34 research outputs found

    Dissection of Splicing Regulation at an Endogenous Locus by Zinc-Finger Nuclease-Mediated Gene Editing

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    Sequences governing RNA splicing are difficult to study in situ due to the great difficulty of traditional targeted mutagenesis. Zinc-finger nuclease (ZFN) technology allows for the rapid and efficient introduction of site-specific mutations into mammalian chromosomes. Using a ZFN pair along with a donor plasmid to manipulate the outcomes of DNA repair, we introduced several discrete, targeted mutations into the fourth intron of the endogenous BAX gene in Chinese hamster ovary cells. Putative lariat branch points, the polypyrimidine tract, and the splice acceptor site were targeted. We recovered numerous otherwise isogenic clones carrying the intended mutations and analyzed the effect of each on BAX pre-mRNA splicing. Mutation of one of three possible branch points, the polypyrimidine tract, and the splice acceptor site all caused exclusion of exon five from BAX mRNA. Interestingly, these exon-skipping mutations allowed usage of cryptic splice acceptor sites within intron four. These data demonstrate that ZFN-mediated gene editing is a highly effective tool for dissection of pre-mRNA splicing regulatory sequences in their endogenous context

    Addressing climate change with behavioral science: a global intervention tournament in 63 countries

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    Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors

    Addressing climate change with behavioral science:A global intervention tournament in 63 countries

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    Toward Supporting CS1 Instructors and Learners With Fine-Grained Topic Detection in Online Judges

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    Online judges (OJ) are a popular tool to support programming learning. However, one major issue with OJs is that problems are often put together without any associated meta-information that could, for example, be used to help classify problems. This meta-information could be extremely valuable to help users quickly find what types of problems they need most. To face this problem, several OJ administrators have recently begun manually annotating the topics of problems based on computer science-related subjects, such as dynamic programming, graphs, and data structures. Initially, these topics were used to support programming competitions and experienced learners. However, with OJs being increasingly used to support CS1 classes, such topic annotation needs to be extended to suit CS1 learners and instructors. In this work, for the first time, to the best of our knowledge, we propose and validate a predictive model that can automatically detect fine-grained topics of problems based on the CS1 syllabus. After experimenting with many shallow and deep learning models with different word representations based on cutting-edge NLP techniques, our best model is a CNN, achieving an F1-score of 88.9%. We then present how our model can be used for various applications, including (i) facilitating the search process of problems for CS1 learners and instructors and (ii) how it can be integrated into a system to recommend problems in OJs
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