紡織品中分散染料的檢測研究和代謝組學預測吉非替尼對非小細胞肺癌療效探究
發(fā)布時間：2018-08-14 20:09
【摘要】：第一部分：紡織品中十七種分散染料的檢測研究紡織品與人類生活息息相關(guān),其中的致敏分散染料的使用不當勢必會影響身體健康。本課題利用新型的檢測手段超高效合相色譜-質(zhì)譜聯(lián)用的方法對紡織品常用的17種致敏分散染料進行檢測分析,主要做了以下研究內(nèi)容：1.實驗應用超高效合相色譜-三重四級桿串聯(lián)質(zhì)譜法(UPC2-TQMS),建立了紡織品中十七種致敏分散染料—分散橙1,分散黃39,分散橙37,分散橙3,分散藍124,分散黃9,分散黃49,分散紅1,分散黃3,分散藍3,分散紅11,分散藍106,分散紅17,分散棕1,分散藍102,分散黃1,分散藍1的分析方法。實驗以超聲萃取為樣品前處理手段,考察了固定相、柱溫、背壓等儀器條件對分離度的影響,最終采用Waters ACQUITY UPC2TM BEH(1.7μm, 3×100 mm I.D.)色譜柱進行分離,柱溫45℃,背壓1600 psi,流動相為CO2(A)和甲醇(B),流速2 mL·min-1,流出時間5 min,通過質(zhì)譜多反應監(jiān)測模式(MRM),得到樣品的定量限為0.1-2.0μg·mL-1,檢出限是0.02～1.0μg·mL-1,線性相關(guān)系數(shù)大于0.99,加標回收率是70.55～103.03%,相對標準偏差(RSD)小于9%(n=5),方法重現(xiàn)性較好且用于實際樣品檢測。2.考察了BEH、BEH 2-Ethyl-pyridine、HSS C18 SB以及CSH Fluorophenyl四種色譜柱對不同基團的分散染料的分離檢測情況。結(jié)果表明,對于HSS C18 SB柱,樣品整體保留時間延長。含有蒽醌結(jié)構(gòu)的染料在CSH Fluorophenyl中出峰較晚,該固定相對含有芳香結(jié)構(gòu)順反異構(gòu)體具有很好的選擇性及分離度。這部分內(nèi)容提供了含有偶氮、葸醌、苯胺、羥基類的物質(zhì)用于四種固定相適用性的參考依據(jù)。第二部分：代謝組學方法預測吉非替尼對非小細胞肺癌患者療效的探究吉非替尼作為治療非小細胞肺癌的主要藥物之一有較好的治療效果,同時價格不菲。但吉非替尼并不是對所有非小細胞肺癌患者都有療效,尋找有效的生物標志物預測服用吉非替尼肺癌患者的治療效果具有重要意義,不僅可以降低病人的經(jīng)濟負擔,而且還幫助醫(yī)生選擇正確有效的治療方案。本實驗運用超高效液相色譜-高分辨飛行時間質(zhì)譜聯(lián)用技術(shù)(UHPLC-QTOFMS)對134個生存時間不同的肺癌患者的血清進行分析,結(jié)合統(tǒng)計學軟件對結(jié)果進行代謝組學研究。主要內(nèi)容和結(jié)果如下：1.利用甲醇溶劑對1 34個非小細胞肺癌患者的血清進行沉淀蛋白前處理,樣品用UHPLC-QTOFMS上機檢測。具體分析條件如下：色譜柱是Waters ACQUITY UHPLCTM BEH C,8(1.7 μm,2.1×100 mm I.D.),柱溫45℃,流動相由甲醇(A)-0.2%甲酸的水溶液(B)組成,流速0.35 mL·min-1,樣品洗脫時間為22 min。134個血清樣品連續(xù)進樣,并采集電噴霧電離源(ESI)的正、負模式下的樣品信息,最終獲得代謝指紋圖譜。2.通過Markerlynx V4.1軟件將圖譜數(shù)據(jù)轉(zhuǎn)為三維矩陣,進行峰對齊、峰匹配以及歸一化,導入SIMCA-P軟件中進行偏最小二乘-判別分析,通過SPSS軟件進行Kaplan-Meier生存時間分析,Logrank檢驗,并運用COX回歸模型進行多因素分析,最終找出22個重要的差異代謝物,從中進一步篩選出2種潛在代謝物。3.通過飛行時間質(zhì)譜獲得的精確分子質(zhì)量,以及二極質(zhì)譜碎片斷裂分析,在HMDB數(shù)據(jù)庫中找到匹配代謝物信息,從而推斷標志物,初步解釋可能的生物學意義。最終實驗確定了兩個代謝物為PC類磷脂化合物,為臨床治療非小細胞肺癌方面提供有效的治療方案。
[Abstract]:The first part is about the determination of seventeen disperse dyes in textiles. There is a close relationship between textiles and human life. Improper use of sensitized disperse dyes is bound to affect human health. The main research contents are as follows: 1. The 17 sensitized disperse dyes in textiles, disperse orange 1, disperse yellow 39, disperse orange 37, disperse orange 3, disperse blue 124, disperse yellow 9, disperse yellow 49, disperse red 1, disperse yellow 3, disperse blue 3, disperse red, disperse red, disperse orange 1, disperse blue 3, disperse red, disperse orange 1, disperse orange 3, disperse blue 3, disperse red, disperse orange 1, disperse orange 1, dispers 11, Disperse Blue 106, Disperse Red 17, Disperse Brown 1, Disperse Blue 102, Disperse Yellow 1, Disperse Blue 1. The influence of the stationary phase, column temperature and back pressure on the separation was investigated by ultrasonic extraction. Finally, the separation was carried out by Waters ACQUITY UPC2TM BEH (1.7 micron, 3 *100 mm I.D.) column at 45 C. The mobile phase was CO2 (A) and methanol (B), the flow rate was 2 mL min 1, the flow time was 5 min. The quantitative limit was 0.1-2.0 UG mL 1, the detection limit was 0.02-1.0 UG mL 1, the linear correlation coefficient was over 0.99, the recovery was 70.55-103.03%, and the RSD was less than 9% (n = 5). The separation and determination of disperse dyes with different groups on BEH, BEH 2-Ethyl-pyridine, HSS C18 SB and CSH Fluorophenyl columns were investigated. The results showed that for HSS C18 SB column, the overall retention time of the sample was prolonged. Dyes containing anthraquinone structure were found in CSH Fluorophenyl. This section provides a reference for the applicability of four stationary phases containing azo, anthraquinone, aniline and hydroxyl groups. Part II: Metabonomic methods to predict the efficacy of gefitinib in patients with non-small cell lung cancer. However, gefitinib is not effective for all patients with non-small cell lung cancer. It is important to look for effective biomarkers to predict the efficacy of gefitinib in the treatment of lung cancer. Ultra-high performance liquid chromatography-high resolution time-of-flight mass spectrometry (UHPLC-QTOFMS) was used to analyze the serum of 134 lung cancer patients with different survival time, and metabonomics study was carried out with statistical software. The contents and results are as follows: 1. The serum samples of 134 patients with non-small cell lung cancer were pretreated with methanol and detected by UHPLC-QTOFMS. The specific analysis conditions are as follows: Waters ACQUITY UHPLC TM BEH C, 8 (1.7 micron, 2.1 *100 mm I.D.), column temperature 45 and mobile phase is water-soluble methanol (A) - 0.2% formic acid. The metabolic fingerprint was obtained by collecting the positive and negative patterns of the electrospray ionization source (ESI). 2. The metabolic fingerprint was transformed into a three-dimensional matrix by Markerlynx V4.1 software, and the peak alignment, peak matching and normalization were performed. Partial least squares-discriminant analysis was performed in SIMCA-P software, Kaplan-Meier survival time analysis was performed by SPSS software, Logrank test was performed, and COX regression model was used for multivariate analysis. Finally, 22 important differential metabolites were identified, and two potential metabolites were further screened out. 3. Accurate fractions were obtained by time-of-flight mass spectrometry. Quantum mass and fragmentation analysis of polar mass spectroscopy were used to identify matching metabolites in the HMDB database to infer markers and preliminarily explain the possible biological significance.
【學位授予單位】：北京化工大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：R734.2;TS197
本文編號：2183984
[Abstract]:The first part is about the determination of seventeen disperse dyes in textiles. There is a close relationship between textiles and human life. Improper use of sensitized disperse dyes is bound to affect human health. The main research contents are as follows: 1. The 17 sensitized disperse dyes in textiles, disperse orange 1, disperse yellow 39, disperse orange 37, disperse orange 3, disperse blue 124, disperse yellow 9, disperse yellow 49, disperse red 1, disperse yellow 3, disperse blue 3, disperse red, disperse red, disperse orange 1, disperse blue 3, disperse red, disperse orange 1, disperse orange 3, disperse blue 3, disperse red, disperse orange 1, disperse orange 1, dispers 11, Disperse Blue 106, Disperse Red 17, Disperse Brown 1, Disperse Blue 102, Disperse Yellow 1, Disperse Blue 1. The influence of the stationary phase, column temperature and back pressure on the separation was investigated by ultrasonic extraction. Finally, the separation was carried out by Waters ACQUITY UPC2TM BEH (1.7 micron, 3 *100 mm I.D.) column at 45 C. The mobile phase was CO2 (A) and methanol (B), the flow rate was 2 mL min 1, the flow time was 5 min. The quantitative limit was 0.1-2.0 UG mL 1, the detection limit was 0.02-1.0 UG mL 1, the linear correlation coefficient was over 0.99, the recovery was 70.55-103.03%, and the RSD was less than 9% (n = 5). The separation and determination of disperse dyes with different groups on BEH, BEH 2-Ethyl-pyridine, HSS C18 SB and CSH Fluorophenyl columns were investigated. The results showed that for HSS C18 SB column, the overall retention time of the sample was prolonged. Dyes containing anthraquinone structure were found in CSH Fluorophenyl. This section provides a reference for the applicability of four stationary phases containing azo, anthraquinone, aniline and hydroxyl groups. Part II: Metabonomic methods to predict the efficacy of gefitinib in patients with non-small cell lung cancer. However, gefitinib is not effective for all patients with non-small cell lung cancer. It is important to look for effective biomarkers to predict the efficacy of gefitinib in the treatment of lung cancer. Ultra-high performance liquid chromatography-high resolution time-of-flight mass spectrometry (UHPLC-QTOFMS) was used to analyze the serum of 134 lung cancer patients with different survival time, and metabonomics study was carried out with statistical software. The contents and results are as follows: 1. The serum samples of 134 patients with non-small cell lung cancer were pretreated with methanol and detected by UHPLC-QTOFMS. The specific analysis conditions are as follows: Waters ACQUITY UHPLC TM BEH C, 8 (1.7 micron, 2.1 *100 mm I.D.), column temperature 45 and mobile phase is water-soluble methanol (A) - 0.2% formic acid. The metabolic fingerprint was obtained by collecting the positive and negative patterns of the electrospray ionization source (ESI). 2. The metabolic fingerprint was transformed into a three-dimensional matrix by Markerlynx V4.1 software, and the peak alignment, peak matching and normalization were performed. Partial least squares-discriminant analysis was performed in SIMCA-P software, Kaplan-Meier survival time analysis was performed by SPSS software, Logrank test was performed, and COX regression model was used for multivariate analysis. Finally, 22 important differential metabolites were identified, and two potential metabolites were further screened out. 3. Accurate fractions were obtained by time-of-flight mass spectrometry. Quantum mass and fragmentation analysis of polar mass spectroscopy were used to identify matching metabolites in the HMDB database to infer markers and preliminarily explain the possible biological significance.
【學位授予單位】：北京化工大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：R734.2;TS197
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