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Recent advances in isolation and detection of exosomal microRNAs related to Alzheimer's disease
Abstract
Alzheimer's disease, a progressive neurological condition, is associated with various internal and external risk factors in the disease's early stages. Early diagnosis of Alzheimer's disease is essential for treatment management. Circulating exosomal microRNAs could be a new class of valuable biomarkers for early Alzheimer's disease diagnosis. Different kinds of biosensors have been introduced in recent years for the detection of these valuable biomarkers. Isolation of the exosomes is a crucial step in the detection process which is traditionally carried out by multi-step ultrafiltration. Microfluidics has improved the efficiency and costs of exosome isolation by implementing various effects and forces on the nano and microparticles in the microchannels. This paper reviews recent advancements in detecting Alzheimer's disease related exosomal microRNAs based on methods such as electrochemical, fluorescent, and SPR. The presented devices' pros and cons and their efficiencies compared with the gold standard methods are reported. Moreover, the application of microfluidic devices to detect Alzheimer's disease related biomarkers is summarized and presented. Finally, some challenges with the performance of novel technologies for isolating and detecting exosomal microRNAs are addressed.
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“Interestingly, even more exosome-derived miRNA detection methods were developed by the most recent technologies, to optimize the sensitivity and minimize the costs of detection [64].”
From miR-92a-3p and miR-320a are Upregulated in Plasma Neuron-Derived Extracellular Vesicles of Patients with Frontotemporal Dementia (2025) · cites this paper as [64]
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Recent advances in biosensors for detection of exosomes
Zhu, X., Chen, H., Zhou, Y., Wu, J., Ramakrishna, S., Peng, X., Nanda, H. S., & Zhou, Y. (2021) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2021.100280 · Cited by 24
The Microfluidic Toolbox for Analyzing Exosome Biomarkers of Aging
DeCastro, J., Littig, J., Chou, P. P., Mack‐Onyeike, J., Srinivasan, A., Conboy, M. J., Conboy, I. M., & Aran, K. (2021) · Molecules · doi:10.3390/molecules26030535 · Cited by 21
Liao, X., Li, Z., Peng, T., Li, J., Qin, F., & Huang, Z. (2017) · Luminescence · doi:10.1002/bio.3338 · Cited by 16
Teoh, B. Y., Lim, Y. M., Chong, W. Y., Subramaniam, M., Tan, Z. Z., Misran, M., Suk, V. R. E., Lo, K. W., & Lee, P. F. (2022) · Biomedical Microdevices · doi:10.1007/s10544-022-00609-z · Cited by 13
Guo, Y., Liu, D., Yang, Q., Shi, W., Yang, Z., Chen, J., & Xiang, J. (2021) · Analytical Letters · doi:10.1080/00032719.2021.2008950 · Cited by 12
Zhu, Y., Tian, Y., & Zheng, T. (2022) · Chemical Communications · doi:10.1039/d1cc07050a · Cited by 10
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Cited by
Manzini, V., Cappelletti, P., Orefice, N. S., Brentari, I., Rigby, M. J., Lo Giudice, M., Feligioni, M., Rivabene, R., Crestini, A., Manfredi, F., et al. (2025) · Molecular Neurobiology · doi:10.1007/s12035-024-04386-z · Cited by 16
Metadata
- Authors
- Pishbin, E., Sadri, F., Dehghan, A., Kiani, M. J., Hashemi, N., Zare, I., Mousavi, P., & Rahi, A.
- ORCID
- Venue
- Environmental Research
- Publisher
- Elsevier BV
- Published
- 2023-06
- Volume
- 227
- Pages
- 115705
- ISSN
- 0013-9351
- Cited by
- 25
- References
- 112
- Language
- en
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
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 ›
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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.