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    Method for treating cancer using betulinic acid rich herbal extract
    2.
    发明申请
    Method for treating cancer using betulinic acid rich herbal extract 审中-公开
    使用富含桦木酸的草药提取物治疗癌症的方法

    公开(公告)号：US20060159783A1

    公开(公告)日：2006-07-20

    申请号：US11219482

    申请日：2005-09-02

    申请人： Rama Mukherjee ,  Dhiraj Khattar ,  Manu Jaggi ,  Anu Singh ,  Mukesh Kumar ,  Honey Bala

    发明人： Rama Mukherjee ,  Dhiraj Khattar ,  Manu Jaggi ,  Anu Singh ,  Mukesh Kumar ,  Honey Bala

    IPC分类号： A61K36/906

    CPC分类号： A61K31/56 ,  A61K36/725

    摘要： This invention relates to an orally effective herbal extract-based composition having broad-spectrum anticancer activity, more specifically a method of treating, inhibiting and/or preventing malignant tumors of the colon, intestine, stomach, breast, melanoma, glioblastoma, lung, cervix, ovary, prostate, oral cavity, larynx, liver, pancreas, kidney, bladder, endothelial cells, leukemia and myeloma using a herbal extract of Zizyphus, rich in betulinic acid. An advantage of the extract is that the betulinic acid has low systemic toxicity. The extract inhibits Protein Kinase C activity of cancer cells and induces apoptosis.

    摘要翻译： 本发明涉及具有广谱抗癌活性的口服有效的草药提取物组合物，更具体地，涉及治疗，抑制和/或预防结肠，肠，胃，乳腺，黑素瘤，成胶质细胞瘤，肺，子宫颈恶性肿瘤的方法 ，卵巢，前列腺，口腔，喉，肝，胰腺，肾，膀胱，内皮细胞，白血病和骨髓瘤，使用梓属的草药提取物，富含桦木酸。 提取物的优点是桦木酸具有低的全身毒性。 提取物抑制癌细胞的蛋白激酶C活性并诱导细胞凋亡。

    AUTOMATED FIELD-MAPPING OF ACCOUNT NAMES FOR FORM POPULATION
    3.
    发明申请
    AUTOMATED FIELD-MAPPING OF ACCOUNT NAMES FOR FORM POPULATION 审中-公开

    公开(公告)号：US20180285982A1

    公开(公告)日：2018-10-04

    申请号：US15472266

    申请日：2017-03-28

    申请人： Yogish Pai ,  Anu Singh ,  Steve George Goyette ,  Ram Shamanna ,  Peter Thomas ,  Madhusudhanan Dharumaraj

    发明人： Yogish Pai ,  Anu Singh ,  Steve George Goyette ,  Ram Shamanna ,  Peter Thomas ,  Madhusudhanan Dharumaraj

    IPC分类号： G06Q40/00 ,  G06Q10/10 ,  G06Q10/06 ,  G06F9/44

    摘要： A system for account mapping includes functionality for obtaining more than one labeled accounts labeled by more than one accountant; pre-processing more than one labeled accounts using natural language processing, using the more than one pre-processed labeled accounts to train an account mapping model that performs multinomial classification; receiving an account name from an accounting application where the account name includes a text label for an account included in a chart of accounts; generating an account mapping by applying the account mapping model to the account name, where the account mapping includes a type of the account, a sub-type of the account, a code, and a series associated with an accounting form; returning the account mapping to the accounting application through an Application Programming Interface (API); and receiving a corrected account mapping from an accountant and using the corrected account mapping as a new text label to incrementally update the account mapping model.