Specific targeting of pro-death NMDA receptor signals with differing reliance on the NR2B PDZ ligand.

NMDA receptors (NMDARs) mediate ischemic brain damage, for which interactions between the C termini of NR2 subunits and PDZ domain proteins within the NMDAR signaling complex (NSC) are emerging therapeutic targets. However, expression of NMDARs in a non-neuronal context, lacking many NSC components, can still induce cell death. Moreover, it is unclear whether targeting the NSC will impair NMDAR-dependent prosurvival and plasticity signaling. We show that the NMDAR can promote death signaling independently of the NR2 PDZ ligand, when expressed in non-neuronal cells lacking PSD-95 and neuronal nitric oxide synthase (nNOS), key PDZ proteins that mediate neuronal NMDAR excitotoxicity. However, in a non-neuronal context, the NMDAR promotes cell death solely via c-Jun N-terminal protein kinase (JNK), whereas NMDAR-dependent cortical neuronal death is promoted by both JNK and p38. NMDAR-dependent pro-death signaling via p38 relies on neuronal context, although death signaling by JNK, triggered by mitochondrial reactive oxygen species production, does not. NMDAR-dependent p38 activation in neurons is triggered by submembranous Ca(2+), and is disrupted by NOS inhibitors and also a peptide mimicking the NR2B PDZ ligand (TAT-NR2B9c). TAT-NR2B9c reduced excitotoxic neuronal death and p38-mediated ischemic damage, without impairing an NMDAR-dependent plasticity model or prosurvival signaling to CREB or Akt. TAT-NR2B9c did not inhibit JNK activation, and synergized with JNK inhibitors to ameliorate severe excitotoxic neuronal loss in vitro and ischemic cortical damage in vivo. Thus, NMDAR-activated signals comprise pro-death pathways with differing requirements for PDZ protein interactions. These signals are amenable to selective inhibition, while sparing synaptic plasticity and prosurvival signaling.

A female melanin ornament signals offspring fluctuating asymmetry in the barn owl.

Sexual selection theory predicts that males advertise quality by displaying extravagant ornaments. By contrast, whether phenotypic variation in females has a signalling function remains an open question. Here, to our knowledge, we provide the first evidence that a female plumage trait can signal fluctuating asymmetry in the offspring. We experimentally demonstrate in wild barn owls (Tyto alba) that the extent to which females display black spots on their plumage does not only signal offspring parasite resistance as shown in a previous study but also developmental homeostasis in the offspring. A greater number of spotted females produced offspring that had more symmetrical feathers during the period of growth. Males, that pair non-randomly with respect to female plumage spottiness therefore appear to gain substantial benefits by mating with heavily spotted females. Genetic variation in plumage spottiness is nevertheless maintained as the covariation between offspring body mass and mother plumage spottiness varies annually depending on environmental conditions.

Horizontal transfer of exosomal microRNAs transduce apoptotic signals between pancreatic beta-cells.

BACKGROUND: Diabetes mellitus is a common metabolic disorder characterized by dysfunction of insulin-secreting pancreatic beta-cells. MicroRNAs are important regulators of beta-cell activities. These non-coding RNAs have recently been discovered to exert their effects not only inside the cell producing them but, upon exosome-mediated transfer, also in other recipient cells. This novel communication mode remains unexplored in pancreatic beta-cells. In the present study, the microRNA content of exosomes released by beta-cells in physiological and physiopathological conditions was analyzed and the biological impact of their transfer to recipient cells investigated. RESULTS: Exosomes were isolated from the culture media of MIN6B1 and INS-1 derived 832/13 beta-cell lines and from mice, rat or human islets. Global profiling revealed that the microRNAs released in MIN6B1 exosomes do not simply reflect the content of the cells of origin. Indeed, while a subset of microRNAs was preferentially released in exosomes others were selectively retained in the cells. Moreover, exposure of MIN6B1 cells to inflammatory cytokines changed the release of several microRNAs. The dynamics of microRNA secretion and their potential transfer to recipient cells were next investigated. As a proof-of-concept, we demonstrate that if cel-miR-238, a C. Elegans microRNA not present in mammalian cells, is expressed in MIN6B1 cells a fraction of it is released in exosomes and is transferred to recipient beta-cells. Furthermore, incubation of untreated MIN6B1 or mice islet cells in the presence of microRNA-containing exosomes isolated from the culture media of cytokine-treated MIN6B1 cells triggers apoptosis of recipient cells. In contrast, exosomes originating from cells not exposed to cytokines have no impact on cell survival. Apoptosis induced by exosomes produced by cytokine-treated cells was prevented by down-regulation of the microRNA-mediating silencing protein Ago2 in recipient cells, suggesting that the effect is mediated by the non-coding RNAs. CONCLUSIONS: Taken together, our results suggest that beta-cells secrete microRNAs that can be transferred to neighboring beta-cells. Exposure of donor cells to pathophysiological conditions commonly associated with diabetes modifies the release of microRNAs and affects survival of recipient beta-cells. Our results support the concept that exosomal microRNAs transfer constitutes a novel cell-to-cell communication mechanism regulating the activity of pancreatic beta-cells.

Derivation of an observer model adapted to irregular signals based on convolution channels.

Anthropomorphic model observers are mathe- matical algorithms which are applied to images with the ultimate goal of predicting human signal detection and classification accuracy across varieties of backgrounds, image acquisitions and display conditions. A limitation of current channelized model observers is their inability to handle irregularly-shaped signals, which are common in clinical images, without a high number of directional channels. Here, we derive a new linear model observer based on convolution channels which we refer to as the "Filtered Channel observer" (FCO), as an extension of the channelized Hotelling observer (CHO) and the nonprewhitening with an eye filter (NPWE) observer. In analogy to the CHO, this linear model observer can take the form of a single template with an external noise term. To compare with human observers, we tested signals with irregular and asymmetrical shapes spanning the size of lesions down to those of microcalfications in 4-AFC breast tomosynthesis detection tasks, with three different contrasts for each case. Whereas humans uniformly outperformed conventional CHOs, the FCO observer outperformed humans for every signal with only one exception. Additive internal noise in the models allowed us to degrade model performance and match human performance. We could not match all the human performances with a model with a single internal noise component for all signal shape, size and contrast conditions. This suggests that either the internal noise might vary across signals or that the model cannot entirely capture the human detection strategy. However, the FCO model offers an efficient way to apprehend human observer performance for a non-symmetric signal.

Emergent power hierarchies and group performance (Published online: 7 Oct. 2014)

In newly formed groups, informal hierarchies emerge automatically and readily. In this study, we argue that emergent group hierarchies enhance group performance (Hypothesis 1) and we assume that the more the power hierarchy within a group corresponds to the task-competence differences of the individual group members, the better the group performs (Hypothesis 2). Twelve three-person groups and 28 four-person groups were investigated while solving the Winter Survival Task. Results show that emerging power hierarchies positively impact group performance but the alignment between task-competence and power hierarchy did not affect group performance. Thus, emergent power hierarchies are beneficial for group performance and although they were on average created around individual group members' competence, this correspondence was not a prerequisite for better group performance.

A model of gender prejudice, power, and discrimination: How hierarchy-enhancing factors predominate over hierarchy-attenuating factors

Gender inequalities remain an issue in our society and particularly in the workplace. Several factors can explain this gender difference in top-level managerial positions such as career ambitions but also biases against women. In our chapter, we propose a model explaining why gender inequalities and particularly discrimination against women is still present in our societies despite social norms and existing legislation on gender equality. To this purpose, we review research on discrimination through two different approaches, (a) a prejudice approach through the justification-suppression model developed by Crandall and Eshleman (2003) and (b) a power approach through the social dominance theory (Pratto, Sidanius, Stallworth, & Malle, 1994; Sidanius & Pratto, 1999). In our work, we integrate these two approaches and propose a model of gender prejudice, power and discrimination. The integration of these two approaches contributes to a better understanding of how discrimination against women is formed and maintained over time.

Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics.

Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association studies (GWAS) across genes and pathways is a strategy to improve statistical power and gain biological insight. Here, we present Pascal (Pathway scoring algorithm), a powerful tool for computing gene and pathway scores from SNP-phenotype association summary statistics. For gene score computation, we implemented analytic and efficient numerical solutions to calculate test statistics. We examined in particular the sum and the maximum of chi-squared statistics, which measure the strongest and the average association signals per gene, respectively. For pathway scoring, we use a modified Fisher method, which offers not only significant power improvement over more traditional enrichment strategies, but also eliminates the problem of arbitrary threshold selection inherent in any binary membership based pathway enrichment approach. We demonstrate the marked increase in power by analyzing summary statistics from dozens of large meta-studies for various traits. Our extensive testing indicates that our method not only excels in rigorous type I error control, but also results in more biologically meaningful discoveries.