RESUMEN
Many of the lifespan-related genes have been identified in eukaryotes ranging from the yeast to human. However, there is limited information available on the longevity genes that are essential for cell proliferation. Here, we investigated whether the essential genes encoding DNA-binding transcription factors modulated the replicative lifespan of Saccharomyces cerevisiae. Heterozygous diploid knockout strains for FHL1, RAP1, REB1, and MCM1 genes showed significantly short lifespan. (1)H-nuclear magnetic resonance analysis indicated a characteristic metabolic profile in the Δfhl1/FHL1 mutant. These results strongly suggest that FHL1 regulates the transcription of lifespan related metabolic genes. Thus, heterozygous knockout strains could be the potential materials for discovering further novel lifespan genes.
Asunto(s)
Proteínas de Unión al ADN/genética , Factores de Transcripción Forkhead/genética , Proteína 1 de Mantenimiento de Minicromosoma/genética , Proteínas de Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/citología , Proteínas de Unión a Telómeros/genética , Factores de Transcripción/genética , Proteínas de Unión al ADN/metabolismo , Factores de Transcripción Forkhead/metabolismo , Eliminación de Gen , Regulación Fúngica de la Expresión Génica , Técnicas de Silenciamiento del Gen , Genes Fúngicos , Metaboloma , Proteína 1 de Mantenimiento de Minicromosoma/metabolismo , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/metabolismo , Proteínas de Saccharomyces cerevisiae/metabolismo , Complejo Shelterina , Proteínas de Unión a Telómeros/metabolismo , Factores de Transcripción/metabolismoRESUMEN
The electrocardiogram (ECG) monitoring has become a helpful tool for detecting a number of heart diseases. High quality ECG is utilized by the physicians for interpretation and identification of physiological and pathological phenomena. ECG recordings, however, are often corrupted by motion artifacts even when patient is sleeping due to his or her positional change. In this paper, we proposed a new method of detecting motion artifact ECG noise during sleeping based on acceleration data. The experimental recordings of ECG and acceleration signal were collected from 8 subjects. The result in this study demonstrated that the proposed approach is effective for detecting corruption of ECG signal.
