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    C-TERMINAL FRAGMENT OF TETANUS TOXIN (HC) FOR TREATMENT OF DEPRESSION
    12.
    发明申请
    C-TERMINAL FRAGMENT OF TETANUS TOXIN (HC) FOR TREATMENT OF DEPRESSION 有权

    公开(公告)号：US20210361739A1

    公开(公告)日：2021-11-25

    申请号：US16878809

    申请日：2020-05-20

    Applicant: Howard University

    Inventor： Yousef TIZABI

    IPC: A61K38/16

    Abstract: C-terminal domain of the heavy chain of tetanus toxin (Hc-TeTx) provides therapeutic effects in motor impairments associated with Parkinson disease (PD), and provides long lasting antidepressant effects, thus useful in treating and mitigating depression, particularly PD-depression co-morbid condition. A method for treating or mitigating depression, including administrating an effective amount of C-terminal domain of the heavy chain of tetanus toxin (Hc-TeTx) to a subject in need thereof. A method for treating or mitigating motor impairments associated with Parkinson's disease (PD), including administrating an effective amount of C-terminal domain of the heavy chain of tetanus toxin (Hc-TeTx) to a subject in need thereof.

    Voxel-Resolution Myocardial Blood Flow Analysis
    18.
    发明申请
    Voxel-Resolution Myocardial Blood Flow Analysis 审中-公开
    体素分辨率心肌血流分析

    公开(公告)号：US20160242718A1

    公开(公告)日：2016-08-25

    申请号：US15026697

    申请日：2014-10-03

    Applicant: HOWARD UNIVERSITY

    Inventor： John M. M. Anderson

    IPC: A61B6/00 ,  G06T7/00 ,  A61B5/0275

    CPC classification number: A61B6/507 ,  A61B5/0044 ,  A61B5/02755 ,  A61B6/037 ,  G06F19/00 ,  G06T7/0016 ,  G06T2207/10104 ,  G06T2207/30104 ,  G16H50/50

    Abstract: A myocardial blood flow analysis scan includes incorporating a pharmacological kinetic model with the standard factor analysis model where each time activity curve is assumed to be a linear combination of factor curves. Pharmacological kinetics based factor analysis of dynamic structures (K-FADS-II) model can be applied, whereby estimating factor curves in the myocardium can be physiologically meaningful is provided. Additional optional aspects include performing a discretization to transform continuous-time K-FADS-II model into a discrete-time K-FADS-II model and application of an iterative Improved Voxel-Resolution myocardial blood flow (IV-MBF) algorithm. Where the model is applied without assumption that a right ventricle tissue curve and a left ventricle tissue curve obey a particular mathematical relationship, a least squares objective function can be applied to obtain estimates for parameters of the pharmacological kinetic model by applying a majorize-minimize optimization technique to iteratively estimate the curves.

    Abstract translation: 心肌血流分析扫描包括将药理动力学模型与标准因子分析模型结合，其中每个活动曲线被假定为因子曲线的线性组合。 可以应用动态结构（K-FADS-II）模型的药理动力学因子分析，从而提供心肌中估计因子曲线的生理意义。 其他可选方面包括执行离散化以将连续时间的K-FADS-II模型转换为离散时间的K-FADS-II模型，并应用迭代改进的体素分辨率心肌血流（IV-MBF）算法。 在没有假设右心室组织曲线和左心室组织曲线遵循特定数学关系的情况下应用模型的情况下，可以应用最小二乘方目标函数以通过应用主要最小化优化来获得药理动力学模型参数的估计 迭代估计曲线的技术。

    Using An MM-Principle to Enforce a Sparsity Constraint on Fast Image Data Estimation From Large Image Data Sets
    19.
    发明申请
    Using An MM-Principle to Enforce a Sparsity Constraint on Fast Image Data Estimation From Large Image Data Sets 有权
    使用MM原理来强制从大图像数据集快速图像数据估计的稀疏约束

    公开(公告)号：US20160202346A1

    公开(公告)日：2016-07-14

    申请号：US14305934

    申请日：2014-06-16

    Applicant: Howard University

    Inventor： John M. M. Anderson ,  Mandoye Ndoye ,  Oludotun Ode ,  Henry C. Ogworonjo

    IPC: G01S7/292 ,  G01S13/88

    CPC classification number: G01S7/292 ,  G01S7/2923 ,  G01S13/0209 ,  G01S13/885 ,  G01S13/887 ,  G01S13/89 ,  G06K9/00791 ,  G06K9/6277

    Abstract: The mathematical majorize-minimize principle is applied in various ways to process the image data to provide a more reliable image from the backscatter data using a reduced amount of memory and processing resources. A processing device processes the data set by creating an estimated image value for each voxel in the image by iteratively deriving the estimated image value through application of a majorize-minimize principle to solve a maximum a posteriori (MAP) estimation problem associated with a mathematical model of image data from the data. A prior probability density function for the unknown reflection coefficients is used to apply an assumption that a majority of the reflection coefficients are small. The described prior probability density functions promote sparse solutions automatically estimated from the observed data.

    Abstract translation: 数学主要最小化原理以各种方式应用于处理图像数据，以使用减少量的存储器和处理资源从后向散射数据提供更可靠的图像。 处理装置通过使用主要最小化原理迭代地导出估计图像值来求解与数学模型相关联的最大后验（MAP）估计问题，通过为图像中的每个体素创建估计图像值来处理数据集 的图像数据。 用于未知反射系数的先验概率密度函数用于应用大多数反射系数小的假设。 所描述的先验概率密度函数促进从观测数据自动估计的稀疏解。

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