The fate of steroid estrogens: Partitioning during wastewater treatment and onto river sediments

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2010 Springer Science+Business Media B.V.The partitioning of steroid estrogens in wastewater treatment and receiving waters is likely to influence their discharge to, and persistence in, the environment. This study investigated the partitioning behaviour of steroid estrogens in both laboratory and field studies. Partitioning onto activated sludge from laboratory-scale Husmann units was rapid with equilibrium achieved after 1 h. Sorption isotherms and Kd values decreased in the order 17α-ethinyl estradiol > 17α-estradiol > estrone > estriol without a sorption limit being achieved (1/n >1). Samples from a wastewater treatment works indicated no accumulation of steroid estrogens in solids from primary or secondary biological treatment, however, a range of steroid estrogens were identified in sediment samples from the River Thames. This would indicate that partitioning in the environment may play a role in the long-term fate of estrogens, with an indication that they will be recalcitrant in anaerobic conditions.EPSR

Multiple Imputation Ensembles (MIE) for dealing with missing data

Missing data is a significant issue in many real-world datasets, yet there are no robust methods for dealing with it appropriately. In this paper, we propose a robust approach to dealing with missing data in classification problems: Multiple Imputation Ensembles (MIE). Our method integrates two approaches: multiple imputation and ensemble methods and compares two types of ensembles: bagging and stacking. We also propose a robust experimental set-up using 20 benchmark datasets from the UCI machine learning repository. For each dataset, we introduce increasing amounts of data Missing Completely at Random. Firstly, we use a number of single/multiple imputation methods to recover the missing values and then ensemble a number of different classifiers built on the imputed data. We assess the quality of the imputation by using dissimilarity measures. We also evaluate the MIE performance by comparing classification accuracy on the complete and imputed data. Furthermore, we use the accuracy of simple imputation as a benchmark for comparison. We find that our proposed approach combining multiple imputation with ensemble techniques outperform others, particularly as missing data increases

Singular values of the Dirac operator in dense QCD-like theories

We study the singular values of the Dirac operator in dense QCD-like theories at zero temperature. The Dirac singular values are real and nonnegative at any nonzero quark density. The scale of their spectrum is set by the diquark condensate, in contrast to the complex Dirac eigenvalues whose scale is set by the chiral condensate at low density and by the BCS gap at high density. We identify three different low-energy effective theories with diquark sources applicable at low, intermediate, and high density, together with their overlapping domains of validity. We derive a number of exact formulas for the Dirac singular values, including Banks-Casher-type relations for the diquark condensate, Smilga-Stern-type relations for the slope of the singular value density, and Leutwyler-Smilga-type sum rules for the inverse singular values. We construct random matrix theories and determine the form of the microscopic spectral correlation functions of the singular values for all nonzero quark densities. We also derive a rigorous index theorem for non-Hermitian Dirac operators. Our results can in principle be tested in lattice simulations.Comment: 3 references added, version published in JHE

Missing Data in Randomized Clinical Trials for Weight Loss: Scope of the Problem, State of the Field, and Performance of Statistical Methods

BACKGROUND: Dropouts and missing data are nearly-ubiquitous in obesity randomized controlled trails, threatening validity and generalizability of conclusions. Herein, we meta-analytically evaluate the extent of missing data, the frequency with which various analytic methods are employed to accommodate dropouts, and the performance of multiple statistical methods. METHODOLOGY/PRINCIPAL FINDINGS: We searched PubMed and Cochrane databases (2000-2006) for articles published in English and manually searched bibliographic references. Articles of pharmaceutical randomized controlled trials with weight loss or weight gain prevention as major endpoints were included. Two authors independently reviewed each publication for inclusion. 121 articles met the inclusion criteria. Two authors independently extracted treatment, sample size, drop-out rates, study duration, and statistical method used to handle missing data from all articles and resolved disagreements by consensus. In the meta-analysis, drop-out rates were substantial with the survival (non-dropout) rates being approximated by an exponential decay curve (e(-lambdat)) where lambda was estimated to be .0088 (95% bootstrap confidence interval: .0076 to .0100) and t represents time in weeks. The estimated drop-out rate at 1 year was 37%. Most studies used last observation carried forward as the primary analytic method to handle missing data. We also obtained 12 raw obesity randomized controlled trial datasets for empirical analyses. Analyses of raw randomized controlled trial data suggested that both mixed models and multiple imputation performed well, but that multiple imputation may be more robust when missing data are extensive. CONCLUSION/SIGNIFICANCE: Our analysis offers an equation for predictions of dropout rates useful for future study planning. Our raw data analyses suggests that multiple imputation is better than other methods for handling missing data in obesity randomized controlled trials, followed closely by mixed models. We suggest these methods supplant last observation carried forward as the primary method of analysis

Estimating the role of casual contact from the community in transmission of Bordetella pertussis to young infants

The proportion of infant pertussis cases due to transmission from casual contact in the community has not been estimated since before the introduction of pertussis vaccines in the 1950s. This study aimed to estimate the proportion of pertussis transmission due to casual contact using demographic and clinical data from a study of 95 infant pertussis cases and their close contacts enrolled at 14 hospitals in France, Germany, Canada, and the U.S. between February 2003 and September 2004. A complete case analysis was conducted as well as multiple imputation (MI) to account for missing data for participants and close contacts who did not participate. By considering all possible close contacts, the MI analysis estimated 66% of source cases were close contacts, implying the minimum attributable proportion of infant cases due to transmission from casual contact with community members was 34% (95% CI = 24%, 44%). Estimates from the complete case analysis were comparable but less precise. Results were sensitive to changes in the operational definition of a source case, which broadened the range of MI point estimates of transmission from casual community contact to 20%–47%. We conclude that casual contact appears to be responsible for a substantial proportion of pertussis transmission to young infants

Prognostic implications of the Quebec Task Force classification of back-related leg pain: An analysis of longitudinal routine clinical data

Background: Low back pain (LBP) patients with related leg pain have a more severe profile than those with local LBP and a worse prognosis. Pain location above or below the knee and the presence of neurological signs differentiate patients with different profiles, but knowledge about the prognostic value of these subgroups is sparse. The objectives of this study were (1) to investigate whether subgroups consisting of patients with Local LBP only, LBP + leg pain above the knee, LBP + leg pain below the knee, and LBP + leg pain and neurological signs had different prognoses, and (2) to determine if this was explained by measured baseline factors. Methods. Routine clinical data were collected during the first visit to an outpatient department and follow-ups were performed after 3 and 12 months. Patients were divided into the four subgroups and associations between subgroups and the outcomes of activity limitation, global perceived effect (GPE) after 3 months, and sick leave after 3 months were tested by means of generalised estimating equations. Models were univariate (I), adjusted for duration (II), and adjusted for all baseline differences (III). Results: A total of 1,752 patients were included, with a 76% 3-month and 70% 12-month follow-up. Subgroups were associated with activity limitation in all models (p < 0.001). Local LBP had the least and LBP + neurological signs the most severe limitations at all time-points, although patients with neurological signs improved the most. Associations with GPE after 3 months were only significant in Model I. Subgroups were associated with sick leave after 3 months in model I and II, with sick leave being most frequent in the subgroup with neurological signs. No significant differences were found in any pairwise comparisons of patients with leg pain above or below the knee. Conclusions: Subgrouping LBP patients, based on pain location and neurological signs, was associated with activity limitation and sick leave, but not with GPE. The presence of neurological signs and pain in the leg both have prognostic implications but whether that leg pain without neurological signs is above or below the knee does not

Response of bone turnover markers to raloxifene treatment in postmenopausal women with osteopenia.

Introduction: The change in bone turnover markers (BTM) in response to osteoporosis therapy can be assessed by a decrease beyond the least significant change (LSC) or below the mean of the reference interval (RI). We compared the performance of these two approaches in women treated with raloxifene. Methods: Fifty postmenopausal osteopenic women, (age 51-72y) were randomised to raloxifene or no treatment for 2 years. Blood samples were collected for the measurement of BTM. The LSC for each marker was calculated from the untreated women and the RI obtained from healthy premenopausal women (age 35-40y). Bone mineral density (BMD) was measured at the spine and hip. Results: There was a decrease in BTM in response to raloxifene treatment; percentage change at 12 weeks, CTX -39% (95% CI -48 to -28) and PINP -32% (95% CI -40 to -23) P<0.001. The proportion of women classified as responding to treatment using LSC at 12 weeks was: CTX 38%, PINP 52%, at 48 weeks CTX 60%, PINP 65%. For the RI approach; at 12 weeks CTX and PINP 38%, at 48 weeks CTX 40%, PINP 45%. There was a significant difference in the change in spine BMD in the raloxifene treated group compared to the no-treatment group at week 48; difference 0.031 g/cm2, (95% CI 0.016 to 0.046, P<0.001). Conclusions: The two approaches identified women that reached the target for treatment using BTM. Both LSC and RI criteria appear useful in identifying treatment response but the two approaches do not fully overlap and may be complementary