The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Quantitative and Multiplexed MicroRNA Sensing in Living Cells Based on Peptide Nucleic Acid and Nano Graphene Oxide (PANGO)
Abstract
MicroRNA (miRNA) is an important small RNA which regulates diverse gene expression at the post-transcriptional level. miRNAs are considered as important biomarkers since abnormal expression of specific miRNAs is associated with many diseases including cancer and diabetes. Therefore, it is important to develop biosensors to quantitatively detect miRNA expression levels. Here, we develop a nanosized graphene oxide (NGO) based miRNA sensor, which allows quantitative monitoring of target miRNA expression levels in living cells. The strategy is based on tight binding of NGO with peptide nucleic acid (PNA) probes, resulting in fluorescence quenching of the dye that is conjugated to the PNA, and subsequent recovery of the fluorescence upon addition of target miRNA. PNA as a probe for miRNA sensing offers many advantages including high sequence specificity, high loading capacity on the NGO surface compared to DNA and resistance against nuclease-mediated degradation. The present miRNA sensor allowed the detection of specific target miRNAs with the detection limit as low as ~1 pM and the simultaneous monitoring of three different miRNAs in a living cell.
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
Cites
Bartel (2004) · doi:10.1016/s0092-8674(04)00045-5 · Cited by 34,714
Preparation of Graphitic Oxide
Hummers, W. S., & Offeman, R. E. (1958) · Journal of the American Chemical Society · doi:10.1021/ja01539a017 · Cited by 29,920
MicroRNA signatures in human cancers
Calin, G. A., & Croce, C. M. (2006) · Nature Reviews Cancer · doi:10.1038/nrc1997 · Cited by 7,590
MicroRNAs: small RNAs with a big role in gene regulation
He, L., & Hannon, G. J. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1379 · Cited by 7,118
Real-time quantification of microRNAs by stem-loop RT-PCR
Chen, C. (2005) · Nucleic Acids Research · doi:10.1093/nar/gni178 · Cited by 4,952
MicroRNA Gene Expression Deregulation in Human Breast Cancer
Iorio, M. V., Ferracin, M., Liu, C.-G., Veronese, A., Spizzo, R., Sabbioni, S., Magri, E., Pedriali, M., Fabbri, M., Campiglio, M., et al. (2005) · Cancer Research · doi:10.1158/0008-5472.can-05-1783 · Cited by 4,053
MicroRNA-21 Is an Antiapoptotic Factor in Human Glioblastoma Cells
Chan, J. A., Krichevsky, A. M., & Kosik, K. S. (2005) · Cancer Research · doi:10.1158/0008-5472.can-05-0137 · Cited by 2,557
PNA hybridizes to complementary oligonucleotides obeying the Watson–Crick hydrogen-bonding rules
Egholm, M., Buchardt, O., Christensen, L., Behrens, C., Freier, S. M., Driver, D. A., Berg, R. H., Kim, S. K., Norden, B., & Nielsen, P. E. (1993) · Nature · doi:10.1038/365566a0 · Cited by 2,079
A Graphene Platform for Sensing Biomolecules
Lu, C., Yang, H., Zhu, C., Chen, X., & Chen, G. (2009) · Angewandte Chemie International Edition · doi:10.1002/anie.200901479 · Cited by 2,051
MicroRNA profiling: approaches and considerations
Pritchard, C. C., Cheng, H. H., & Tewari, M. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3198 · Cited by 1,765
A Graphene Nanoprobe for Rapid, Sensitive, and Multicolor Fluorescent DNA Analysis
He, S., Song, B., Li, D., Zhu, C., Qi, W., Wen, Y., Wang, L., Song, S., Fang, H., & Fan, C. (2010) · Advanced Functional Materials · doi:10.1002/adfm.200901639 · Cited by 1,376
Protocol: a highly sensitive RT-PCR method for detection and quantification of microRNAs
Varkonyi-Gasic, E., Wu, R., Wood, M., Walton, E. F., & Hellens, R. P. (2007) · Plant Methods · doi:10.1186/1746-4811-3-12 · Cited by 1,186
Circulating microRNA in body fluid: a new potential biomarker for cancer diagnosis and prognosis
Kosaka, N., Iguchi, H., & Ochiya, T. (2010) · Cancer Science · doi:10.1111/j.1349-7006.2010.01650.x · Cited by 1,147
Aptamer/Graphene Oxide Nanocomplex for in Situ Molecular Probing in Living Cells
Wang, Y., Li, Z., Hu, D., Lin, C.-T., Li, J., & Lin, Y. (2010) · Journal of the American Chemical Society · doi:10.1021/ja103169v · Cited by 1,053
Cationic Polymer Based Gene Delivery Systems
De Smedt, S. C., Demeester, J., & Hennink, W. E. (2000) · Pharmaceutical Research · doi:10.1023/a:1007548826495 · Cited by 884
Peptide nucleic acids (PNA). Oligonucleotide analogs with an achiral peptide backbone
Egholm, M., Buchardt, O., Nielsen, P. E., & Berg, R. H. (1992) · Journal of the American Chemical Society · doi:10.1021/ja00031a062 · Cited by 738
Novina, C. D., & Sharp, P. A. (2004) · Nature · doi:10.1038/430161a · Cited by 724
miR-29 miRNAs activate p53 by targeting p85α and CDC42
Park, S.-Y., Lee, J. H., Ha, M., Nam, J.-W., & Kim, V. N. (2009) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.1533 · Cited by 606
Self-citationYan, L. X., Wu, Q. N., Zhang, Y., Li, Y. Y., Liao, D. Z., Hou, J. H., Fu, J., Zeng, M. S., Yun, J. P., Wu, Q. L., et al. (2011) · Breast Cancer Research · doi:10.1186/bcr2803 · Cited by 323
A sensitive non-radioactive northern blot method to detect small RNAs
Kim, S. W., Li, Z., Moore, P. S., Monaghan, A. P., Chang, Y., Nichols, M., & John, B. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkp1235 · Cited by 303
Profiling microRNA expression with microarrays
Yin, J. Q., Zhao, R. C., & Morris, K. V. (2008) · Trends in Biotechnology · doi:10.1016/j.tibtech.2007.11.007 · Cited by 283
Dong, H., Zhang, J., Ju, H., Lu, H., Wang, S., Jin, S., Hao, K., Du, H., & Zhang, X. (2012) · Analytical Chemistry · doi:10.1021/ac300721u · Cited by 255
microRNA: A Master Regulator of Cellular Processes for Bioengineering Systems
Sun, W., Julie Li, Y.-S., Huang, H.-D., Shyy, J. Y.-J., & Chien, S. (2010) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-070909-105314 · Cited by 236
MicroRNAs in development and disease
Erson, A., & Petty, E. (2008) · Clinical Genetics · doi:10.1111/j.1399-0004.2008.01076.x · Cited by 228
Dong, H., Ding, L., Yan, F., Ji, H., & Ju, H. (2011) · Biomaterials · doi:10.1016/j.biomaterials.2011.02.001 · Cited by 221
Cui, L., Lin, X., Lin, N., Song, Y., Zhu, Z., Chen, X., & Yang, C. J. (2012) · Chem. Commun. · doi:10.1039/c1cc15412e · Cited by 194
Chou, S. S., De, M., Luo, J., Rotello, V. M., Huang, J., & Dravid, V. P. (2012) · Journal of the American Chemical Society · doi:10.1021/ja306767y · Cited by 192
Gaylord, B. S., Massie, M. R., Feinstein, S. C., & Bazan, G. C. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0407578101 · Cited by 175
Naked Eye Detection of Lung Cancer Associated miRNA by Paper Based Biosensing Platform
Yıldız, Ü. H., Palaniappan, A., & Liedberg, B. (2012) · Analytical Chemistry · doi:10.1021/ac3034008 · Cited by 96
Induction of miR-21 by Retinoic Acid in Estrogen Receptor-positive Breast Carcinoma Cells
Terao, M., Fratelli, M., Kurosaki, M., Zanetti, A., Guarnaccia, V., Paroni, G., Tsykin, A., Lupi, M., Gianni’, M., Goodall, G. J., et al. (2010) · Journal of Biological Chemistry · doi:10.1074/jbc.m110.184994 · Cited by 91
Graphene oxide for rapid microRNA detection
Lu, Z., Zhang, L., Deng, Y., et al. (2012) · Nanoscale · doi:10.1039/c2nr31497e · Cited by 81
Metadata
- Authors
- Ryoo, S.-R., Lee, J., Yeo, J., Na, H.-K., Kim, Y.-K., Jang, H., Lee, J. H., Han, S. W., Lee, Y., Kim, V. N., & Min, D.-H.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-06-19
- Volume
- 7
- Issue
- 7
- Pages
- 5882-5891
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2082005641
- Cited by
- 309
- References
- 31
- FWCI
- 13.18
- 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.
