File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Microfluidics-Based Systems in Diagnosis of Alzheimer’s Disease and Biomimetic Modeling

TitleMicrofluidics-Based Systems in Diagnosis of Alzheimer’s Disease and Biomimetic Modeling
Authors
KeywordsAlzheimer’s disease (AD)
microfluidic chips
AD biomarkers
blood–brain barrier (BBB)
three-dimensional AD model
Issue Date2020
PublisherMDPI AG. The Journal's web site is located at http://www.mdpi.com/journal/micromachines
Citation
Micromachines, 2020, v. 11 n. 9, p. article no. 787 How to Cite?
AbstractEarly detection and accurate diagnosis of Alzheimer’s disease (AD) is essential for patient care and disease treatment. Microfluidic technology is emerging as an economical and versatile platform in disease detection and diagnosis. It can be conveniently integrated with nanotechnology and/or biological models for biomedical functional and pre-clinical treatment study. These strengths make it advantageous in disease biomarker detection and functional analysis against a wide range of biological backgrounds. This review highlights the recent developments and trends of microfluidic applications in AD research. The first part looks at the principles and methods for AD diagnostic biomarker detection and profiling. The second part discusses how microfluidic chips, especially organ-on-a-chip platforms, could be used as an independent approach and/or integrated with other technologies in AD biomimetic functional analysis.
Persistent Identifierhttp://hdl.handle.net/10722/290047
ISSN
2023 Impact Factor: 3.0
2023 SCImago Journal Rankings: 0.549
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Y-
dc.contributor.authorLi, D-
dc.contributor.authorZhao, P-
dc.contributor.authorNandakumar, K-
dc.contributor.authorWang, L-
dc.contributor.authorSong, Y-
dc.date.accessioned2020-10-22T08:21:20Z-
dc.date.available2020-10-22T08:21:20Z-
dc.date.issued2020-
dc.identifier.citationMicromachines, 2020, v. 11 n. 9, p. article no. 787-
dc.identifier.issn2072-666X-
dc.identifier.urihttp://hdl.handle.net/10722/290047-
dc.description.abstractEarly detection and accurate diagnosis of Alzheimer’s disease (AD) is essential for patient care and disease treatment. Microfluidic technology is emerging as an economical and versatile platform in disease detection and diagnosis. It can be conveniently integrated with nanotechnology and/or biological models for biomedical functional and pre-clinical treatment study. These strengths make it advantageous in disease biomarker detection and functional analysis against a wide range of biological backgrounds. This review highlights the recent developments and trends of microfluidic applications in AD research. The first part looks at the principles and methods for AD diagnostic biomarker detection and profiling. The second part discusses how microfluidic chips, especially organ-on-a-chip platforms, could be used as an independent approach and/or integrated with other technologies in AD biomimetic functional analysis.-
dc.languageeng-
dc.publisherMDPI AG. The Journal's web site is located at http://www.mdpi.com/journal/micromachines-
dc.relation.ispartofMicromachines-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectAlzheimer’s disease (AD)-
dc.subjectmicrofluidic chips-
dc.subjectAD biomarkers-
dc.subjectblood–brain barrier (BBB)-
dc.subjectthree-dimensional AD model-
dc.titleMicrofluidics-Based Systems in Diagnosis of Alzheimer’s Disease and Biomimetic Modeling-
dc.typeArticle-
dc.identifier.emailWang, L: lqwang@hku.hk-
dc.identifier.emailSong, Y: songy@hku.hk-
dc.identifier.authorityWang, L=rp00184-
dc.identifier.authoritySong, Y=rp00488-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3390/mi11090787-
dc.identifier.pmid32825153-
dc.identifier.pmcidPMC7569794-
dc.identifier.scopuseid_2-s2.0-85090402198-
dc.identifier.hkuros316022-
dc.identifier.volume11-
dc.identifier.issue9-
dc.identifier.spagearticle no. 787-
dc.identifier.epagearticle no. 787-
dc.identifier.isiWOS:000581911600001-
dc.publisher.placeSwitzerland-
dc.identifier.issnl2072-666X-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats