The DOI matches its Crossref record.
Fast, Ultrasensitive Virus Detection Using a Young Interferometer Sensor
Abstract
We report the application of an integrated optical Young interferometer sensor for ultrasensitive, real-time, direct detection of viruses. We have validated the sensor by detecting herpes simplex virus type 1 (HSV-1), but the principle is generally applicable. Detection of HSV-1 virus particles was performed by applying the virus sample onto a sensor surface coated with a specific antibody against HSV-1. The performance of the sensor was tested by monitoring virus samples at clinically relevant concentrations. We show that the Young interferometer sensor can specifically and sensitively detect HSV-1 at very low concentrations (850 particles/mL). We have further demonstrated that the sensor can specifically detect HSV-1 suspended in serum. Extrapolation of the results indicates that the sensitivity of the sensor approaches the detection of a single virus particle binding, yielding a sensor of unprecedented sensitivity with wide applications for viral diagnostics.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Posthuma-Trumpie, G. A., Korf, J., & van Amerongen, A. (2009) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-008-2287-2 · Cited by 1,540
Highly sensitive fluorescence detection system for microfluidic lab-on-a-chip
Ryu, G., Huang, J., Hofmann, O., Walshe, C. A., Sze, J. Y. Y., McClean, G. D., Mosley, A., Rattle, S. J., deMello, J. C., deMello, A. J., et al. (2011) · Lab on a Chip · doi:10.1039/c0lc00586j · Cited by 93
Metadata
- Authors
- Ymeti, A., Greve, J., Lambeck, P. V., Wink, T., van Hövell, Beumer, Wijn, R. R., Heideman, R. G., Subramaniam, V., & Kanger, J. S.
- Venue
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2006-12-29
- Volume
- 7
- Issue
- 2
- Pages
- 394-397
- ISSN
- 1530-6984 (ISSN-L)
- 1530-6992
- OpenAlex
- W2023282503
- Cited by
- 287
- References
- 0
- FWCI
- 10.73
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Fast, Ultrasensitive Virus Detection Using a Young Interferometer Sensor. https://app.cochat.ai/papers/10.1021/nl062595n
- The paper
- Ymeti, A., Greve, J., Lambeck, P. V., Wink, T., van Hövell, Beumer, Wijn, R. R., Heideman, R. G., Subramaniam, V., & Kanger, J. S. (2007). Fast, Ultrasensitive Virus Detection Using a Young Interferometer Sensor. Nano Letters. https://doi.org/10.1021/nl062595n
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
