ArticleNanoscale advances2020
Eight biomarkers on a novel strip for early diagnosis of acute myocardial infarction.
Article in Nanoscale advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Dual colorimetric-photothermal lateral flow immunoassay based on Au@Pt nanozymes for sensitive detection of cardiac troponin I.Mikrochimica acta · 2026Article
- Biosensing Platforms for Cardiac Biomarker Detection.ACS omega · 2024Review
- Identification of Hub Genes and Immune Infiltration in Coronary Artery Disease: A Risk Prediction Model.Journal of inflammation research · 2024Article
- Progress in the Optical Sensing of Cardiac Biomarkers.Biosensors · 2023Review
- Review
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate detection of markers in human serum is important in the early diagnosis of acute myocardial infarction (AMI). This work presents a novel eight biomarker strip, which combines dry chemistry with a fluorescence lateral flow assay. Eight AMI markers were employed simultaneously for sensitive detection, including cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C), uric acid (UA), myoglobin (Myo), creatine kinase-MB (CK-MB), and cardiac troponin I (cTnI). The strip offers the advantages of simple fabrication, convenience, time-saving detection and accurate assessment for AMI. Moreover, the strip possesses acceptable applicability for human serum. This proposed strategy establishes a remarkable platform for the construction of a multi-target detection strip that is feasible for accurate detection for real human serum samples.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.