Publications by authors named "Yun-Nam Chan"
The aim of this pilot study was to predict the risk of gestational diabetes mellitus (GDM) by the elemental content in fingernails and urine with machine learning analysis. Sixty seven pregnant women (34 control and 33 GDM patient) were included. Fingernails and urine were collected in the first and second trimesters, respectively.
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- Humans are exposed to various environmental pollutants, and abnormal levels of essential elements in the body can be linked to different diseases.
- Although blood is commonly used for biomonitoring, it only indicates short-term exposure and involves invasive sampling, leading researchers to explore non-invasive alternatives like hair, nails, and urine.
- The review discusses analytical methods for non-invasive samples, including sample collection and preparation, while addressing the need for better correlations between these samples and blood for effective human biomonitoring.