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Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

Blood Studies for Cardiovascular System I: Cardiac Biomarkers

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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)
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Updated: Jan 7, 2026

Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
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生物标志物 生物标志物

Srinivasan Vairavan1, Alankar Atreya2, Nicholas Cummins3

  • 1Janssen Research and Development, Titusville, NJ, USA.

Alzheimer's & dementia : the journal of the Alzheimer's Association
|December 26, 2025
PubMed
概括
此摘要是机器生成的。

在阿尔茨海默病 (AD) 诊断之前,言语变化就会出现. 讲故事任务中的声学标记显示了在临床前和临床前阶段早期发现AD的潜力,有助于临床试验.

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科学领域:

  • 神经学 神经学
  • 语音语言病理学 语言病理学
  • 生物标志物 生物标志物

背景情况:

  • 阿尔茨海默氏病 (AD) 之前,有几十年的言语和语言变化.
  • 频繁语音评估的数字工具为早期AD临床试验提供了前景.
  • 在RADAR-AD研究中,研究了不同AD (ATN) 阶段的故事叙述任务中的声学语音标记.

研究的目的:

  • 评估声学语音标记器在检测阿尔茨海默病 (AD) 早期症状方面的实用性.
  • 在AD的综合症阶段内分析与粉样蛋白 (A), (T) 和神经退行 (N) 状态相关的语音模式.
  • 评估语音标记在改善AD临床试验查方面的潜力.

主要方法:

  • 与四组159名参与者进行的横截面研究:健康对照 (HC),临床前AD (临床前AD). 亚丁病),前期性亚丁病 (大约约) AD) 和轻度的AD.
  • 通过使用12种欧洲语言的Mezurio智能手机应用程序通过基于语音的故事叙述任务 (Story Time) 收集的语音样本.
  • 线性混合效应模型用于分析语音数据,将参与者,故事和语言视为随机效应,人口学变量视为固定效应.

主要成果:

  • 临床前的AD (A+T+) 与对照组相比显示出明显较低的关节率.
  • 生产性AD (A+T+) 也表现出较低的发音率,以及语音速度,声音和语音特征的差异.
  • 产生性AD (A+T-) 在动和发声段中显示出显著的差异.

结论:

  • 话语流的微妙,陶驱动的变化可以在阿尔茨海默病的临床前阶段就被检测出来.
  • 声学语音标志物显示出在AD临床试验中增强查的潜力.
  • 这项研究得到了创新药品倡议联合企业 (赠款第806999号) 的支持.