Unity in defence: honeybee workers exhibit conserved molecular responses to diverse pathogens

This is the final version of the article. Available from the publisher via the DOI in this record.Background: Organisms typically face infection by diverse pathogens, and hosts are thought to have developed specific responses to each type of pathogen they encounter. The advent of transcriptomics now makes it possible to test this hypothesis and compare host gene expression responses to multiple pathogens at a genome-wide scale. Here, we performed a meta-analysis of multiple published and new transcriptomes using a newly developed bioinformatics approach that filters genes based on their expression profile across datasets. Thereby, we identified common and unique molecular responses of a model host species, the honey bee (Apis mellifera), to its major pathogens and parasites: the Microsporidia Nosema apis and Nosema ceranae, RNA viruses, and the ectoparasitic mite Varroa destructor, which transmits viruses. Results: We identified a common suite of genes and conserved molecular pathways that respond to all investigated pathogens, a result that suggests a commonality in response mechanisms to diverse pathogens. We found that genes differentially expressed after infection exhibit a higher evolutionary rate than non-differentially expressed genes. Using our new bioinformatics approach, we unveiled additional pathogen-specific responses of honey bees; we found that apoptosis appeared to be an important response following microsporidian infection, while genes from the immune signalling pathways, Toll and Imd, were differentially expressed after Varroa/virus infection. Finally, we applied our bioinformatics approach and generated a gene co-expression network to identify highly connected (hub) genes that may represent important mediators and regulators of anti-pathogen responses. Conclusions: Our meta-analysis generated a comprehensive overview of the host metabolic and other biological processes that mediate interactions between insects and their pathogens. We identified key host genes and pathways that respond to phylogenetically diverse pathogens, representing an important source for future functional studies as well as offering new routes to identify or generate pathogen resilient honey bee stocks. The statistical and bioinformatics approaches that were developed for this study are broadly applicable to synthesize information across transcriptomic datasets. These approaches will likely have utility in addressing a variety of biological questions.This article is a joint effort of the working group TRANSBEE and an outcome of two workshops kindly supported by sDiv, the Synthesis Centre for Biodiversity Sciences within the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, funded by the German Science Foundation (FZT 118). New datasets were performed thanks to the Insect Pollinators Initiative (IPI grant BB/I000100/1 and BB/I000151/1), with participation of the UK-USA exchange funded by the BBSRC BB/I025220/1 (datasets #4, 11 and 14). The IPI is funded jointly by the Biotechnology and Biological Sciences Research Council, the Department for Environment, Food and Rural Affairs, the Natural Environment Research Council, the Scottish Government and the Wellcome Trust, under the Living with Environmental Change Partnershi

Vascular disrupting agents in clinical development

Growth of human tumours depends on the supply of oxygen and nutrients via the surrounding vasculature. Therefore tumour vasculature is an attractive target for anticancer therapy. Apart from angiogenesis inhibitors that compromise the formation of new blood vessels, a second class of specific anticancer drugs has been developed. These so-called vascular disrupting agents (VDAs) target the established tumour vasculature and cause an acute and pronounced shutdown of blood vessels resulting in an almost complete stop of blood flow, ultimately leading to selective tumour necrosis. As a number of VDAs are now being tested in clinical studies, we will discuss their mechanism of action and the results obtained in preclinical studies. Also data from clinical studies will be reviewed and some considerations with regard to the future development are given

Towards a Classification of Non-interactive Computational Assumptions in Cyclic Groups

We study non-interactive computational intractability assumptions in prime-order cyclic groups. We focus on the broad class of computational assumptions which we call target assumptions where the adversary’s goal is to compute concrete group elements. Our analysis identifies two families of intractability assumptions, the q-Generalized Diffie-Hellman Exponent (q-GDHE) assumptions and the q-Simple Fractional (q-SFrac) assumptions (a natural generalization of the q-SDH assumption), that imply all other target assumptions. These two assumptions therefore serve as Uber assumptions that can underpin all the target assumptions where the adversary has to compute specific group elements. We also study the internal hierarchy among members of these two assumption families. We provide heuristic evidence that both families are necessary to cover the full class of target assumptions. We also prove that having (polynomially many times) access to an adversarial 1-GDHE oracle, which returns correct solutions with non-negligible probability, entails one to solve any instance of the Computational Diffie-Hellman (CDH) assumption. This proves equivalence between the CDH and 1-GDHE assumptions. The latter result is of independent interest. We generalize our results to the bilinear group setting. For the base groups, our results translate nicely and a similar structure of non-interactive computational assumptions emerges. We also identify Uber assumptions in the target group but this requires replacing the q-GDHE assumption with a more complicated assumption, which we call the bilinar gap assumption. Our analysis can assist both cryptanalysts and cryptographers. For cryptanalysts, we propose the q-GDHE and the q-SDH assumptions are the most natural and important targets for cryptanalysis in prime-order groups. For cryptographers, we believe our classification can aid the choice of assumptions underpinning cryptographic schemes and be used as a guide to minimize the overall attack surface that different assumptions expose

Physical Attractiveness, Altruism and Cooperation in an Ultimatum Game

Explaining cooperative tendencies through an evolutionary lens has been problematic for theorists. Traditional explanations derive from theories of reciprocity, biological markets, and more recently via partner choice and sexual selection. The sexual selection hypothesis has been tested within game-theoretic frameworks gaining empirical sup- port in explaining the evolution of altruism. Males have been found to be more altruistic towards attractive females. However, previous research has predominantly adopted a design where participants are not engaging with ‘real people’. Instead, participants make decisions when viewing images or hypothetical scenarios without visual cues. The present study aimed to investigate the sexual selection hypothesis using a face-to-face game theoretic framework. One hundred and thirty-eight participants played a 2-round ultimatum game with chocolate coins as the monetary incentive. We find, that physical attractiveness had no influence on generosity and cooperation when participants play a face-to-face ultimatum game. Instead, proposers were fair when allocating stakes, offering an average of half the endowment to responders. This study refutes the link between the sexual selection hypothesis and generosity when playing economic games with real people. Fairness appeared to drive generosity and cooperation

Effects of psychological and psychosocial interventions on sport performance:a meta-analysis

Background: Psychologists are increasingly supporting the quest for performance enhancement in sport and there is a need to evaluate the evidence base underpinning their work. Objectives: To synthesize the most rigorous available research that has evaluated psychological, social, and psychosocial interventions with sport performers on variables relating to their athletic performance, and to address some of the perplexing issues in the sport psychology intervention literature (e.g., do interventions have a lasting effect on sport performance?). Methods: Randomized controlled trials were identified through electronic databases, hand-searching volumes of pertinent journals, scrutinizing reference lists of previous reviews, and contacting experts in the evaluation of interventions in this field. Included studies were required to evaluate the effects of psychological, social, or psychosocial interventions on sport performance in athletes when compared to a no-treatment or placebo-controlled treatment comparison group. A random effects meta-analysis calculating the standardized mean difference (Hedges’ g), meta-regressions, and trim and fill analyses were conducted. Data were analyzed at post-test and follow-up (ranging from 1 to 4 weeks after the intervention finished) assessments. Results: Psychological and psychosocial interventions were shown to enhance sport performance at post-test (k = 35, n = 997, Hedges’ g = 0.57, 95 % CI = 0.22–0.92) and follow-up assessments (k = 8, n = 189, Hedges’ g = 1.16, 95 % CI = 0.25–2.08); no social interventions were included or evaluated. Larger effects were found for psychosocial interventions and there was some evidence that effects were greatest in coach-delivered interventions and in samples with a greater proportion of male participants. Conclusions: Psychological and psychosocial interventions have a moderate positive effect on sport performance, and this effect may last at least a month following the end of the intervention. Future research would benefit from following guidelines for intervention reporting