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  1. Home
  2. Browse by Author

Browsing by Author "Perez, CA"

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    Acetylcholinesterase accelerates assembly of amyloid-beta-peptides into Alzheimer's fibrils: Possible role of the peripheral site of the enzyme
    (1996) Inestrosa, N.C.; Alvarez, A; Perez, CA; Moreno, RD; Vicente, M; Linker, C; Casanueva, OI; Soto, C; Garrido, J
    Acetylcholinesterase (AChE), an important component of cholinergic synapses, colocalizes with amyloid-beta peptide (A beta) deposits of Alzheimer's brain. We report here that bovine brain AChE, as well as the human and mouse recombinant enzyme, accelerates amyloid formation from wild-type A beta and a mutant A beta peptide, which alone produces few amyloid-like fibrils. The action of AChE was independent of the subunit array of the enzyme, was not affected by edrophonium, an active site inhibitor, but it was affected by propidium, a peripheral anionic binding site ligand. Butyrylcholinesterase, an enzyme that lacks the peripheral site, did not affect amyloid formation. Furthermore, AChE is a potent amyloid-promoting factor when compared with other A beta-associated proteins. Thus, in addition to its role in cholinergic synapses, AChE may function by accelerating A beta formation and could play a role during amyloid deposition in Alzheimer's brain.
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    Acetylcholinesterase, a senile plaque component, affects the fibrillogenesis of amyloid-beta-peptides
    (1995) Alvarez, A; Bronfman, F; Perez, CA; Vicente, M; Garrido, J; Inestrosa, NC
    Acetylcholinesterase (AChE) colocalizes with amyloid-beta peptide (A beta) deposits present in the brain of Alzheimer's patients. Recent studies showed that A beta(1-40) Can adopt two different conformational states in solution (an amyloidogenic conformer, A beta ac, and a non-amyloidogenic conformer, A beta nac) which have distinct abilities to form amyloid fibrils. We report here that AChE binds A beta nac and accelerates amyloid formation by the same peptide. No such effect was observed with A beta ac, the amyloidogenic conformer, suggesting that AChE acts as a 'pathological chaperone' inducing a conformational transition from A beta nac into A beta ac in vitro.
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    Genetic design of biologically inspired receptive fields for neural pattern recognition
    (2003) Perez, CA; Salinas, CA; Estévez, PA; Valenzuela, PM
    This paper proposes a new method to design, through simulated evolution, biologically inspired receptive fields in feed forward neural networks (NNs). The method is intended to enhance pattern recognition performance by creating new neural architectures specifically tuned for a particular pattern recognition problem. It is proposed a combined neural architecture composed of two networks in cascade: a feature extraction network (FEN) followed by a neural classifier. The FEN is composed of several layers with receptive fields constructed by an additive superposition of excitatory and inhibitory fields. A genetic algorithm (GA) is used to select the receptive fields parameters to improve the classification performance. The parameters are the receptive field, size, orientation, and bias as well as the number of different receptive fields in each layer. Based on a random initial population where each individual represents a different neural architecture, the GA creates new enhanced individuals. The method is applied to the problems of handwritten digit classification and face recognition. In both problems, results show strong dependency between the NN classification performance and the receptive fields architecture. The GA selected parameters of the receptive fields that produced improvements in the classification. performance on the test set up to 90.8% for the problem of handwritten digit classification and up to 84.2% for the face recognition problem. On the same test sets, results were compared advantageously to standard feed forward multilayer perceptron (MLP) NNs where receptive fields are not explicitly defined. The MLP reached a maximum classification performance of 84.9% and 77.5% in both problems; respectively.

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