RNA-Binding protein HuR and the members of miR-200 family play an unconventional role in the regulation of c-Jun mRNA

Post-transcriptional gene regulation is a fundamental step for coordinating cellular response in a variety of processes. RNA-binding proteins (RBPs) and microRNAs (miRNAs) are the most important factors responsible for this regulation. Here we report that different components of the miR-200 family are involved in c-Jun mRNA regulation with the opposite effect. While miR-200b inhibits c-Jun protein production, miR-200a tends to increase the JUN amount through a stabilization of its mRNA. This action is dependent on the presence of the RBP HuR that binds the 3′UTR of c-Jun mRNA in a region including the mir-200a binding site. The position of the binding site is fundamental; by mutating this site, we demonstrate that the effect is not micro-RNA specific. These results indicate that miR-200a triggers a microRNA-mediated stabilization of c-Jun mRNA, promoting the binding of HuR with c-Jun mRNA. This is the first example of a positive regulation exerted by a microRNA on an important oncogene in proliferating cells

Ariel - Volume 8 Number 1

Executive Editor James W. Lockard, Jr. Issue Editor Michael J. Grimes Business Manager Neeraj K. Kanwal Managing Editor Edward H. Jasper University News Richard J. Perry World News William D.B. Hiller Opinions Elizabeth A. McGuire Features Patrick P. Sokas Sports Desk Shahab S. Minassian Managing Associate Brenda Peterson Photography Robert D. Lehman, Jr. Graphics Christine M. Kuhnl

Gaussian Approximation Potentials: the accuracy of quantum mechanics, without the electrons

We introduce a class of interatomic potential models that can be automatically generated from data consisting of the energies and forces experienced by atoms, derived from quantum mechanical calculations. The resulting model does not have a fixed functional form and hence is capable of modeling complex potential energy landscapes. It is systematically improvable with more data. We apply the method to bulk carbon, silicon and germanium and test it by calculating properties of the crystals at high temperatures. Using the interatomic potential to generate the long molecular dynamics trajectories required for such calculations saves orders of magnitude in computational cost.Comment: v3-4: added new material and reference

Ariel - Volume 8 Number 3

Executive Editor James W. Lockard, Jr. Business Manager Neeraj K. Kanwal University News Richard J . Perry World News Doug Hiller Opinions Elizabeth A. McGuire Features Patrick P. Sokas Sports Desk Shahab S. Minassian Managing Editor Edward H. Jasper Managing Associate Brenda Peterson Photography Editor Robert D. Lehman. Jr. Graphics Christine M. Kuhnl

Deep interactive evolution

This paper describes an approach that combines generative adversarial networks (GANs) with interactive evolutionary computation (IEC). While GANs can be trained to produce lifelike images, they are normally sampled randomly from the learned distribution, providing limited control over the resulting output. On the other hand, interactive evolution has shown promise in creating various artifacts such as images, music and 3D objects, but traditionally relies on a hand-designed evolvable representation of the target domain. The main insight in this paper is that a GAN trained on a specific target domain can act as a compact and robust genotype-to-phenotype mapping (i.e. most produced phenotypes do resemble valid domain artifacts). Once such a GAN is trained, the latent vector given as input to the GAN's generator network can be put under evolutionary control, allowing controllable and high-quality image generation. In this paper, we demonstrate the advantage of this novel approach through a user study in which participants were able to evolve images that strongly resemble specific target images.Comment: 16 pages, 5 figures, Published at EvoMUSART EvoStar 201