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    • 13. 发明申请
    • Abnormalities of Phosphatase 2A (PP2A) for Diagnosis and Treatment of Alzheimer's Disease
    • 磷酸酶2A(PP2A)用于阿尔茨海默病诊断和治疗的异常
    • US20090029355A1
    • 2009-01-29
    • US11660868
    • 2004-11-15
    • Wei-Qin ZhaoDaniel L. Alkon
    • Wei-Qin ZhaoDaniel L. Alkon
    • C12Q1/68C12Q1/42G01N33/53C07K16/00
    • C12Q1/6883C12Q2600/136C12Q2600/158G01N33/6896
    • This invention relates to methods of diagnosing Alzheimer's disease and methods of screening for compounds for the treatment or prevention of Alzheimer's disease. The methods are based upon newly discovered differences in protein phosphatase 2A (PP2A) function and related molecular events in Alzheimer's disease cells compared to control cells. In one embodiment, differences in basal PP2A gene expression in Alzheimer's cells are compared to controls. In another embodiment differences in PP2A protein and enzyme activity are compared in test and control cells. In another embodiment differences in response to substances that inhibit PP2A function are compared. Still another embodiment detects differences in the subcellular distribution of phosphorylated Erk1/2, a substrate of PP2A, in normal and Alzheimer's disease cells. The detection of Alzheimer's disease-specific differences in PP2A function and related events in peripheral tissues provides the basis for highly practical and efficient tests and diagnostic test kits for the early diagnosis of Alzheimer's disease, as well as providing a biochemical basis for identifying therapeutic targets for drug development.
    • 本发明涉及诊断阿尔茨海默病的方法和筛选用于治疗或预防阿尔茨海默病的化合物的方法。 该方法基于新发现的蛋白磷酸酶2A(PP2A)功能和阿尔茨海默病细胞相关分子事件与对照细胞相比的差异。 在一个实施方案中,将阿尔茨海默氏病细胞中基础PP2A基因表达的差异与对照进行比较。 在另一个实施方案中,在测试和对照细胞中比较了PP2A蛋白质和酶活性的差异。 在另一个实施方案中,比较了抑制PP2A功能的物质的反应差异。 另一个实施方案检测正常和阿尔茨海默氏病细胞中磷酸化Erk1 / 2(PP2A底物)的亚细胞分布的差异。 检测外周组织中PP2A功能和相关事件中的阿尔茨海默病特异性差异为高龄实用和有效的测试和诊断试剂盒提供了基础,用于早期诊断阿尔茨海默氏病,并为确定治疗靶点提供了生物化学依据 药物开发。
    • 14. 发明授权
    • Dynamically stable associative learning neural system
    • 动态稳定关联学习神经系统
    • US5402522A
    • 1995-03-28
    • US80860
    • 1993-06-22
    • Daniel L. AlkonThomas P. VoglKim L. Blackwell
    • Daniel L. AlkonThomas P. VoglKim L. Blackwell
    • G06N3/04G06F15/18
    • G06N3/04
    • A dynamically stable associative learning neural network system include a plurality of synapses (122,22-28), a non-linear function circuit (30) and an adaptive weight circuit (150) for adjusting the weight of each synapse based upon the present signal and the prior history of signals applied to the input of the particular synapse and the present signal and the prior history of signals applied to the input of a predetermined set of other synapses. An embodiment of a conditional-signal neuron circuit (100) receives input signals from conditional stimuli and an unconditional-signal neuron circuit (110) receives input signals from unconditional stimuli. A neural network (200) is formed by a set of conditional-signal and unconditional-signal neuron circuits connected by flow-through synapses to form separate paths between each input (215) and a corresponding output (245). In one embodiment, the neural network (200) is initialized by varying the weight of the input signals from conditional stimuli, until a dynamic equilibrium is reached.
    • 动态稳定的关联学习神经网络系统包括多个突触(122,22-28),非线性函数电路(30)和自适应加权电路(150),用于根据本信号调整每个突触的重量 以及施加到特定突触的输入的信号的先前历史和当前信号以及施加到预定的其它突触组的输入的信号的先前历史。 条件信号神经元电路(100)的实施例从条件刺激接收输入信号,无条件信号神经元电路(110)从无条件刺激接收输入信号。 神经网络(200)由一组通过流通突触连接的条件信号和无条件信号神经元电路形成,以在每个输入(215)和相应的输出(245)之间形成分离的路径。 在一个实施例中,通过改变来自条件刺激的输入信号的权重来初始化神经网络(200),直到达到动态平衡。