NEW METALLOCENE CATALYST AND USE THEREOF
    1.
    发明申请

    公开(公告)号:WO2022248517A1

    公开(公告)日:2022-12-01

    申请号:PCT/EP2022/064136

    申请日:2022-05-24

    Abstract: The present invention relates to a catalyst of Formula (I) wherein R2, R3, R4, R5, R6, R7, R8, R9, R10, R11, L1, M1, Q1, and Q2 have the meaning defined in the description and claims. The present invention also relates to a catalyst composition comprising at least one catalyst according to the invention, an optional activator; an optional support; and an optional co-catalyst. The present invention also relates to the use of a catalyst or catalyst composition according to the invention for the preparation of an olefin polymer. The present invention also relates to an olefin polymerization process, the process comprising: contacting a catalyst or a catalyst composition according to the invention, with an olefin monomer, optionally hydrogen, and optionally one or more olefin comonomers; polymerizing the monomer, and the optionally one or more olefin comonomers, in the presence of the at least one catalyst composition, and optional hydrogen, thereby obtaining an olefin polymer. The present invention also relates to olefin polymers and articles comprising said olefin polymer.

    METHOD FOR GENERATING A SURGICAL PROCESS MODEL

    公开(公告)号:WO2020239961A1

    公开(公告)日:2020-12-03

    申请号:PCT/EP2020/064930

    申请日:2020-05-28

    Abstract: A method for generation a surgical process model as a temporal sequence of semantic data describing a surgical process at a semantic level. The method comprises obtaining from the simulator (1000) at least one temporal sequence of digital data (1001) describing at a physical level the virtual surgical process simulated by the simulator in a virtual space, wherein the digital data comprise interaction data representing interactions between objects in the virtual space and kinematic data related to object displacements in the virtual space; automatically converting (1010, 1020, 1040, 1060), based on at least one configuration file (1002), said at least one temporal sequence of digital data into said temporal sequence of semantic data. The configuration file (1002) comprises semantic data representative of one or more surgical process activities and a set of one or more activity detection rules respectively associated with one or more surgical process activities defined by the semantic data.

    METHOD FOR PREDICTING THE SURVIVAL TIME OF A PATIENT SUFFERING FROM HEPATOCELLULAR CARCINOMA

    公开(公告)号:WO2018189215A1

    公开(公告)日:2018-10-18

    申请号:PCT/EP2018/059229

    申请日:2018-04-11

    CPC classification number: C12Q1/6886 C12Q2600/118 C12Q2600/158

    Abstract: The invention relates to the prediction of the outcome of a patient suffering from HCC. This study was conducted to determine whether non-proliferative HCCs carrying wild-type CTNNB1 warrant consideration as a distinct, clinically relevant tumor subclass. The inventors constructed an 1133-HCC transcriptomic metadata set and identified four HCC subclasses by discriminant analyses and hierarchical clustering. They developed a method to predict CTNNB1 mutations in an independent set of 225 β-catenin-sequenced HCCs and validated HCC classification, CTNNB1 mutation prediction and survival analyses in an independent 210-HCC full-genome sequenced RNAseq dataset. Altogether, analysis of data from 1568 HCC patients identified two new well-differentiated, low-proliferation subclasses of HCCs. Both subclasses (periportal-type and perivenous-type) showed favorable outcomes. Periportal-type HCCs showed the highest 2-year recurrence-free survival rates by multivariate analysis, suggesting that these tumors have the lowest potential for early recurrence among all HCCs. Thus, the invention relates to a method for predicting the survival time of a patient suffering from HCC comprising determining the expression level of the genes elected in the group consisting in AGXT, FETUB, GLS2, GNMT, SLC10A1 and SLC22A7.

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