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系統識別號 U0026-0108201719311300
論文名稱(中文) 利用超高效液相層析高解析質譜儀偵測毛髮中鄰苯二甲酸酯類的暴露標記作為長期暴露的評估
論文名稱(英文) Detection of phthalate exposure markers in hairs using UPLC-HRMS for long-term exposure assessment
校院名稱 成功大學
系所名稱(中) 環境醫學研究所
系所名稱(英) Institute of Environmental and Occupational Health
學年度 105
學期 2
出版年 106
研究生(中文) 曹嘉云
研究生(英文) Chia-Yun Tsao
學號 S76044094
學位類別 碩士
語文別 英文
論文頁數 95頁
口試委員 指導教授-廖寶琦
召集委員-陳皓君
口試委員-廖寶玫
口試委員-許菁芳
中文關鍵字 鄰苯二甲酸二丙基庚酯  暴露標記  毛髮  長期暴露  鄰苯二甲酸酯類 
英文關鍵字 DPHP  exposure markers  hairs  long-term exposure  phthalate 
學科別分類
中文摘要 生物監測鄰苯二甲酸酯類暴露最常見的方法為偵測尿液中的鄰苯二甲酸酯類代謝物,然而鄰苯二甲酸酯類代謝物在體內會快速地被排出,因此尿液樣本被視為僅能代表短期的暴露情況。相較於尿液,毛髮可能可以提供長達幾個月的暴露評估,因此本研究的目的為找尋毛髮中鄰苯二甲酸二丙基庚酯(DPHP)的暴露標記,並利用老鼠模型來探討毛髮是否能用來作為長期暴露的評估。以口服給予Wistar大鼠五種不同劑量的DPHP連續七天,收集DPHP暴露期間(第1和7天)和暴露後(第14和28天)的尿液樣本及暴露後(第28天)的毛髮樣本。利用質量虧損過濾法(MDF)、同位素追蹤法(SMAIT)和正交最小平方區別分析法(OPLS-DA)來找尋在尿液與毛髮中的暴露標記,並藉由檢定劑量效應關係來驗證暴露標記。在第1、7、14和28天的尿液中,MDF/SMAIT分別找到12、19、5、0個被驗證的暴露標記,而OPLS-DA找到45、63、7、0個被驗證的暴露標記。在28天的毛髮中,MDF/SMAIT分別找尋到6個被驗證的標記,而OPLS-DA找尋到31個被驗證的標記。MDF/SMAIT和OPLS-DA在不同天的尿液與毛髮中一共找到108個暴露標記,這些暴露標記被用來探討長期暴露的評估。在第1、7、14和28天的尿液中分別有65、86、28和0個暴露標記具有劑量效應關係,在28天的毛髮中則有37個暴露標記,結果顯示停止暴露DPHP後,相較於尿液,毛髮能被用來作為DPHP長期暴露的評估和代表過去的暴露。以第7天尿液和28天毛髮為代表來比較尿液與毛髮中的暴露標記,我們發現在MDF/SMAIT找到的暴露標記中,雖然有5個暴露標記同時在尿液與毛髮中具有劑量效應關係,但分別有14和1個標記僅能在尿液或毛髮中觀察到劑量效應關係,在OPLS-DA找到的標記中有22個交集,然而分別有48和14個標記僅能在尿液或毛髮中觀察到劑量效應關係。除此之外我們也觀察到DPHP的一階代謝物MPHP僅在毛髮中具有劑量效應關係,在尿液中則無劑量效應關係,且4個先前報導過的DPHP代謝物在尿液中的訊號強度排序與在毛髮中不同。結果顯示暴露標記的化學結構不同可能會導致尿液與毛髮中訊號強度的差異,因此當毛髮被用來作為長期暴露評估時,應使用在毛髮中找尋到的暴露標記來進行暴露評估。36個毛髮的暴露標記中有12個標記的結構被認為是DPHP結構相關的代謝物,其中有6個暴露標記的訊號強度大於4個已知的DPHP代謝物,這6個暴露標記因具有較高的訊號強度和潛在的結構專一性,因此可能比已知的代謝物更適合用來作為暴露的評估。
英文摘要 The most common way of biomonitoring phthalate exposure is by detecting the urinary phthalate metabolites. Because phthalate metabolites are rapidly excreted out of the body via urine, urine samples are considered to represent short-term exposure. Compared to urine, hairs potentially provide a longer determination windows for several months. The aim of this study is to identify di-2(propylheptyl) phthalate (DPHP) exposure markers in urine and hairs and to investigate whether hairs can be used for long-term exposure assessments using a rat model. Wistar rats were orally administrated with 5 different DPHP dosages for 7 days. The urine samples were collected during (the 1st and 7th days) and after (the 14th, and 28th days) exposure to DPHP and hair samples were collected after exposure to DPHP (the 28th days). The exposure marker candidates were identified by mass defect filter (MDF), signal mining algorithm with isotope tracing (SMAIT), and orthogonal partial least squares-discriminant analysis (OPLS-DA) and validated by examining dose-response relationships in urine and hair samples. In the 1st, 7th, 14th, and 28th day urine, MDF/SMAIT identified 12, 19, 5, and 0 validated exposure markers, respectively, and OPLS-DA identified 45, 63, 7, and 0 validated exposure markers, respectively. In the 28th day hair, MDF/SMAIT identified 6 validated markers and OPLS-DA identified 31 markers. The 108 exposure markers identified by MDF/SMAIT or OPLS-DA in the different day urine or hairs were used to investigate the long-term exposure assessment. A total of 65, 86, 28, and 0 markers showed dose-response in the 1st, 7th, 14th ,and 28th day urine samples, respectively. In the 28th day hair, 37 markers were observed dose-response. The results indicate that hairs can be used for long-term exposure assessments of DPHP and represent the past exposure after stopping administration. Using the 7th day urine and 28th day hair as representative to compare exposure markers in urine and hairs, we observed that 5 markers were identified simultaneously in urine and hairs by MDF/SMAIT, but 14 and 1 markers showed dose-response only in urine or hairs, respectively. OPLS-DA identified the 22 overlapping markers between urine and hairs, but there were 48 and 14 markers showed dose-response only in urine and hairs, respectively. Besides, we observed mono-(2-propylheptyl) phthalate (MPHP) which is a minor urinary DPHP metabolite showed dose-response in hairs but not in urine. The intensity ranking of the 4 previously reported DPHP metabolites in urine was different from that in hairs. These results indicate that the chemical structures may result in the difference of rankings of exposure markers in urine and hairs. When hairs were used for log-term exposure assessments, the exposure markers should be identified in hairs. The structures of 12 out of 36 exposure markers in the 28th day hair were confirmed as DPHP structure-related metabolites. Among these 12 exposure markers, the intensity of 6 markers were greater than 4 known DPHP metabolites. The 6 exposure markers might be better than 4 known DPHP metabolites used for exposure assessment because of higher signal intensity and potential structure specificity.
論文目次 摘要.....................................................I
Abstract...............................................III
致謝.....................................................V
List of Tables........................................VIII
List of Figures.......................................VIII
List of Appendixes......................................IX
Abbreviations............................................X
Chapter 1 Research background............................1
1-1 Di-(2-propylheptyl) phthalate........................1
1-1-1 Physical and chemical properties...................1
1-1-2 Usage of DPHP......................................1
1-1-3 Toxicity of DPHP...................................3
1-1-4 Metabolism of DPHP.................................3
1-1-5 Biomonitoring of DPHP exposure.....................4
1-2 The strategies of exposure marker searching..........5
1-2-1 Mass defect filter (MDF)...........................5
1-2-2 Signal mining algorithm with isotope tracing (SMAIT)..................................................5
1-2-3 Orthogonal partial least squares-discriminant analysis (OPLS-DA).......................................6
Chapter 2 Objectives.....................................7
Chapter 3 Materials and methods..........................8
3-1 Research Scheme......................................8
3-2 Animal experiments..................................10
3-2-1 Rat urine pretreatment............................11
3-2-2 Rat hairs pretreatment............................13
3-2-3 UPLC-HRMS analysis................................14
3-3 Method of exposure markers identification...........16
3-3-1 Data processing...................................16
3-3-2 Mass accuracy calibration.........................16
3-3-3 MDF/SMAIT.........................................17
3-3-4 OPLS-DA...........................................18
3-3-5 Statistics........................................18
3-4 Structure identification of exposure markers........19
3-4-1 UPLC-MS/MS analysis...............................19
3-4-2 Structure identification..........................20
Chapter 4 Results and discussion........................21
4-1 Probable exposure marker candidates identification..21
4-1-1 Exposure marker candidates identified by MDF/SMAIT...............................................21
4-1-2 Exposure marker candidates identified by OPLS-DA..21
4-2 Exposure markers validation using a rat model.......27
4-2-1 Validation of exposure marker in urine identified by MDF/SMAIT...............................................27
4-2-2 Validation of exposure marker in hair identified by MDF/SMAIT...............................................35
4-2-3 Validation of exposure markers in urine identified by OPLS-DA..............................................38
4-2-4 Validation of exposure markers in hair identified by OPLS-DA.................................................51
4-3 Summary of exposure markers identified by MDF/SMAIT, and OPLS-DA.............................................55
4-4 Long-term exposure assessment of DPHP...............63
4-5 A comparison of exposure markers in urine and hairs.65
4-6 Structure identification of exposure markers........72
Chapter 5 Conclusions...................................79
Chapter 6 References....................................81
Appendix................................................84
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