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Time for a Change in the Research Paradigm for Alzheimers Disease: The Value of a Chaotic Matrix Modeling Approach

机译:改变阿尔茨海默氏病研究范式的时机:混沌矩阵建模方法的价值

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摘要

The amyloid cascade hypothesis, based on the genetic data from early onset, familial forms of the disease, has been the dominant model for many years and involves over production and deposition of the beta amyloid protein as causal in the disease process. However, it does not apply very well to the more common, later onset, sporadic form of the disease, where a wider range of factors appear to be involved in disease progression. Over recent years, data illustrating reciprocal interactions between the amyloid precursor protein (APP) and its various metabolites with many factors involved in normal synaptic plasticity have emerged. These feedback relationships have the potential to affect the complex kinase cascades involved in every aspect of neuronal function. Further, data regarding the multiple roles of the presenilins have the potential to allow the over expression and deposition of the amyloid beta protein to be both a cause and consequence of disease progression, with relevance in both sporadic and familial of Alzheimer's disease (AD). Disease progression might be better explained by a chaotic matrix of factors and raises the question again whether AD should be approached as a single entity or as a syndrome, with important consequences for disease identification and treatment.
机译:淀粉样蛋白级联假说基于疾病的早期发病,家族形式的遗传数据,多年来一直是主要模型,涉及β淀粉样蛋白的过度生产和沉积,这是疾病过程中的原因。但是,它不适用于这种疾病的更常见,更晚发作的散发形式,在该形式中,广泛的因素似乎与疾病的发展有关。近年来,已经出现了说明淀粉样蛋白前体蛋白(APP)及其各种代谢物与正常突触可塑性中涉及的许多因素之间相互相互作用的数据。这些反馈关系可能会影响神经元功能各个方面涉及的复杂激酶级联反应。此外,关于早老蛋白的多种作用的数据有可能使淀粉样β蛋白的过度表达和沉积成为疾病进展的原因和结果,与散发性和家族性阿尔茨海默氏病(AD)有关。疾病发展可能通过混沌的因素矩阵来更好地解释,并再次提出一个问题,即应将AD作为一个整体还是作为一个综合症,对疾病的识别和治疗具有重要的意义。

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