MicroRNAs (miRNAs) are a class of 20–24 nt non-coding RNAs that regulate gene expression primarily through post-transcriptional repression or mRNA degradation in a sequence-specific manner. The roles of miRNAs are just beginning to be understood, but the study of miRNA function has been limited by poor understanding of the general principles of gene regulation by miRNAs. Here we used CNE cells from a human nasopharyngeal carcinoma cell line as a cellular system to investigate miRNA-directed regulation of VEGF and other angiogenic factors under hypoxia, and to explore the principles of gene regulation by miRNAs. Through computational analysis, 96 miRNAs were predicted as putative regulators of VEGF. But when we analyzed the miRNA expression profile of CNE and four other VEGF-expressing cell lines, we found that only some of these miRNAs could be involved in VEGF regulation, and that VEGF may be regulated by different miRNAs that were differentially chosen from 96 putative regulatory miRNAs of VEGF in different cells. Some of these miRNAs also co-regulate other angiogenic factors (differential regulation and co-regulation principle). We also found that VEGF was regulated by multiple miRNAs using different combinations, including both coordinate and competitive interactions. The coordinate principle states that miRNAs with independent binding sites in a gene can produce coordinate action to increase the repressive effect of miRNAs on this gene. By contrast, the competitive principle states when multiple miRNAs compete with each other for a common binding site, or when a functional miRNA competes with a false positive miRNA for the same binding site, the repressive effects of miRNAs may be decreased. Through the competitive principle, false positive miRNAs, which cannot directly repress gene expression, can sometimes play a role in miRNA-mediated gene regulation. The competitive principle, differential regulation, multi-miRNA binding sites, and false positive miRNAs might be useful strategies in the avoidance of unwanted cross-action among genes targeted by miRNAs with multiple targets.

Understanding shadows from a single image spontaneously derives into two types of task in previous studies, containing shadow detection and shadow removal. In this paper, we present a multi-task perspective, which is not embraced by any existing work, to jointly learn both detection and removal in an end-to-end fashion that aims at enjoying the mutually improved benefits from each other. Our framework is based on a novel STacked Conditional Generative Adversarial Network (ST-CGAN), which is composed of two stacked CGANs, each with a generator and a discriminator. Specifically, a shadow image is fed into the first generator which produces a shadow detection mask. That shadow image, concatenated with its predicted mask, goes through the second generator in order to recover its shadow-free image consequently. In addition, the two corresponding discriminators are very likely to model higher level relationships and global scene characteristics for the detected shadow region and reconstruction via removing shadows, respectively. More importantly, for multi-task learning, our design of stacked paradigm provides a novel view which is notably different from the commonly used one as the multi-branch version. To fully evaluate the performance of our proposed framework, we construct the first large-scale benchmark with 1870 image triplets (shadow image, shadow mask image, and shadow-free image) under 135 scenes. Extensive experimental results consistently show the advantages of ST-CGAN over several representative state-of-the-art methods on two large-scale publicly available datasets and our newly released one.

We have tested the hypothesis that severe acute respiratory syndrome (SARS) coronavirus protein E (SCoVE) and its homologs in other coronaviruses associate through their putative transmembrane domain to form homooligomeric alpha-helical bundles in vivo. For this purpose, we have analyzed the results of molecular dynamics simulations where all possible conformational and aggregational space was systematically explored. Two main assumptions were considered; the first is that protein E contains one transmembrane alpha-helical domain, with its N- and C-termini located in opposite faces of the lipid bilayer. The second is that protein E forms the same type of transmembrane oligomer and with identical backbone structure in different coronaviruses. The models arising from the molecular dynamics simulations were tested for evolutionary conservation using 13 coronavirus protein E homologous sequences. It is extremely unlikely that if any of our assumptions were not correct we would find a persistent structure for all the sequences tested. We show that a low energy dimeric, trimeric and two pentameric models appear to be conserved through evolution, and are therefore likely to be present in vivo. In support of this, we have observed only dimeric, trimeric, and pentameric aggregates for the synthetic transmembrane domain of SARS protein E in SDS. The models obtained point to residues essential for protein E oligomerization in the life cycle of the SARS virus, specifically N15. In addition, these results strongly support a general model where transmembrane domains transiently adopt many aggregation states necessary for function.

TGF‐β signaling involves a wide array of signaling molecules and multiple controlling events. Scaffold proteins create a functional proximity of signaling molecules and control the specificity of signal transduction. While many components involved in the TGF‐β pathway have been elucidated, little is known about how those components are coordinated by scaffold proteins. Here, we show that Axin activates TGF‐β signaling by forming a multimeric complex consisting of Smad7 and ubiquitin E3 ligase Arkadia. Axin depends on Arkadia to facilitate TGF‐β signaling, as their small interfering RNAs reciprocally abolished the stimulatory effect on TGF‐β signaling. Specific knockdown of Axin or Arkadia revealed that Axin and Arkadia cooperate with each other in promoting Smad7 ubiquitination. Pulse‐chase experiments further illustrated that Axin significantly decreased the half‐life of Smad7. Axin also induces nuclear export of Smad7. Interestingly, Axin associates with Arkadia and Smad7 independently of TGF‐β signal, in contrast to its transient association with inactive Smad3. However, coexpression of Wnt‐1 reduced Smad7 ubiquitination by downregulating Axin levels, underscoring the importance of Axin as an intrinsic regulator in TGF‐β signaling.

Cell-derived exosomes are leading candidates for in vivo drug delivery carriers. In particular, exosomes derived from 293T cells are used most frequently, although exosome dosing has varied greatly among studies. Considering their biological origin, it is crucial to characterize the molecular composition of exosomes if large doses are to be administered in clinical settings. In this study, we present the first comprehensive analysis of the protein, messenger RNA and microRNA profiles of 293T cell-derived exosomes; then, we characterized these data using Gene Ontology annotation and Kyoto Encyclopedia for Genes and Genomes pathway analysis. Our study will provide the basis for the selection of 293T cell-derived exosome drug delivery systems. Profiling the exosomal signatures of 293T cells will lead to a better understanding of 293T exosome biology and will aid in the identification of any harmful factors in exosomes that could cause adverse clinical effects.