SYSTEM AND METHOD FOR CLASIFYING CELLS AND THE PHARMACEUTICAL TREATMENT OF SUCH CELLS USING RAMAN SPECTROSCOPY
    1.
    发明申请
    SYSTEM AND METHOD FOR CLASIFYING CELLS AND THE PHARMACEUTICAL TREATMENT OF SUCH CELLS USING RAMAN SPECTROSCOPY 审中-公开
    使用拉曼光谱法分离细胞的系统和方法以及这种细胞的药物治疗

    公开(公告)号:WO2007081874A2

    公开(公告)日:2007-07-19

    申请号:PCT/US2007000397

    申请日:2007-01-05

    Abstract: 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.

    Abstract translation: 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。

    APPARATUS AND METHOD FOR CHEMICAL IMAGING OF A BIOLOGICAL SAMPLE

    公开(公告)号:CA2586476A1

    公开(公告)日:2006-08-17

    申请号:CA2586476

    申请日:2005-04-28

    Applicant: CHEMIMAGE CORP

    Abstract: In one embodiment, the disclosure relates to a method for determining illumination parameters for a stained sample, the method may include providing a stained sample and obtaining an absorption band of the sample; obtaining an emission band of the sample and determining the illumination parameters for the sample as a function of the absorption band and the emission band of the sample.

    SPECTROSCOPIC SYSTEM AND METHOD FOR PREDICTING OUTCOME OF DISEASE
    4.
    发明申请
    SPECTROSCOPIC SYSTEM AND METHOD FOR PREDICTING OUTCOME OF DISEASE 审中-公开
    光谱学系统和预测疾病预测的方法

    公开(公告)号:WO2008100582A3

    公开(公告)日:2008-10-09

    申请号:PCT/US2008001988

    申请日:2008-02-14

    Abstract: A system and method to predict the progression of disease of a test sample is provided A group of known biological samples is provided, each having an associated known outcome including a non-diseased or diseased sample. A Raman data set is obtained for each known biological sample. Each data set is analyzed to identify a diseased or non-diseased reference data set. A first database is generated which contains reference Raman data sets for all diseased samples. A second-database is generated which contains reference data sets for all non-diseased samples. A test Raman data set of a test biological sample having an unknown disease status is received. A diagnostic is provided as to whether the test sample is non-diseased or diseased The diagnostic is obtained by comparing the test data set against the reference data sets in the databases using a chemometric technique to predict the progression of disease.

    Abstract translation: 提供了一种用于预测测试样品的疾病进展的系统和方法。提供了一组已知的生物样品,每个具有相关联的已知结果,包括非患病或患病样品。 获得每个已知生物样品的拉曼数据集。 分析每个数据集以识别患病或非患病参考数据集。 生成包含所有患病样本的参考拉曼数据集的第一个数据库。 生成包含所有非病变样本的参考数据集的第二数据库。 接收具有未知疾病状态的测试生物样品的测试拉曼数据集。 提供了关于测试样品是否患病或患病的诊断。诊断是通过使用化学计量技术比较测试数据集与数据库中的参考数据集来预测疾病进展而获得的。

    SPECTROSCOPIC SYSTEM AND METHOD FOR PREDICTING OUTCOME OF DISEASE
    5.
    发明申请
    SPECTROSCOPIC SYSTEM AND METHOD FOR PREDICTING OUTCOME OF DISEASE 审中-公开
    光谱学系统和预测疾病预测的方法

    公开(公告)号:WO2008100582A2

    公开(公告)日:2008-08-21

    申请号:PCT/US2008001988

    申请日:2008-02-14

    Abstract: 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.

    Abstract translation: 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。

Patent Agency Ranking