| Summary: | 碩士 === 國立臺灣大學 === 化學研究所 === 107 === There is a high chance for a human to have adverse health outcomes because of the long term chronic exposure under a polluted environment or having improper lifestyles. However, the interactions between the human, surrounding environment and the lifestyles are complicated and hard to fathom with only one single technique. Therefore, we demonstrated examples of clarifying these interactions by combining multiple techniques.
The behaviors and conditions of individuals influence the environment. As a result, screening the composition of the chemicals of indoor dust allows us to get a deeper insight into the relationships between individuals and the environment. On the other hand, to understand the human health-habit interaction, we investigated the effect of chewing betel quid and intaking functional food. In our approach, we apply mass spectrometry (MS) to obtain diverse and high-quality information from various samples. Time-resolved chemical information was also obtained by tandem mass spectrometry technique. Furthermore, combining the MS data with high-throughput data processing strategies, such as GNPS and machine learning, we were able to analyze tremendous data within a little amount of time and to use the same framework in different samples.
In this thesis, we used mass spectrometry combining analysis strategies to demonstrate that (1) the relationship between human, surrounding environment and the lifestyles can be understood by the combination of tandem mass spectrometry and data analysis platforms, including GNPS and supervised machine learning; (2) applying pDART significantly increase the analysis throughput while maintaining the quantitative accuracy compared to the traditional LC-MS approach.
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