Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 464

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Dual-Mode Ultrasensitive Quantification of MicroRNA in Living Cells by Chiroplasmonic Nanopyramids Self-Assembled from Gold and Upconversion Nanoparticles

Li, Si, Xu, Liguang, Ma, Wei, Wu, Xiaoling, Sun, Maozhong, Kuang, Hua, Wang, Libing, Kotov, Nicholas A., Xu, Chuanlai·2016·Journal of the American Chemical Society

Abstract

Chiral self-assembled nanomaterials with biological applications have attracted great interest. In this study, DNA-driven gold-upconversion nanoparticle (Au-UCNP) pyramids were fabricated to detect intracellular microRNA (miRNA) in real time. The Au-UCNP pyramids are doubly optically active, displaying strong plasmonic circular dichroism (CD) at 521 nm and significant luminescence in 500-600 nm, and therefore can be monitored by both of them. CD will decrease while the luminescence intensity increases in the presence of miRNA. The experimental results show that the CD intensity had an outstanding linear range from 0.073 to 43.65 fmol/10 μg(RNA) and a limit of detection (LOD) of 0.03 fmol/10 μg(RNA), whereas the luminescence intensity ranged from 0.16 to 43.65 fmol/10 μg(RNA) with a LOD of 0.12 fmol/10 μg(RNA). These data indicate that the CD signal is much more sensitive to the concentration of miRNA than the luminescent signal, which is attributed to the strong CD intensity arising from the spin angular momentum of the photon interaction with chiral nanostructures and the plasmonic enhancement of the intrinsic chirality of DNA molecules in the pyramids. This approach opens up a new avenue to the ultrasensitive detection and quantification of miRNA in living cells.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/jacs.5b10309

Cites

2 of 2 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Cites

Cited by

See all 464

Metadata

Authors
Li, S., Xu, L., Ma, W., Wu, X., Sun, M., Kuang, H., Wang, L., Kotov, N. A., & Xu, C.
Venue
Journal of the American Chemical Society
Published
2015-12-29
Volume
138
Issue
1
Pages
306-312
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2197075717
Cited by
464
References
2
FWCI
19.04
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.