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相关概念视频

Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

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Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
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Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers01:19

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Cardiac biomarkers are critical in diagnosing, prognosing, and managing cardiovascular diseases. Routine measurement of specific biomarkers such as B-type natriuretic peptide (BNP), C-reactive protein (CRP), and homocysteine (Hcy) is common practice in clinical settings to evaluate heart function and predict cardiovascular events.
These markers indicate stress or strain on the heart muscle:
Natriuretic Peptides (BNP)
Cardiac myocytes produce these hormones in response to ventricular stretching...
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生物标志物 生物标志物

Nopparat Suthprasertporn1, Sitong Zhou2, Jacob Conston1

  • 1University of California, Davis, Sacramento, CA, USA.

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概括
此摘要是机器生成的。

标准化的生物流体处理和质量控制确保了各种研究场所的可靠生物标志物数据. 这些协调方法提高了大规模临床研究数据的一致性.

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科学领域:

  • 临床研究 临床研究
  • 生物标志物发现发现
  • 神经科学是一个神经科学.

背景情况:

  • 该DVCID项目旨在招募2250个不同的美国人进行认知,血液和神经成像分析.
  • 加州大学戴维斯分校的存储库核心 (RC) 管理20个站点的血液处理,银行和生物标志物分析.
  • 标准操作程序 (SOP) 对于一致和可比的分析结果至关重要.

研究的目的:

  • 详细说明生物流体样本处理和数据管理在多个研究场所的协调策略.
  • 评估影响样本完整性和数据可靠性的分析前,分析和分析后因素.
  • 通过使用Quanterix Simoa HD-XTM分析仪,确保统一和可靠的定量生物标记数据.

主要方法:

  • 实施标准化血液处理协议,包括特定的真空管和冷格式.
  • 利用数据协调方法,例如为批量桥接重新分析,以最大限度地减少量化变化.
  • 进行分析后的质量控制,以评估和限制运行内的,运行之间的和分批之间的变化 (CV ≤10-15%).

主要成果:

  • 标准化的协议确保了所有参与站点的一致的样本处理和存储.
  • 协调策略成功地将生物标志物量化中的变异性降到最低.
  • 分析后的QC证实,可变性保持在可接受的范围内,生物标志物数据在不同地点没有显著差异.

结论:

  • 在多中心研究中,协调的策略和标准操作程序对于可靠的生物流体收集,处理,储存和生物标志物量化至关重要.
  • 这些实践确保了样本完整性和数据的一致性,支持了强大的生物标志物研究.
  • 改进的数据可比性促进了临床和生物标志物研究中的跨队列研究和更大规模的调查.