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Related Concept Videos

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:
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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.
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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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Biomarkers.

Wen Zhang1,2, Sheelakumari Raghavan1, Jianqiao Tian1,3

  • 1Department of Radiology, Mayo Clinic, Rochester, MN, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 24, 2025
PubMed
Summary
This summary is machine-generated.

Aging white matter shows increased metabolism, not decreased, as cognitive function declines. This atypical white matter signature may indicate a compensatory response to aging and disease, potentially linked to cognitive resilience.

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Gerontology

Background:

  • White matter (WM) metabolism in aging and dementia is understudied compared to gray matter.
  • Previous research focused on reduced metabolism in gray matter (GM) during aging and dementia.

Purpose of the Study:

  • Investigate WM metabolic changes associated with aging and dementia.
  • Examine relationships between WM metabolism, Alzheimer's Disease (AD) biomarkers, and cognitive decline.

Main Methods:

  • Analyzed data from 3,169 participants (MCSA and ADNI) using MRI, amyloid-PET, and FDG-PET.
  • Employed voxel-wise regression to identify WM metabolic changes linked to cognition.
  • Utilized structural equation models and regression analyses to explore driving factors and predictive utility of WM metabolism.

Main Results:

  • Identified an atypical WM signature (AWM-Signature) in the corona radiata with increased metabolism correlating with cognitive decline.
  • AWM-Signature hypermetabolism linked to increased age, amyloidosis, vascular disease, neuroinflammation, and reduced WM neurite density.
  • AWM-Signature hypermetabolism predicted faster cognitive decline, contrasting with GM and typical WM findings.

Conclusions:

  • Observed unexpected increases in WM metabolism in the corona radiata during aging and disease.
  • These metabolic changes may represent a compensatory response, potentially indicating cognitive resilience.
  • Further research is needed to understand the role of these WM metabolic changes in maintaining cognitive function.