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重型肝炎预后相关蛋白质质谱分析及预测模型构建
李烨,王波,邓存良
0
(西南医科大学附属医院感染科)
摘要:
【摘要】 目的 比较不同临床结局乙肝病毒(HBV)相关重型肝炎和正常人血浆中的蛋白质指纹图谱,筛选出与重型肝炎预后相关的差异蛋白,为重型肝炎预后判断提供依据。方法 采用CM10联合表面增强激光解析飞行时间质谱(SELDITOFMS)技术,检测35例HBV相关重型肝炎和15例正常人血浆蛋白质谱获得血浆蛋白指纹图谱。结果 HBV相关重型肝炎和正常人血浆中一共检测出57个蛋白峰,最终筛选出M/Z为M349279、M564911、M393656、M756886、M860112的5个差异蛋白峰建立分类树模型,该模型对重型肝炎预后判断的敏感性为7200%,特异性为10000%,准确性为80%。结论 SELDITOFMS技术可以用于重型肝炎患者预后相关血浆蛋白的筛选,利用这些差异表达的蛋白建立的分类树模型对重型肝炎患者预后判断具有重要的临床价值。
关键词:  重型肝炎  预后模型  蛋白指纹图谱
DOI:
基金项目:四川省重点学科建设项目(SZD0421);四川省卫计委科研项目(130365)
Proteomic mass spectrometry analysis and the prediction model construction associated with prognosis of severe hepatitis
LI Ye,WANG Bo,DENG Cunliang
(Department of Infection, The Affiliated Hospital of Southwest Medical University)
Abstract:
【Abstract】 Objective To obtain the plasma protein fingerprints of HBVrelated severe hepatitis patients with different clinical outcomes and healthy people, screen out differential proteins associated with the prognosis of severe hepatitis, and establish the prediction model using these differential proteins and provide the basis for the prognosis of severe hepatitis. Methods Plasma specimens of patients with HBVrelated severe hepatitis and normal healthy human were detected by SELDITOFMS,and the plasma protein fingerprints were obtained with CM10.Results 57 differently expressed protein peaks were detected by the analysis of Biomarker Wizard software between HBVrelated severe hepatitis patients and healthy controls.The decision tree classification model was composed of 5 discriminative protein peaks selecting from survival group and death group. These differential protein peaks were M 3492_79, M 5649_11, M 3936_56, M 7568_86 and M 8601_12. The sensitivity of the decision tree model to the prognosis of patients with HBVrelated severe hepatitis was 7200%. The specificity and veracity were 10000% and 80%. Conclusion SELDITOFMS can screen out differential proteins associated with the prognosis of severe hepatitis. It is important to use those protein peaks to establish the classification tree model for the clinical outcomes of severe hepatitis.
Key words:  Severe hepatitis  Prognosis mode  Protein fingerprinting

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