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Cited by 543

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Label-free biomarker detection from whole blood

Open access
Stern, Eric, Vacic, Aleksandar, Rajan, Nitin K., Criscione, Jason M., Park, Jason, Ilic, Bojan R., Mooney, David J., Reed, Mark A., Fahmy, Tarek M.·2010·Nature Nanotechnology

Abstract

Label-free nanosensors can detect disease markers to provide point-of-care diagnosis that is low-cost, rapid, specific and sensitive. However, detecting these biomarkers in physiological fluid samples is difficult because of ionic screening. Here, we overcome this limitation by using distinct components within the sensor to perform purification and detection.1 A microfluidic purification chip captures multiple biomarkers simultaneously from blood samples and releases them, after washing, into purified buffer for sensing by a silicon nanoribbon detector. This two-stage approach isolates the detector from the complex environment of whole blood, and reduces its minimum required sensitivity by effectively pre-concentrating the biomarkers. We show specific and quantitative detection of two model cancer antigens from a 10 uL sample of whole blood in less than 20 minutes.

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Crossref · 10.1038/nnano.2009.353

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Metadata

Authors
Stern, E., Vacic, A., Rajan, N. K., Criscione, J. M., Park, J., Ilic, B. R., Mooney, D. J., Reed, M. A., & Fahmy, T. M.
Venue
Nature Nanotechnology
Published
2009-12-13
Volume
5
Issue
2
Pages
138-142
ISSN
  • 1748-3387 (ISSN-L)
  • 1748-3395
OpenAlex
W2023834245
Cited by
543
References
3
FWCI
10.68
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Label-free biomarker detection from whole blood. https://app.cochat.ai/papers/10.1038/nnano.2009.353
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Stern, E., Vacic, A., Rajan, N. K., Criscione, J. M., Park, J., Ilic, B. R., Mooney, D. J., Reed, M. A., & Fahmy, T. M. (2010). Label-free biomarker detection from whole blood. Nature Nanotechnology. https://doi.org/10.1038/nnano.2009.353

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.