Determining Consistency of Spatial Dispersion of Nematodes in Small Plots

Nematode population densities in field plots were estimated by collecting samples consisting of 12 soil cores. Plots encompassed a variety of plant hosts and sampling dates, and provided data on the population densities of seven species of plant-parasitic nematodes. Three separate samples were collected per plot on each sampling date to obtain estimates of the mean and variance of numbers for each species. For each nematode species, these estimates were used to derive the Taylor''s Power Law regression over plots having identical hosts and sampling dates. For some nematode species, comparisons of regression equations among different sampling dates on the same host revealed similarities in values of a and b from Taylor''s Power Law. Parameters of Taylor''s Power Law relationships were used to develop sampling plans and to obtain estimates of sample precision. Precision estimates from specific and general sampling plans are illustrated for Belonolaimus longicaudatus.     

Nutrients Other than Selenium Are Important for Promoting Children’s Health in Kashin-Beck Disease Areas

Overall nutritional status has been proved associated with people’s health. The overall nutritional status of children in Kashin-Beck disease (KBD) areas has been overlooked for decades. Therefore, it is worth investigating in the current generation to gather evidence and make suggestions for improvement. A cross-sectional study with three 24-h dietary recalls was conducted to collect raw data on the daily food intake of children. Recorded food was converted into daily nutrient intakes using CDGSS 3.0 software. WHO AnthroPlus software was used to analyse the BMI-for-age z-score (BAZ) for estimating the overall nutrition status of children. All the comparisons and regression analyses were conducted with SPSS 18.0 software. Multiple nutrient intakes among children from the Se-supplemented KBD-endemic were under the estimated average requirement. The protein-to-carbohydrate ratio (P/C ratio) was significantly higher in children from the non-Se-supplemented KBD-endemic area than the other areas (P < 0.001). The children’s BAZ was negatively associated with age (B = ?0.095, P < 0.001) and the number of KBD relatives (B = ?0.277, P = 0.04), and it was positively associated with better housing conditions, receiving colostrum, and daily intakes of niacin and zinc by multivariate regression analysis (F = 10.337, R = 0.609, P < 0.001).Compared to non-Se-supplemented KBD-endemic area and non-endemic areas, children in Se-supplemented KBD-endemic areas have an insufficient intake of multiple nutrients. School breakfast and lunch programmes are recommended, and strict implementation is the key to ensuring a positive effect.     

Compound co-occurrence and biosynthetic inference

Zavarin suggested that co-occurrence of terpenoids in plants provides an indication of likely biosynthetic relationships when enzymatic and tracer results are unavailable to determine the matter. Zavarin's proposal is here evaluated with data from another class of secondary metabolites, the glucosinolates, where biosynthetic pathways are well known. Three datasets from taxa of Cakile and Streptanthus (Cruciferae) were analyzed statistically with SPSS programs. Pair-wise comparisons of compounds tested their assignment to one of three possible categories: related by one-carbon chain extension; related by cleavage of terminal methylthio-group to produce a double bond; or no close relationship. While one dataset showed a tendency for chain-extended compounds to correlate significantly, the data exhibited no strong indication overall that co-occurring compounds were any more likely to be biosynthetically linked than not. Furthermore, contrasting positive and negative correlations for biosynthetically related pairs indicated that co-occurrence did not track mechanisms of biosynthesis. Hence, compound co-occurrence by itself provides no clear guide to biosynthetic relationships. By analogy, similar results can be expected for other classes of diverse secondary metabolites such as flavonoids and terpenoids.     

Matrix-based concordance correlation coefficient for repeated measures

Summary In many clinical studies, Lin's concordance correlation coefficient (CCC) is a common tool to assess the agreement of a continuous response measured by two raters or methods. However, the need for measures of agreement may arise for more complex situations, such as when the responses are measured on more than one occasion by each rater or method. In this work, we propose a new CCC in the presence of repeated measurements, called the matrix‐based concordance correlation coefficient (MCCC) based on a matrix norm that possesses the properties needed to characterize the level of agreement between two p× 1 vectors of random variables. It can be shown that the MCCC reduces to Lin's CCC when p= 1. For inference, we propose an estimator for the MCCC based on U‐statistics. Furthermore, we derive the asymptotic distribution of the estimator of the MCCC, which is proven to be normal. The simulation studies confirm that overall in terms of accuracy, precision, and coverage probability, the estimator of the MCCC works very well in general cases especially when n is greater than 40. Finally, we use real data from an Asthma Clinical Research Network (ACRN) study and the Penn State Young Women's Health Study for demonstration.     

Repeatability of strain magnitude and strain rate measurements in the periodontal ligament using fibre Bragg gratings: An ex vivo study in a swine model

Measurement of periodontal ligament (PDL) strain in an ex vivo or in vivo setting of a complete tooth-PDL-bone complex (TPBC) has yet to be achieved in the literature. The objective of this study was to investigate inter- and intra-TPBC PDL strain measurement using fibre Bragg grating (FBG) strain sensors. Second and third premolars from the left and the right side of four swine mandibles were removed to yield sixteen TPBC samples. Samples were secured in a miniature load-frame equipped with a digital actuator used to apply apical-directed displacement to the tooth. The same tooth on left and right sides of the mouth were exposed to the same loading condition over ten trials allowing for comparisons in a split-mouth study. Displacements of 0.2 and 0.3 mm were considered along with displacement rates of 0.025, 0.05, and 0.1 mm/s, yielding six loading combinations. Hypothesis testing between left and right teeth revealed FBGs did not always measure the same strain between left and right TPBCs. For all strain measures, the average coefficient of variation (CV) (all data collected) was 2.16 (range: 0.274–10.71). For repeated measures in single TPBCs, the minimum CV ranged from 0.037 to 0.449, and generally coincided with the time of maximum strain measured over the test duration. Based on the findings of this study, it is suggested that FBGs can provide repeatable ex vivo strain measures in the PDL of complete TPBCs.     

Analyzing digital vector waveforms of 0–3000 Hz magnetic fields for health studies

To improve the assessment of magnetic field exposures for occupational health studies, the Multiwave® System III (MW3) was developed to capture personal exposures to the three‐dimensional magnetic field vector B (t) in the 0–3000 Hz band. To process hundreds of full‐shift MW3 measurements from epidemiologic studies, new computer programs were developed to calculate the magnetic field's physical properties and its interaction with biological systems through various mechanisms (magnetic induction, radical pair interactions, ion resonance, etc.). For automated calculations in the frequency domain, the software uses new algorithms that remove artifacts in the magnetic field's Fourier transform due to electronic noise and the person's motion through perturbations in the geomagnetic field from steel objects. These algorithms correctly removed the Fourier transform artifacts in 92% of samples and have improved the accuracy of frequency‐dependent metrics by as much as 3300%. The output of the MwBatch software is a matrix of 41 exposure metrics calculated for each 2/15 s sample combined with 8 summary metrics for the person's full‐period exposure, giving 294 summary‐exposure metrics for each person monitored. In addition, the MwVisualizer software graphically explores the magnetic field's vector trace, its component waveforms, and the metrics over time. The output was validated against spreadsheet calculations with pilot data. This software successfully analyzed full‐shift MW3 monitoring with 507 electric utility workers, comprising over 1 million vector waveforms. The software's output can be used to test hypotheses about magnetic field biology and disease with biophysical models and also assess compliance with exposure limits. Bioelectromagnetics 31:391–405, 2010. © 2010 Wiley‐Liss, Inc.     

Lameness detection in dairy cattle: single predictor v. multivariate analysis of image-based posture processing and behaviour and performance sensing

The objective of this study was to evaluate if a multi-sensor system (milk, activity, body posture) was a better classifier for lameness than the single-sensor-based detection models. Between September 2013 and August 2014, 3629 cow observations were collected on a commercial dairy farm in Belgium. Human locomotion scoring was used as reference for the model development and evaluation. Cow behaviour and performance was measured with existing sensors that were already present at the farm. A prototype of three-dimensional-based video recording system was used to quantify automatically the back posture of a cow. For the single predictor comparisons, a receiver operating characteristics curve was made. For the multivariate detection models, logistic regression and generalized linear mixed models (GLMM) were developed. The best lameness classification model was obtained by the multi-sensor analysis (area under the receiver operating characteristics curve (AUC)=0.757±0.029), containing a combination of milk and milking variables, activity and gait and posture variables from videos. Second, the multivariate video-based system (AUC=0.732±0.011) performed better than the multivariate milk sensors (AUC=0.604±0.026) and the multivariate behaviour sensors (AUC=0.633±0.018). The video-based system performed better than the combined behaviour and performance-based detection model (AUC=0.669±0.028), indicating that it is worthwhile to consider a video-based lameness detection system, regardless the presence of other existing sensors in the farm. The results suggest that Θ₂, the feature variable for the back curvature around the hip joints, with an AUC of 0.719 is the best single predictor variable for lameness detection based on locomotion scoring. In general, this study showed that the video-based back posture monitoring system is outperforming the behaviour and performance sensing techniques for locomotion scoring-based lameness detection. A GLMM with seven specific variables (walking speed, back posture measurement, daytime activity, milk yield, lactation stage, milk peak flow rate and milk peak conductivity) is the best combination of variables for lameness classification. The accuracy on four-level lameness classification was 60.3%. The accuracy improved to 79.8% for binary lameness classification. The binary GLMM obtained a sensitivity of 68.5% and a specificity of 87.6%, which both exceed the sensitivity (52.1%±4.7%) and specificity (83.2%±2.3%) of the multi-sensor logistic regression model. This shows that the repeated measures analysis in the GLMM, taking into account the individual history of the animal, outperforms the classification when thresholds based on herd level (a statistical population) are used.     

Detection of Patient Subgroups with Differential Expression in Omics Data: A Comprehensive Comparison of Univariate Measures

Detection of yet unknown subgroups showing differential gene or protein expression is a frequent goal in the analysis of modern molecular data. Applications range from cancer biology over developmental biology to toxicology. Often a control and an experimental group are compared, and subgroups can be characterized by differential expression for only a subgroup-specific set of genes or proteins. Finding such genes and corresponding patient subgroups can help in understanding pathological pathways, diagnosis and defining drug targets. The size of the subgroup and the type of differential expression determine the optimal strategy for subgroup identification. To date, commonly used software packages hardly provide statistical tests and methods for the detection of such subgroups. Different univariate methods for subgroup detection are characterized and compared, both on simulated and on real data. We present an advanced design for simulation studies: Data is simulated under different distributional assumptions for the expression of the subgroup, and performance results are compared against theoretical upper bounds. For each distribution, different degrees of deviation from the majority of observations are considered for the subgroup. We evaluate classical approaches as well as various new suggestions in the context of omics data, including outlier sum, PADGE, and kurtosis. We also propose the new FisherSum score. ROC curve analysis and AUC values are used to quantify the ability of the methods to distinguish between genes or proteins with and without certain subgroup patterns. In general, FisherSum for small subgroups and -test for large subgroups achieve best results. We apply each method to a case-control study on Parkinson''s disease and underline the biological benefit of the new method.     

Genetic diversity of commercially grown Moringa oleifera Lam. cultivars from India by RAPD, ISSR and cytochrome P450-based markers

Moringa oleifera is a less used, drought-tolerant tropical plant, rich in nutritionally and nutraceutically important bioactive compounds. It is native to India and now under cultivation in many countries, but no data is available on genetic variability. Three DNA marker techniques, i.e., random amplified polymorphic DNA (RAPD), inter simple sequence repeat (ISSR) and cytochrome P₄₅₀ gene-based markers were used for the detection of genetic variability in eight Indian cultivars of M. oleifera, collected from various states of India. A total of 17 RAPD, 6 ISSR and 7 pairs of cytochrome P₄₅₀-based markers generated 48.68, 48.57 and 40.00 % polymorphisms, respectively. The marker index (MI) for each of these marker systems (3.25 for RAPD, 4.73 ISSR and 2.95 for Cyt P₄₅₀-based markers) suggest that ISSR markers are the most effective for assessment of genetic diversity. Based on the three types of marker data, the eight cultivars of M. oleifera were grouped into four sub-clusters in a dendrogram, but without any distinct geographical pattern. This suggests spread of planting material and high rates of gene flow through cross pollination. High bootstrap values (94.4 and 82.3) were obtained at major nodes of the dendrogram using the winboot software. The dendrogram and PCA plots generated from the binary data matrices of the three marker systems were found highly concordant to each other. This study reveals a huge genetic diversity among the cultivars and this can be utilised for conservation and cultivar development in breeding programmes to produce high yielding, nutritionally superior cultivars.     

Do Baseline P-Values Follow a Uniform Distribution in Randomised Trials?

Background

The theory has been put forward that if a null hypothesis is true, P-values should follow a Uniform distribution. This can be used to check the validity of randomisation.

Method

The theory was tested by simulation for two sample t tests for data from a Normal distribution and a Lognormal distribution, for two sample t tests which are not independent, and for chi-squared and Fisher’s exact test using small and using large samples.

Results

For the two sample t test with Normal data the distribution of P-values was very close to the Uniform. When using Lognormal data this was no longer true, and the distribution had a pronounced mode. For correlated tests, even using data from a Normal distribution, the distribution of P-values varied from simulation run to simulation run, but did not look close to Uniform in any realisation. For binary data in a small sample, only a few probabilities were possible and distribution was very uneven. With a sample of two groups of 1,000 observations, there was great unevenness in the histogram and a poor fit to the Uniform.

Conclusions

The notion that P-values for comparisons of groups using baseline data in randomised clinical trials should follow a Uniform distribution if the randomisation is valid has been found to be true only in the context of independent variables which follow a Normal distribution, not for Lognormal data, correlated variables, or binary data using either chi-squared or Fisher’s exact tests. This should not be used as a check for valid randomisation.     

Phenological asynchrony between herbivorous insects and their hosts: signal of climate change or pre-existing adaptive strategy?

Climate change alters phenological relations between interacting species. We might expect the historical baseline, or starting-point, for such effects to be precise synchrony between the season at which a consumer most requires food and the time when its resources are most available. We synthesize evidence that synchrony was not the historical condition in two insect–plant interactions involving Edith''s checkerspot butterfly (Euphydryas editha), the winter moth (Operophtera brumata) and their host plants. Initial observations of phenological mismatch in both systems were made prior to the onset of anthropogenically driven climate change. Neither species can detect the phenology of its host plants with precision. In both species, evolution of life history has involved compromise between maximizing fecundity and minimizing mortality, with the outcome being superficially maladaptive strategies in which many, or even most, individuals die of starvation through poor synchrony with their host plants. Where phenological asynchrony or mismatch with resources forms the starting point for effects of anthropogenic global warming, consumers are particularly vulnerable to impacts that exacerbate the mismatch. This vulnerability likely contributed to extinction of a well-studied metapopulation of Edith''s checkerspot, and to the skewed geographical pattern of population extinctions underlying a northward and upward range shift in this species.     

medplot: A Web Application for Dynamic Summary and Analysis of Longitudinal Medical Data Based on R

In biomedical studies the patients are often evaluated numerous times and a large number of variables are recorded at each time-point. Data entry and manipulation of longitudinal data can be performed using spreadsheet programs, which usually include some data plotting and analysis capabilities and are straightforward to use, but are not designed for the analyses of complex longitudinal data. Specialized statistical software offers more flexibility and capabilities, but first time users with biomedical background often find its use difficult. We developed medplot, an interactive web application that simplifies the exploration and analysis of longitudinal data. The application can be used to summarize, visualize and analyze data by researchers that are not familiar with statistical programs and whose knowledge of statistics is limited. The summary tools produce publication-ready tables and graphs. The analysis tools include features that are seldom available in spreadsheet software, such as correction for multiple testing, repeated measurement analyses and flexible non-linear modeling of the association of the numerical variables with the outcome. medplot is freely available and open source, it has an intuitive graphical user interface (GUI), it is accessible via the Internet and can be used within a web browser, without the need for installing and maintaining programs locally on the user’s computer. This paper describes the application and gives detailed examples describing how to use the application on real data from a clinical study including patients with early Lyme borreliosis.     

Batch effect correction for genome-wide methylation data with Illumina Infinium platform

Background

Paclitaxel is a microtubule-stabilizing drug that has been commonly used in treating cancer. Due to genetic heterogeneity within patient populations, therapeutic response rates often vary. Here we used the NCI60 panel to identify SNPs associated with paclitaxel sensitivity. Using the panel's GI50 response data available from Developmental Therapeutics Program, cell lines were categorized as either sensitive or resistant. PLINK software was used to perform a genome-wide association analysis of the cellular response to paclitaxel with the panel's SNP-genotype data on the Affymetrix 125 k SNP array. FastSNP software helped predict each SNP's potential impact on their gene product. mRNA expression differences between sensitive and resistant cell lines was examined using data from BioGPS. Using Haploview software, we investigated for haplotypes that were more strongly associated with the cellular response to paclitaxel. Ingenuity Pathway Analysis software helped us understand how our identified genes may alter the cellular response to paclitaxel.

Results

43 SNPs were found significantly associated (FDR < 0.005) with paclitaxel response, with 10 belonging to protein-coding genes (CFTR, ROBO1, PTPRD, BTBD12, DCT, SNTG1, SGCD, LPHN2, GRIK1, ZNF607). SNPs in GRIK1, DCT, SGCD and CFTR were predicted to be intronic enhancers, altering gene expression, while SNPs in ZNF607 and BTBD12 cause conservative missense mutations. mRNA expression analysis supported these findings as GRIK1, DCT, SNTG1, SGCD and CFTR showed significantly (p < 0.05) increased expression among sensitive cell lines. Haplotypes found in GRIK1, SGCD, ROBO1, LPHN2, and PTPRD were more strongly associated with response than their individual SNPs.

Conclusions

Our study has taken advantage of available genotypic data and its integration with drug response data obtained from the NCI60 panel. We identified 10 SNPs located within protein-coding genes that were not previously shown to be associated with paclitaxel response. As only five genes showed differential mRNA expression, the remainder would not have been detected solely based on expression data. The identified haplotypes highlight the role of utilizing SNP combinations within genomic loci of interest to improve the risk determination associated with drug response. These genetic variants represent promising biomarkers for predicting paclitaxel response and may play a significant role in the cellular response to paclitaxel.     

THE REFRACTIVE INDICES OF WHOLE CELLS

Refractive indices of intact sporangiophores of Phycomyces were computed from measurements of focal length and radius of curvature of the cells. For the six cells studied, effective values of n were obtained ranging from 1.35 to 1.40. The average effective n was 1.38. Senn''s determination of refractive indices of other plants cells gave much higher values: n = 1.37 to 1.52. The precision of the method and possible sources of this discrepancy are discussed.     

Diverse parentage relationships in paternal mouthbrooding fishes

While mouthbrooding is not an uncommon parental care strategy in fishes, paternal mouthbrooding only occurs in eight fish families and is little studied. The high cost of paternal mouthbrooding to the male implies a low risk of investment in another male''s offspring but genetic parentage patterns are poorly known for paternal mouthbrooders. Here, we used single-nucleotide polymorphism genetic data to investigate parentage relationships of broods of two mouthbrooders of northern Australian rivers, mouth almighty Glossamia aprion and blue catfish Neoarius graeffei. For N. graeffei, we found that the parentage pattern was largely monogamous with the brooder male as the sire. For G. aprion, the parentage pattern was more heterogeneous including observations of monogamous broods with the brooder male as the sire (73%), polygyny (13%), cuckoldry (6%) and a brood genetically unrelated to the brooder male (6%). Findings demonstrate the potential for complex interrelationships of male care, paternity confidence and mating behaviour in mouthbrooding fishes.     

Feuerborn's hypothesis of hypopygial circumversion in schizophoran Diptera: A repetition and reappraisal of Schräder's (1927) studies

Schräder's (1927) investigations on the hypopygial circumversion in Calliphora (Diptera : Calliphoridae) pupae have been repeated with improved techniques and more efficient control and Feuerborn's (1922) hypothesis of hypopygial circumversion has been disproved. The development of the male reproductive organs is described. Serious defects and ambiguities in Schräder's (1927) techniques invalidate his claims for hypopygial circumversion in pupal Calliphora. Salzer's (1968) claims of a double chiasmata in the hypopygial nervous system have been modified. The available evidence shows that no rotation of the hypopygial segments occurs in either the pupal or the pharate adult stages of Calliphora vicinia. It is suggested that the unique schizophoran ductus-hindgut relationship originated as a result of the coiling of the larval and adult alimentary canals, causing an internal clockwise (seen anteriorly) displacement of the organs concerned. The causes of the observed hypopygial sexual differences are discussed.     

Major Soybean Maturity Gene Haplotypes Revealed by SNPViz Analysis of 72 Sequenced Soybean Genomes

In this Genomics Era, vast amounts of next-generation sequencing data have become publicly available for multiple genomes across hundreds of species. Analyses of these large-scale datasets can become cumbersome, especially when comparing nucleotide polymorphisms across many samples within a dataset and among different datasets or organisms. To facilitate the exploration of allelic variation and diversity, we have developed and deployed an in-house computer software to categorize and visualize these haplotypes. The SNPViz software enables users to analyze region-specific haplotypes from single nucleotide polymorphism (SNP) datasets for different sequenced genomes. The examination of allelic variation and diversity of important soybean [Glycine max (L.) Merr.] flowering time and maturity genes may provide additional insight into flowering time regulation and enhance researchers'' ability to target soybean breeding for particular environments. For this study, we utilized two available soybean genomic datasets for a total of 72 soybean genotypes encompassing cultivars, landraces, and the wild species Glycine soja. The major soybean maturity genes E1, E2, E3, and E4 along with the Dt1 gene for plant growth architecture were analyzed in an effort to determine the number of major haplotypes for each gene, to evaluate the consistency of the haplotypes with characterized variant alleles, and to identify evidence of artificial selection. The results indicated classification of a small number of predominant haplogroups for each gene and important insights into possible allelic diversity for each gene within the context of known causative mutations. The software has both a stand-alone and web-based version and can be used to analyze other genes, examine additional soybean datasets, and view similar genome sequence and SNP datasets from other species.