A Randomized Controlled Trial to Measure Spillover Effects of a Combined Water, Sanitation, and Handwashing Intervention in Rural Bangladesh.

Water, sanitation, and handwashing interventions may confer spillover effects on intervention recipients' neighbors by interrupting pathogen transmission. We measured geographically local spillovers in the Water Quality, Sanitation, and Handwashing (WASH) Benefits Study, a cluster-randomized trial in rural Bangladesh, by comparing outcomes among neighbors of intervention versus those of control participants. Geographically defined clusters were randomly allocated to a compound-level intervention (i.e., chlorinated drinking water, upgraded sanitation, and handwashing promotion) or control arm. From January 2015 to August 2015, in 180 clusters, we enrolled 1,799 neighboring children who were age matched to trial participants who would have been eligible for the study had they been conceived slightly earlier or later. After 28 months of intervention, we quantified fecal indicator bacteria in toy rinse and drinking water samples and measured soil-transmitted helminth infections and caregiver-reported diarrhea and respiratory illness. Neighbors' characteristics were balanced across arms. Detectable Escherichia coli prevalence in tubewell samples was lower for intervention participants' neighbors than control participants' (prevalence ratio = 0.83; 95% confidence interval: 0.73, 0.95). Fecal indicator bacteria prevalence did not differ between arms for other environmental samples. Prevalence was similar in neighbors of intervention participants versus those of control participants for soil-transmitted helminth infection, diarrhea, and respiratory illness. A compound-level water, sanitation, and handwashing intervention reduced neighbors' tubewell water contamination but did not affect neighboring children's health

FRESHWATER ANIMAL DIVERSITY ASSESSMENT Global diversity of mayflies (Ephemeroptera, Insecta) in freshwater

Abstract The extant global Ephemeroptera fauna is represented by over 3,000 described species in 42 families and more than 400 genera. The highest generic diversity occurs in the Neotropics, with a correspondingly high species diversity, while the Palaearctic has the lowest generic diversity, but a high species diversity. Such distribution patterns may relate to how long evolutionary processes have been carrying on in isolation in a bioregion. Over an extended period, there may be extinction of species, but evolution of more genera. Dramatic extinction events such as the K-T mass extinction have affected current mayfly diversity and distribution. Climatic history plays an important role in the rate of speciation in an area, with regions which have been climatically stable over long periods having fewer species per genus, when compared to regions subjected to climatic stresses, such as glaciation. A total of 13 families are endemic to specific bioregions, with eight among them being monospecific. Most of these have restricted distributions which may be the result of them being the relict of a previously more diverse, but presently almost completely extinct family, or may be the consequence of vicariance events, resulting from evolution due to long-term isolation

Inboard and outboard radial electric field wells in the H- and I-mode pedestal of Alcator C-Mod and poloidal variations of impurity temperature

We present inboard (HFS) and outboard (LFS) radial electric field (E[subscript r]) and impurity temperature (T[subscript z]) measurements in the I-mode and H-mode pedestal of Alcator C-Mod. These measurements reveal strong Er wells at the HFS and the LFS midplane in both regimes and clear pedestals in T[subscript z], which are of similar shape and height for the HFS and LFS. While the H-mode E[subscript r] well has a radially symmetric structure, the E[subscript r] well in I-mode is asymmetric, with a stronger ExB shear layer at the outer edge of the E[subscript r] well, near the separatrix. Comparison of HFS and LFS profiles indicates that impurity temperature and plasma potential are not simultaneously flux functions. Uncertainties in radial alignment after mapping HFS measurements along flux surfaces to the LFS do not, however, allow direct determination as to which quantity varies poloidally and to what extent. Radially aligning HFS and LFS measurements based on the T[subscript z] profiles would result in substantial inboard-outboard variations of plasma potential and electron density. Aligning HFS and LFS E[subscript r] wells instead also approximately aligns the impurity poloidal flow profiles, while resulting in a LFS impurity temperature exceeding the HFS values in the region of steepest gradients by up to 70%. Considerations based on a simplified form of total parallel momentum balance and estimates of parallel and perpendicular heat transport time scales seem to favor an approximate alignment of the E[subscript r] wells and a substantial poloidal asymmetry in impurity temperature.United States. Dept. of Energy (Cooperative Agreement DE-FC02-99ER54512)Swiss National Science Foundatio

PathEx: a novel multi factors based datasets selector web tool

<p>Abstract</p> <p>Background</p> <p>Microarray experiments have become very popular in life science research. However, if such experiments are only considered independently, the possibilities for analysis and interpretation of many life science phenomena are reduced. The accumulation of publicly available data provides biomedical researchers with a valuable opportunity to either discover new phenomena or improve the interpretation and validation of other phenomena that partially understood or well known. This can only be achieved by intelligently exploiting this rich mine of information.</p> <p>Description</p> <p>Considering that technologies like microarrays remain prohibitively expensive for researchers with limited means to order their own experimental chips, it would be beneficial to re-use previously published microarray data. For certain researchers interested in finding gene groups (requiring many replicates), there is a great need for tools to help them to select appropriate datasets for analysis. These tools may be effective, if and only if, they are able to re-use previously deposited experiments or to create new experiments not initially envisioned by the depositors. However, the generation of new experiments requires that all published microarray data be completely annotated, which is not currently the case. Thus, we propose the PathEx approach.</p> <p>Conclusion</p> <p>This paper presents PathEx, a human-focused web solution built around a two-component system: one database component, enriched with relevant biological information (expression array, omics data, literature) from different sources, and another component comprising sophisticated web interfaces that allow users to perform complex dataset building queries on the contents integrated into the PathEx database.</p

Early prediction of median survival among a large AIDS surveillance cohort

<p>Abstract</p> <p>Background</p> <p>For individuals with AIDS, data exist relatively soon after diagnosis to allow estimation of "early" survival quantiles (<it>e.g.</it>, the 0.10, 0.15, 0.20 and 0.30 quantiles, etc.). Many years of additional observation must elapse before median survival, a summary measure of survival, can be estimated accurately. In this study, a new approach to predict AIDS median survival is presented and its accuracy tested using AIDS surveillance data.</p> <p>Methods</p> <p>The data consisted of 96,373 individuals who were reported to the HIV/AIDS Reporting System of the California Department of Health Services Office of AIDS as of December 31, 1996. We defined cohorts based on quarter year of diagnosis (<it>e.g.</it>, the "931" cohort consists of individuals diagnosed with AIDS in the first quarter of 1993). We used early quantiles (estimated using the Inverse Probability of Censoring Weighted estimator) of the survival distribution to estimate median survival by assuming a linear relationship between the earlier quantiles and median survival. From this model, median survival was predicted for cohorts for which a median could not be estimated empirically from the available data. This prediction was compared with the actual medians observed when using updated survival data reported at least five years later.</p> <p>Results</p> <p>Using the 0.15 quantile as the predictor and the data available as of December 31, 1996, we were able to predict the median survival of four cohorts (933, 934, 941, and 942) to be 34, 34, 31, and 29 months. Without this approach, there were insufficient data with which to make any estimate of median survival. The actual median survival of these four cohorts (using data as of December 31, 2001) was found to be 32, 40, 46, and 80 months, suggesting that the accuracy for this approach requires a minimum of three years to elapse from diagnosis to the time an accurate prediction can be made.</p> <p>Conclusion</p> <p>The results of this study suggest that early and accurate prediction of median survival time after AIDS diagnosis may be possible using early quantiles of the survival distribution. The methodology did not seem to work well during a period of significant change in survival as observed with highly active antiretroviral treatment, but results suggest that it may work well in a time of more gradual improvement in survival.</p

Nowcasting pandemic influenza A/H1N1 2009 hospitalizations in the Netherlands

During emerging epidemics of infectious diseases, it is vital to have up-to-date information on epidemic trends, such as incidence or health care demand, because hospitals and intensive care units have limited excess capacity. However, real-time tracking of epidemics is difficult, because of the inherent delay between onset of symptoms or hospitalizations, and reporting. We propose a robust algorithm to correct for reporting delays, using the observed distribution of reporting delays. We apply the algorithm to pandemic influenza A/H1N1 2009 hospitalizations as reported in the Netherlands. We show that the proposed algorithm is able to provide unbiased predictions of the actual number of hospitalizations in real-time during the ascent and descent of the epidemic. The real-time predictions of admissions are useful to adjust planning in hospitals to avoid exceeding their capacity

The relationship between retinal vessel calibre and knee cartilage and BMLs

10.1186/1471-2474-13-255BMC Musculoskeletal Disorders13

Proteinortho: Detection of (Co-)orthologs in large-scale analysis

<p>Abstract</p> <p>Background</p> <p>Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases.</p> <p>Results</p> <p>The program <monospace>Proteinortho</monospace> described here is a stand-alone tool that is geared towards large datasets and makes use of distributed computing techniques when run on multi-core hardware. It implements an extended version of the reciprocal best alignment heuristic. We apply <monospace>Proteinortho</monospace> to compute orthologous proteins in the complete set of all 717 eubacterial genomes available at NCBI at the beginning of 2009. We identified thirty proteins present in 99% of all bacterial proteomes.</p> <p>Conclusions</p> <p><monospace>Proteinortho</monospace> significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware.</p