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American Journal of Biochemistry and Biotechnology
Article . 2007 . Peer-reviewed
Data sources: Crossref
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Biomedicine and Informatics Model of Alzheimer’s disease

Authors: Chang-Hua Zou; Kang Cheng;

Biomedicine and Informatics Model of Alzheimer’s disease

Abstract

In a perspective of biomedicine and informatics, the mechanism of Alzheimer's, senile amnesia, or other aging-associated and cognitive impairment related diseases involve four important informative processing procedures: propagation, consolidation, retrieval and cognition, In this study, we systematically model the four procedures based on published experimental data. When modeling the propagation, we develop an equivalent circuit of biological membrane to describe how the neuron signals are propagated, attenuated, compensated, transferred, oscillated and filtered; and how wrong signals are related to the diseases. Our circuit involves complex admittances, resonance angular frequencies, propagating constants, active pump currents, transfer functions in frequency domain and memory functions in time domain. Our circuit explains recurrent of brain neurons and clinical EEG frequencies as well as represents an encoding of current or electric field intensity (EFI). When modeling the consolidation and the retrieval of long term memory (LTM), we emphasize the EFI consists of a non conservative electric field intensity (NCEFI) and a conservative electric field intensity (CEFI). It is mostly a NCEFI of acquired information to evoke an informative flow: from the inherited or mutant DNA to the transcribed RNA, from the transcribed RNA to the translated proteins. Some new synthesized proteins relate to the memory functions. The charges of the proteins and the memory functions mostly store the LTM and play an important role during the LTM retrieval. When modeling the cognition in working memory (WM), our model demonstrates: if a sum of two sets of EFI signals is enhanced positively (or negatively), at a sub-cellular level (especially at the axon hillock), the sum supports a positive (or negative) cognition; otherwise, the sum tends to be no cognition. A set of related brain neurons in WM work organically to vote, by EFI signal outputs through their axons, if they recognize or cognize an object.

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    9
    popularity
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    Average
    influence
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    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Top 10%
Average
gold