Clinically oriented Alzheimer's biosensors: expanding the horizons towards point-of-care diagnostics and beyond

Murti, Bayu Tri; Putri, Athika Darumas; Huang, Yu-Lieh; Wei, Shih Min; Peng, Chih Wei; Yang, Po Kang

doi:10.1039/d1ra01553b

Cited by 10 publications

(4 citation statements)

References 231 publications

(318 reference statements)

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“…Plasmonic nanomaterials have been extensively utilized for diagnostic applications because of their unique properties, such as a large surface area, easy surface modification, and distinct surface plasmon resonance [1][2][3][4][5][6][7][8][9][10]. Among various plasmonic nanomaterials, gold-based nanomaterials with tunable size and shape have been extensively applied for biomedical detection based on their optical and structural characteristics [11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Plasmonic Gold Nanoisland Film for Bacterial Theranostics

et al. 2021

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Plasmonic nanomaterials have been intensively explored for applications in biomedical detection and therapy for human sustainability. Herein, plasmonic gold nanoisland (NI) film (AuNIF) was fabricated onto a glass substrate by a facile seed-mediated growth approach. The structure of the tortuous gold NIs of the AuNIF was demonstrated by scanning electron microscopy and energy-dispersive X-ray spectroscopy. Based on the ultraviolet-visible spectrum, the AuNIF revealed plasmonic absorption with maximum intensity at 624 nm. With the change to the surface topography created by the NIs, the capture efficiency of Escherichia coli (E. coli) by the AuNIF was significantly increased compared to that of the glass substrate. The AuNIF was applied as a surface-enhanced Raman scattering (SERS) substrate to enhance the Raman signal of E. coli. Moreover, the plasmonic AuNIF exhibited a superior photothermal effect under irradiation with simulated AM1.5 sunlight. For photothermal therapy, the AuNIF also displayed outstanding efficiency in the photothermal killing of E. coli. Using a combination of SERS detection and photothermal therapy, the AuNIF could be a promising platform for bacterial theranostics.

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Section: Introductionmentioning

confidence: 99%

Plasmonic Gold Nanoisland Film for Bacterial Theranostics

et al. 2021

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“…The future of Raman-based liquid biopsy detection systems for NDs and brain disorders holds significant promise in revolutionizing diagnostic and monitoring approaches. 220,221 Early detection is crucial for initiating interventions before significant neurological damage occurs. Continued efforts to identify novel biomarkers associated with NDs in biofluids may lead to the discovery of early and predictive markers.…”

Section: Conclusion and Future Prospectsmentioning

confidence: 99%

Unveiling brain disorders using liquid biopsy and Raman spectroscopy

Ranasinghe,

Wang,

Huang

2024

Nanoscale

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“…A new chain-shaped electrode was developed to avoid the edge effect of the electric field distribution by immobilizing a specific anti-Ab antibody onto a self-assembled monolayer functionalized inter-digitated chain-shaped electrode designed to improve the sensing area homogeneity. Recent studies highlight various types of bio-sensors, which include electrochemical, fluorescent, and (FET)-based sensor configurations for AD clinical monitoring [28].…”

Section: Bio-sensors For Biofluid Marker Detection In Admentioning

confidence: 99%

Revolutionizing the Early Detection of Alzheimer’s Disease through Non-Invasive Biomarkers: The Role of Artificial Intelligence and Deep Learning

Vrahatis

Skolariki

Krokidis

et al. 2023

Sensors

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Alzheimer’s disease (AD) is now classified as a silent pandemic due to concerning current statistics and future predictions. Despite this, no effective treatment or accurate diagnosis currently exists. The negative impacts of invasive techniques and the failure of clinical trials have prompted a shift in research towards non-invasive treatments. In light of this, there is a growing need for early detection of AD through non-invasive approaches. The abundance of data generated by non-invasive techniques such as blood component monitoring, imaging, wearable sensors, and bio-sensors not only offers a platform for more accurate and reliable bio-marker developments but also significantly reduces patient pain, psychological impact, risk of complications, and cost. Nevertheless, there are challenges concerning the computational analysis of the large quantities of data generated, which can provide crucial information for the early diagnosis of AD. Hence, the integration of artificial intelligence and deep learning is critical to addressing these challenges. This work attempts to examine some of the facts and the current situation of these approaches to AD diagnosis by leveraging the potential of these tools and utilizing the vast amount of non-invasive data in order to revolutionize the early detection of AD according to the principles of a new non-invasive medicine era.

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Clinically oriented Alzheimer's biosensors: expanding the horizons towards point-of-care diagnostics and beyond

Abstract: Advancements of clinically driven biosensors in current Alzheimer's diagnosis are highlighted in both in vitro and in vivo applications.

Cited by 10 publications

References 231 publications

Plasmonic Gold Nanoisland Film for Bacterial Theranostics

Plasmonic Gold Nanoisland Film for Bacterial Theranostics

Unveiling brain disorders using liquid biopsy and Raman spectroscopy

Revolutionizing the Early Detection of Alzheimer’s Disease through Non-Invasive Biomarkers: The Role of Artificial Intelligence and Deep Learning

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