ReviewCombinatorial chemistry & high throughput screening2025
Magnetic Nanomaterials for Sample Preparation of Disease-related Biomarkers.
Review in Combinatorial chemistry & high throughput screening, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
Funding
Abstract
Measuring clinically relevant biomarkers is critical for disease screening, diagnosis, and therapeutic monitoring. However, analyzing trace biomarkers in complex biological fluids remains challenging. Magnetic solid phase extraction (MSPE) has recently emerged as a promising sample preparation approach due to its simplicity, efficiency, and ability to selectively isolate biomarkers. Databases, including PubMed, Web of Science, and Scopus, were systematically searched for studies on MSPE for clinical biomarkers. Key findings on nanomaterial synthesis strategies, surface modifications, and applications in biomarker isolation were synthesized. Recent research demonstrates magnetic nanoparticles with tailored surface chemistry can selectively extract biomarkers like cancer antigens, neurotransmitters, and pharmaceuticals from matrices such as plasma, urine, and serum. MSPE enables clinically relevant limits of detection, high recovery, and purification in a rapid and simple workflow. This technique shows significant potential to improve clinical diagnostics. Further research on novel magnetic materials and surface functionalization is warranted. This review provides insights for researchers aiming to develop MSPE methods for sensitive and selective analysis of clinical biomarkers.
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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.