Depositional environments for strata cored in CRP-3 (Cape Roberts Project), Victoria Land Basin, Antarctica: palaeoglaciological and palaeoclimatological inferences

Cape Roberts Project drill core 3 (CRP-3) was obtained from Roberts ridge, a sea-floor high located at 77°S, 12 km offshore from Cape Roberts in western McMurdo Sound, Antarctica. The recovered core is about 939 m long and comprises strata dated as being early Oligocene (possibly latest Eocene) in age, resting unconformably on ∼ 116 m of basement rocks consisting of Palaeozoic Beacon Supergroup sediments. The core includes ten facies commonly occuring in five major associations that are repeated in particular sequences throughout the core and which are interpreted as representing different depositional environments through time. Depositional systems inferred to be represented in the succession include: outer shelf, inner shelf, nearshore to shoreface each under iceberg influence, deltaic and/or grounding-line fan, and ice proximal-ice marginal-subglacial (mass flow/rainout diamictite/subglacial till) singly or in combination. The record is taken to represent the initial talus/alluvial fan setting of a glaciated rift margin adjacent to the block-uplifted Transantarctic Mountains. Development of a deltaic succession upcore was probably associated with the formation of palaeo-Mackay valley with temperate glaciers in its headwaters. At that stage glaciation was intense enough to support glaciers ending in the sea elsewhere along the coast, but a local glacier was fluctuating down to the sea by the time the youngest part of CRP-3 was being deposited. Changes in palaeoenvironmental interpretations in this youngest part of the core are used to estimate relative glacial proximity to the drillsite through time. These inferred glacial fluctuations are compared with the global δ18O and Mg/Ca curves to evaluate the potential of glacial fluctuations on Antarctica for influencing these records of global change. Although the comparisons are tentative at present, the records do have similarities, but there are also some differences that require further evaluation.

Simultaneous administration of a cocktail of markers to measure renal drug elimination pathways: absence of a pharmacokinetic interaction between fluconazole and sinistrin, p-aminohippuric acid and pindolol

Aims Previous studies suggest that estimated creatinine clearance, the conventional measure of renal function, does not adequately reflect charges in renal drug handling in some patients, including the immunosuppressed. The aim of this study was to develop and validate a cocktail of markers. to be given in a single administration, capable of detecting alterations in the renal elimination pathways of glomerular filtration, tubular secretion and tubular reabsorption. Methods Healthy male subjects (n = 12) received intravenously infused 2500 mg sinistrin (glomerular filtration) and 440 mg p-aminohippuric acid (PAH; anion secretion), and orally administered 100 mg fluconazole (reabsorption) and 15 mg rac-pindolol (cation secretion). The potential interaction between these markers was investigated in a pharmacokinetic study where markers (M) or fluconazole (F) were administered alone or together (M + F). Validated analytical methods were used to measure plasma and urine concentrations in order to quantify the renal handling of each marker. Plasma protein binding of fluconazole was measured by ultrafiltration. All subjects had an estimated creatinine clearance within the normal range. The renal clearance of each marker (Mean +/- s.d.) was calculated as the ratio of the amount excreted in urine and thearea-under-the-concentration-time curve. Statistical comparisons were made using a paired t-test and 95% confidence intervals were reported. Results The renal clearances of sinistrin (M: 119 +/- 31 ml min(-1); M + F: 130 +/- 40 ml min(-1); P = 0.32), PAH (M: 469 +/- 145 ml min(-1); M + F: 467 +/- 146 ml min(-1); P = 0.95), R-pindolol (M: 204 +/- 41 ml min(-1); M + F: 190 +/- 41 ml min(-1); P = 0.39; n = 11), S-pindolol (M: 225 +/- 55 ml min(-1); M + F: 209 +/- 60 ml min(-1); P = 0.27; n = 11) and fluconazole (F: 14.9 +/-3.8 ml min(-1); M + F: 13.6 +/- 3.4 ml min(-1); P = 0.16) were similar when the markers or fluconazole were administered alone (M or F) or as a cocktail (M + F). Conclusions This study found no interaction between markers and fluconazole in healthy male subjects, suggesting that a single administration of this cocktail of markers of different renal processes call be used to simultaneously investigate pathways of renal drug elimination.

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.

Isolation of a novel G-protein gamma-subunit from Arabidopsis thaliana and its interaction with G beta

There is increasing evidence that heterotrimeric G-proteins (G-proteins) are involved in many plant processes including phytohormone response, pathogen defence and stomatal control. In animal systems, each of the three G-protein subunits belong to large multigene families; however, few subunits have been isolated from plants. Here we report the cloning of a second plant G-protein γ-subunit (AGG2) from Arabidopsis thaliana. The predicted AGG2 protein sequence shows 48% identity to the first identified Arabidopsis Gγ-subunit, AGG1. Furthermore, AGG2 contains all of the conserved characteristics of γ-subunits including a small size (100 amino acids, 11.1 kDa), C-terminal CAAX box and a N-terminal α-helix region capable of forming a coiled-coil interaction with the β-subunit. A strong interaction between AGG2 and both the tobacco (TGB1) and Arabidopsis (AGB1) β-subunits was observed in vivo using the yeast two-hybrid system. The strong association between AGG2 and AGB1 was confirmed in vitro. Southern and Northern analyses showed that AGG2 is a single copy gene in Arabidopsis producing two transcripts that are present in all tissues tested. The isolation of a second γ-subunit from A. thaliana indicates that plant G-proteins, like their mammalian counterparts, may form different heterotrimer combinations that presumably regulate multiple signal transduction pathways.

Patchy populations in stochastic environments: Critical number of patches for persistence

We introduce a model for the dynamics of a patchy population in a stochastic environment and derive a criterion for its persistence. This criterion is based on the geometric mean (GM) through time of the spatial-arithmetic mean of growth rates. For the population to persist, the GM has to be greater than or equal to1. The GM increases with the number of patches (because the sampling error is reduced) and decreases with both the variance and the spatial covariance of growth rates. We derive analytical expressions for the minimum number of patches (and the maximum harvesting rate) required for the persistence of the population. As the magnitude of environmental fluctuations increases, the number of patches required for persistence increases, and the fraction of individuals that can be harvested decreases. The novelty of our approach is that we focus on Malthusian local population dynamics with high dispersal and strong environmental variability from year to year. Unlike previous models of patchy populations that assume an infinite number of patches, we focus specifically on the effect that the number of patches has on population persistence. Our work is therefore directly relevant to patchily distributed organisms that are restricted to a small number of habitat patches.

Biometrical Genetics

Biometrical genetics is the science concerned with the inheritance of quantitative traits. In this review we discuss how the analytical methods of biometrical genetics are based upon simple Mendelian principles. We demonstrate how the phenotypic covariance between related individuals provides information on the relative importance of genetic and environmental factors influencing that trait, and how factors such as assortative mating, gene-environment correlation and genotype-environment interaction complicate such interpretations. Twin and adoption studies are discussed as well as their assumptions and limitations. Structural equation modeling (SEM) is introduced and we illustrate how this approach may be applied to genetic problems. In particular, we show how SEM can be used to address complicated issues such as analyzing the causes of correlation between traits or determining the direction of causation (DOC) between variables. (C) 2002 Elsevier Science B.V. All rights reserved.

Interaction between natural and sexual selection during the evolution of mate recognition

The interaction between natural and sexual selection is central to many theories of how mate choice and reproductive isolation evolve, but their joint effect on the evolution of mate recognition has not, to my knowledge, been investigated in an evolutionary experiment. Natural and sexual selection were manipulated in interspecific hybrid populations of Drosophila to determine their effects on the evolution of a mate recognition system comprised of cuticular hydrocarbons (CHCs). The effect of natural selection in isolation indicated that CHCs were costly for males and females to produce. The effect of sexual selection in isolation indicated that females preferred males with a particular CHC composition. However, the interaction between natural and sexual selection had a greater effect on the evolution of the mate recognition system than either process in isolation. When natural and sexual selection were permitted to operate in combination, male CHCs became exaggerated to a greater extent than in the presence of sexual selection alone, and female CHCs evolved against the direction of natural selection. This experiment demonstrated that the interaction between natural and sexual selection is critical in determining the direction and magnitude of the evolutionary response of the mate recognition system.

Gene-Environment Interaction Effects on Behavioral Variation and Risk of Complex Disorders: The Example of Alcoholism and Other Psychiatric Disorders

There have been few replicated examples of genotype x environment interaction effects on behavioral variation or risk of psychiatric disorder. We review some of the factors that have made detection of genotype x environment interaction effects difficult, and show how genotype x shared environment interaction (GxSE) effects are commonly confounded with genetic parameters in data from twin pairs reared together. Historic data on twin pairs reared apart can in principle be used to estimate such GxSE effects, but have rarely been used for this purpose. We illustrate this using previously published data from the Swedish Adoption Twin Study of Aging (SATSA), which suggest that GxSE effects could account for as much as 25% of the total variance in risk of becoming a regular smoker. Since few separated twin pairs will be available for study in the future, we also consider methods for modifying variance components linkage analysis to allow for environmental interactions with linked loci.