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1.
Org Biomol Chem ; 20(14): 2922-2938, 2022 04 06.
Artículo en Inglés | MEDLINE | ID: mdl-35322840

RESUMEN

An aplyronine A-swinholide A hybrid, consisting of the macrolactone part of aplyronine A and the side chain part of swinholide A, was designed, synthesized, and biologically evaluated. This hybrid induced protein-protein interactions between two major cytoskeletal proteins actin and tubulin in the same manner as aplyronine A, and exhibited potent cytotoxicity and actin-depolymerizing activity. The importance of the methoxy group in the N,N,O-trimethylserine ester was clarified by the structure-activity relationship studies of the amino acid moiety by using the hybrid analogs. Furthermore, the comparison of the actin-depolymerizing activities between the side chain analogs of aplyronine A and swinholide A showed that the side chain analog of swinholide A had much weaker actin-depolymerizing activity than that of aplyronine A.


Asunto(s)
Antineoplásicos , Macrólidos , Actinas/efectos de los fármacos , Antineoplásicos/química , Antineoplásicos/farmacología , Células HeLa , Humanos , Macrólidos/química , Macrólidos/farmacología , Toxinas Marinas , Relación Estructura-Actividad
2.
Chem Commun (Camb) ; 54(68): 9537-9540, 2018 Aug 21.
Artículo en Inglés | MEDLINE | ID: mdl-30094443

RESUMEN

An aplyronine A-swinholide A hybrid, consisting of the macrolactone part of aplyronine A and the side chain part of swinholide A, was designed, synthesized, and evaluated for biological activities. The hybrid retained strong cytotoxicity and actin-depolymerizing activity. In addition, the hybrid induced protein-protein interactions (PPI) between actin and tubulin in the manner of aplyronine A.


Asunto(s)
Actinas/metabolismo , Antineoplásicos/farmacología , Macrólidos/farmacología , Toxinas Marinas/farmacología , Tubulina (Proteína)/metabolismo , Antineoplásicos/síntesis química , Antineoplásicos/química , Células HeLa , Humanos , Macrólidos/síntesis química , Macrólidos/química , Toxinas Marinas/síntesis química , Toxinas Marinas/química , Conformación Molecular , Unión Proteica , Estereoisomerismo , Moduladores de Tubulina/síntesis química , Moduladores de Tubulina/química , Moduladores de Tubulina/farmacología
3.
IEEE Trans Syst Man Cybern B Cybern ; 37(5): 1357-72, 2007 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-17926715

RESUMEN

We present a new approach for online incremental word acquisition and grammar learning by humanoid robots. Using no data set provided in advance, the proposed system grounds language in a physical context, as mediated by its perceptual capacities. It is carried out using show-and-tell procedures, interacting with its human partner. Moreover, this procedure is open-ended for new words and multiword utterances. These facilities are supported by a self-organizing incremental neural network, which can execute online unsupervised classification and topology learning. Embodied with a mental imagery, the system also learns by both top-down and bottom-up processes, which are the syntactic structures that are contained in utterances. Thereby, it performs simple grammar learning. Under such a multimodal scheme, the robot is able to describe online a given physical context (both static and dynamic) through natural language expressions. It can also perform actions through verbal interactions with its human partner.


Asunto(s)
Biomimética/métodos , Cibernética/métodos , Procesamiento de Lenguaje Natural , Redes Neurales de la Computación , Reconocimiento de Normas Patrones Automatizadas/métodos , Robótica/métodos , Software de Reconocimiento del Habla , Algoritmos , Inteligencia Artificial , Humanos
4.
Neural Netw ; 20(8): 893-903, 2007 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-17826947

RESUMEN

An enhanced self-organizing incremental neural network (ESOINN) is proposed to accomplish online unsupervised learning tasks. It improves the self-organizing incremental neural network (SOINN) [Shen, F., Hasegawa, O. (2006a). An incremental network for on-line unsupervised classification and topology learning. Neural Networks, 19, 90-106] in the following respects: (1) it adopts a single-layer network to take the place of the two-layer network structure of SOINN; (2) it separates clusters with high-density overlap; (3) it uses fewer parameters than SOINN; and (4) it is more stable than SOINN. The experiments for both the artificial dataset and the real-world dataset also show that ESOINN works better than SOINN.


Asunto(s)
Algoritmos , Inteligencia Artificial , Simulación por Computador , Redes Neurales de la Computación , Biomimética , Análisis por Conglomerados , Cibernética , Retroalimentación , Procesamiento de Imagen Asistido por Computador , Almacenamiento y Recuperación de la Información , Dinámicas no Lineales , Análisis Numérico Asistido por Computador , Reconocimiento de Normas Patrones Automatizadas , Procesamiento de Señales Asistido por Computador
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