The DOI matches its Crossref record.
Sensitive Immunoassay of a Biomarker Tumor Necrosis Factor-α Based on Poly(guanine)-Functionalized Silica Nanoparticle Label
Abstract
A novel electrochemical immunosensor for the detection of tumor necrosis factor-alpha (TNF-alpha) based on poly(guanine)-functionalized silica nanoparticles (NPs) label is presented. The detection of mouse TNF-alpha via immunological reaction is based on a dual signal amplification: (1) a large amount of guanine residues introduced on the electrode surface through sandwich immunoreaction and poly(guanine)-functionalized silica NP label; (2) Ru(bpy)3(2+)-induced catalytic oxidation of guanine, which results in great enhancement of anodic current. The synthesized silica NP conjugates were characterized with atomic force microscopy, X-ray photoelectron spectroscopy, and electrochemistry. These experiments confirmed that poly(guanine) and avidin were immobilized on the surface of silica NPs. The performance of the electrochemical immunosensor was evaluated and some experiment parameters (e.g., concentration of Ru(bpy)3(2+), incubation time of TNF-alpha, etc.) were optimized. The detection limit for TNF-alpha is found to be 5.0 x 10(-11) g mL(-1) (2.0 pM), which corresponds to 60 amol of TNF-alpha in 30 microL of sample. This immunosensor based on the poly(guanine)-functionalized silica NP label offers great promise for rapid, simple, cost-effective analysis of biological samples.
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
Du, D., Zou, Z., Shin, Y., Wang, J., Wu, H., Engelhard, M. H., Liu, J., Aksay, I. A., & Lin, Y. (2010) · Analytical Chemistry · doi:10.1021/ac100036p · Cited by 448
Self-citationKartikasari, A. E. R., Huertas, C. S., Mitchell, A., & Plebanski, M. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.692142 · Cited by 343
Bioanalytical Chemistry of Cytokines–a Review
Stenken, J. A., & Poschenrieder, A. J. (2015) · Analytica Chimica Acta · doi:10.1016/j.aca.2014.10.009 · Cited by 302
Nanotechnology-based electrochemical sensors for biomonitoring chemical exposures
Barry, R. C., Lin, Y., Wang, J., Liu, G., & Timchalk, C. A. (2009) · Journal of Exposure Science & Environmental Epidemiology · doi:10.1038/jes.2008.71 · Cited by 73
Self-citation
Metadata
- Authors
- Wang, J., Liu, G., Engelhard, M. H., & Lin, Y.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2006-08-24
- Volume
- 78
- Issue
- 19
- Pages
- 6974-6979
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W1976121079
- Cited by
- 174
- References
- 0
- FWCI
- 6.02
- 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
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.
