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Recolector de Ciencia Abierta, RECOLECTA
Doctoral thesis . 2024
License: CC BY NC ND
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Nuevos modelos celulares y animales para el estudio del cáncer y el envejecimiento

Authors: Rodríguez Arango, Javier;

Nuevos modelos celulares y animales para el estudio del cáncer y el envejecimiento

Abstract

El envejecimiento y sus enfermedades asociadas tienen un impacto social y económico cada vez mayor como consecuencia del progresivo envejecimiento de las sociedades. La OMS prevé que la población de más de 60 años se duplique para 2030 y la población de más de 80 años se triplique para 2050. En este contexto, es imprescindible profundizar en el estudio de los procesos asociados al envejecimiento y sus enfermedades asociadas. En la presente Tesis Doctoral hemos contribuido al estudio de estos procesos generando nuevos modelos murinos y celulares de desarrollo de patologías asociadas al envejecimiento como son la Leucemia Linfática Crónica (LLC) y las alteraciones metabólicas, así como un modelo celular para la identificación de genes candidatos de reversión de senescencia, un proceso inherente al envejecimiento, mediante el uso de un sistema basado en CRISPR/Cas9.

Country
Spain
Related Organizations
Keywords

Nuevos modelos murinos, Envejecimiento, Cáncer

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selected citations
These citations are derived from selected sources.
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!
0
Average
Average
Average
Green