Integrated model for genomic prediction under additive and non-additive genetic architecture.

Using data from genome-wide molecular markers, genomic selection procedures have proved useful for estimating breeding values and phenotypic prediction. The link between an individual genotype and phenotype has been modelled using a number of parametric methods to estimate individual breeding value. It has been observed that parametric methods perform satisfactorily only when the system under study has additive genetic architecture. To capture non-additive (dominance and epistasis) effects, nonparametric approaches have also been developed; however, they typically fall short of capturing additive effects. The idea behind this study is to select the most appropriate model from each parametric and nonparametric category and build an integrated model that can incorporate the best features of both models. It was observed from the results of the current study that GBLUP performed admirably under additive architecture, while SVM's performance in non-additive architecture was found to be encouraging. A robust model for genomic prediction has been developed in light of these findings, which can handle both additive and epistatic effects simultaneously by minimizing their error variance. The developed integrated model has been assessed using standard evaluation measures like predictive ability and error variance.

Surveillance of RNase P, PMMoV, and CrAssphage in wastewater as indicators of human fecal concentration across urban sewer neighborhoods, Kentucky.

Wastewater surveillance has been widely used as a supplemental method to track the community infection levels of severe acute respiratory syndrome coronavirus 2. A gap exists in standardized reporting for fecal indicator concentrations, which can be used to calibrate the primary outcome concentrations from wastewater monitoring for use in epidemiological models. To address this, measurements of fecal indicator concentration among wastewater samples collected from sewers and treatment centers in four counties of Kentucky (N = 650) were examined. Results from the untransformed wastewater data over 4 months of sampling indicated that the fecal indicator concentration of human ribonuclease P (RNase P) ranged from 5.1 × 101 to 1.15 × 106 copies/ml, pepper mild mottle virus (PMMoV) ranged from 7.23 × 103 to 3.53 × 107 copies/ml, and cross-assembly phage (CrAssphage) ranged from 9.69 × 103 to 1.85 × 108 copies/ml. The results showed both regional and temporal variability. If fecal indicators are used as normalization factors, knowing the daily sewer system flow of the sample location may matter more than rainfall. RNase P, while it may be suitable as an internal amplification and sample adequacy control, has less utility than PMMoV and CrAssphage as a fecal indicator in wastewater samples when working at different sizes of catchment area. The choice of fecal indicator will impact the results of surveillance studies using this indicator to represent fecal load. Our results contribute broadly to an applicable standard normalization factor and assist in interpreting wastewater data in epidemiological modeling and monitoring.

Spatial evaluation of prevalence, pattern and predictors of cervical cancer screening in India.

OBJECTIVE: To investigate the social determinants of cervical cancer screening and report the locations vulnerable to poor utilization of cervical cancer screening services. STUDY DESIGN: An ecological study with the data derived from fourth round of the National Family Health Survey conducted in India in the period 2015-2016. METHODS: The study focused on the percentage of women who have never undergone cervical cancer screening across 639 districts in India. Moran's I statistic was used to investigate the overall clustering of location. The Getis-Ord Gi* statistic was used for the detection of significant local clusters. Spatial error, spatial lag, spatial Durbin and spatial Durbin error models were compared, and the model with best fit was reported. ArcGIS, GeoDa and R software were used for the analysis. RESULTS: The existence of spatial autocorrelation (Moran's I = 0.61) necessitates the consideration of spatial component while studying the screening data. A significant clustering of districts with poor screening has been observed in the North-Central and North-Eastern regions of India. The geographic arrangement of the percentage of women who have undergone cervical cancer screening was associated with the percentage of women with poor wealth index (P < 0.001), not using a modern method of contraception (P < 0.001), residing in rural areas (P = 0.033) and never heard of sexually transmitted infection (P = 0.014). The range of percentage of women getting cervix screened for cancer was 0.5-68.4%, presenting the heterogeneity among the population elements. CONCLUSION: A higher risk of poor cervical cancer screening is observed in the districts where most of the women have poor wealth index, reside in urban area, have never heard of sexually transmitted infection and do not use a modern method of contraception.

An efficient algorithm for protein structure comparison using elastic shape analysis.

BACKGROUND: Protein structure comparison play important role in in silico functional prediction of a new protein. It is also used for understanding the evolutionary relationships among proteins. A variety of methods have been proposed in literature for comparing protein structures but they have their own limitations in terms of accuracy and complexity with respect to computational time and space. There is a need to improve the computational complexity in comparison/alignment of proteins through incorporation of important biological and structural properties in the existing techniques. RESULTS: An efficient algorithm has been developed for comparing protein structures using elastic shape analysis in which the sequence of 3D coordinates atoms of protein structures supplemented by additional auxiliary information from side-chain properties are incorporated. The protein structure is represented by a special function called square-root velocity function. Furthermore, singular value decomposition and dynamic programming have been employed for optimal rotation and optimal matching of the proteins, respectively. Also, geodesic distance has been calculated and used as the dissimilarity score between two protein structures. The performance of the developed algorithm is tested and found to be more efficient, i.e., running time reduced by 80-90 % without compromising accuracy of comparison when compared with the existing methods. Source codes for different functions have been developed in R. Also, user friendly web-based application called ProtSComp has been developed using above algorithm for comparing protein 3D structures and is accessible free. CONCLUSIONS: The methodology and algorithm developed in this study is taking considerably less computational time without loss of accuracy (Table 2). The proposed algorithm is considering different criteria of representing protein structures using 3D coordinates of atoms and inclusion of residue wise molecular properties as auxiliary information.

Fatty acids and TxA(2) generation, in the absence of platelet-COX-1 activity.

BACKGROUND AND AIMS: Omega-3 fatty acids suppress Thromboxane A(2) (TxA(2)) generation via mechanisms independent to that of aspirin therapy. We sought to evaluate whether baseline omega-3 fatty acid levels influence arachidonic acid proven platelet-cyclooxygenase-1 (COX-1) independent TxA(2) generation (TxA(2) generation despite adequate aspirin use). METHODS AND RESULTS: Subjects with acute myocardial infarction, stable CVD or at high risk for CVD, on adequate aspirin therapy were included in this study. Adequate aspirin action was defined as complete inhibition of platelet-COX-1 activity as assessed by <10% change in light transmission aggregometry to ≥1 mmol/L arachidonic acid. TxA(2) production was measured via liquid chromatography-tandem mass spectrometry for the stable TxA(2) metabolite 11-dehydro-thromboxane B2 (UTxB2) in urine. The relationship between baseline fatty acids, demographics and UTxB(2) were evaluated. Baseline omega-3 fatty acid levels were not associated with UTxB(2) concentration. However, smoking was associated with UTxB(2) in this study. CONCLUSION: Baseline omega-3 fatty acid levels do not influence TxA(2) generation in patients with or at high risk for CVD receiving adequate aspirin therapy. The association of smoking and TxA(2) generation, in the absence of platelet COX-1 activity, among aspirin treated patients warrants further study.

Assessing aboveground tropical forest biomass using Google Earth canopy images.

Reducing Emissions from Deforestation and Forest Degradation (REDD) in efforts to combat climate change requires participating countries to periodically assess their forest resources on a national scale. Such a process is particularly challenging in the tropics because of technical difficulties related to large aboveground forest biomass stocks, restricted availability of affordable, appropriate remote-sensing images, and a lack of accurate forest inventory data. In this paper, we apply the Fourier-based FOTO method of canopy texture analysis to Google Earth's very-high-resolution images of the wet evergreen forests in the Western Ghats of India in order to (1) assess the predictive power of the method on aboveground biomass of tropical forests, (2) test the merits of free Google Earth images relative to their native commercial IKONOS counterparts and (3) highlight further research needs for affordable, accurate regional aboveground biomass estimations. We used the FOTO method to ordinate Fourier spectra of 1436 square canopy images (125 x 125 m) with respect to a canopy grain texture gradient (i.e., a combination of size distribution and spatial pattern of tree crowns), benchmarked against virtual canopy scenes simulated from a set of known forest structure parameters and a 3-D light interception model. We then used 15 1-ha ground plots to demonstrate that both texture gradients provided by Google Earth and IKONOS images strongly correlated with field-observed stand structure parameters such as the density of large trees, total basal area, and aboveground biomass estimated from a regional allometric model. Our results highlight the great potential of the FOTO method applied to Google Earth data for biomass retrieval because the texture-biomass relationship is only subject to 15% relative error, on average, and does not show obvious saturation trends at large biomass values. We also provide the first reliable map of tropical forest aboveground biomass predicted from free Google Earth images.

Operating characteristics of a Simon two-stage phase II clinical trial design incorporating continuous toxicity monitoring.

Phase II clinical trials are usually designed to measure efficacy, but safety is also an important end point. Previous authors recommended a method to monitor toxic events after each patient is enrolled, which is also known as continuously monitoring the toxicity. In this work, we investigate combining the usual Simon two-stage design to monitor response with the continuous toxicity monitoring methodology. Theoretical justification is given for the nominal size, probability of early termination, and average sample size under the null hypothesis of the combined testing procedure. A series of simulations are performed to investigate the performance of the combined procedure.

An evaluation of a Simon 2-Stage phase II clinical trial design incorporating toxicity monitoring.

Phase II clinical trials are usually designed to measure efficacy but patient safety is also a very important aspect. Previous authors suggested a methodology that allows one to monitor the cumulative number of toxic events after each patient is treated, which is also known as continuous toxicity monitoring. In this work we describe how to combine the continuous toxicity monitoring methodology with the Simon 2-Stage design for response. Then we investigate through simulation the combined procedure's type I and type II error rates under various combinations of design parameters. We include the underlying relationship between toxicity and response in our examination of the error rates.

Asymptomatic kidney stones in long-term survivors of childhood acute lymphoblastic leukemia.

We hypothesized an association between renal calculi and bone mineral density (BMD) deficits, shown in adults, exists in survivors of childhood acute lymphoblastic leukemia (ALL). Thus, we analyzed the associations between quantitative computed tomography (QCT)-determined renal calcifications and clinical parameters (gender, race, age at diagnosis and age at the time of QCT), BMD, treatment exposures and Tanner stage. We investigated the associations between stone formation and nutritional intake, serum and urinary calcium and creatinine levels, and urinary calcium/creatinine ratio. Exact chi(2)-test was used to compare categorical patient characteristics, and the Wilcoxon-Mann-Whitney test to compare continuous measurements. Of 424 participants, 218 (51.4%) were males; 371 (87.5%) were nonblack. Most (n=270; 63.7%) were >or=3.5 years at ALL diagnosis. Mean (s.d.) and median (range) BMD Z-scores of the entire cohort were -0.4 (1.2) and -0.5 (-3.9 to 5.1), respectively. Nineteen participants (10 males; 10 Caucasians) had kidney stones (observed prevalence of 4.5%; 19/424) with a significant negative association between stone formation and body habitus (body mass index, P=0.003). Stone formation was associated with treatment protocol (P=0.009) and treatment group (0.007). Thus, kidney stones in childhood ALL survivors could herald the future deterioration of renal function and development of hypertension. Long-term follow-up imaging may be warranted in these patients to monitor for progressive morbidity.

Testing threshold and hormesis in a random effects dose-response model applied to developmental toxicity data.

Here we describe a random effects threshold dose-response model for clustered binary-response data from developmental toxicity studies. For our model we assume that a hormetic effect occurs in addition to a threshold effect. Therefore, the dose-response curve is based on two components: relationships below the threshold (hormetic u-shaped model) and those above the threshold (logistic model). In the absence of hormesis and threshold effects, the estimation procedure is straightforward. We introduce score tests that are derived from a random effects hormetic-threshold dose-response model. The model and tests are applied to clustered binary data from developmental toxicity studies of animals to test for hormesis and threshold effects. We also compare the score test and likelihood ratio test to test for hormesis and threshold effects in a simulated study.

Quality of life as conveyed by pediatric patients with cancer.

Quality-of-life instruments have provided important advances in measuring the quality of life of pediatric patients receiving treatment for cancer. However, the bases of these instruments have not included first-hand reports from the patients; thus, these instruments may be conceptually incomplete. We directly solicited from pediatric patients their perspectives regarding their quality of life during treatment for cancer. We conducted two pilot studies: 23 patients (aged 8-15 years) participated in the first, a cross-sectional study; and 13 patients (aged 10-18 years) participated in the second, a 2-year longitudinal study. Data were analyzed by using a semantic-content method, and the following six domains were recognized in data from both of the studies: symptoms, usual activities, social/family interactions, health status, mood, and the meaning of being ill. These domains were compared with those of seven established pediatric oncology quality-of-life instruments, none of which included all six of these domains; the domain most frequently missing was the meaning of being ill domain. Here we present a new definition of the quality of life of pediatric oncology patients that is based on six domains; this definition may ensure the completeness and sensitivity of these important instruments.

Acute health-related quality of life in children undergoing stem cell transplant: I. Descriptive outcomes.

There has been little empirical documentation of the acute effects of bone marrow or stem cell transplant (BMT) on children. In the present study, the responses of 153 children undergoing BMT were assessed in a prospective, longitudinal design. Children were assessed at the time of admission for transplant, then underwent weekly assessments to week +6, followed by monthly assessment to month +6. Data were obtained both by parent report and patient report (for patients age 5 and up) using the BASES scales. The major findings are: (1) children undergoing BMT enter the hospital with an already heightened level of distress (defined by high levels of somatic symptoms and mood disturbance, and low levels of activity) that increases dramatically following conditioning, reaching a peak approximately 1 week following transplant; (2) this increased distress is transient, declining rapidly back to admission levels by week +4 to week +5, followed by a further decline to presumed basal levels by months 4-6; and (3) the trajectories of distress depicted by both parent and child report are remarkably similar, each providing confirmatory support for the validity of the findings. These findings confirm a number of widely held clinical impressions that had not previously been documented empirically, and point to the need for new interventions or more intensive approaches to supportive care aimed at reducing levels of distress during the acute phase of transplant.

Acute health-related quality of life in children undergoing stem cell transplant: II. Medical and demographic determinants.

Medical and demographic variables were examined as predictors of acute health-related quality of life (HRQL), specifically, somatic distress, mood disturbance and activity levels, during the period of bone marrow transplant (BMT) hospitalization, and the transition phase in the months following hospital discharge. The responses of 153 children undergoing BMT were assessed by both parent report and patient self-report in a prospective longitudinal design. Type of transplant, diagnosis, age, gender, and socio-economic status (SES) were examined as predictor variables of patient outcome. Type of transplant, patient age, and SES emerged as significant determinants of patient response. Children undergoing unrelated donor (MUD) transplants experiencing the highest levels of distress, followed by those undergoing matched-sibling BMT, while those undergoing autologous transplant experienced the lowest levels of distress. Younger patients experienced lower levels of distress and better HRQL than older children and adolescents. Although patients from different SES backgrounds appeared very similar at the time of hospital admission, those from lower SES backgrounds demonstrated greater distress and disturbance in HRQL subsequently, and throughout the first 6 months post BMT. These findings help to target specific subgroups of patients that may be in greater need of preventive interventions or more aggressive supportive care.

Hydatid disease in children may have an atypical presentation.

Although there is voluminous literature describing various aspects of hydatid disease in children, little attention has been paid to the small group of patients whose symptoms result in atypical presentation. This article addresses this problem, describing the features in ten children aged from 2 to 12 years. The sites of involvement were within a choledochal cyst (1). the pelvic cavity (1), the spleen (1), and transverse mesocolon. Albendazole was efficacious in the treatment of one recurrent case, as well as in preventing recurrence.

Characterization of uncertainty and variability in residential radon cancer risks.

Radon, a naturally occurring gas found at some level in most homes, is an established risk factor for human lung cancer. The U.S. National Research Council has recently completed a comprehensive evaluation of the health risks of residential exposure to radon and developed models for projecting radon lung cancer risks to the general population. This analysis suggests that radon may play a role in the etiology of 10-15% of all lung cancer cases in the United States, although these estimates are subject to considerable uncertainty. In this article, we present a detailed analysis of uncertainty and variability in estimates of lung cancer risk due to residential exposure to radon. We use a general framework for the analysis of uncertainty and variability that we developed previously. Specifically, we focus on estimates of the age-specific excess relative risk (ERR) and lifetime relative risk (LRR), both of which vary substantially among individuals. We also consider estimates of the population attributable risk (PAR), which reflects the proportion of the lung cancer burden attributable to radon. Variability in the ERR and LRR is largely determined by variability in residential exposure levels and in the dosimetric K-factor used to extrapolate from occupational to environmental settings. Uncertainty in the ERR and LRR is due to uncertainty in the model parameters, notably those reflecting the carcinogenic potency of radon and the modifying effect of attained age. Uncertainty in the PAR is determined by uncertainty about the values of the parameters in the risk models used to estimate the PAR. Uncertainty in radon levels in homes and the dosimetric K-factor contribute comparatively little to uncertainty in the PAR. These results suggest that reduction in uncertainty about the PAR for radon induced lung cancer can only be achieved if more reliable risk projection models can be developed.

Uncertainty and variability analysis in multiplicative risk models.

Currently, there is a trend away from the use of single (often conservative) estimates of risk to summarize the results of risk analyses in favor of stochastic methods which provide a more complete characterization of risk. The use of such stochastic methods leads to a distribution of possible values of risk, taking into account both uncertainty and variability in all of the factors affecting risk. In this article, we propose a general framework for the analysis of uncertainty and variability for use in the commonly encountered case of multireplicative risk models, in which risk may be expressed as a product of two or more risk factors. Our analytical methods facilitate the evaluation of overall uncertainty and variability in risk assessment, as well as the contributions of individual risk factors to both uncertainty and variability which is cumbersome using Monte Carlo methods. The use of these methods is illustrated in the analysis of potential cancer risks due to the ingestion of radon in drinking water.

Ecology of microbial population of soils of North Bihar as affected by soil factors.

The determination of the number of bacteria, actinomycetes, and fungi in 72 soil samples of different sugar cane soils in North Bihar (India) and the calculation of the correlations between these values and the content of organic carbon, total nitrogen, total soluble salts, available P2O5, and water-soluble K2O gave these results: 1. Significant and positive correlations were found between the content of organic carbon in the soil and the number of actinomycetes and fungi. 2. Significant and negative correlations were found between the content of water-soluble salts and the number of microorganisms. 3. There is a significant and positive correlatin between the number of bacteria and fungi and the total nitrogen content and and the available P2O5.