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    HYDROGEL-MEDIATED TISSUE ANALYSIS
    51.
    发明申请
    HYDROGEL-MEDIATED TISSUE ANALYSIS 审中-公开
    氢化介质组织分析

    公开(公告)号：US20140357526A1

    公开(公告)日：2014-12-04

    申请号：US14293397

    申请日：2014-06-02

    申请人： Vanderbilt University

    发明人： Richard Caprioli ,  Glenn A. Harris ,  Joshua J. Nicklay

    IPC分类号： G01N33/68 ,  C12Q1/37

    CPC分类号： G01N33/6848 ,  C12Q1/37 ,  G01N33/6851 ,  G01N33/6887 ,  G01N2570/00

    摘要： A method for analyzing the polypeptide content of animal tissue is described. The method includes the steps of (a) providing an animal tissue specimen; (b) depositing one or more portions of a hydrogel mixture including a protease on spatially discrete portions of the animal tissue specimen; (c) allowing sufficient time to pass for animal tissue under the hydrogel mixture to be form a digested mixture of animal tissue and hydrogel mixture; (d) removing the digested mixture from the animal tissue and extracting the polypeptides from the digested mixture to provide an extract; and (e) analyzing the polypeptide content of the extract by mass spectrometry.

    摘要翻译： 描述了用于分析动物组织的多肽含量的方法。 该方法包括以下步骤：（a）提供动物组织标本; （b）在动物组织样本的空间上分离的部分上沉积包含蛋白酶的水凝胶混合物的一个或多个部分; （c）允许足够的时间通过水凝胶混合物下的动物组织以形成动物组织和水凝胶混合物的消化混合物; （d）从动物组织中除去消化的混合物并从消化的混合物中提取多肽以提供提取物; 和（e）通过质谱分析提取物的多肽含量。

    Disease diagnosis method, marker screening method and marker using TOF-SIMS
    52.
    发明授权
    Disease diagnosis method, marker screening method and marker using TOF-SIMS 有权
    疾病诊断方法，标记筛选方法和使用TOF-SIMS的标记

    公开(公告)号：US08871438B2

    公开(公告)日：2014-10-28

    申请号：US13570507

    申请日：2012-08-09

    申请人： Tae Geol Lee ,  Dae Won Moon ,  Byong Chul Yoo ,  In Hoo Kim

    发明人： Tae Geol Lee ,  Dae Won Moon ,  Byong Chul Yoo ,  In Hoo Kim

    IPC分类号： G01N33/574 ,  G01N33/68

    CPC分类号： G01N33/6851 ,  G01N33/57446 ,  Y10T436/173845 ,  Y10T436/200833

    摘要： The present invention relates to a disease diagnosis method, a marker screening method, and a marker using a time-of-flight secondary ion mass spectrometry (TOF-SIMS), and more particularly, to a large intestine cancer diagnosis method, a large intestine cancer marker screening method, and a large intestine cancer marker using a time-of-flight secondary ion mass spectrometry (TOF-SIMS). Specifically, the present invention provides a method diagnosing a disease using a pattern of secondary ion mass (m/z) peaks of biological samples measured using a time-of-flight secondary ion mass spectrometry (TOF-SIMS) as a marker, a marker screening method being a reference judging an existence or non-existence of a disease, and a marker configured of specific secondary ion mass peaks.

    摘要翻译： 本发明涉及疾病诊断方法，标记筛选方法和使用飞行时间二次离子质谱法（TOF-SIMS）的标记物，更具体地，涉及大肠癌诊断方法，大肠 癌症标志物筛选方法和使用飞行时间二次离子质谱（TOF-SIMS）的大肠癌标记物。 具体地，本发明提供使用飞行时间二次离子质谱法（TOF-SIMS）作为标记测定的生物样品的二次离子质量（m / z）峰图案，标记物 筛选方法是判断疾病的存在或不存在的参考，以及由特定二次离子质量峰构成的标记。

    Method for the Early Detection of Renal Disease Using Proteomics
    55.
    发明申请
    Method for the Early Detection of Renal Disease Using Proteomics 有权
    使用蛋白质组学早期检测肾脏疾病的方法

    公开(公告)号：US20140080166A1

    公开(公告)日：2014-03-20

    申请号：US14044953

    申请日：2013-10-03

    申请人： Children's Hospital Medical Center

    发明人： Prasad Devarajan

    IPC分类号： G01N33/68

    CPC分类号： G01N33/6851 ,  G01N33/6842 ,  G01N33/6848 ,  G01N33/6893 ,  G01N2570/00 ,  G01N2800/226 ,  G01N2800/32 ,  G01N2800/347 ,  G01N2800/52

    摘要： A method for the detection of an early biomarker for assessing a change in renal status in a mammalian subject following a renal event. The method typically includes the steps of (a) providing a body fluid sample obtained from a mammalian subject; (b) analyzing the molecular weight of the proteins in the sample using proteome analysis; and (c) identifying the presence of a protein in the sample selected from the group consisting of a 6.4 kDa protein, a 28.5 kDa protein, a 33 kDa protein, a 44 kDa protein, a 67 kDa protein, and combinations thereof. The presence of one of these proteins can serve as an early biomarker for assessing a change in renal status. The levels of these proteins can be compared to predetermined levels, and thus provide a determination of the subject's renal status. The invention also includes a method of assessing the administration of aprotinin during cardio-pulmonary bypass surgery and provides for methods where the level of the 6.4 kDa biomarker in the subject's urine directs a caregiver's therapeutic decision regarding the intra-operative administration of aprotinin.

    摘要翻译： 一种用于检测早期生物标志物的方法，用于评估肾事件后哺乳动物受试者中肾状态的变化。 该方法通常包括以下步骤：（a）提供从哺乳动物受试者获得的体液样品; （b）使用蛋白质组分析分析样品中蛋白质的分子量; 和（c）鉴定在选自6.4kDa蛋白质，28.5kDa蛋白质，33kDa蛋白质，44kDa蛋白质，67kDa蛋白质及其组合的样品中的样品中蛋白质的存在。 这些蛋白质之一的存在可以作为评估肾脏状态变化的早期生物标志物。 可以将这些蛋白质的水平与预定水平进行比较，从而提供受试者的肾脏状态的确定。 本发明还包括评估心肺 - 肺旁路手术中抑肽酶的施用的方法，并提供了方法，其中受试者尿液中的6.4kDa生物标志物的水平指导了关于在胃肠外施用抑肽酶的护理人员的治疗决定。

    Artificial neural network proteomic tumor classification
    57.
    发明授权
    Artificial neural network proteomic tumor classification 有权
    人工神经网络蛋白质组学肿瘤分类

    公开(公告)号：US08642349B1

    公开(公告)日：2014-02-04

    申请号：US11837883

    申请日：2007-08-13

    申请人： Timothy J. Yeatman ,  Jeff Xiwu Zhou ,  Gregory C. Bloom ,  Steven A. Eschrich

    发明人： Timothy J. Yeatman ,  Jeff Xiwu Zhou ,  Gregory C. Bloom ,  Steven A. Eschrich

    IPC分类号： G01N33/00

    CPC分类号： G01N33/6851 ,  G01N33/57419

    摘要： Here the inventors describe a tumor classifier based on protein expression. Also disclosed is the use of proteomics to construct a highly accurate artificial neural network (ANN)-based classifier for the detection of an individual tumor type, as well as distinguishing between six common tumor types in an unknown primary diagnosis setting. Discriminating sets of proteins are also identified and are used as biomarkers for six carcinomas. A leave-one-out cross validation (LOOCV) method was used to test the ability of the constructed network to predict the single held out sample from each iteration with a maximum predictive accuracy of 87% and an average predictive accuracy of 82% over the range of proteins chosen for its construction.

    摘要翻译： 这里发明人描述了基于蛋白质表达的肿瘤分类器。 还公开了使用蛋白质组学构建用于检测单个肿瘤类型的高度准确的人造神经网络（ANN）分类器，以及区分未知主要诊断设置中的六种常见肿瘤类型。 鉴定的蛋白质组也被鉴定，并被用作6个癌症的生物标志物。 使用一次性交叉验证（LOOCV）方法来测试构建的网络从每次迭代中预测单个保留样本的能力，其最大预测精度为87％，平均预测精度为82％，超过 为其构建选择的蛋白质范围。

    Expression quantification using mass spectrometry
    59.
    发明授权
    Expression quantification using mass spectrometry 有权
    使用质谱法进行表达量化

    公开(公告)号：US08633031B2

    公开(公告)日：2014-01-21

    申请号：US12571005

    申请日：2009-09-30

    申请人： Christine L. Hunter

    发明人： Christine L. Hunter

    IPC分类号： G01N33/00 ,  B01D59/44

    CPC分类号： G01N33/68 ,  G01N33/6848 ,  G01N33/6851 ,  G01N2333/90209

    摘要： In various aspects, the present teachings provide systems, methods, assays and kits for the absolute quantitation of protein expression. In various aspects, the present teachings provide methods of determining the concentration of one or more proteins of interest in one or more samples of interest. In various aspects, the present teachings provide methods of determining the absolute concentration of one or more isoforms of a protein using standard samples of signature protein fragments and parent-daughter ion transition monitoring (PDITM). In various embodiments, the absolute concentration of multiple isoforms of a biomolecule in a sample, multiple proteins in a biological process, a combination of multiple samples, or combinations thereof, can be determined in a multiplex fashion using the present teachings. In various aspects, provided are methods of assessing the response of a biological system to a chemical agent.

    摘要翻译： 在各个方面，本教导提供用于蛋白质表达的绝对定量的系统，方法，测定和试剂盒。 在各个方面，本教导提供了确定感兴趣的一种或多种感兴趣的一种或多种感兴趣的蛋白质的浓度的方法。 在各个方面，本教导提供使用标记蛋白片段和父 - 子离子转移监测（PDITM）的标准样品测定蛋白质的一种或多种同种型的绝对浓度的方法。 在各种实施方案中，可以使用本教导以多种方式确定样品中生物分子的多种同种型，生物过程中的多种蛋白，多种样品的组合或其组合的绝对浓度。 在各个方面，提供了评估生物系统对化学试剂的响应的方法。

    Deep-MALDI TOF mass spectrometry of complex biological samples, e.g., serum, and uses thereof
    60.
    发明申请
    Deep-MALDI TOF mass spectrometry of complex biological samples, e.g., serum, and uses thereof 有权
    复合生物样品例如血清的深MALDI TOF质谱法及其用途

    公开(公告)号：US20130320203A1

    公开(公告)日：2013-12-05

    申请号：US13836436

    申请日：2013-03-15

    申请人： BIODESIX, INC.

    发明人： Heinrich Röder ,  Senait Asmellash ,  Jenna Allen ,  Maxim Tsypin

    IPC分类号： G01N33/487

    CPC分类号： G01N33/487 ,  G01N33/6851 ,  H01J49/0004 ,  H01J49/164 ,  H01J49/40

    摘要： A method of analyzing a biological sample, for example serum or other blood-based samples, using a MALDI-TOF mass spectrometer instrument is described. The method includes the steps of applying the sample to a sample spot on a MALDI-TOF sample plate and directing more than 20,000 laser shots to the sample at the sample spot and collecting mass-spectral data from the instrument. In some embodiments at least 100,000 laser shots and even 500,000 shots are directed onto the sample. It has been discovered that this approach, referred to as “deep-MALDI”, leads to a reduction in the noise level in the mass spectra and that a significant amount of additional spectral information can be obtained from the sample. Moreover, peaks visible at lower number of shots become better defined and allow for more reliable comparisons between samples.

    摘要翻译： 描述了使用MALDI-TOF质谱仪器分析生物样品，例如血清或其它基于血液的样品的方法。 该方法包括以下步骤：将样品施加到MALDI-TOF样品板上的样品点上，并将20,000多次激光照射引导到样品点处的样品并从仪器收集质谱数据。 在一些实施例中，至少100,000次激光照射甚至50万次照射被引导到样品上。 已经发现，称为“深MALDI”的方法导致质谱中噪声水平的降低，并且可以从样品获得大量附加的光谱信息。 此外，在较少的镜头可见的峰值变得更好地定义并且允许样品之间更可靠的比较。