Lifespan extension without fertility reduction following dietary addition of the autophagy activator Torin1 in Drosophila melanogaster

Autophagy is a highly conserved mechanism for cellular repair that becomes progressively down-regulated during normal ageing. Hence, manipulations that activate autophagy could increase lifespan. Previous reports show that manipulations to the autophagy pathway can result in longevity extension in yeast, flies, worms and mammals. Under standard nutrition, autophagy is inhibited by the nutrient sensing kinase Target of Rapamycin (TOR). Therefore, manipulations of TOR that increase autophagy may offer a mechanism for extending lifespan. Ideally, such manipulations should be specific and minimise off-target effects, and it is important to discover additional methods for ‘clean’ lifespan manipulation. Here we report an initial study into the effect of up-regulating autophagy on lifespan and fertility in Drosophila melanogaster by dietary addition of Torin1. Activation of autophagy using this selective TOR inhibitor was associated with significantly increased lifespan in both sexes. Torin1 induced a dose-dependent increase in lifespan in once-mated females. There was no evidence of a trade-off between longevity and fecundity or fertility. Torin1-fed females exhibited significantly elevated fecundity, but also elevated egg infertility, resulting in no net change in overall fertility. This supports the idea that lifespan can be extended without trade-offs in fertility and suggest that Torin1 may be a useful tool with which to pursue anti-ageing research

Crowdsourcing hypothesis tests: Making transparent how design choices shape research results

To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer fiveoriginal research questions related to moral judgments, negotiations, and implicit cognition. Participants from two separate large samples (total N > 15,000) were then randomly assigned to complete one version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: materials from different teams renderedstatistically significant effects in opposite directions for four out of five hypotheses, with the narrowest range in estimates being d = -0.37 to +0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for two hypotheses, and a lack of support for three hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, while considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim.</div