Barbie Banished from the Small Screen: The Proposed European Ban on Children\u27s Television Advertising

This Comment first presents a brief history of European policy governing children\u27s television advertising in Europe and lists the current regula-tions in the various EU member states, ranging from Britain\u27s deferential guidelines to Sweden\u27s draconian stance. The next two sections examine arguments both for and against the ban. Impassioned consumer advocates decry television advertising to children as preying upon young impressionable minds; indignant industry groups marshal arguments such as the increasing sophistication of children and the freedom of commercial speech. Finally, after forecasting a doubtful future for the proposed absolute ban on children\u27s television across Europe, this Comment concludes that a watchful eye should still be kept over advertisers to children, particularly in light of the increase in commercialism in the European classroom

Modulation of collagen-induced arthritis by adenovirus-mediated intra-articular expression of modified collagen type II

INTRODUCTION: Rheumatoid arthritis (RA) is a systemic disease manifested by chronic inflammation in multiple articular joints, including the knees and small joints of the hands and feet. We have developed a unique modification to a clinically accepted method for delivering therapies directly to the synovium. Our therapy is based on our previous discovery of an analog peptide (A9) with amino acid substitutions made at positions 260 (I to A), 261 (A to B), and 263 (F to N) that could profoundly suppress immunity to type II collagen (CII) and arthritis in the collagen-induced arthritis model (CIA). METHODS: We engineered an adenoviral vector to contain the CB11 portion of recombinant type II collagen and used PCR to introduce point mutations at three sites within (CII(124-402, 260A, 261B, 263D)), (rCB11-A9) so that the resulting molecule contained the A9 sequence at the exact site of the wild-type sequence. RESULTS: We used this construct to target intra-articular tissues of mice and utilized the collagen-induced arthritis model to show that this treatment strategy provided a sustained, local therapy for individual arthritic joints, effective whether given to prevent arthritis or as a treatment. We also developed a novel system for in vivo bioimaging, using the firefly luciferase reporter gene to allow serial bioluminescence imaging to show that luciferase can be detected as late as 18 days post injection into the joint. CONCLUSIONS: Our therapy is unique in that we target synovial cells to ultimately shut down T cell-mediated inflammation. Its effectiveness is based on its ability to transform potential inflammatory T cells and/or bystander T cells into therapeutic (regulatory-like) T cells which secrete interleukin (IL)-4. We believe this approach has potential to effectively suppress RA with minimal side effects

Adiponectin Haploinsufficiency Promotes Mammary Tumor Development in MMTV-PyVT Mice by Modulation of Phosphatase and Tensin Homolog Activities

Background: Adiponectin is an adipokine possessing beneficial effects on obesity-related medical complications. A negative association of adiponectin levels with breast cancer development has been demonstrated. However, the precise role of adiponectin deficiency in mammary carcinogenesis remains elusive. Methodology/Principal Findings: In the present study, MMTV-polyomavirus middle T antigen (MMTV-PyVT) transgenic mice with reduced adiponectin expressions were established and the stromal effects of adiponectin haploinsufficiency on mammary tumor development evaluated. In mice from both FVB/N and C57BL/6J backgrounds, insufficient adiponectin production promoted mammary tumor onset and development. A distinctive basal-like subtype of tumors, with a more aggressive phenotype, was derived from adiponectin haplodeficient MMTV-PyVT mice. Comparing with those from control MMTV-PyVT mice, the isolated mammary tumor cells showed enhanced tumor progression in re-implanted nude mice, accelerated proliferation in primary cultures, and hyperactivated phosphatidylinositol-3-kinase (PI3K)/Akt/beta-catenin signaling, which at least partly attributed to the decreased phosphatase and tensin homolog (PTEN) activities. Further analysis revealed that PTEN was inactivated by a redox-regulated mechanism. Increased association of PTEN-thioredoxin complexes was detected in tumors derived from mice with reduced adiponectin levels. The activities of thioredoxin (Trx1) and thioredoxin reductase (TrxR1) were significantly elevated, whereas treatment with either curcumin, an irreversible inhibitor of TrxR1, or adiponectin largely attenuated their activities and resulted in the re-activation of PTEN in these tumor cells. Moreover, adiponectin could inhibit TrxR1 promoter-mediated transcription and restore the mRNA expressions of TrxR1. Conclusion: Adiponectin haploinsufficiency facilitated mammary tumorigenesis by down-regulation of PTEN activity and activation of PI3K/ Akt signalling pathway through a mechanism involving Trx1/TrxR1 redox regulations. © 2009 Lam et al.published_or_final_versio

Serotonylation of Vascular Proteins Important to Contraction

BACKGROUND:Serotonin (5-hydroxytryptamine, 5-HT) was named for its source (sero-) and ability to modify smooth muscle tone (tonin). The biological effects of 5-HT are believed to be carried out by stimulation of serotonin receptors at the plasma membrane. Serotonin has recently been shown to be synthesized in vascular smooth muscle and taken up from external sources, placing 5-HT inside the cell. The enzyme transglutaminase uses primary amines such as 5-HT to covalently modify proteins on glutamine residues. We tested the hypothesis that 5-HT is a substrate for transglutaminase in arterial vascular smooth muscle, with protein serotonylation having physiological function. METHODOLOGY/PRINCIPAL FINDINGS:The model was the rat aorta and cultured aortic smooth muscle cells. Western analysis demonstrated that transglutaminase II was present in vascular tissue, and transglutaminase activity was observed as a cystamine-inhibitable incorporation of the free amine pentylamine-biotin into arterial proteins. Serotonin-biotin was incorporated into alpha-actin, beta-actin, gamma-actin, myosin heavy chain and filamin A as shown through tandem mass spectrometry. Using antibodies directed against biotin or 5-HT, immunoprecipitation and immunocytochemistry confirmed serotonylation of smooth muscle alpha-actin. Importantly, the alpha-actin-dependent process of arterial isometric contraction to 5-HT was reduced by cystamine. CONCLUSIONS:5-HT covalently modifies proteins integral to contractility and the cytoskeleton. These findings suggest new mechanisms of action for 5-HT in vascular smooth muscle and consideration for intracellular effects of primary amines

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. Practitioner Points: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.</p

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. Practitioner Points: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.</p

In vivo hippocampal subfield volumes in bipolar disorder—A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta‐Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1‐weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed‐effects models and mega‐analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = −0.20), cornu ammonis (CA)1 (d = −0.18), CA2/3 (d = −0.11), CA4 (d = −0.19), molecular layer (d = −0.21), granule cell layer of dentate gyrus (d = −0.21), hippocampal tail (d = −0.10), subiculum (d = −0.15), presubiculum (d = −0.18), and hippocampal amygdala transition area (d = −0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non‐users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe