Castillo Salazar, David Ricardo
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Preferred name
Castillo Salazar, David Ricardo
Main Affiliation
Ambato
Email
davidcastillo@uti.edu.ec
Scopus Author ID
57210800584

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Chemical profiling and cholinesterase inhibitory activity of five phaedranassa herb. (amaryllidaceae) species from ecuador

2020 , Moreno R. , Tallini L.R. , Castillo Salazar, David Ricardo , Osorio E.H. , Montero E. , Bastida J. , Oleas N.H. , León K.A.

It is estimated that 50 million people in the world live with dementia, 60-70% of whom suffer from Alzheimer's disease (AD). Different factors are involved in the development of AD, including a reduction in the cholinergic neurotransmission level. The Amaryllidaceae plant family contains an exclusive, large, and still understudied alkaloid group characterized by a singular skeleton arrangement and a broad spectrum of biological activities. The chemistry and biodiversity of Ecuadorian representatives of the Phaedranassa genus (Amaryllidaceae) have not been widely studied. In this work, five Ecuadorian Phaedranassa species were examined in vitro for their activity towards the enzymes acetyl- (AChE) and butyrylcholinesterase (BuChE), and the alkaloid profile of bulb extracts was analyzed by GC-MS. The species Phaedranassa cuencana and Phaedranassa dubia showed the most AChE and BuChE inhibitory activity, respectively. To obtain insight into the potential role of the identified alkaloids in these inhibitory effects, docking experiments were carried out, and cantabricine showed in silico inhibitory activity against both cholinesterase structures. Our results show that Amaryllidaceae species from Ecuador are a potential source of new drugs for the palliative treatment of AD. © 2020 by the authors.

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Ontological Model in the Identification of Emotional Aspects in Alzheimer Patients

2023 , Castillo Salazar, David Ricardo , Lanzarini L. , Gómez H. , Thirumuruganandham, S , Castillo Salazar D.X.

The present work describes the development of a conceptual representation model of the domain of the theory of formal grammars and abstract machines through ontological modeling. The main goal is to develop an ontology capable of deriving new knowledge about the mood of an Alzheimer’s patient in the categories of wandering, nervous, depressed, disoriented or bored. The patients are from elderly care centers in Ambato Canton-Ecuador. The population consists of 147 individuals of both sexes, diagnosed with Alzheimer’s disease, with ages ranging from 75 to 89 years. The methods used are the taxonomic levels, the semantic categories and the ontological primitives. All these aspects allow the computational generation of an ontological structure, in addition to the use of the proprietary tool Pellet Reasoner as well as Apache NetBeans from Java for process completion. As a result, an ontological model is generated using its instances and Pellet Reasoner to identify the expected effect. It is noted that the ontologies come from the artificial intelligence domain. In this case, they are represented by aspects of real-world context that relate to common vocabularies for humans and applications working in a domain or area of interest. © 2023 by the authors.

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