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    Pyrazolopyrimidine compounds
    93.
    发明专利
    Pyrazolopyrimidine compounds 未知

    公开(公告)号：NZ707432A

    公开(公告)日：2020-01-31

    申请号：NZ70743213

    申请日：2013-11-15

    Applicant: UNIV HEALTH NETWORK

    Inventor： LIU YONG ,  PAULS HEINZ W ,  LAUFER RADOSLAW ,  LI SZE-WAN ,  SAMPSON PETER BRENT ,  FEHER MIKLOS ,  NG GRACE ,  PATEL NARENDRA KUMAR B ,  LANG YUNHUI

    IPC: C07D487/04 ,  A61K31/519 ,  A61P35/00

    Abstract: The present teachings provide a compound represented by structural formula (II-A0), or a pharmaceutically acceptable salt thereof. R1 is –NHRb1, where Rb1 is alkyl which may be optionally substituted with one or more groups as defined herein. R2 is optionally substituted heterocycloalkyl, heteroaryl, optionally substituted aryloxy, optionally substituted heteroaryloxy, optionally substituted heterocyclyloxy or substituted amino (and wherein the substituents are as defined herein). R4 is chloro or methyl. Rd is cyclopropyl. Specific compounds include N-cyclopropyl-4-(7-(((trans-3-hydroxy-3-methylcyclobutyl)methyl)amino)-5-(pyridin-3-yloxy)pyrazolo[1,5-a]pyrimidin-3-yl)-2-methylbenzamide (CFI-402257) and N-cyclopropyl-4-(7-((cyclopropylmethyl)amino)-5-(((1S,2R)-2-hydroxycyclohexyl)amino)pyrazolo[1,5-a]pyrimidin-3-yl)-2-methylbenzamide. Also described are pharmaceutical compositions and uses thereof, such as for the inhibitors of tyrosine threonine kinase (TTK) and for the treatment of cancers such as pancreatic cancer, prostate cancer, lung cancer, melanoma, breast cancer, colon cancer, or ovarian cancer.

    METHODS FOR GENERATING HEPATOCYTES AND CHOLANGIOCYTES FROM PLURIPOTENT STEM CELLS
    96.
    发明专利
    METHODS FOR GENERATING HEPATOCYTES AND CHOLANGIOCYTES FROM PLURIPOTENT STEM CELLS 未知

    公开(公告)号：ZA201506189B

    公开(公告)日：2019-11-27

    申请号：ZA201506189

    申请日：2015-08-25

    Applicant: UNIV HEALTH NETWORK ,  HOSPITAL FOR SICK CHILDREN

    Inventor： GORDON KELLER ,  SHINICHIRO OGAWA ,  ANAND GHANEKAR ,  CHRISTINE BEAR ,  BINITA M KAMATH ,  MINA OGAWA ,  JAMES SURAPISITCHAT

    Abstract: Methods for producing hepatocyte and/or cholangiocyte lineage cells from pluripotent stem cells, the method comprising (a) specifying the extended nodal agonist treated induced endodermal cell population to obtain a cell population comprising hepatocyte and/or cholangiocyte progenitors by contacting the extended nodal agonist treated induced endodermal cell population with specification media comprising a FGF agonist and a BMP4 agonist and/or active conjugates and/or fragments thereof; (b) inducing maturation, and optionally further lineage specification and/or expansion of the hepatocyte and/or cholangiocyte progenitors of the cell population to obtain a population comprising hepatocyte lineage cells such as hepatoblasts, hepatocytes and/or cholangiocytes, the inducing maturation step comprising generating aggregates of the cell population. Optionally, the method also comprises activating the cAMP pathway within the aggregates and forming co-aggregates.

    System and method for filtering time-varying data for physiological signal prediction
    98.
    发明专利
    System and method for filtering time-varying data for physiological signal prediction 未知

    公开(公告)号：GB201913131D0

    公开(公告)日：2019-10-30

    申请号：GB201913131

    申请日：2019-09-12

    Applicant: GOVERNING COUNCIL OF THE UNIV OF TORONTO ,  UNIV HEALTH NETWORK

    Abstract: Systems and methods for filtering time-varying data for filtering and extracting a predicted physiological signal. A method including: segmenting the time-varying data into temporal windows; using a trained filter machine learning model, predicting an error for each prediction of the physiological signal for each window of time-varying data, the filter machine learning model trained using physiological signal predictions based on training time-varying data and known values of the physiological signal for the training time-varying data; discarding each window of time-varying data when the predicted error for such window is greater than a threshold; and where the window of time-varying data is not discarded, outputting at least one of the window of time-varying data and the predicted error for each prediction of the physiological signal.

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