Distinct physiological mechanisms underlie altered glycinergic synaptic transmission in the murine mutants spastic, spasmodic, and oscillator

Spastic (spa), spasmodic (spd), and oscillator (ot) mice have naturally occurring glycine receptor ( GlyR) mutations, which manifest as motor deficits and an exaggerated startle response. Using whole-cell recording in hypoglossal motoneurons, we compared the physiological mechanisms by which each mutation alters GlyR function. Mean glycinergic miniature IPSC ( mIPSC) amplitude and frequency were dramatically reduced (> 50%) compared with controls for each mutant. mIPSC decay times were unchanged in spa/spa (4.5 +/- 0.3 vs 4.7 +/- 0.2 ms), reduced in spd/spd (2.7 +/- 0.2 vs 4.7 +/- 0.2 ms), and increased in ot/ot (12.3 +/- 1.2 vs 4.8 +/- 0.2 ms). Thus, in spastic, GlyRs are functionally normal but reduced in number, whereas in spasmodic, GlyR kinetics is faster. The oscillator mutation results in complete absence of alpha 1-containing GlyRs; however, some non-alpha 1-containing GlyRs persist at synapses. Fluctuation analysis of membrane current, induced by glycine application to outside-out patches, showed that mean single-channel conductance was increased in spa/spa (64.2 +/- 4.9 vs 36.1 +/- 1.4 pS), but unchanged in spd/spd (32.4 +/- 2.1 vs 35.3 +/- 2.1 pS). GlyR-mediated whole-cell currents in spa/spa exhibited increased picrotoxin sensitivity (27 vs 71% block for 100 mu M), indicating alpha 1 homomeric GlyR expression. The picrotoxin sensitivity of evoked glycinergic IPSCs and conductance of synaptic GlyRs, as determined by nonstationary variance analysis, were identical for spa/spa and controls. Together, these findings show the three mutations disrupt GlyR-mediated inhibition via different physiological mechanisms, and the spastic mutation results in compensatory alpha 1 homomeric GlyRs at extrasynaptic loci.

Evaluation of the indirect measures of rock brittleness and fracture toughness in rock cutting

Performance prediction models for partial face mechanical excavators, when developed in laboratory conditions, depend on relating the results of a set of rock property tests and indices to specific cutting energy (SE) for various rock types. There exist some studies in the literature aiming to correlate the geotechnical properties of intact rocks with the SE, especially for massive and widely jointed rock environments. However, those including direct and/or indirect measures of rock fracture parameters such as rock brittleness and fracture toughness, along with the other rock parameters expressing different aspects of rock behavior under drag tools (picks), are rather limited. With this study, it was aimed to investigate the relationships between the indirect measures of rock brittleness and fracture toughness and the SE depending on the results of a new and two previous linear rock cutting programmes. Relationships between the SE, rock strength parameters, and the rock index tests have also been investigated in this study. Sandstone samples taken from the different fields around Ankara, Turkey were used in the new testing programme. Detailed mineralogical analyses, petrographic studies, and rock mechanics and rock cutting tests were performed on these selected sandstone specimens. The assessment of rock cuttability was based on the SE. Three different brittleness indices (B1, B2, and B4) were calculated for sandstones samples, whereas a toughness index (T-i), being developed by Atkinson et al.(1), was employed to represent the indirect rock fracture toughness. The relationships between the SE and the large amounts of new data obtained from the mineralogical analyses, petrographic studies, rock mechanics, and linear rock cutting tests were evaluated by using bivariate correlation and curve fitting techniques, variance analysis, and Student's t-test. Rock cutting and rock property testing data that came from well-known studies of McFeat-Smith and Fowell(2) and Roxborough and Philips(3) have also been employed in statistical analyses together with the new data. Laboratory tests and subsequent analyses revealed that there were close correlations between the SE and B4 whereas no statistically significant correlation has been found between the SE and T-i. Uniaxial compressive and Brazilian tensile strengths and Shore scleroscope hardness of sandstones also exhibited strong relationships with the SE. NCB cone indenter test had the greatest influence on the SE among the other engineering properties of rocks, confirming the previous studies in rock cutting and mechanical excavation. Therefore, it was recommended to employ easy-to-use index tests of NCB cone indenter and Shore scleroscope in the estimation of laboratory SE of sandstones ranging from very low to high strengths in the absence of a rock cutting rig to measure it until the easy-to-use universal measures of the rock brittleness and especially the rock fracture toughness, being an intrinsic rock property, are developed.

Precision-recall operating characteristic (P-ROC) curves in imprecise environments

Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this paper, we consider the case of imprecise environments, where little may be known about these factors and they may well vary significantly when the system is applied. Specifically, the use of precision-recall analysis is investigated and compared to the more well known performance measures such as error-rate and the receiver operating characteristic (ROC). We argue that while ROC analysis is invariant to variations in class priors, this invariance in fact hides an important factor of the evaluation in imprecise environments. Therefore, we develop a generalised precision-recall analysis methodology in which variation due to prior class probabilities is incorporated into a multi-way analysis of variance (ANOVA). The increased sensitivity and reliability of this approach is demonstrated in a remote sensing application.

Analysis of Melanoma Onset: Assessing Familial Aggregation by Using Estimating Equations and Fitting Variance Components via Bayesian Random Effects Models

We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.

Genetic influence on the variance in P3 amplitude and latency

The P3(00) event-related potential (ERP) component is widely used as a measure of cognitive functioning and provides a sensitive electrophysiological index of the attentional and working memory demands of a task. This study investigated what proportion of the variance in the amplitude and latency of the P3, elicited in a delayed response working memory task, could be attributed to genetic factors. In 335 adolescent twin pairs and 48 siblings, the amplitude and latency of the P3 were examined at frontal, central, and parietal sites. Additive genetic factors accounted for 48% to 61% of the variance in P3 amplitude. Approximately one-third of the genetic variation at frontal sites was mediated by a common genetic factor that also influenced the genetic variation at parietal and central sites. Familial resemblance in P3 latency was due to genetic influence that accounted for 44% to 50% of the variance. Genetic covariance in P3 latency across sites was substantial, with a large part of the variance found at parietal, central, and frontal sites attributed to a common genetic factor. The findings provide further evidence that the P3 is a promising phenotype of neural activity of the brain and has the potential to be used in linkage and association analysis in the search for quantitative trait loci (QTLs) influencing cognition.

Some vocabulary and grammar for the analysis of multi-environment trials, as applied to the analysis of FPB and PPB trials

For the improvement of genetic material suitable for on farm use under low-input conditions, participatory and formal plant breeding strategies are frequently presented as competing options. A common frame of reference to phrase mechanisms and purposes related to breeding strategies will facilitate clearer descriptions of similarities and differences between participatory plant breeding and formal plant breeding. In this paper an attempt is made to develop such a common framework by means of a statistically inspired language that acknowledges the importance of both on farm trials and research centre trials as sources of information for on farm genetic improvement. Key concepts are the genetic correlation between environments, and the heterogeneity of phenotypic and genetic variance over environments. Classic selection response theory is taken as the starting point for the comparison of selection trials (on farm and research centre) with respect to the expected genetic improvement in a target environment (low-input farms). The variance-covariance parameters that form the input for selection response comparisons traditionally come from a mixed model fit to multi-environment trial data. In this paper we propose a recently developed class of mixed models, namely multiplicative mixed models, also called factor-analytic models, for modelling genetic variances and covariances (correlations). Mixed multiplicative models allow genetic variances and covariances to be dependent on quantitative descriptors of the environment, and confer a high flexibility in the choice of variance-covariance structure, without requiring the estimation of a prohibitively high number of parameters. As a result detailed considerations regarding selection response comparisons are facilitated. ne statistical machinery involved is illustrated on an example data set consisting of barley trials from the International Center for Agricultural Research in the Dry Areas (ICARDA). Analysis of the example data showed that participatory plant breeding and formal plant breeding are better interpreted as providing complementary rather than competing information.

Comparative analysis of genetic diversity in the mangrove species Avicennia marina (Forsk.) Vierh. (Avicenniaceae) detected by AFLPs and SSRs

Avicennia marina is an important mangrove species with a wide geographical and climatic distribution which suggests that large amounts of genetic diversity are available for conservation and breeding programs. In this study we compare the informativeness of AFLPs and SSRs for assessing genetic diversity within and among individuals, populations and subspecies of A. marina in Australia. Our comparison utilized three SSR loci and three AFLP primer sets that were known to be polymorphic, and could be run in a single analysis on a capillary electrophoresis system, using different-colored fluorescent dyes. A total of 120 individuals representing six populations and three subspecies were samplcd. At the locus level, SSRs were considerably more variable than AFLPs, with a total of 52 alleles and an average heterozygosity of 0.78. Average heterozygosity for AFLPs was 0.193, but all of the 918 bands scored were polymorphic. Thus, AFLPs were considerably more efficient at revealing polymorphic loci than SSRs despite lower average heterozygosities. SSRs detected more genetic differentiation between populations (19 vs 9%) and subspecies (35 vs 11%) than AFLPs. Principal co-ordinate analysis revealed congruent patterns of genetic relationships at the individual, population and subspecific levels for both data sets. Mantel testing confirmed congruence between AFLP and SSR genetic distances among, but not within, population comparisons, indicating that the markers were segregating inde- pendently but that evolutionary groups (populations and subspecies) were similar. Three genetic criteria of importance for defining priorities for ex situ collections or in situ conservation programs (number of alleles, number of locally common alleles and number of private alleles) were correlated between the AFLP and SSR data sets. The congruence between AFLP and SSR data sets suggest that either method, or a combination, is applicable to expanded genetic studies of mangroves. The codominant nature of SSRs makes them ideal for further population-based investigations, such as mating-system analyses, for which the dominant AFLP markers are less well suited. AFLPs may be particularly useful for monitoring propagation programs and identifying duplicates within collections, since a single PCR assay can reveal many loci at once.

Levene tests of homogeneity of variance for general block and treatment designs

This article develops a weighted least squares version of Levene's test of homogeneity of variance for a general design, available both for univariate and multivariate situations. When the design is balanced, the univariate and two common multivariate test statistics turn out to be proportional to the corresponding ordinary least squares test statistics obtained from an analysis of variance of the absolute values of the standardized mean-based residuals from the original analysis of the data. The constant of proportionality is simply a design-dependent multiplier (which does not necessarily tend to unity). Explicit results are presented for randomized block and Latin square designs and are illustrated for factorial treatment designs and split-plot experiments. The distribution of the univariate test statistic is close to a standard F-distribution, although it can be slightly underdispersed. For a complex design, the test assesses homogeneity of variance across blocks, treatments, or treatment factors and offers an objective interpretation of residual plot.

Reflections on the statistical analysis of personality and norms in war, peace, and prejudice: Are deviant minorities the problem?

The compelling quality of the Global Change simulation study (Altemeyer, 2003), in which high RWA (right-wing authoritarianism)/high SDO (social dominance orientation) individuals produced poor outcomes for the planet, rests on the inference that the link between high RWA/SDO scores and disaster in the simulation can be generalized to real environmental and social situations. However, we argue that studies of the Person × Situation interaction are biased to overestimate the role of the individual variability. When variables are operationalized, strongly normative items are excluded because they are skewed and kurtotic. This occurs both in the measurement of predictor constructs, such as RWA, and in the outcome constructs, such as prejudice and war. Analyses of normal linear statistics highlight personality variables such as RWA, which produce variance, and overlook the role of norms, which produce invariance. Where both normative and personality forces are operating, as in intergroup contexts, the linear analysis generates statistics for the sample that disproportionately reflect the behavior of the deviant, antinormative minority and direct attention away from the baseline, normative position. The implications of these findings for the link between high RWA and disaster are discussed.

Cosegregation analysis of natriuretic peptide genes and blood pressure in the spontaneously hypertensive rat

1. The natriuretic peptide precursor A (Nppa) and B (Nppb) genes are candidate genes for hypertension and cardiac hypertrophy in the spontaneously hypertensive rat (SHR). The purpose of the present study was to determine the role of the Nppa and Nppb genes in the development of hypertension in the SHR. 2. A cohort (n = 162) of F2 segregating intercross animals was established between strains of hypertensive SHR and normotensive Wistar-Kyoto rats. Blood pressure and heart weight were measured in each rat at 12-16 weeks of age. Rats were genotyped using 11 informative microsatellite markers, distributed in the vicinity of the Nppa marker on rat chromosome 5 including an Nppb marker. The phenotype values were compared with genotype using the computer package MAP-MAKER 3.0 (Whitehead Institute, Boston, MA, USA) to determine whether there was a link between the genetic variants of the natriuretic peptide family and blood pressure or cardiac hypertrophy. 3. A strong correlation was observed between the Nppa marker and blood pressure. A quantitative trait locus (QTL) for blood pressure on chromosome 5 was identified between the Nppa locus and the D5Mgh15 marker, less than 2 cM from the Nppa locus. The linkage score for the blood pressure QTL on chromosome 5 was 3.8 and the QTL accounted for 43% of the total variance of systolic blood pressure, 54% of diastolic blood pressure and 59% of mean blood pressure. No association was found between the Nppb gene and blood pressure. This is the first report of linkage between the Nppa marker and blood pressure in the rat. There was no correlation between the Nppa or Nppb genes or other markers in this region and either heart weight or left ventricular weight in F2 rats. 4. These findings suggest the existence of a blood pressure-dependent Nppa marker variant or a gene close to Nppa predisposing to spontaneous hypertension in the rat. It provides a strong foundation for further detailed genetic studies in congenic strains, which may help to narrow down the location of this gene and lead to positional cloning.

Multivariate QTL linkage analysis suggests a QTL for platelet count on chromosome 19q

Platelet count is a highly heritable trait with genetic factors responsible for around 80% of the phenotypic variance. We measured platelet count longitudinally in 327 monozygotic and 418 dizygotic twin pairs at 12, 14 and 16 years of age. We also performed a genome-wide linkage scan of these twins and their families in an attempt to localize QTLs that influenced variation in platelet concentrations. Suggestive linkage was observed on chromosome 19q13.13-19q13.31 at 12 (LOD=2.12, P=0.0009), 14 (LOD=2.23, P=0.0007) and 16 (LOD=1.01, P=0.016) years of age and multivariate analysis of counts at all three ages increased the LOD to 2.59 (P=0.0003). A possible candidate in this region is the gene for glycoprotein VI, a receptor involved in platelet aggregation. Smaller linkage peaks were also seen at 2p, 5p, 5q, 10p and 15q. There was little evidence for linkage to the chromosomal regions containing the genes for thrombopoietin (3q27) and the thrombopoietin receptor (1q34), suggesting that polymorphisms in these genes do not contribute substantially to variation in platelet count between healthy individuals.

Proteomic analysis of k-casein micro-heterogeneity

The proteome of bovine milk is dominated by just six gene products that constitute approximately 95% of milk protein. Nonetheless, over 150 protein spots can be readily detected following two-dimensional electrophoresis of whole milk. Many of these represent isoforms of the major gene products produced through extensive posttranslational modification. Peptide mass fingerprinting of in-gel tryptic digests (using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) in reflectron mode with alpha-cyano-4-hydroxycinnamic acid as the matrix) identified 10 forms of K-casein with isoelectric point (pl) values from 4.47 to 5.81, but could not distinguish between them. MALDI-TOF MS in linear mode, using sinapinic acid as the matrix, revealed a large tryptic peptide (mass > 5990 Da) derived from the C-terminus that contained all the known sites of genetic variance, phosphorylation and glycosylation. Two genetic variants present as singly or doubly phosphorylated forms could be distinguished using mass data alone. Glycoforms containing a single acidic tetrasaccharide were also identified. The differences in electrophoretic mobility of these isoforms were consistent with the addition of the acidic groups. While more extensively glycosylated forms were also observed, substantial loss of N-acetylneuraminic acid from the glycosyl group was evident in the MALDI spectra such that ions corresponding to the intact glycopeptide were not observed and assignment of the glycoforms was not possible. However, by analysing the pl shifts observed on the two-dimensional gels in conjunction with the MS data, the number of N-acetylneuraminic acid residues, and hence the glycoforms present, could be determined.

Population effects on individual systolic blood pressure: A multilevel analysis of the World Health Organization MONICA project

Individuals from the same population share a number of contextual circumstances that may condition a common level of blood pressure over and above individual characteristics. Understanding this population effect is relevant for both etiologic research and prevention strategies. Using multilevel regression analyses, the authors quantified the extent to which individual differences in systolic blood pressure (SBP) could be attributed to the population level. They also investigated possible cross-level interactions between the population in which a person lived and pharmacological (antihypertensive medication) and nonpharmacological (body mass index) effects on individual SBP. They analyzed data on 23,796 men and 24,986 women aged 35-64 years from 39 worldwide Monitoring of Trends and Determinants in Cardiovascular Disease (MONICA) study populations participating in the final survey of this World Health Organization project (1989-1997). SBP was positively associated with low educational achievement, high body mass index, and use of antihypertensive medication and, for women, was negatively associated with smoking. About 7-8% of all SBP differences between subjects were attributed to the population level. However, this population effect was particularly strong (i.e., 20%) in antihypertensive medication users and overweight women. This empirical evidence of a population effect on individual SBP emphasizes the importance of developing population-wide strategies to reduce individual risk of hypertension.

Genetic time-series analysis identifies a major QTL for in vivo alcohol metabolism not predicted by in vitro studies of structural protein polymorphism at the ADH1B or ADH1C loci

After ingestion of a standardized dose of ethanol, alcohol concentrations were assessed, over 3.5 hours from blood (six readings) and breath (10 readings) in a sample of 412 MZ and DZ twins who took part in an Alcohol Challenge Twin Study (ACTS). Nearly all participants were subsequently genotyped on two polymorphic SNPs in the ADH1B and ADH1C loci known to affect in vitro ADH activity. In the DZ pairs, 14 microsatellite markers covering a 20.5 cM region on chromosome 4 that includes the ADH gene family were assessed, Variation in the timed series of autocorrelated blood and breath alcohol readings was studied using a bivariate simplex design. The contribution of a quantitative trait locus (QTL) or QTL's linked to the ADH region was estimated via a mixture of likelihoods weighted by identity-by-descent probabilities. The effects of allelic substitution at the ADH1B and ADH1C loci were estimated in the means part of the model simultaneously with the effects sex and age. There was a major contribution to variance in alcohol metabolism due to a QTL which accounted for about 64% of the additive genetic covariation common to both blood and breath alcohol readings at the first time point. No effects of the ADH1B*47His or ADH1C*349Ile alleles on in vivo metabolism were observed, although these have been shown to have major effects in vitro. This implies that there is a major determinant of variation for in vivo alcohol metabolism in the ADH region that is not accounted for by these polymorphisms. Earlier analyses of these data suggested that alcohol metabolism is related to drinking behavior and imply that this QTL may be protective against alcohol dependence.

Repeated occurrence of basal cell carcinoma of the skin and multifailure survival analysis: Follow-up data from the nambour skin cancer prevention trial

The aim of this study was to apply multifailure survival methods to analyze time to multiple occurrences of basal cell carcinoma (BCC). Data from 4.5 years of follow-up in a randomized controlled trial, the Nambour Skin Cancer Prevention Trial (1992-1996), to evaluate skin cancer prevention were used to assess the influence of sunscreen application on the time to first BCC and the time to subsequent BCCs. Three different approaches of time to ordered multiple events were applied and compared: the Andersen-Gill, Wei-Lin-Weissfeld, and Prentice-Williams-Peterson models. Robust variance estimation approaches were used for all multifailure survival models. Sunscreen treatment was not associated with time to first occurrence of a BCC (hazard ratio = 1.04, 95% confidence interval: 0.79, 1.45). Time to subsequent BCC tumors using the Andersen-Gill model resulted in a lower estimated hazard among the daily sunscreen application group, although statistical significance was not reached (hazard ratio = 0.82, 95% confidence interval: 0.59, 1.15). Similarly, both the Wei-Lin-Weissfeld marginal-hazards and the Prentice-Williams-Peterson gap-time models revealed trends toward a lower risk of subsequent BCC tumors among the sunscreen intervention group. These results demonstrate the importance of conducting multiple-event analysis for recurring events, as risk factors for a single event may differ from those where repeated events are considered.