The Two Faces of Social Interaction Reward in Animal Models of Drug Dependence

Drug dependence is a serious health and social problem. Social factors can modify vulnerability to developing drug dependence, acting as risk factors or protective factors. Whereas stress and peer environment that encourage substance use may increase drug taking, strong attachments between family members and peer environment that do not experience drug use may protect against drug taking and, ultimately, drug dependence. The rewarding effects of drug abuse and social interaction can be evaluated using animal models. In this review we focus on evaluating social interaction reward in the conditioned place preference paradigm. We give an overview of how social interaction, if made available within the drug context, may facilitate, promote and interact with the drug’s effects. However, social interaction, if offered alternatively outside the drug context, may have pronounced protective effects against drug abuse and relapse. We also address the importance of the weight difference parameter between the social partners in determining the positive or “agonistic” versus the hostile or “antagonistic” social interaction. We conclude that understanding social interaction reward and its subsequent effects on drug reward is sorely needed for therapeutic interventions against drug dependence.     

Mapping QTLs with digenic epistasis under multiple environments and predicting heterosis based on QTL effects

Mixed linear model approach was proposed for mapping QTLs with the digenic epistasis and QTL by environment (QE) interaction as well as additive and dominant effects. Monte Carlo simulations indicated that the proposed method could provide unbiased estimations for both positions and genetic main effects of QTLs, as well as unbiased predictions for QE interaction effects. A method was suggested for predicting heterosis based on individual QTL effects. The immortalized F₂ (IF₂) population constructed by random mating among RI or DH lines is appropriate for mapping QTLs with epistasis and their QE interaction. Based on the models and methodology proposed, we developed a QTL mapping software, QTLMapper 2.0 on the basis of QTLmapper 1.0, which is suitable for analyzing populations of DH, RIL, F₂ and IF₂. Data of thousand grain weight of IF₂ population with 240 lines derived from elite hybrid rice Shanyou 63 were analyzed as a worked example.     

INFLUENCE OF PANEL INCONSISTENCY ON THE OUTCOME OF SENSORY EVALUATIONS FROM DESCRIPTIVE PANELS

Different types of panelist by treatment interaction are explored to determine how they influence the outcomes of discrimination tests. The study compares the situations where panelists are considered as fixed or random effects over the range of most testing conditions for small panels (5–15 panelists) that replicate their judgements. Magnitude interaction and nonperceivers or nondiscriminators have minor effects on test outcomes. Cross-over interaction increases the chances for a type II error, especially when panelists are considered as random effects. False discrimination increases the chances for a type I error when panelists are considered as fixed effects. Applications of methods to reduce the chances for these errors in the testing for differences among treatments are discussed.     

Genetic and heterosis analysis for cooking quality traits of indica rice in different environments

Genetic effects and genotype×environment (GE) interaction effects on the cooking quality traits of indica rice (Oryza sativa L.) were analyzed based on a genetic model for quantitative traits of triploid endosperm in cereal crops. Nine cytoplasmic male-sterile lines as females and 5 restoring lines as males were used in an incomplete diallel cross over 2 years. The cooking quality traits studied were observed to be mainly controlled by genetic effects, but GE interaction effects, especially for amylose content (AC) and alkali spreading score (ASS), were also indicated. Among the genetic effects, seed direct effects and maternal effects were the main components of AC and ASS, respectively; cytoplasmic effects were the main components of gel consistency (GC). Among the GE interaction effects, AC and ASS were mainly affected by maternal interaction effects and GC by direct interaction effects. Additive effects and/or additive interaction effects were the main factors controlling the performance of rice cooking quality traits except for GC which was affected by dominant interaction effects. For AC and GC, there were seed heterosis and/or maternal heterosis. The predicated genetic effects indicated that four parents were better than the others in improving the rice cooking quality traits of the progenies. It was shown that genetic heterosis and GE interaction heterosis were important, especially for amylose content trait in early season indica rice.     

Mechanochemical coupling in eukaryotic flagella

Quantitative analyses of ATP hydrolysis coupled to movement of eukaryotic flagella is important for understanding the relationship between ATP hydrolysis and movement. The difference in ATPase activity between intact motile axonemes (that is the cytoskeletal core of flagella) and homogenized or immotile axonemes has been assumed to be coupled to movement. However, recent findings on rates of steps in the dynein ATPase cycle and the effect of interaction with microtubules on those steps call for reassessment of movement-coupled ATPase. From these studies, it is clear that dynein ATPase activity is not as tightly coupled to interaction with microtubules as myosin ATPase activity is coupled to interaction with actin. The method by which axonemal movement is inhibited will critically affect the interpretation of difference in ATPase activity. If the homogenization or similar methods uncouple dynein, the difference in ATPase activity is not a useful measurement. Greater understanding of the relationship between dynein kinetics and axonemal movement may be obtained by use of conditions and substrates with known effects at specific steps in the dynein mechanochemical cycle and quantitating their effects on movement.     

Using Information Interaction to Discover Epistatic Effects in Complex Diseases

It is widely agreed that complex diseases are typically caused by the joint effects of multiple instead of a single genetic variation. These genetic variations may show stronger effects when considered together than when considered individually, a phenomenon known as epistasis or multilocus interaction. In this work, we explore the applicability of information interaction to discover pairwise epistatic effects related with complex diseases. We start by showing that traditional approaches such as classification methods or greedy feature selection methods (such as the Fleuret method) do not perform well on this problem. We then compare our information interaction method with BEAM and SNPHarvester in artificial datasets simulating epistatic interactions and show that our method is more powerful to detect pairwise epistatic interactions than its competitors. We show results of the application of information interaction method to the WTCCC breast cancer dataset. Our results are validated using permutation tests. We were able to find 89 statistically significant pairwise interactions with a p-value lower than . Even though many recent algorithms have been designed to find epistasis with low marginals, we observed that all (except one) of the SNPs involved in statistically significant interactions have moderate or high marginals. We also report that the interactions found in this work were not present in gene-gene interaction network STRING.     

The effect of urea and guanidinium chloride on activity of subtilisin Carlsberg

As shown by viscosity and optical rotation dispersion measurements, subtilisin Carlsberg is not denatured in the presence of 10 M urea or 6 M guanidinium chloride. This unusual structural stability made it possible to investigate the effects of these hydrophobic-bond breaking solutes on various aspects of the enzymic interaction with substrates and inhibitors. The binding of the competitive inhibitor N-benzoylarginine was decreased by urea or guanidinium chloride. The nature of this effect was such as to implicate hydrophobic interaction as making a major contribution to the binding. By contrast, Ks for the substrates N-acetyltyrosine ethyl ester, N-benzoylarginine ethyl ester and N-trans-cinnamoylimidazole was apparently unchanged by the presence of urea or guanidinium chloride. The influence of these solutes on kcat for the substrates was rather involved. Tentative hypotheses are put forward to account for the effects seen.     

Variance components models for gene-environment interaction in twin analysis.

Gene-environment interaction is likely to be a common and important source of variation for complex behavioral traits. Often conceptualized as the genetic control of sensitivity to the environment, it can be incorporated in variance components twin analyses by partitioning genetic effects into a mean part, which is independent of the environment, and a part that is a linear function of the environment. The model allows for one or more environmental moderator variables (that possibly interact with each other) that may i). be continuous or binary ii). differ between twins within a pair iii). interact with residual environmental as well as genetic effects iv) have nonlinear moderating properties v). show scalar (different magnitudes) or qualitative (different genes) interactions vi). be correlated with genetic effects acting upon the trait, to allow for a test of gene-environment interaction in the presence of gene-environment correlation. Aspects and applications of a class of models are explored by simulation, in the context of both individual differences twin analysis and, in a companion paper (Purcell & Sham, 2002) sibpair quantitative trait locus linkage analysis. As well as elucidating environmental pathways, consideration of gene-environment interaction in quantitative and molecular studies will potentially direct and enhance gene-mapping efforts.     

Relationships between ecological interaction modifications and diffuse coevolution: similarities, differences, and causal links

A major empirical approach in community ecology is to describe the dynamics of a community by examining small subsets of species. Unfortunately, interaction modifications, which cause pair-wise interaction coefficients to depend on the presence or absence of additional species, can make it difficult to predict the overall dynamics of species within a community from experiments with pairs of species. In a similar fashion, one of the major approaches in evolutionary ecology has been to describe the likely evolutionary dynamics of a single species by focusing on the selection imposed by a limited number of other species within the community. However, recent work on diffuse coevolution indicates that selection pressures due to one species can change in the presence of other species. The magnitude of the difficulty that interaction modifications and diffuse coevolution present for predicting ecological and evolutionary dynamics is an unresolved question. Here we outline the similarities and differences between the two topics, discuss experimental and statistical approaches to studying them, and make predictions about when ecological interaction modifications are likely to cause diffuse coevolution. Since the currencies for interaction modifications are usually fitness components such as growth, fecundity, or survival, is it likely that these will translate into corresponding differences in the relative fitness of individuals or genotypes, and thus in general these two phenomena will occur together. We argue that community ecologists and evolutionary ecologists will both benefit from experiments that test for the effects of interaction modifications, and that studies of the mechanisms driving interaction modifications and diffuse coevolution (e.g., changes in behavior, nonlinear effects on shared resources, genetic covariances) will aid our progress in understanding the ecological and evolutionary dynamics of communities.     

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.     

Press perturbation experiments and the indeterminacy of ecological interactions: effects of taxonomic resolution and experimental duration

The outcomes of press perturbation experiments on community dynamics are difficult to predict because there is a high degree of indeterminacy in the strength and direction of ecological interactions. Ecologists need to quantify uncertainties in estimates of interaction strength, by determining all the possible values a given interaction strength could take and the relative likelihood of each value. In this study, we assess the degree to which fish effects on zooplankton and phytoplankton are indeterminate in direction using a combination of experimental data and Monte Carlo simulations. Based on probability distributions of interaction strength (i.e. effect magnitude), we estimated the probability of each fish interaction being negative, positive or undetermined in direction. We then investigated how interaction strength and its predictability might vary with experimental duration and the taxonomic resolution of food web data. Results show that most effects of fish on phyto- and zooplankton were indeed indeterminate, and that the effects of fish were more predictable in direction as the taxonomic resolution of food web data decreased and the experimental duration increased. Results also show that most distributions of interaction strength were not normal, suggesting that normal based statistical procedures for testing hypothesis about interaction strength may be misleading, as well as predictions of food web models assuming normal distributions of interaction strength. By considering the probability distributions and confidence intervals of interaction parameters, ecologists would better understand the outcomes of species interactions and make more realistic predictions about our perturbations in natural food webs.     

Nuclear magnetic resonance study of doxorubicin binding to cardiolipin containing magnetically oriented phospholipid bilayers

Doxorubicin (DOX) is a potent anthracycline cancer drug whose interaction with anionic membrane phospholipids, such as cardiolipin (CL), is thought to contribute to its cytotoxicity as well as induce cardiotoxic side effects. We have studied the interaction of DOX with a CL containing model membrane system using high resolution, oriented sample (31)P and (2)H NMR. The model membrane system is composed of a bilayer forming phospholipid and a detergent that breaks the extended bilayers into disc-shaped micelles (bicelles) that can orient in a magnetic field. The effects of DOX on the phospholipid bilayer were monitored using samples containing dimyristoylphosphatidylcholine (DMPC), selectively deuterated in either headgroup or acyl chain positions, and measuring the changes in (2)H quadrupolar splittings as DOX was added. Changes in quadrupolar splittings upon DOX addition provide evidence for interaction with both surface and buried sites within the membrane bilayer.     

Affect-modulated startle: interactive influence of catechol-O-methyltransferase Val158Met genotype and childhood trauma

The etiology of emotion-related disorders such as anxiety or affective disorders is considered to be complex with an interaction of biological and environmental factors. Particular evidence has accumulated for alterations in the dopaminergic and noradrenergic system--partly conferred by catechol-O-methyltransferase (COMT) gene variation--for the adenosinergic system as well as for early life trauma to constitute risk factors for those conditions. Applying a multi-level approach, in a sample of 95 healthy adults, we investigated effects of the functional COMT Val158Met polymorphism, caffeine as an adenosine A2A receptor antagonist (300 mg in a placebo-controlled intervention design) and childhood maltreatment (CTQ) as well as their interaction on the affect-modulated startle response as a neurobiologically founded defensive reflex potentially related to fear- and distress-related disorders. COMT val/val genotype significantly increased startle magnitude in response to unpleasant stimuli, while met/met homozygotes showed a blunted startle response to aversive pictures. Furthermore, significant gene-environment interaction of COMT Val158Met genotype with CTQ was discerned with more maltreatment being associated with higher startle potentiation in val/val subjects but not in met carriers. No main effect of or interaction effects with caffeine were observed. Results indicate a main as well as a GxE effect of the COMT Val158Met variant and childhood maltreatment on the affect-modulated startle reflex, supporting a complex pathogenetic model of the affect-modulated startle reflex as a basic neurobiological defensive reflex potentially related to anxiety and affective disorders.     

A General Framework for Formal Tests of Interaction after Exhaustive Search Methods with Applications to MDR and MDR-PDT

The initial presentation of multifactor dimensionality reduction (MDR) featured cross-validation to mitigate over-fitting, computationally efficient searches of the epistatic model space, and variable construction with constructive induction to alleviate the curse of dimensionality. However, the method was unable to differentiate association signals arising from true interactions from those due to independent main effects at individual loci. This issue leads to problems in inference and interpretability for the results from MDR and the family-based compliment the MDR-pedigree disequilibrium test (PDT). A suggestion from previous work was to fit regression models post hoc to specifically evaluate the null hypothesis of no interaction for MDR or MDR-PDT models. We demonstrate with simulation that fitting a regression model on the same data as that analyzed by MDR or MDR-PDT is not a valid test of interaction. This is likely to be true for any other procedure that searches for models, and then performs an uncorrected test for interaction. We also show with simulation that when strong main effects are present and the null hypothesis of no interaction is true, that MDR and MDR-PDT reject at far greater than the nominal rate. We also provide a valid regression-based permutation test procedure that specifically tests the null hypothesis of no interaction, and does not reject the null when only main effects are present. The regression-based permutation test implemented here conducts a valid test of interaction after a search for multilocus models, and can be applied to any method that conducts a search to find a multilocus model representing an interaction.     

烤烟主要农艺性状的遗传与相关分析

利用包括基因型与环境互作的加性-显性遗传模型,对14个烤烟品种(系)及其配制的41个杂交组合在4个环境下的7个农艺性状表现进行遗传分析。结果表明,株高、节距、腰叶宽主要受加性效应控制,叶数、腰叶长受显性×环境互作效应影响最大,茎围以加性×环境互作效应、显性×环境互作效应为主,产量以加性效应、显性×环境互作效应为主。适应当地生态条件的品种（系）具有较高的正向加性效应。许多组合的显性主效应及在各试验点的显性×环境互作效应在方向上不尽一致,杂交组合的选配宜针对特定的生态环境进行。性状相关分析表明,大多数成对性状的各项相关系数为正值,且多以加性遗传相关为主,可利用株高对产量进行间接选择。
     

The effects of personal interaction on triglyceride and uric acid levels, and coronary risk in a managerial population: a longitudinal study

This two year longitudinal study of managers investigated whether the level of interaction with other individuals was a job stressor that influences coronary risk factors. The results presented here show that increased levels of interaction were associated with increased serum triglyceride and increased serum uric acid levels. It is suggested that past research positing stress effects from responsibility for people may be due to interaction levels rather than responsibility per se. It was also found that Type A behavior and physical activity levels moderated these effects. While it is difficult to say that personal interaction, as a job stressor, contributes very significantly to either coronary risk factors or coronary heart disease the evidence supports the hypothesis that the amount of interaction has some specific stress effects.     

Its Preferential Interactions with Biopolymers Account for Diverse Observed Effects of Trehalose

Biopolymer homeostasis underlies the health of organisms, and protective osmolytes have emerged as one strategy used by Nature to preserve biopolymer homeostasis. However, a great deal remains unknown about the mechanism of action of osmolytes. Trehalose, as a prominent example, stabilizes proteins against denaturation by extreme temperature and denaturants, preserves membrane integrity upon freezing or in dry conditions, inhibits polyQ-mediated protein aggregation, and suppresses the aggregation of denatured proteins. The underlying thermodynamic mechanisms of such diverse effects of trehalose remain unclear or controversial. In this study, we applied the surface-additive method developed in the Record laboratory to attack this issue. We characterized the key features of trehalose-biopolymer preferential interactions and found that trehalose has strong unfavorable interactions with aliphatic carbon and significant favorable interactions with amide/anionic oxygen. This dissection has allowed us to elucidate the diverse effects of trehalose and to identify the crucial functional group(s) responsible for its effects. With (semi)quantitative thermodynamic analysis, we discovered that 1) the unfavorable interaction of trehalose with hydrophobic surfaces is the dominant factor in its effect on protein stability, 2) the favorable interaction of trehalose with polar amides enables it to inhibit polyQ-mediated protein aggregation and the aggregation of denatured protein in general, and 3) the favorable interaction of trehalose with phosphate oxygens, together with its unfavorable interaction with aliphatic carbons, enables trehalose to preserve membrane integrity in aqueous solution. These results provide a basis for a full understanding of the role of trehalose in biopolymer homeostasis and the reason behind its evolutionary selection as an osmolyte, as well as for a better application of trehalose as a chemical chaperone.     

Individual and combined effects of fine sediment and the herbicide glyphosate on benthic macroinvertebrates and stream ecosystem function

相似文献   

Interaction with eIF5B is essential for Vasa function during development

The DEAD-box RNA helicase Vasa (Vas) is required for germ cell development and function, as well as for embryonic somatic posterior patterning. Vas interacts with the general translation initiation factor eIF5B (cIF2, also known as dIF2), and thus may regulate translation of specific mRNAs. In order to investigate which functions of Vas are related to translational control, we have analyzed the effects of site-directed vas mutations that reduce or eliminate interaction with eIF5B. Reduction in Vas-eIF5B interaction during oogenesis leads to female sterility, with phenotypes similar to a vas null mutation. Accumulation of Gurken (Grk) protein is greatly reduced when Vas-eIF5B interaction is reduced, suggesting that this interaction is crucial for translational regulation of grk. In addition, we show that reduction in Vas-eIF5B interaction virtually abolishes germ cell formation in embryos, while producing a less severe effect on somatic posterior patterning. We conclude that interaction with the general translation factor eIF5B is essential for Vas function during development.     

Quantitative interpretations of double mutations of enzymes.

The quantitative effect of a second mutation on a mutant enzyme may be antagonistic, absent, partially additive, additive, or synergistic with respect to the first mutation. Depending on which kinetic or thermodynamic parameter of an enzyme is measured, the same two mutations can interact differently in the double mutant. Additive effects of two mutations on an equilibrium constant, such as the dissociation constant of the enzyme-substrate complex (KS), occur when noninteracting residues which facilitate the same step (substrate binding) are mutated. Partially additive effects result from the cooperative interaction with the substrate of the two residues mutated, and synergistic effects result from the anticooperative interaction with the substrate of the two residues mutated. An alternative explanation for synergy is extensive unfolding of the enzyme. Antagonistic effects on an equilibrium constant such as KS result from opposing structural effects of the two mutations on substrate binding. No additional effect of the second mutation in the double mutant represents a limiting case of either partial additivity or antagonism [corrected]. The interactions of the effects of two mutations on a rate constant such as kcat have the same explanations as those given above for equilibrium constants since the binding of a rate-limiting transition state is occurring. However, due to kinetic complexity, the following exceptions and additions exist. Additive effects of two mutations on kcat occur when noninteracting residues which facilitate the same step are mutated, provided this step is rate limiting. If the affected step is not rate limiting then synergistic effects of the two mutations are observed as each mutation causes the step to become progressively more rate limiting. Additive effects on kcat also occur when the two mutations affect consecutive steps, provided one of them is rate limiting. Partially additive effects on kcat also occur when noninteracting residues facilitating consecutive, non-rate-limiting steps are mutated. These concepts, when applied to published data on double mutants of delta 5-3-ketosteroid isomerase, staphylococcal nuclease, tyrosyl-tRNA synthetase, glutathione reductase, and subtilisin, provide deeper insights into the independent, cooperative, anticooperative, or antagonistic interactions of amino acid residues in the binding of substrates, activators, and inhibitors and in promoting catalysis.