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1. 发明授权

US07570356B2 System and method for classifying cells and the pharmaceutical treatment of such cells using Raman spectroscopy 有权
标题翻译：使用拉曼光谱分析细胞的系统和方法以及这种细胞的药物处理
公开(公告)号：US07570356B2
公开(公告)日：2009-08-04
申请号：US11650378
申请日：2007-01-05
申请人： Janice L. Panza , John Maier , Jason Neiss
发明人： Janice L. Panza , John Maier , Jason Neiss
IPC分类号： G01J3/44 , G01J3/00
CPC分类号： G01J3/44 , G01J3/28 , G01J3/36 , G01N15/1475 , G01N21/65 , G01N2015/1006 , G01N2015/1488 , G01N2021/656
摘要： A system and method to distinguish normal cells from apoptotic cells. A pre-determined vector space is selected where the vector space mathematically describes a first plurality of reference Raman data sets for normal cells and a second plurality of reference Raman data sets for apoptotic cells. A sample is irradiated with substantially monochromatic light generating a target Raman data set based on scattered photons. The target Raman data set is transformed into a vector space defined by the pre-determined vector space. A distribution of transformed data is analyzed in the pre-determined vector space. Based on the analysis, the sample is classified as containing normal cells, apoptotic cells, and a combination of normal and apoptotic cells. The sample includes the step of treating the sample with a pharmaceutical agent prior to irradiating the sample. Based on the classification, the therapeutic efficiency of the pharmaceutical agent is assessed.
摘要翻译：将正常细胞与凋亡细胞区分开的系统和方法。选择预定矢量空间，其中矢量空间在数学上描述用于正常细胞的第一多个参考拉曼数据集和用于凋亡细胞的第二多个参考拉曼数据集。用基本上单色的光照射样品，产生基于散射光子的目标拉曼数据集。目标拉曼数据集被转换成由预定向量空间定义的向量空间。在预定向量空间中分析变换数据的分布。基于分析，样品被分类为含有正常细胞，凋亡细胞，以及正常细胞和凋亡细胞的组合。样品包括在照射样品之前用药剂处理样品的步骤。根据分类，评估药剂的治疗效果。

2. 发明申请

US20100093015A1 Spectroscopic systems and methods for classifying and pharmaceutically treating cells 有权
标题翻译：用于分类和药物治疗细胞的光谱系统和方法
公开(公告)号：US20100093015A1
公开(公告)日：2010-04-15
申请号：US12462350
申请日：2009-08-03
申请人： Janice L. Panza , John Maier , Jason Neiss
发明人： Janice L. Panza , John Maier , Jason Neiss
IPC分类号： C12Q1/02 , C12M1/34
CPC分类号： G01J3/44 , G01J3/10 , G01J3/36 , G01N15/1475 , G01N21/6458 , G01N21/65 , G01N2015/1006 , G01N2015/1488 , G02B21/0096
摘要： A system and method to distinguish normal cells from cells having undergone a biochemical change. A pre-determined vector space is selected where the vector space mathematically describes a first plurality of reference spectral data sets for normal cells and a second plurality of reference spectral data sets for cells having undergone a biochemical change. A sample is irradiated to generate a target spectral data set based on photons absorbed, reflected, emitted, or scattered by the sample. The target spectral data set is transformed into a pre-determined vector space. A distribution of transformed data is analyzed in the pre-determined vector space. Based on the analysis, the sample is classified as containing normal cells, cells having undergone a biochemical change, and combinations thereof. The method includes treating the sample with a pharmaceutical agent prior to irradiating the sample and using the classification to assess the efficiency of the pharmaceutical agent.
摘要翻译：将正常细胞与经历生物化学变化的细胞区分开的系统和方法。选择预定向量空间，其中矢量空间数学地描述正常小区的第一多个参考频谱数据集，以及已经历生化变化的小区的第二多个参考频谱数据集。照射样品以基于样品吸收，反射，发射或散射的光子产生目标光谱数据集。将目标光谱数据集转换为预定向量空间。在预定向量空间中分析变换数据的分布。基于该分析，将样品分类为含有正常细胞，经历生物化学变化的细胞及其组合。该方法包括在照射样品之前用药剂处理样品并使用分类来评估药剂的效率。

3. 发明申请

US20080273199A1 Spectroscopic system and method for predicting outcome of disease 有权
标题翻译：光谱系统和预测疾病结局的方法
公开(公告)号：US20080273199A1
公开(公告)日：2008-11-06
申请号：US12070010
申请日：2008-02-14
申请人： John Maier , Jeffrey Cohen , Janice L. Panza , Amy J. Drauch
发明人： John Maier , Jeffrey Cohen , Janice L. Panza , Amy J. Drauch
IPC分类号： G01J3/44
CPC分类号： G01N21/65 , G01J3/02 , G01J3/0291 , G01J3/0294 , G01J3/2823 , G01J3/44 , G01J2003/2826 , G01N2021/656 , G01N2201/1293 , G01N2201/1296
摘要： A system and method to predict the progression of disease of a test sample. A group of known biological samples is provided. Each known biological sample has an associated known outcome including a non-diseased sample or a diseased sample. A Raman data set is obtained for each known biological sample. Each Raman data set is analyzed to identify a diseased or non-diseased reference Raman data set depending on whether respective biological sample is the non-diseased sample or the diseased sample. A first database is generated where the first database contains reference Raman data sets for all diseased samples. A second database is generated where the second database contains reference Raman data sets for all non-diseased samples. A test Raman data set of a test biological sample is received, where the test biological sample has an unknown disease status. A diagnostic is provided as to whether the test sample is a non-diseased sample or a diseased sample. The diagnostic is obtained by comparing the test Raman data set against the reference Raman data sets in the first and the second databases using a chemometric technique. A prediction of the progression of disease may be then provided.
摘要翻译：一种预测测试样本疾病进展的系统和方法。提供了一组已知的生物样品。每个已知的生物样品具有相关的已知结果，包括非患病样品或患病样品。获得每个已知生物样品的拉曼数据集。分析每个拉曼数据集，以根据相应的生物样品是非患病样品还是患病样品来鉴定患病或非患病参考拉曼数据集。生成第一个数据库，其中第一个数据库包含所有患病样本的参考拉曼数据集。生成第二数据库，其中第二数据库包含所有非患病样本的参考拉曼数据集。接受测试生物样品的测试拉曼数据集，其中测试生物样品具有未知的疾病状态。提供了关于测试样品是否是非患病样品或患病样品的诊断。通过使用化学计量技术将测试拉曼数据集与第一和第二数据库中的参考拉曼数据集进行比较来获得诊断。可以提供疾病进展的预测。

4. 发明授权

US07808633B2 Spectroscopic system and method for predicting outcome of disease 有权
标题翻译：光谱系统和预测疾病结局的方法
公开(公告)号：US07808633B2
公开(公告)日：2010-10-05
申请号：US12070010
申请日：2008-02-14
申请人： John Maier , Jeffrey Cohen , Janice L. Panza , Amy J. Drauch
发明人： John Maier , Jeffrey Cohen , Janice L. Panza , Amy J. Drauch
IPC分类号： G01J3/44 , G01N21/65
CPC分类号： G01N21/65 , G01J3/02 , G01J3/0291 , G01J3/0294 , G01J3/2823 , G01J3/44 , G01J2003/2826 , G01N2021/656 , G01N2201/1293 , G01N2201/1296
摘要： A system and method to predict the progression of disease of a test sample. A group of known biological samples is provided. Each known biological sample has an associated known outcome including a non-diseased sample or a diseased sample. A Raman data set is obtained for each known biological sample. Each Raman data set is analyzed to identify a diseased or non-diseased reference Raman data set depending on whether respective biological sample is the non-diseased sample or the diseased sample. A first database is generated where the first database contains reference Raman data sets for all diseased samples. A second database is generated where the second database contains reference Raman data sets for all non-diseased samples. A test Raman data set of a test biological sample is received, where the test biological sample has an unknown disease status. A diagnostic is provided as to whether the test sample is a non-diseased sample or a diseased sample. The diagnostic is obtained by comparing the test Raman data set against the reference Raman data sets in the first and the second databases using a chemometric technique. A prediction of the progression of disease may be then provided.
摘要翻译：一种预测测试样本疾病进展的系统和方法。提供了一组已知的生物样品。每个已知的生物样品具有相关的已知结果，包括非患病样品或患病样品。获得每个已知生物样品的拉曼数据集。分析每个拉曼数据集，以根据相应的生物样品是非患病样品还是患病样品来鉴定患病或非患病参考拉曼数据集。生成第一个数据库，其中第一个数据库包含所有患病样本的参考拉曼数据集。生成第二数据库，其中第二数据库包含所有非患病样本的参考拉曼数据集。接受测试生物样品的测试拉曼数据集，其中测试生物样品具有未知的疾病状态。提供了关于测试样品是否是非患病样品或患病样品的诊断。通过使用化学计量技术将测试拉曼数据集与第一和第二数据库中的参考拉曼数据集进行比较来获得诊断。可以提供疾病进展的预测。

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