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Updated: Jul 3, 2026

Thrombus Profiling Assay: A Microfluidics-Based Platform for Comprehensively Characterizing Biomechanical Thrombogenesis
Published on: January 9, 2026
The potential biomarkers for thromboembolism detected by SELDI-TOF-MS
Mei Hong1, Xiaoping Zhang, Yu Hu
1Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Introduction:
Few studies were concerned about searching for specific biomarkers for thromboembolic (arterial and venous) diseases by the use of Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS).
Materials And Methods:
We screened for potential biomarkers in 69 plasma samples, including samples from 20 patients with idiopathetic deep vein thrombosis (DVT), 20 patients with acute myocardial infarction (AMI), and 29 healthy controls without a history of thromboembolism. Pretreated plasma samples were analyzed on the Protein Biology System IIc plus SELDI-TOF-MS (Ciphergen Biosystems, Fremont, CA). Proteomic spectra of mass to charge ratio (m/z) were generated by the application of plasma to immobilized metal affinity capture (IMAC-3) ProteinChip arrays activated with copper.
Results:
A pattern of three biomarkers (m/z: 2 667, 5 914, and 6 890 Da, respectively) with a total accuracy of 100% was selected based on their collective contribution to the optimal separation between patients with AMI and healthy controls. Another spattern consisting of only one biomarker (m/z: 5 914 Da) could totally discriminate patients with DVT and control subjects. For further analysis between patients with AMI and those with DVT, a pattern of four biomarkers (m/z: 3 418, 5 271, 33 378, and 68 125 Da, respectively) was selected with a total accuracy of 82.5%.
Conclusions:
Plasma proteomic profiling with SELDI-TOF-MS and ProteinChip technologies provides high sensitivity and specificity in discriminating patients with thrombosis and healthy subjects. The discovered biomarkers might show great potential for early diagnosis of thromboembolic diseases.
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