The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Ultrasensitive and Highly Selective Detection of Alzheimer’s Disease Biomarker Using Two-Photon Rayleigh Scattering Properties of Gold Nanoparticle
Open accessAbstract
Alzheimer's disease (AD) is a progressive mental disorder disease, which affects 26.6 million people worldwide and estimated increments can be 100 millions by 2050. Since there is no cure at present, early diagnosis of AD is crucial for the current drug treatments. Driven by the need, here we demonstrate for the first time that monoclonal anti-tau antibody-coated gold nanoparticle based two-photon scattering assay can be used for the detection of Alzheimer's tau protein in the 1 pg/mL level which is about 2 orders of magnitude lower than cutoff values (195 pg/mL) for tau protein in CSF (cerebrospinal fluid). We have shown that when anti-tau antibody-coated gold nanoparticles were mixed with 20 ng/mL of tau protein, two-photon Rayleigh scattering intensity (TPRS) increases by about 16 times. The mechanism of TPRS intensity change has been discussed. Our data demonstrated that our TPRS assay is highly sensitive to tau protein and it can distinguish from BSA, which is one of the most abundant protein components in CSF. Our results demonstrate the potential for a broad application of this type of nanobionanotechnology in practical biomedical applications.
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
Apolipoprotein E and its receptors in Alzheimer's disease: pathways, pathogenesis and therapy
Bu, G. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2620 · Cited by 1,168
Thirty years of Alzheimer's disease genetics: the implications of systematic meta-analyses
Bertram, L., & Tanzi, R. E. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2494 · Cited by 747
Buerger, K., Ewers, M., Pirttila, T., Zinkowski, R., Alafuzoff, I., Teipel, S. J., DeBernardis, J., Kerkman, D., McCulloch, C., Soininen, H., et al. (2006) · Brain · doi:10.1093/brain/awl269 · Cited by 586
Cited by
Ray, P. C. (2010) · Chemical Reviews · doi:10.1021/cr900335q · Cited by 773
Self-citationNeurotherapeutic applications of nanoparticles in Alzheimer’s disease
Sahni, J. K., Doggui, S., Ali, J., Baboota, S., Dao, L., & Ramassamy, C. (2011) · Journal of Controlled Release · doi:10.1016/j.jconrel.2010.11.033 · Cited by 219
Recent Advancements of Nanomedicine in Neurodegenerative Disorders Theranostics
Mukherjee, S., Madamsetty, V. S., Bhattacharya, D., Roy Chowdhury, S., Paul, M. K., & Mukherjee, A. (2020) · Advanced Functional Materials · doi:10.1002/adfm.202003054 · Cited by 152
Neurotheranostics as Personalized Medicines
Kevadiya, B. D., Ottemann, B. M., Thomas, M. B., Mukadam, I., Nigam, S., McMillan, J., Gorantla, S., Bronich, T. K., Edagwa, B., & Gendelman, H. E. (2019) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2018.10.011 · Cited by 124
Theranostic implications of nanotechnology in multiple sclerosis: a future perspective.
Singh, A. V., Khare, M., Gade, W. N., & Zamboni, P. (2012) · Autoimmune Diseases · doi:10.1155/2012/160830 · Cited by 58
Self-citation
Metadata
- Authors
- Neely, A., Perry, C., Varisli, B., Singh, A. K., Arbneshi, T., Senapati, D., Kalluri, J. R., & Ray, P. C.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2009-08-19
- Volume
- 3
- Issue
- 9
- Pages
- 2834-2840
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2090276988
- Cited by
- 244
- References
- 3
- FWCI
- 7.68
- Type
- journal article
- Language
- en
- Open access
- green
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.