Showing 101 - 120 results of 125,733 for search '(((( auc values decrease ) OR ( i levels increased ))) OR ( ((i large) OR (a large)) decrease ))', query time: 2.07s Refine Results
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    Deletion of murine <i>Rhoh</i> leads to de-repression of <i>Bcl-6</i> via decreased KAISO levels and accelerates a malignancy phenotype in a murine model of lymphoma by Hiroto Horiguchi (3215001)

    Published 2022
    “…The loss of Rhoh in Bcl-6<sup>Tg</sup> mice led to a more rapid disease progression. Mechanistically, we demonstrated that deletion of Rhoh in these murine lymphoma cells was associated with decreased levels of the RhoH binding partner KAISO, a dual-specific Zinc finger transcription factor, de-repression of KAISO target Bcl-6, and downregulation of the BCL-6 target Blimp-1. …”
  3. 103

    Modelling of Large Protein Complexes by Patrick Bryant (11606596)

    Published 2022
    “…However, predicting protein complexes with more than a handful of chains is still unfeasible, as the accuracy rapidly decreases with the number of chains and the protein size is limited by the memory on a GPU. …”
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    Capturing the Transient Microstructure of a Physically Assembled Gel Subjected to Temperature and Large Deformation by Rosa Maria Badani Prado (11501833)

    Published 2021
    “…Here, we report the real-time change in the structure of physically assembled triblock copolymer gels that consist of 10 and 20 wt % of poly­(styrene)–poly­(isoprene)–poly­(styrene) [PS–PI–PS] triblock copolymer in mineral oil (i) during the gelation process with decreasing temperature, (ii) subjected to large oscillatory deformation, and (iii) during the stress-relaxation process after the application of a step strain. …”
  6. 106

    Capturing the Transient Microstructure of a Physically Assembled Gel Subjected to Temperature and Large Deformation by Rosa Maria Badani Prado (11501833)

    Published 2021
    “…Here, we report the real-time change in the structure of physically assembled triblock copolymer gels that consist of 10 and 20 wt % of poly­(styrene)–poly­(isoprene)–poly­(styrene) [PS–PI–PS] triblock copolymer in mineral oil (i) during the gelation process with decreasing temperature, (ii) subjected to large oscillatory deformation, and (iii) during the stress-relaxation process after the application of a step strain. …”
  7. 107

    Data_Sheet_1_The Proximal Drivers of Large Fires: A Pyrogeographic Study.docx by Hamish Clarke (8666307)

    Published 2020
    “…As in most fire-prone environments, the majority of annual burned area is due to a relatively small number of large fires. We train and test an Artificial Neural Network’s ability to predict spatial patterns in the probability of large fires (>1,250 ha) in forests and grasslands as a function of proxies of the four major controls on fire activity. …”
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