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Hunsinger, Scott ; Janicki, Thomas (Ed.)To investigate the state-of-the-art of virtual reality in special education, we reviewed the related research over the past ten years. Strategies and approaches of the study design have been characterized and categorized based on their research focuses. Both perspectives from the special educators and the students with special needs are addressed. This study reveals that immersive virtual reality is effective in special education, while challenges still remain in this area. We provide insights for future studies and also call for more collaboration among researchers, practitioners, and educators.more » « lessFree, publicly-accessible full text available November 1, 2024
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Abstract MicroRNAs (miRNAs) are important regulators of genes expression. Their levels are precisely controlled through modulating the activity of the microprocesser complex (MC). Here, we report that JANUS, a homology of the conserved U2 snRNP assembly factor in yeast and human, is required for miRNA accumulation. JANUS associates with MC components Dicer-like 1 (DCL1) and SERRATE (SE) and directly binds the stem-loop of pri-miRNAs. In a hypomorphic janus mutant, the activity of DCL1, the numbers of MC, and the interaction of primary miRNA transcript (pri-miRNAs) with MC are reduced. These data suggest that JANUS promotes the assembly and activity of MC through its interaction with MC and/or pri-miRNAs. In addition, JANUS modulates the transcription of some pri-miRNAs as it binds the promoter of pri-miRNAs and facilitates Pol II occupancy of at their promoters. Moreover, global splicing defects are detected in janus. Taken together, our study reveals a novel role of a conserved splicing factor in miRNA biogenesis.
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Free, publicly-accessible full text available October 1, 2024
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Afocal telescopes are often used as foreoptics to existing imaging systems to allow for application flexibility. To properly combine an afocal telescope with an existing imaging system, the exit pupil of the afocal telescope and the entrance pupil of the imaging system must be coincident. Additionally, the exit pupil of the afocal telescope must be well-formed; that is, it must be the correct size and shape to mitigate pupil-matching challenges. This work introduces processes for designing freeform afocal telescopes with an emphasis on understanding how to analyze and control the exit pupil quality of such systems. The included 3-mirror design examples demonstrate the advantages of using freeform surfaces in afocal systems and quantify the tradeoffs required to improve the exit pupil quality.
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Free, publicly-accessible full text available April 5, 2024
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Free, publicly-accessible full text available March 1, 2024
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Free, publicly-accessible full text available February 1, 2024
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Abstract Quantitative assessment of single cell fluxome is critical for understanding the metabolic heterogeneity in diseases. Unfortunately, laboratory-based single cell fluxomics is currently impractical, and the current computational tools for flux estimation are not designed for single cell-level prediction. Given the well-established link between transcriptomic and metabolomic profiles, leveraging single cell transcriptomics data to predict single cell fluxome is not only feasible but also an urgent task. In this study, we present FLUXestimator, an online platform for predicting metabolic fluxome and variations using single cell or general transcriptomics data of large sample-size. The FLUXestimator webserver implements a recently developed unsupervised approach called single cell flux estimation analysis (scFEA), which uses a new neural network architecture to estimate reaction rates from transcriptomics data. To the best of our knowledge, FLUXestimator is the first web-based tool dedicated to predicting cell-/sample-wise metabolic flux and metabolite variations using transcriptomics data of human, mouse and 15 other common experimental organisms. The FLUXestimator webserver is available at http://scFLUX.org/, and stand-alone tools for local use are available at https://github.com/changwn/scFEA. Our tool provides a new avenue for studying metabolic heterogeneity in diseases and has the potential to facilitate the development of new therapeutic strategies.