Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits

Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.

Drug susceptibility testing of anaerobic protozoa

A simple technique for routine, reproducible global surveillance of the drug susceptibility status of the anaerobic protozoa Trichomonas, Entamoeba, and Giardia is described, Data collected using this technique can be readily compared among different laboratories and with previously reported data. The technique employs a commercially available sachet and bag system to generate a low-oxygen environment and log, drug dilutions in microtiter plates, which can be monitored without aerobic exposure, to assay drug-resistant laboratory lines and clinically resistant isolates. MICs (after 2 days) of 3.2 and 25 muM indicated metronidazole-sensitive and highly clinically resistant isolates of T. vaginalis in anaerobic assays, respectively. The aerobic MICs were 25 and > 200 muM. MICs (1 day) of 12.5 to 25 muM were found for axenic lines of E. histolytica, and MICs for G. duodenalis (3 days) ranged from 6.3 muM for metronidazole-sensitive isolates to 50 muM for laboratory metronidazole-resistant lines. This technique should encourage more extensive monitoring of drug resistance in these organisms.

Immunohistochemistry versus microsatellite instability testing in phenotyping colorectal tumors

Purpose: To compare microsatellite instability (MSI) testing with immunohistochemical (IHC) detection of hMLH1 and hMSH2 in colorectal cancer. Patients and Methods: Colorectal cancers from 1, 144 patients were assessed for DNA mismatch repair deficiency by two methods: MSI testing and IHC detection of hMLH1 and hMSH2 gene products. High-frequency MSI (MSI-H) was defined as more than 30% instability of at least five markers; low-level MSI (MSI-L) was defined as 1% to 29% of loci unstable. Results: Of 1, 144 tumors tested, 818 showed intact expression of hMLH1 and hMSH2. Of these, 680 were microsatellite stable (MSS), 27 were MSI-H, and 111 were MSI-L. In all, 228 tumors showed absence of hMLH1 expression and 98 showed absence of hMSH2 expression: all were MSI-H. Conclusion: IHC in colorectal tumors for protein products hMLH1 and hMSH2 provides a rapid, cost-effective, sensitive (92.3%), and extremely specific (100%) method for screening for DNA mismatch repair defects. The predictive value of normal IHC for an MSS/MSI-L phenotype was 96.7%, and the predictive value of abnormal IHC was 100% for an MSI-H phenotype. Testing strategies must take into account acceptability of missing some cases of MSI-H tumors if only IHC is performed. (C) 2002 by American Society of Clinical Oncology.

A portable load cell for in-situ ore impact breakage testing

This paper discusses the design and characterisation of a short, and hence portable impact load cell for in-situ quantification of ore breakage properties under impact loading conditions. Much literature has been published in the past two decades about impact load cells for ore breakage testing. It has been conclusively shown that such machines yield significant quantitative energy-fragmentation information about industrial ores. However, documented load cells are all laboratory systems that are not adapted for in-situ testing due to their dimensions and operating requirements. The authors report on a new portable impact load cell designed specifically for in-situ testing. The load cell is 1.5 m in height and weighs 30 kg. Its physical and operating characteristics are detailed in the paper. This includes physical dimensions, calibration and signal deconvolution. Emphasis is placed on the deconvolution issue, which is significant for such a short load cell. Finally, it is conclusively shown that the short load cell is quantitatively as accurate as its larger laboratory analogues. (C) 2062 Elsevier Science B.V. All rights reserved.

Design, development, and testing of X-band amplifying reflectarrays

The design and development of two X-band amplifying reflectarrays is presented. The arrays use dual-polarized aperture coupled patch antennas with FET transistors and phasing circuits to amplify a microwave signal and to radiate it in a chosen direction. Two cases are considered, one when a reflectarray converts a spherical wave due to a feed horn into a plane wave radiated into a boresight direction, and two, when the reflectarray converts a spherical wave due to a dual-polarized four-element feed array into a co-focal spherical wave. This amplified signal is received in an orthogonal port of the feed array so that the entire structure acts as a spatial power combiner. The two amplifying arrays are tested in the near-field zone for phase distribution over their apertures to achieve the required beam formation. Alternatively, their radiation patterns or gains are investigated.

Interspecific variation in plumage colour among birds: species recognition or light environment?

The traditional explanation for interspecific plumage colour variation in birds is that colour differences between species are adaptations to minimize the risk of hybridization. Under this explanation, colour differences between closely related species of birds represent reproductive character displacement. An alternative explanation is that interspecific variation in plumage colour is an adaptive response to variation in light environments across habitats. Under this explanation, differences in colour between closely related species are a product of selection on signal efficiency. We use a comparative approach to examine these two hypotheses, testing the effects of sympatry and habitat use, respectively, on divergence in male plumage colour. Contrary to the prediction of the Species Isolation Hypothesis, we find no evidence that sympatric pairs of species are consistently more divergent in coloration than are allopatric pairs of species. However, in agreement with the Light Environment Hypothesis, we find significant associations between plumage coloration and habitat use. All of these results remain qualitatively unchanged irrespective of the statistical methodology used to compare reflectance spectra, the body regions used in the analyses, or the exclusion of areas of plumage not used in sexual displays. Our results suggest that, in general, interspecific variation in plumage colour among birds is more strongly influenced by the signalling environment than by the risk of hybridization.

Testing insect movement theory: empirical analysis of pest data routinely collected from agricultural crops

Observations of an insect's movement lead to theory on the insect's flight behaviour and the role of movement in the species' population dynamics. This theory leads to predictions of the way the population changes in time under different conditions. If a hypothesis on movement predicts a specific change in the population, then the hypothesis can be tested against observations of population change. Routine pest monitoring of agricultural crops provides a convenient source of data for studying movement into a region and among fields within a region. Examples of the use of statistical and computational methods for testing hypotheses with such data are presented. The types of questions that can be addressed with these methods and the limitations of pest monitoring data when used for this purpose are discussed. (C) 2002 Elsevier Science B.V. All rights reserved.

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.

Testing the relationship between morphological and molecular rates of change along phylogenies

Molecular evolution has been considered to be essentially a stochastic process, little influenced by the pace of phenotypic change. This assumption was challenged by a study that demonstrated an association between rates of morphological and molecular change estimated for total-evidence phylogenies, a finding that led some researchers to challenge molecular date estimates of major evolutionary radiations. Here we show that Omland's (1997) result is probably due to methodological bias, particularly phylogenetic nonindependence, rather than being indicative of an underlying evolutionary phenomenon. We apply three new methods specifically designed to overcome phylogenetic bias to 13 published phylogenetic datasets for vertebrate taxa, each of which includes both morphological characters and DNA sequence data. We find no evidence of an association between rates of molecular and morphological rates of change.

Clinical evaluation of the WOMAC 3.0 OA Index in numeric rating scale format using a computerized touch screen version

Background: The Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index is a previously described self-administered questionnaire covering three domains: pain, stiffness and function. It has been validated in patients with osteoarthritis (OA) of the hip or knee in a paper-based format. Aim: To validate the WOMAC 3.0 using a numerical rating scale in a computerized touch screen format allowing immediate evaluation of the questionnaire. In the computed version cartoons, written and audio instruments were included in order facilitate application. Methods: Fifty patients, demographically balanced, with radiographically proven primary hip or knee OA completed the classical paper and the new computerized WOMAC version. Subjects were randomized either to paper format or computerized format first to balance possible order effects, Results: The intra-class correlation coefficients for pain, stiffness and function values were 0.915, 0.745 and 0.940, respectively. The Spearman correlation coefficients for pain, stiffness and function were 0.88, 0.77 and 0.87, respectively. Conclusion: These data indicate that the computerized WOMAC OA index 3.0 is comparable to the paper WOMAC in all three dimensions. The computerized version would allow physicians to get an immediate result and if present a direct comparison with a previous exam. (C) 2002 OsteoArthritis Research Society International. Published by Elsevier Science Ltd. All rights reserved.