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Identification of Human Age Using Trace Element Concentrations in Hair and the Support Vector Machine Method
- Source :
- Biological Trace Element Research, 143(3), 1441-1450. Humana Press
- Publication Year :
- 2011
- Publisher :
- Humana Press, 2011.
-
Abstract
- Trace element content in hair is affected by the age of the donor. Hair samples of subjects from four counties in China where people are known to have long lifespan ("longevity counties") were collected and the trace element content determined. Samples were subdivided into three age groups based on the age of the donors from whom these were taken: children (0-15 years); elderly (80-99 years); and centenarians (a parts per thousand yen100 years). We compared the trace element content in hair of different age groups of subjects. Support vector machine classification results showed that a non-linear polynomial kernel function could be used to classify the three age groups of people. Age did not have a significant effect on the content of Ca and Cd in human hair. The content of Li, Mg, Mn, Zn, Cr, Cu, and Ni in human hair changed significantly with age. The magnitude of the age effect on trace element content in hair was in the order Cu > Zn > Ni > Mg > Mn > Cr > Li. Cu content in hair decreased significantly with increasing age. The hair of centenarians had higher levels of Li and Mn, and lower levels of Cr, Cu, and Ni comparing with that of the children and elderly subjects. This could be a beneficial factor of their long lifespan.
- Subjects :
- Adult
Age effect
Support vector machine
Adolescent
Endocrinology, Diabetes and Metabolism
Clinical Biochemistry
Biochemistry
Inorganic Chemistry
Young Adult
Animal science
Age
Elderly
Age groups
Centenarians
Humans
Child
Children
Aged
Support vector machine classification
Aged, 80 and over
integumentary system
Chemistry
Biochemistry (medical)
Metallurgy
Infant, Newborn
Trace element
Infant
General Medicine
Middle Aged
Trace Elements
Child, Preschool
sense organs
Hair
Subjects
Details
- Language :
- English
- ISSN :
- 01634984
- Volume :
- 143
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Biological Trace Element Research
- Accession number :
- edsair.doi.dedup.....8627b7c8ebc683c0968142ba25903a0d