Age before beauty? Relationships between fertilization success and age-dependent ornaments in barn swallows

When males become more ornamented and reproduce more successfully as they grow older, phenotypic correlations between ornament exaggeration and reproductive success can be confounded with age effects in cross-sectional studies, and thus say relatively little about sexual selection on these traits. This is exemplified here in a correlative study of male fertilization success in a large colony of American barn swallows (Hirundo rustica erythrogaster). Previous studies of this species have indicated that two sexually dimorphic traits, tail length and ventral plumage coloration, are positively correlated with male fertilization success, and a mechanism of sexual selection by female choice has been invoked. However, these studies did not control for potential age-related variation in trait expression. Here, we show that male fertilization success was positively correlated with male tail length but not with plumage coloration. We also show that 1-year-old males had shorter tails and lower fertilization success than older males. This age effect accounted for much of the covariance between tail length and fertilization success. Still, there was a positive relationship between tail length and fertilization success among older males. But as this group consisted of males from different age classes, an age effect may be hidden in this relationship as well. Our data also revealed a longitudinal increase in both tail length and fertilization success for individual males. We argue that age-dependent ornament expression and reproductive performance in males complicate inferences about female preferences and sexual selection

Imaging biomarker roadmap for cancer studies.

Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use.Development of this roadmap received support from Cancer Research UK and the Engineering and Physical Sciences Research Council (grant references A/15267, A/16463, A/16464, A/16465, A/16466 and A/18097), the EORTC Cancer Research Fund, and the Innovative Medicines Initiative Joint Undertaking (grant agreement number 115151), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies' in kind contribution

Interpreting behavioural data from Radio-Acoustic Positioning Telemetry (RAPT) systems

To detect behavioural patterns of individually tagged squid Loligo vulgaris reynaudii in a Radio-Acoustic Positioning Telemetry (RAPT) buoy array, trajectories reflecting the four dimensions of latitude, longitude, depth and time were plotted from data collected during field experiments in South Africa. Finding a continuous curve to represent the sampled trajectories required dealing with anisotropic precision and accuracy, nonuniform sampling rates and improbable outliers. A combination of an operator-controlled smoothing option of an approximating cubic spline and a weight factor assignment based on distance from the mass curve gave the most expedient results when compared with video recordings. Keywords: corrective smoothing, Loligo vulgaris reynaudii, Radio-Acoustic Positioning Telemetry (RAPT), trajectoriesAfrican Journal of Marine Science 2005, 27(2): 395–39

Genetic neuropathology of obsessive psychiatric syndromes

Anorexia nervosa (AN), bulimia nervosa (BN) and obsessive-compulsive disorder (OCD) are complex psychiatric disorders with shared obsessive features, thought to arise from the interaction of multiple genes of small effect with environmental factors. Potential candidate genes for AN, BN and OCD have been identified through clinical association and neuroimaging studies; however, recent genome-wide association studies of eating disorders (ED) so far have failed to report significant findings. In addition, few, if any, studies have interrogated postmortem brain tissue for evidence of expression quantitative trait loci (eQTLs) associated with candidate genes, which has particular promise as an approach to elucidating molecular mechanisms of association. We therefore selected single-nucleotide polymorphisms (SNPs) based on candidate gene studies for AN, BN and OCD from the literature, and examined the association of these SNPs with gene expression across the lifespan in prefrontal cortex of a nonpsychiatric control cohort (N=268). Several risk-predisposing SNPs were significantly associated with gene expression among control subjects. We then measured gene expression in the prefrontal cortex of cases previously diagnosed with obsessive psychiatric disorders, for example, ED (N=15) and OCD/obsessive-compulsive personality disorder or tics (OCD/OCPD/Tic; N=16), and nonpsychiatric controls (N=102) and identified 6 and 286 genes that were differentially expressed between ED compared with controls and OCD cases compared with controls, respectively (false discovery rate (FDR) <5%). However, none of the clinical risk SNPs were among the eQTLs and none were significantly associated with gene expression within the broad obsessive cohort, suggesting larger sample sizes or other brain regions may be required to identify candidate molecular mechanisms of clinical association in postmortem brain data sets

Mechanisms of Disease: biomarkers and molecular targets from microarray gene expression studies in prostate cancer

Molecular biomarkers can serve as useful diagnostic markers, as prognostic markers for predicting clinical behavior, or as targets for new therapeutic strategies. Application of expression microarray technology, which allows the expression of all or most of the genes in the human genome to be analyzed simultaneously, has dramatically enhanced the discovery of prostate cancer biomarkers. The diagnostic markers identified include AMACR (alpha-methylacyl CoA racemase), a protein that has already been translated into clinical use as an aid in distinguishing prostate cancer from benign disease. Individual genes, such as the polycomb gene EZH2 whose expression indicates poor survival, have been identified. The power of microarray technology is that it has allowed the identification of gene signatures (each composed of multiple genes) that might provide improved prediction of clinical outcomes in human prostate cancer. The development of a new method for analyzing expression microarray data, called COPA, has led to the discovery of TMPRSS2 -ERG gene fusion involvement in the development of prostate cancer, while expression analysis of castration-resistant prostate cancer has suggested the use of novel therapeutic approaches for advanced disease. Despite these successes, there are limitations in the application of microarray technology to prostate cancer; for example, unlike with other cancers, this approach has failed to provide a consistent unsupervised classification of the disease. Overcoming the reasons for these failures represents a major challenge for future research endeavors