Genome-wide identification of Ago2 binding sites from mouse embryonic stem cells with and without mature microRNAs

MicroRNAs (miRNAs) are 19–22-nucleotide noncoding RNAs that post-transcriptionally regulate mRNA targets. We have identified endogenous miRNA binding sites in mouse embryonic stem cells (mESCs), by performing photo-cross-linking immunoprecipitation using antibodies to Argonaute (Ago2) followed by deep sequencing of RNAs (CLIP-seq). We also performed CLIP-seq in Dicer[superscript −/−] mESCs that lack mature miRNAs, allowing us to define whether the association of Ago2 with the identified sites was miRNA dependent. A significantly enriched motif, GCACUU, was identified only in wild-type mESCs in 3′ untranslated and coding regions. This motif matches the seed of a miRNA family that constitutes ~68% of the mESC miRNA population. Unexpectedly, a G-rich motif was enriched in sequences cross-linked to Ago2 in both the presence and absence of miRNAs. Expression analysis and reporter assays confirmed that the seed-related motif confers miRNA-directed regulation on host mRNAs and that the G-rich motif can modulate this regulation.Leukemia & Lymphoma Society of AmericaUnited States. Public Health Service (Grant R01-GM34277)United States. Public Health Service (Grant R01-CA133404)National Cancer Institute (U.S.) (Grant P01-CA42063)National Cancer Institute (U.S.) Cancer Center Support (Grant P30-CA14051

Data Lakes: Trends and Perspectives

International audienceAs a relatively new concept, data lake has neither a standard definition nor an acknowledged architecture. Thus, we study the existing work and propose a complete definition and a generic and extensible architecture of data lake. What's more, we introduce three future research axes in connection with our health-care Information Technology (IT) activities. They are related to (i) metadata management that consists of intra- and inter-metadata, (ii) a unified ecosystem for companies' data warehouses and data lakes and (iii) data lake governance

siRNA Nanoparticle Functionalization of Nanostructured Scaffolds Enables Controlled Multilineage Differentiation of Stem Cells

The creation of complex tissues and organs is the ultimate goal in tissue engineering. Engineered morphogenesis necessitates spatially controlled development of multiple cell types within a scaffold implant. We present a novel method to achieve this by adhering nanoparticles containing different small-interfering RNAs (siRNAs) into nanostructured scaffolds. This allows spatial retention of the RNAs within nanopores until their cellular delivery. The released siRNAs were capable of gene silencing BCL2L2 and TRIB2, in mesenchymal stem cells (MSCs), enhancing osteogenic and adipogenic differentiation, respectively. This approach for enhancing a single type of differentiation is immediately applicable to all areas of tissue engineering. Different nanoparticles localized to spatially distinct locations within a single implant allowed two different tissue types to develop in controllable areas of an implant. As a consequence of this, we predict that complex tissues and organs can be engineered by the in situ development of multiple cell types guided by spatially restricted nanoparticles

Dialogical PISA: correct answers are all alike, every incorrect answer is incorrect in its own way

Why do students give incorrect answers in PISA? What are the reasons for giving incorrect answers? Do all incorrect answers reflect only the lack of competence or might even a competent child make a mistake? The aim of this article is to contribute to a better understanding of these issues. In the current investigation, we selected six students who responded incorrectly to one PISA question in mathematics or science when they solved it individually. Then, we analyzed their understanding of the PISA task and their reasoning about it through a dialogical problem solving in triads to identify why they made an incorrect answer. Moreover, we tried to determine how the shared peer interaction might change the understanding and reasoning of the child and enable her/him to solve the task. The results of this study illustrate the differences between incorrect answers reflecting lack of competence and those incorrect answers, which appear for some other reasons. Based on the dialogical problem solving approach, we analyzed these two types of incorrect answers and the reasoning trajectories behind them