Dynamical age differences among coeval star clusters as revealed by blue stragglers

Globular star clusters that formed at the same cosmic time may have evolved rather differently from a dynamical point of view (because that evolution depends on the internal environment) through a variety of processes that tend progressively to segregate stars more massive than the average towards the cluster centre. Therefore clusters with the same chronological age may have reached quite different stages of their dynamical history (that is, they may have different dynamical ages). Blue straggler stars have masses greater than those at the turn-off point on the main sequence and therefore must be the result of either a collision or a mass-transfer event. Because they are among the most massive and luminous objects in old clusters, they can be used as test particles with which to probe dynamical evolution. Here we report that globular clusters can be grouped into a few distinct families on the basis of the radial distribution of blue stragglers. This grouping corresponds well to an effective ranking of the dynamical stage reached by stellar systems, thereby permitting a direct measure of the cluster dynamical age purely from observed properties.Comment: Published on the 20 December 2012 issue of Natur

A randomised controlled trial of cognitive behavioural treatment for obsessive compulsive disorder in children and adolescents

Cognitive behaviour therapy (CBT) for young people with obsessive compulsive disorder (OCD) has become the treatment of first choice. However, the literature is largely based on studies emphasising exposure and response prevention. In this study, we report on a randomised controlled trial of CBT for young people carried out in typical outpatient clinic conditions which focused on cognitions. A randomised controlled trial compares 10 sessions of manualised cognitive behavioural treatment with a 12-week waiting list for adolescents and children with OCD. Assessors were blind to treatment allocation. 21 consecutive patients with OCD aged between 9 and 18 years were recruited. The group who received treatment improved more than a comparison group who waited for 3 months. The second group was treated subsequently using the same protocol and made similar gains. In conclusion, CBT can be delivered effectively to young people with OCD in typical outpatient settings

Are Child and Adolescent Responses to Placebo Higher in Major Depression than in Anxiety Disorders? A Systematic Review of Placebo-Controlled Trials

BACKGROUND: In a previous report, we hypothesized that responses to placebo were high in child and adolescent depression because of specific psychopathological factors associated with youth major depression. The purpose of this study was to compare the placebo response rates in pharmacological trials for major depressive disorder (MDD), obsessive compulsive disorder (OCD) and other anxiety disorders (AD-non-OCD). METHODOLOGY AND PRINCIPAL FINDINGS: We reviewed the literature relevant to the use of psychotropic medication in children and adolescents with internalized disorders, restricting our review to double-blind studies including a placebo arm. Placebo response rates were pooled and compared according to diagnosis (MDD vs. OCD vs. AD-non-OCD), age (adolescent vs. child), and date of publication. From 1972 to 2007, we found 23 trials that evaluated the efficacy of psychotropic medication (mainly non-tricyclic antidepressants) involving youth with MDD, 7 pertaining to youth with OCD, and 10 pertaining to youth with other anxiety disorders (N = 2533 patients in placebo arms). As hypothesized, the placebo response rate was significantly higher in studies on MDD, than in those examining OCD and AD-non-OCD (49.6% [range: 17-90%] vs. 31% [range: 4-41%] vs. 39.6% [range: 9-53], respectively, ANOVA F = 7.1, p = 0.002). Children showed a higher stable placebo response within all three diagnoses than adolescents, though this difference was not significant. Finally, no significant effects were found with respect to the year of publication. CONCLUSION: MDD in children and adolescents appears to be more responsive to placebo than other internalized conditions, which highlights differential psychopathology

Oxaliplatin neurotoxicity – no general ion channel surface-charge effect

<p>Abstract</p> <p>Background</p> <p>Oxaliplatin is a platinum-based chemotherapeutic drug. Neurotoxicity is the dose-limiting side effect. Previous investigations have reported that acute neurotoxicity could be mediated via voltage-gated ion channels. A possible mechanism for some of the effects is a modification of surface charges around the ion channel, either because of chelation of extracellular Ca²⁺, or because of binding of a charged biotransformation product of oxaliplatin to the channel. To elucidate the molecular mechanism, we investigated the effects of oxaliplatin and its chloride complex [Pt(dach)oxCl]^-on the voltage-gated Shaker K channel expressed in <it>Xenopus </it>oocytes. The recordings were made with the two-electrode and the cut-open oocyte voltage clamp techniques.</p> <p>Conclusion</p> <p>To our surprise, we did not see any effects on the current amplitudes, on the current time courses, or on the voltage dependence of the Shaker wild-type channel. Oxaliplatin is expected to bind to cysteines. Therefore, we explored if there could be a specific effect on single (E418C) and double-cysteine (R362C/F416C) mutated Shaker channels previously shown to be sensitive to cysteine-specific reagents. Neither of these channels were affected by oxaliplatin. The clear lack of effect on the Shaker K channel suggests that oxaliplatin or its monochloro complex has no general surface-charge effect on the channels, as has been suggested before, but rather a specific effect to the channels previously shown to be affected.</p

Statistical design of personalized medicine interventions: The Clarification of Optimal Anticoagulation through Genetics (COAG) trial

<p>Abstract</p> <p>Background</p> <p>There is currently much interest in pharmacogenetics: determining variation in genes that regulate drug effects, with a particular emphasis on improving drug safety and efficacy. The ability to determine such variation motivates the application of personalized drug therapies that utilize a patient's genetic makeup to determine a safe and effective drug at the correct dose. To ascertain whether a genotype-guided drug therapy improves patient care, a personalized medicine intervention may be evaluated within the framework of a randomized controlled trial. The statistical design of this type of personalized medicine intervention requires special considerations: the distribution of relevant allelic variants in the study population; and whether the pharmacogenetic intervention is equally effective across subpopulations defined by allelic variants.</p> <p>Methods</p> <p>The statistical design of the Clarification of Optimal Anticoagulation through Genetics (COAG) trial serves as an illustrative example of a personalized medicine intervention that uses each subject's genotype information. The COAG trial is a multicenter, double blind, randomized clinical trial that will compare two approaches to initiation of warfarin therapy: genotype-guided dosing, the initiation of warfarin therapy based on algorithms using clinical information and genotypes for polymorphisms in <it>CYP2C9 </it>and <it>VKORC1</it>; and clinical-guided dosing, the initiation of warfarin therapy based on algorithms using only clinical information.</p> <p>Results</p> <p>We determine an absolute minimum detectable difference of 5.49% based on an assumed 60% population prevalence of zero or multiple genetic variants in either <it>CYP2C9 </it>or <it>VKORC1 </it>and an assumed 15% relative effectiveness of genotype-guided warfarin initiation for those with zero or multiple genetic variants. Thus we calculate a sample size of 1238 to achieve a power level of 80% for the primary outcome. We show that reasonable departures from these assumptions may decrease statistical power to 65%.</p> <p>Conclusions</p> <p>In a personalized medicine intervention, the minimum detectable difference used in sample size calculations is not a known quantity, but rather an unknown quantity that depends on the genetic makeup of the subjects enrolled. Given the possible sensitivity of sample size and power calculations to these key assumptions, we recommend that they be monitored during the conduct of a personalized medicine intervention.</p> <p>Trial Registration</p> <p>clinicaltrials.gov: NCT00839657</p

Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior

Genome-wide associations for birth weight and correlations with adult disease

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease1. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10−8). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (Rg = −0.22, P = 5.5 × 10−13), T2D (Rg = −0.27, P = 1.1 × 10−6) and coronary artery disease (Rg = −0.30, P = 6.5 × 10−9). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10−4). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated

The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia: design, results and future prospects

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites