Measurement of narcotic potency using houseflies

A method is described for the measurement of narcotic potencies of chemical compounds, using houseflies. Narcotic potency measurements give rise to statistical problems which differ from those encountered in toxicity determinations in so far as the narcotic process is reversible, and successive values of the number of affected insects in a group subjected to the test do not normally increase monotonically and in some case considerable oscillation occurs. An earlier method (Bradbury & Armstrong, 1954) used probit analysis, but it is now shown that this treatment and also regression analysis both fail to provide a valid method of dealing with variability in this type of test. A test based on the response of two flies, one male and one female per flask, is now described. The test, based on sixteen flies per compound, gave figures for: α₀, the partial saturation of the test compound giving the same average knock-down time as chloroform at a partial saturation of 0.005; α₁, the partial saturation of the test compound giving knock-down in I hr.; b, the slope of the straight line relating log. knock-down time to log. partial saturation; s, the residual standard deviation of log. knock-down time about its regression line on log. partial saturation. From these values the 95% confidence limits for the slope and for the values of α₀ were calculated. The test also provided information on the convulsive action of compounds and a modification of it was used to determine knock-down times of very potent narcotics at high dosages. Results are presented for fifty-seven halogenated hydrocarbons and the hypothesis that variations in potency between narcotics are determined mainly by rates of diffusion is examined. The results do not support this hypothesis. Narcotic and convulsant potencies measured by the method described are a useful guide to the behaviour of compounds in mouse tests.     

Inference of positive and negative selection on the 5' regulatory regions of Drosophila genes

Both positive selection and negative selection have been shown to drive the evolution of coding regions. It is of interest to know if the corresponding 5' regions of genes may be subjected to selection of comparable intensities. For such a comparison, we chose the Accessory gland protein (Acp) genes as our test case. About 700 bp and 600 bp for the 5' and coding regions, respectively, of eight previously unstudied genes were sequenced from 21 isogenic lines of D. melanogaster and one line from D. simulans. The ratio of divergence at the amino-acid replacement sites (A) over that at the synonymous sites (S) was twice the ratio for common polymorphism. Interestingly, the 5' region shows the same trend, with the 5'/S divergence ratio being 1.8 times higher than the 5'/S ratio for common polymorphism. There are several possible explanations for the 5'/S ratios, including demography, negative selection, and positive selection. Under normal conditions, positive selection is the most likely explanation. If that is true, about 45 to 50 percent of all fixed differences at both the replacement and 5' sites were adaptive, even though the substitution rate in the former is only half that of the latter (K(A)/K(S) approximately 0.3 vs. K(5')/K(S) approximately 0.6). As previous analyses have indicated, the inclusion of slightly deleterious polymorphism confounds the inference of positive selection. The analysis of published polymorphism data covering 97 verified 5' regions of Drosophila suggests more pronounced selective constraint on the 5' untranslated region and the core promoter (together corresponding to approximately 200 bp in this data set) when compared to the more distal portion of the 5' region of genes.     

Quantitative trait loci mapping of resistance to Laodelphax striatellus (Homoptera: Delphacidae) in rice using recombinant inbred lines

Laodelphax striatellus Fallén (Homoptera: Delphacidae), is a serious pest in rice, Oryza sativa L., production. A mapping population consisting of 81 recombinant inbred lines (RILs), derived from a cross between japonica' Kinmaze' and indica' DV85' rice, was used to detect quantitative trait loci (QTLs) for the resistance to L. striatellus. Seedbox screening test (SST), antixenosis test, and antibiosis test were used to evaluate the resistance response of the two parents and 81 RILs to L. striatellus at the seedling stage, and composite interval mapping was used for QTL analysis. When the resistance was measured by SST method, two QTLs conferring resistance to L. striatellus were mapped on chromosome 11, namely, Qsbph11a and Qsbph11b, with log of odds scores 2.51 and 4.38, respectively. The two QTLs explained 16.62 and 27.78% of the phenotypic variance in this population, respectively. In total, three QTLs controlling antixenosis against L. striatellus were detected on chromosomes 3, 4, and 11, respectively, accounting for 37.5% of the total phenotypic variance. Two QTLs expressing antibiosis to L. striatellus were mapped on chromosomes 3 and 11, respectively, explaining 25.9% of the total phenotypic variance. The identified QTL located between markers XNpb202 and C1172 on chromosome 11 was detected repeatedly by three different screening methods; therefore, it may be important to confer the resistance to L. striatellus. Once confirmed in other mapping populations, these QTLs should be useful in breeding for resistance to L. striatellus by marker-assisted selection of different resistance genes in rice varieties.     

Maize and oat antixenosis and antibiosis against Delphacodes kuscheli (Homoptera: Delphacidae), vector of "Mal de Rio Cuarto" of maize in Argentina

"Mal de Rio Cuarto" (MRC) is the most important virus disease of maize, Zea mays L., in Argentina. Several maize lines show different levels of resistance to MRC in the field; however, no studies have been conducted to investigate resistance mechanisms against its insect vector, Delphacodes kuscheli Fennah (Homoptera: Delphacidae). Oat, Avena spp., is the main overwintering host of D. kuscheli and main source of populations that infest maize. Although oat varieties resistant to the greenbug, Schizaphis graminum (Rondani) (Homoptera: Aphididae) are commercially available, their effect on D. kuscheli is unknown. We conducted laboratory experiments to test for the presence of antixenosis and antibiosis resistance mechanisms on six maize lines with different levels of field resistance to MRC, and seven commercial oat cultivars that include two S. graminum-resistant varieties. We did not find antibiotic effects of maize lines on D. kuscheli longevity and survivorship patterns, but we obtained antixenotic effects from the LP2 line (field moderate) due to reduced settling preference and feeding. Oat 'Bonaerense Payé and 'Suregrain INTA' showed both antixenosis and antibiosis, with significantly less settling preference, oviposition in the no-choice test, and reduced total fecundity in comparison with the other varieties studied. The S. graminum-resistant 'Boyera F. A.' and 'Tambera F. A.' did not showed a consistent pattern of resistance versus D. kuscheli across all experiments. Our results indicate the presence of potential sources of insect resistance in the maize lines and oat cultivars tested that may be used in MRC integrated pest management programs.     

Parameter estimation and goodness-of-fit in log binomial regression

An estimate of the risk, adjusted for confounders, can be obtained from a fitted logistic regression model, but it substantially over-estimates when the outcome is not rare. The log binomial model, binomial errors and log link, is increasingly being used for this purpose. However this model's performance, goodness of fit tests and case-wise diagnostics have not been studied. Extensive simulations are used to compare the performance of the log binomial, a logistic regression based method proposed by Schouten et al. (1993) and a Poisson regression approach proposed by Zou (2004) and Carter, Lipsitz, and Tilley (2005). Log binomial regression resulted in "failure" rates (non-convergence, out-of-bounds predicted probabilities) as high as 59%. Estimates by the method of Schouten et al. (1993) produced fitted log binomial probabilities greater than unity in up to 19% of samples to which a log binomial model had been successfully fit and in up to 78% of samples when the log binomial model fit failed. Similar percentages were observed for the Poisson regression approach. Coefficient and standard error estimates from the three models were similar. Rejection rates for goodness of fit tests for log binomial fit were around 5%. Power of goodness of fit tests was modest when an incorrect logistic regression model was fit. Examples demonstrate the use of the methods. Uncritical use of the log binomial regression model is not recommended.     

Natural Selection with Nuclear and Cytoplasmic Transmission. III. Joint Analysis of Segregation and Mtdna in Drosophila Melanogaster

Despite the widespread use of mitochondrial DNA by evolutionary geneticists, relatively little effort has been spent assessing the magnitude of forces maintaining mtDNA sequence diversity. In this study the influence of cytoplasmic variation on viability in Drosophila was examined by analysis of second chromosome segregation. A factorial experiment with balancer chromosomes permitted the effects of cytoplasma and reciprocal crosses to be individually distinguished. The first test used six lines of diverse geographic origin, testing the segregation of all six second chromosomes in all six cytoplasms. The second and third tests were also factorial designs, but used flies from one population in central Pennsylvania. The fourth test was a large chain cross, using 28 lines from the same Pennsylvania population. Only the first test detected a significant nuclear-cytoplasmic effect. Restriction site variation in the mtDNA of all of these lines was assayed by Southern blotting, and statistical tests were performed in an effort to detect an influence of mtDNA type on fitness components. Posterior linear contrasts revealed an effect of mtDNA on segregation only among lines of diverse geographic origin. Within a population, no such influence was detected, even though the experiment was sufficiently large to have revealed statistical significance of a 0.5% segregation difference with a 57% probability.     

A simple method to fit geometric series and broken stick models in community ecology and island biogeography

Species abundance distributions are widely used in explaining natural communities, their natural evolution and the impacts of environmental disturbance. A commonly used approach is that of rank-abundance distributions. Favored, biologically founded models are the geometric series (GS) and the broken stick (BS) model. Comparing observed abundance distributions with those predicted by models is an extremely time-consuming task. Also, using goodness-of-fit tests for frequency distributions (like Chi-square or Kolmogorov–Smirnov tests) to compare observed with expected frequencies is problematic because the best way to calculate expected frequencies may be controversial. More important, the Chi-square test may prove if an observed distribution statistically differs from a model, but does not allow the investigator to choose among competing models from which the observed distribution does not differ. Both models can be easily tested by regression analysis. In GS, if a log scale is used for abundance, the species exactly fall along a straight line. The BS distribution shows up as nearly linear when a log scale is used for the rank axis. Regression analysis is proposed here as a simpler and more efficient method to fit the GS and BS models. Also, regression analysis (1) does not suffer from assumptions related to Chi-square tests; (2) obviates the need to establish expected frequencies, and (3) offers the possibility to choose the best fit among competing models. A possible extension of abundance-rank analysis to species richness on islands is also proposed as a method to discriminate between relict and equilibrial models. Examples of application to field data are also presented.     

A simple method to fit geometric series and broken stick models in community ecology and island biogeography

Species abundance distributions are widely used in explaining natural communities, their natural evolution and the impacts of environmental disturbance. A commonly used approach is that of rank-abundance distributions. Favored, biologically founded models are the geometric series (GS) and the broken stick (BS) model. Comparing observed abundance distributions with those predicted by models is an extremely time-consuming task. Also, using goodness-of-fit tests for frequency distributions (like Chi-square or Kolmogorov–Smirnov tests) to compare observed with expected frequencies is problematic because the best way to calculate expected frequencies may be controversial. More important, the Chi-square test may prove if an observed distribution statistically differs from a model, but does not allow the investigator to choose among competing models from which the observed distribution does not differ. Both models can be easily tested by regression analysis. In GS, if a log scale is used for abundance, the species exactly fall along a straight line. The BS distribution shows up as nearly linear when a log scale is used for the rank axis. Regression analysis is proposed here as a simpler and more efficient method to fit the GS and BS models. Also, regression analysis (1) does not suffer from assumptions related to Chi-square tests; (2) obviates the need to establish expected frequencies, and (3) offers the possibility to choose the best fit among competing models. A possible extension of abundance-rank analysis to species richness on islands is also proposed as a method to discriminate between relict and equilibrial models. Examples of application to field data are also presented.     

DNA sequence variation at a duplicated gene: excess of replacement polymorphism and extensive haplotype structure in the Drosophila melanogaster bicoid region

The bicoid (bcd) gene of Drosophila has played an important role in understanding the system of developmental regulatory genes that controls segmentation in the fruit fly. Several studies in Drosophila and closely related insects suggest that bcd may be the result of a gene duplication in the Dipteran lineage. In addition, the presence of a large, conserved secondary structure in the 3' untranslated region (UTR) makes the bcd gene a good candidate for studying compensatory evolution and the relationship between RNA secondary structure and patterns of standing variation in natural populations. Despite these interesting aspects, a population-level analysis has until now not been performed on bcd. In this study, DNA sequence variation was examined for a 4-kb region of the bcd gene, including a portion of the 5' UTR, the entire coding region, and the 3' UTR, for 25 Drosophila melanogaster isofemale lines from Zimbabwe and one allele from D. simulans. Statistical tests revealed a significant excess of replacement polymorphisms in the D. melanogaster lineage that are clustered in two putative linker regions of the Bicoid protein. This result is consistent with a relaxation of selective constraints in these regions. In addition, we found a distinct haplotype structure and a significantly smaller number of haplotypes than predicted by the standard neutral model. It is unlikely that the haplotype structure is maintained by epistatic selection acting on the secondary structure in the 3' UTR or by the association of the bcd gene with polymorphic inversions. Instead, our two main observations, namely the occurrence of a haplotype structure and the excess of replacement polymorphisms, may indicate that the selective history of this gene is rather complex, involving both the relaxation of purifying selection in some parts of the protein and the action of positive selection in other parts of the gene region.     

Doubly robust tests of exposure effects under high-dimensional confounding

After variable selection, standard inferential procedures for regression parameters may not be uniformly valid; there is no finite-sample size at which a standard test is guaranteed to approximately attain its nominal size. This problem is exacerbated in high-dimensional settings, where variable selection becomes unavoidable. This has prompted a flurry of activity in developing uniformly valid hypothesis tests for a low-dimensional regression parameter (eg, the causal effect of an exposure A on an outcome Y) in high-dimensional models. So far there has been limited focus on model misspecification, although this is inevitable in high-dimensional settings. We propose tests of the null that are uniformly valid under sparsity conditions weaker than those typically invoked in the literature, assuming working models for the exposure and outcome are both correctly specified. When one of the models is misspecified, by amending the procedure for estimating the nuisance parameters, our tests continue to be valid; hence, they are doubly robust. Our proposals are straightforward to implement using existing software for penalized maximum likelihood estimation and do not require sample splitting. We illustrate them in simulations and an analysis of data obtained from the Ghent University intensive care unit.     

Cloned human interferons alpha: differential affinities for polyinosinic acid and relationship between molecular structure and species specificity

The HuIFN-alpha A and HuIFN-alpha D interferons, produced by two independent recombinant bacterial clones, have different affinities for polyinosinic acid (poly I). The monomeric form HuIFN-alpha A (FMM), but not the HuIFN-alpha D, binds to poly (I)-agarose and is protected by poly (I) from thermal inactivation. Other subtypes of HuIFN-alpha A including the monomer SMM and oligomers have no affinity for this polynucleotide. In addition, these interferons show different target cell preferences in agreement with our previous suggestion (23) that the polynucleotide binding domain may be responsible for species specificity. Two significant observations are 1) the fractions of HuIFN-alpha D and HuIFN-alpha A unbound on poly (I)-agarose show higher antiviral inducing activity on heterologous (MDBK) than on homologous (WISH) cells, whereas they induce about the same activity of 2'5' oligoadenylate synthetase in these two cell lines. These fractions are also active on L929 cells. 2) The bound fraction of HuIFN-alpha A induces almost the same antiviral and 2'5' oligoadenylate synthetase activities in MDBK and in WISH cells but neither activity in L929 cells.     

A note on the application of diallel crosses for the analysis of genetic variation in natural populations

Summary The complete diallel cross among homozygous lines can be a useful tool to analyze the genetic architecture of natural populations. However, it represents the natural population only approximately, in particular if the number of lines is small and the analyzed traits exhibit inbreeding depression or other forms of directional dominance. Some incorrect expected mean squares that can be found in the literature suggest tests for genetic variance components that can be misleading under such circumstances. Expected mean squares for a factorial analysis and for a modified Hayman analysis are presented and the effect of the number of lines and directional dominance is discussed.     

Hatch rate of laying hen strains provided a photoperiod during incubation

Implementing a photoperiod during incubation has been shown to be a potential next step to removing one more stressor for newly hatched poultry species. The distribution of hatch over time is a parameter that may be influenced by photoperiod that could benefit from a photoperiod but has not been studied at this time and is the objective of this paper. The impact on hatch rate for three strains of chicken, Barred Plymouth Rock (BR), Lohmann Brown (LB) and Lohmann Lite (LL), was measured following the provision of a 12L : 12D (12 h light : 12 h dark) photoperiod starting at 0, 9 or 17 days of incubation and compared with incubation in the dark. The cumulative number of chicks hatched eggs at four points in time (489, 498, 507 and 516 h of incubation) was analysed using repeated measures analysis in a 3 × 4 factorial arrangement of treatments. Repeated measures analysis was done to determine the main and interaction effects of photoperiod and bird strain, and a regression analysis was used to determine how these effects evolved over time. Lohmann Brown embryos provided a 12L : 12D photoperiod throughout incubation were first to reach 50% of total chicks hatched and rate of hatch from 50% to 75% of total chicks hatched as well. As the LB chicks did not begin to hatch earlier or finish later, the LB strain was the most synchronised when provided a 12L : 12D photoperiod from the beginning of incubation. Similar results were found for LL, but no difference on the percentage hatched over time was found when provided the 12L : 12D photoperiod at the beginning of incubation or at day 9. The BR strain only showed a significant difference in hatch window synchronisation when provided a 12L : 12D photoperiod at day 9 of incubation. These results indicate that the strain of chicken impacts the hatch window, and each strain responds to a photoperiod during incubation differently. This information could be useful for hatchery managers to deal with different strains of chicken for incubation.     

Identification of Dopamine "D3'' and "D4'' Binding Sites, Labelled with [3H]2-Amino-6,7-Dihydroxy- 1,2,3,4- Tetrahydronaphthalene, as High Agonist Affinity States of the D1 and D2 Dopamine Receptors, Respectively

On the basis of affinity differences for spiperone, two binding sites for [3H](+/-)-2-amino-6,7-dihydroxy-1,2,3,4-tetrahydronaphthalene ([3H]ADTN) in the rat brain could be distinguished: "D3" with a low and "D4" with a high affinity for spiperone. Evidence is provided that D3 and D4 sites are related to high agonist affinity states of the D1 and D2 dopamine receptors, respectively. Various well-known selective D1 and D2 agonists and antagonists showed potencies at these sites in agreement with this hypothesis. A comparison of the Bmax values for [3H]ADTN binding to D3 and D4 sites with the numbers of D1 receptors (labelled by [3H]SCH 23390) and of D2 receptors (labelled by [3H]spiperone), both in the striatum and in the mesolimbic system, indicated that under the conditions used for 3H-agonist binding experiments, both populations of D1 and D2 receptors were converted to their high agonist affinity states to a considerable, although different extent. In fact, when competition experiments with [3H]spiperone were performed under the conditions otherwise used for [3H]ADTN binding experiments (instead of the conditions usually used for antagonist binding), substantial shifts of the displacement curves of 3,4-dihydroxyphenylethylamine (dopamine) and ADTN toward higher affinities were observed. A comparison of the effects of various agonists and antagonists in the [3H]ADTN binding experiments and in functional tests revealed a significant correlation between their potencies at D4 binding sites and at D2 receptors modulating the release of [3H]acetylcholine from striatal slices. However, in the situation of the D1/D3 pair, when the measurement of adenylate cyclase activity was taken as a functional test for D1 receptors, agonists were more active in the binding than in the functional test, whereas for many antagonists the opposite was found. The results are discussed with regard to the classification and functional aspects of brain dopamine receptors.     

Behavioural evaluation of methods for assessing fear responses in weaned pigs

Models of anxiety and fear of novelty were evaluated using correlations and principal component analysis. A total of 84 pigs (LandracexYorkshire) from nine different litters were subjected to a tonic immobility (TI) test at the age of 2.5 weeks, an elevated plus-maze (EPM) at the age of 6 weeks, a light/dark (L/D) exploration test at the age of 7 weeks and an open-field (OF) test at the age of 8 weeks.The first component from the principal component analysis had the highest correlation with number of entries into open arms in the EPM but was also highly correlated to variables from the other three tests confirming a common aversion-related element in the four experimental tests. The second component was negatively correlated with percent entries into and time spent on open arms in the EPM, but positively correlated with the number of entries into closed arms in the same test, number of lines crossed in the OF and time spent in the lit compartment of the L/D test. The last point illustrates a negative relationship between "anxiety" and "activity" in the EPM and OF. To achieve purer measures of fear of novelty and activity in the tests, the components were rotated using the Varimax criterion. The rotated factor pattern demonstrated a simple structure where variables related to "anxiety" or "fear of novelty" (i.e., percent entries into open arms and time spent on open arms of the EPM) had the highest loading on factor 1, whereas variables related to activity (i.e., number of entries into the closed arms in the EPM, number of lines crossed in the OF and time spent in the lit compartment of the L/D test) had the highest loading on factor 2. TI duration loaded more strongly on factor 1 ("fear of novelty") than on factor 2 ("activity"), but did not represent any pure measure of either fear of novelty or activity.In conclusion, all of the test variables were related to one another. Open-arm avoidance represented the purest measure of fear of novelty, whereas entries into closed arms and number of lines crossed in the OF were the purest measures of activity. The EPM appeared to provide the best way to separate the fear of novelty and activity-related elements, indicating that the EPM may be a useful behavioural model of fear of novelty or avoidance in pigs.     

Point and Interval Estimation in the Combination of Bioassay Results with Unequal Variances

Symmetric parallel‐line biological assays involve the estimation of (log) relative potencies. The class of p(≥ 2) combination of symmetric parallel line bioassays are considered in this study. A large sample test for the equality of the several potencies is developed. An estimator and a confidence interval are proposed for the common relative potency parameter. The asymptotic distribution of the proposed test‐statistic under the null hypothesis as well as under a contagious hypothesis is derived.     

Resistance to barley scald (Rhynchosporium secalis) in the Ethiopian donor lines 'Steudelli' and 'Jet', analyzed by partial least squares regression and interval mapping

The resistance of barley (Hordeum vulgare L.) to Rhynchosporium secalis (scald) has been investigated in two crosses between the susceptible cv. 'Ingrid' and two resistant Ethiopian landraces, 'Steudelli' and 'Jet'. Doubled haploids were inoculated in replicated tests using two isolates of R. secalis, '4004' and 'WRS1872'. Expression of resistance differed widely between replicated tests. AFLP, SSR and RFLP markers were used to develop chromosome maps. Results have been analysed using partial least squares regression (PLSR) and interval mapping. In PLSR the major covariance structures or 'latent variables' between X (markers) and Y (isolates, tests) are modelled as principal components and their optimal number determined by cross-validation. In 'Steudelli' two QTL were detected, one on each of chromosomes 3H and 7H, in 4 out of 5 tests, while in 'Jet' only one (different) allele at the 3H locus was found. The validated R(2) varied between 11.0% and 64.9% in the replicated tests with '4004'.With isolate 'WRS1872' the 7H locus and another 3H locus were detected. By interval mapping the QTL detected were less stable and generally gave lower R(2) values than PLSR. PLSR does not depend on maps, but interval mapping based on values predicted by PLSR had R(2) around 90%. It is suggested that PLSR may be a useful tool in QTL analysis.     

A Monte Carlo study of tests on data originating from quadrat sampling. I: Data from a Poisson distribution

Computer simulations are used to examine the significance levels and powers of several tests which have been employed to compare the means of Poisson distributions. In particular, attention is focused on the behaviour of the tests when the means are small, as is often the case in ecological studies when populations of organisms are sampled using quadrats. Two approaches to testing are considered. The first assumes a log linear model for the Poisson data and leads to tests based on the deviance. The second employs standard analysis of variance tests following data transformations, including the often used logarithmic and square root transformations. For very small means it is found that a deviance-based test has the most favourable characteristics, generally outperforming analysis of variance tests on transformed data; none of the latter appears consistently better than any other. For larger means the standard analysis of variance on untransformed data performs well.