Evidence map›Paper›PMID 40136948›Full record

ReviewBiosensors2025

Recent Advances in Electrochemical Biosensors for Neurodegenerative Disease Biomarkers.

Mingyu Bae, Nayoung Kim, Euni Cho, Taek Lee, Jin-Ho Lee

Abstract readReview
In one paragraph

Review in Biosensors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mingyu BaeDepartment of Information Convergence Engineering, Pusan National University, Yangsan 50612, Republic of Korea.
Nayoung KimDepartment of Information Convergence Engineering, Pusan National University, Yangsan 50612, Republic of Korea.
Euni ChoDepartment of Information Convergence Engineering, Pusan National University, Yangsan 50612, Republic of Korea.
Taek LeeDepartment of Chemical Engineering, Kwangwoon University, Seoul 01897, Republic of Korea.
Jin-Ho LeeDepartment of Information Convergence Engineering, Pusan National University, Yangsan 50612, Republic of Korea.ORCID 0000-0002-5877-0222

Funding

Pusan National University This work was supported by a 2-Year Research Grant of Pusan National University
6 · The paper itself

Abstract

Neurodegenerative diseases, such as Parkinson's disease (PD) and Alzheimer's disease (AD), represent a growing global health challenge with overlapping biomarkers. Key biomarkers, including α-synucleins, amyloid-β, and Tau proteins, are critical for accurate detection but are often assessed using conventional methods like enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR), which are invasive, costly, and time-intensive. Electrochemical biosensors have emerged as promising tools for biomarker detection due to their high sensitivity, rapid response, and potential for miniaturization. The integration of nanomaterials has further enhanced their performance, improving sensitivity, specificity, and practical application. To this end, this review provides a comprehensive overview of recent advances in electrochemical biosensors for detecting neurodegenerative disease biomarkers, highlighting their strengths, limitations, and future opportunities. By addressing the challenges of early diagnosis, this work aims to stimulate interdisciplinary innovation and improve clinical outcomes for neurodegenerative disease patients.

Indexed as

BiomarkersBiosensing TechniquesElectrochemical TechniquesNeurodegenerative Diseasesalpha-SynucleinAlzheimer DiseaseAmyloid beta-PeptidesHumanstau Proteinsalpha-SynucleinAmyloid beta-PeptidesBiomarkerstau Proteinsamyloid-βelectrochemical biosensorneurodegenerative diseasetau proteinsα-synucleins

Identifiers

PMID40136948
PMCPMC11939888

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.