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1. 发明申请

WO2007040974A2 METHOD FOR QUANTITATIVELY DETERMINING THE LDL PARTICLE NUMBER IN A DISTRIBUTION OF LDL CHOLESTEROL SUBFRACTIONS 审中-公开
标题翻译：定量分析低密度脂蛋白胆固醇的低密度脂蛋白数量的方法
公开(公告)号：WO2007040974A2
公开(公告)日：2007-04-12
申请号：PCT/US2006/036310
申请日：2006-09-18
申请人： BERKELEY HEARTLAB , CLENDENEN, Faith , BOGGESS, Christopher , RUDERMAN, Frank
发明人： CLENDENEN, Faith , BOGGESS, Christopher , RUDERMAN, Frank
IPC分类号： G01N33/00
CPC分类号： G01N33/92
摘要： The invention provides a method (e.g., a computer algorithm) for calculating a number of particles in a LDL subfraction. The method features the steps of: 1) measuring an initial distribution of LDL particles (e.g., a relative mass distribution) from a blood sample; 2) processing the initial distribution of LDL particles with a mathematical model to determine a modified distribution of LDL particles (e.g., a relative particle distribution); 3) determining a total LDL particle number value from a blood sample; and 4) analyzing both the modified distribution of particles and the total LDL particle number value to calculate the particle number value in an LDL subfraction.
摘要翻译：本发明提供了一种用于计算LDL子分数中的粒子数量的方法（例如，计算机算法）。该方法的特征在于：1）测量来自血液样本的LDL颗粒的初始分布（例如相对质量分布）; 2）用数学模型处理LDL颗粒的初始分布，以确定LDL颗粒的修饰分布（例如，相对颗粒分布）; 3）从血液样品中确定总LDL颗粒数值; 和4）分析改性粒子分布和总LDL粒子数值，以计算LDL亚分数中的粒子数值。

2. 发明申请

WO2003087844A1 A METHOD FOR IDENTIFYING AT RISK CARDIOVASCULAR DISEASE PATIENTS 审中-公开
标题翻译：一种识别风险性心脏病患者的方法
公开(公告)号：WO2003087844A1
公开(公告)日：2003-10-23
申请号：PCT/US2003/011375
申请日：2003-04-11
申请人： BERKELEY HEARTLAB, INC. , SHEWMAKE, David , RUDERMAN, Frank , BOGGESS, Christopher , CLENDENEN, Faith
发明人： SHEWMAKE, David , RUDERMAN, Frank , BOGGESS, Christopher , CLENDENEN, Faith
IPC分类号： G01N33/92
CPC分类号： G01N33/92 , G01N2800/32 , G01N2800/52
摘要： The invention provides a data base of LDL, I, IIa, IIb, IIIa, IIb, IVa, IVb and HDL2a, HDL2b, HDL 3a, HDL 3b and HDL 3c together with patient data such as HDL-C, LDL-C, Apo A, ApoB, Lp(a) and patient personal data useful for treatment, diagnosing, and monitoring cardiovascular disease. The data base contains the LDL and HDL subfraction data in quantitative mg/dl values and permits deriving relationship amongst the LDL and HDL values and cardiovascular disease. Quantitative data permits more effective treatment and monitoring of cardiovascular disease. For example, quantitative differences in LDL and HDL subclass levels can determine the need for more or less aggressive treatment. The data base which includes patient events, procedures, interventions which is correlated to LDL and HDl quantitative subclass data permits development of personalized patient treatment plans and monitoring the effectiveness of such treatment. Thus, LDL and HDL quantitative subfraction data can be used to more effectively treat and monitor cardiovascular disease. The invention, for example, provides a method for identifying patients with normal NCEP lipid levels who are in need of treatment for cardiovascular disease comprising measuring one or more LDL or HDL particle subclass levels and identifying abnormal LDL or HDL subclass levels. LDL III a & b and HDL 2b are preferred subclasses.
摘要翻译：本发明提供LDL，I，IIa，IIb，IIIa，IIb，IVa，IVb和HDL2a，HDL2b，HDL 3a，HDL 3b和HDL 3c的数据库以及患者数据如HDL-C，LDL-C，Apo A，ApoB，Lp（a）和患者个人资料可用于治疗，诊断和监测心血管疾病。数据库包含定量mg / dl值中的LDL和HDL次级分数据，并允许LDL和HDL值与心血管疾病之间的关系。定量数据可以更有效地治疗和监测心血管疾病。例如，LDL和HDL亚类水平的定量差异可以确定对或多或少积极治疗的需要。包括与LDL和HDI定量亚类数据相关的患者事件，程序，干预措施的数据库允许开发个性化的患者治疗计划并监测此类治疗的有效性。因此，LDL和HDL定量分数据可用于更有效地治疗和监测心血管疾病。例如，本发明提供了一种用于鉴定需要治疗心血管疾病的正常NCEP脂质水平的患者的方法，包括测量一种或多种LDL或HDL颗粒亚类水平并鉴定异常的LDL或HDL亚类水平。 LDL III a＆b和HDL 2b是优选的亚类。

3. 发明公开

EP1929290A2 METHOD FOR QUANTITATIVELY DETERMINING THE LDL PARTICLE NUMBER IN A DISTRIBUTION OF LDL CHOLESTEROL SUBFRACTIONS 审中-公开
标题翻译： METHOD FOR LDL胆固醇亚的分布的LDL颗粒的数定量测定
公开(公告)号：EP1929290A2
公开(公告)日：2008-06-11
申请号：EP06803789.4
申请日：2006-09-18
申请人： Berkeley Heartlab
发明人： CLENDENEN, Faith , BOGGESS, Christopher , RUDERMAN, Frank
IPC分类号： G01N33/00
CPC分类号： G01N33/92
摘要： The invention provides a method (e.g., a computer algorithm) for calculating a number of particles in a LDL subfraction. The method features the steps of: 1) measuring an initial distribution of LDL particles (e.g., a relative mass distribution) from a blood sample; 2) processing the initial distribution of LDL particles with a mathematical model to determine a modified distribution of LDL particles (e.g., a relative particle distribution); 3) determining a total LDL particle number value from a blood sample; and 4) analyzing both the modified distribution of particles and the total LDL particle number value to calculate the particle number value in an LDL subfraction.

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