenicals to proteins inside of cells and we show that these comparments are necessary to obtain good fits to data. Protein-binding of arsenicals should be explored in future biochemical studies.</p

How does study quality affect the results of a diagnostic meta-analysis?

Background: The use of systematic literature review to inform evidence based practice in diagnostics is rapidly expanding. Although the primary diagnostic literature is extensive, studies are often of low methodological quality or poorly reported. There has been no rigorously evaluated, evidence based tool to assess the methodological quality of diagnostic studies. The primary objective of this study was to determine the extent to which variations in the quality of primary studies impact the results of a diagnostic meta-analysis and whether this differs with diagnostic test type. A secondary objective was to contribute to the evaluation of QUADAS, an evidence-based tool for the assessment of quality in diagnostic accuracy studies. Methods: This study was conducted as part of large systematic review of tests used in the diagnosis and further investigation of urinary tract infection (UTI) in children. All studies included in this review were assessed using QUADAS, an evidence-based tool for the assessment of quality in systematic reviews of diagnostic accuracy studies. The impact of individual components of QUADAS on a summary measure of diagnostic accuracy was investigated using regression analysis. The review divided the diagnosis and further investigation of UTI into the following three clinical stages: diagnosis of UTI, localisation of infection, and further investigation of the UTI. Each stage used different types of diagnostic test, which were considered to involve different quality concerns. Results: Many of the studies included in our review were poorly reported. The proportion of QUADAS items fulfilled was similar for studies in different sections of the review. However, as might be expected, the individual items fulfilled differed between the three clinical stages. Regression analysis found that different items showed a strong association with test performance for the different tests evaluated. These differences were observed both within and between the three clinical stages assessed by the review. The results of regression analyses were also affected by whether or not a weighting (by sample size) was applied. Our analysis was severely limited by the completeness of reporting and the differences between the index tests evaluated and the reference standards used to confirm diagnoses in the primary studies. Few tests were evaluated by sufficient studies to allow meaningful use of meta-analytic pooling and investigation of heterogeneity. This meant that further analysis to investigate heterogeneity could only be undertaken using a subset of studies, and that the findings are open to various interpretations. Conclusion: Further work is needed to investigate the influence of methodological quality on the results of diagnostic meta-analyses. Large data sets of well-reported primary studies are needed to address this question. Without significant improvements in the completeness of reporting of primary studies, progress in this area will be limited