Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/40426
Title: Metal-Organic Frameworks as Sensors for Human Amyloid Diseases
Author: Leite, José P.
Figueira, Flávio
Mendes, Ricardo F.
Almeida Paz, Filipe A.
Gales, Luís
Keywords: Alzheimer’s disease
Amyloid biomarke
Diagnostic
Immunosensor
Metal−organic frameworks
Amyloid diseases
Biosensors
Amyloid inhibition
Issue Date: 24-Mar-2023
Publisher: American Chemical Society
Abstract: Metal-organic frameworks (MOFs) are versatile compounds with emergent applications in the fabrication of biosensors for amyloid diseases. They hold great potential in biospecimen protection and unprecedented probing capabilities for optical and redox receptors. In this Review, we summarize the main methodologies employed in the fabrication of MOF-based sensors for amyloid diseases and collect all available data in the literature related to their performance (detection range, limit of detection, recovery, time of analysis, among other parameters). Nowadays, MOF sensors have evolved to a point where they can, in some cases, outperform technologies employed in the detection of several amyloid biomarkers (amyloid β peptide, α-synuclein, insulin, procalcitonin, and prolactin) present in biological fluids, such as cerebrospinal fluid and blood. A special emphasis has been given by researchers on Alzheimer's disease monitoring to the detriment of other amyloidosis that are underexploited despite their societal relevance (e.g., Parkinson's disease). There are still important obstacles to overcome in order to selectively detect the various peptide isoforms and soluble amyloid species associated with Alzheimer's disease. Furthermore, MOF contrast agents for imaging peptide soluble oligomers in living humans are also scarce (if not nonexistent), and action in this direction is unquestionably required to clarify the contentious link between the amyloidogenic species and the disease, guiding research toward the most promising therapeutic strategies.
Peer review: yes
URI: http://hdl.handle.net/10773/40426
DOI: 10.1021/acssensors.2c02741
ISSN: 2379-3694
Appears in Collections:CICECO - Artigos
DQ - Artigos

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