Research On Hydrogen And Oxygen Stable Isotope Among Residents’ Fingernails Of Different Cities

Stable isotopes technology plays an increasingly important role in inferring spatiotemporal information of people’s life,with the gradual improvement of the judicial authentication and the development of traceability technology.As an emerging chemical tracer,the hydrogen and oxygen stable isotopes are valuable in geoscience,environmental ecology and forensic science.The fingernail,one of the potential and practical biomarkers,has many advantages such as not being afraid of pollution,easy collection and storage,long detection window time limit,clean and safe and so on.It has a high evidence and application value in forensic science and its analytical potential is gradually being tapped at present.It’s of great practical significance to establish the method of inferring spatiotemporal information of people’s life based on stable hydrogen and oxygen stable isotopes in fingernails.280 samples from domestic 9 cities were collected.Theirδ²H andδ¹⁸O values were determined by Elemental Analysis-Isotope Ratio Mass Spectrometer（EA-IRMS）.And their regional differences were analyzed and discussed by three classification models.Sample volume,standards,pretreatment methods and detection conditions were considered and optimized respectively.Among them,pre-treatment methods include cleaning,drying and storaging samples,while the detection conditions include the temperature of combustion tube and chromatographic column.Finally,samples volume were 300±10μg,standards were CBS,KHS,and USGS42.Samples were firstly washed with methanol/chloroform（2:1,v/v）and deionized water successively,and then dried at 80℃for 3.5h.After that,standards and samples were wrapped in Ag cup and stored together in storage box for 7 days.Flash2000 Elemental Analyzer and 253Plus Isotope Ratio Mass Spectrometer were selected for determining theδ²H andδ¹⁸O value.The temperature of combustion tube and chromatographic column was 1300℃and 80℃.δ²H andδ¹⁸O values from demostic nine cities were different,which was related to the altitude,latitude,distance from coastline and so on.It’s difficult to directly distinguish samples by theδ²H andδ¹⁸O values in fingernails.Fisher discriminant analysis,radial basis function neural network and K-nearest neighbor analysis,the several supervised pattern recognition methods,were used as algorithms of constructing classifiers to further differentiate samples.The KNN model,as the optimal model,has the high total classification accuracy and F-measure for differentiating fingernails from demostic nine cities.