Evidence map›Paper›PMID 41770368›Full record

ReviewMikrochimica acta2026

Recent advances in microfluidic technologies for the detection of Alzheimer's disease biomarkers: toward point-of-care neurodiagnostic.

Subham Preetam, Richa Mishra, Saad Alghamdi, Akhmed Aslam, Shailendra Thapliyal, Sarvesh Rustagi, R K Govindarajan, Soumya Pandit, Jutishna Bora, Muhammad Fazle Rabbee and 2 more

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In one paragraph

Review in Mikrochimica acta, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Subham Preetam *Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Dalseong-gun, Daegu, 42988, South Korea. subhampreetam@dgist.ac.kr.
Richa MishraDepartment of Computer Engineering, Parul Institute of Engineering and Technology (PIET), Parul University, Ta. Waghodia, Vadodara, 391760, Gujarat, India.
Saad AlghamdiDepartment of Clinical Laboratory Sciences, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia.
Akhmed AslamDepartment of Clinical Laboratory Sciences, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia.
Shailendra ThapliyalUttaranchal Institute of Technology, Uttaranchal University, Dehradun, 248007, India.
Sarvesh RustagiDepartment of food Technology, Dev Bhoomi Uttarakhand University, Dehradun, Uttrakhand, 248007, India.
R K GovindarajanDepartment of Biotechnology, Karpagam Academy of Higher Education, Coimbatore, 641021, Tamil Nadu, India.
Soumya PanditDepartment of Life Sciences, School of Biosciences and Technology, Sharda University, Noida, 201301, UP, India.
Jutishna BoraAmity Institute of Biotechnology, Amity University Jharkhand, Ranchi, 834002, India.
Muhammad Fazle RabbeeDepartment of Biotechnology, Yeungnam University, Gyeongsan, Gyeongbuk, 38541, Republic of Korea.
Nayan TalukdarProgramming of Biotechnology, Faculty of Science, Assam Down Town University, Guwahati, 781026, Assam, India.
Sumira MalikUniversity Center for Research & Development (UCRD) Chandigarh University, NH-05 Chandigarh- Ludhiana Highway, Mohali, Punjab, India. smalik@rnc.amity.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer’s disease (AD) is the most common form of dementia. It poses a major global health challenge due to its increasing prevalence and lack of early diagnostic tools. Conventional diagnostic approaches such as cerebrospinal fluid analysis and neuroimaging are invasive, expensive, and not well-suited for large-scale screening. In recent years, microfluidic technologies have emerged as a transformative platform for the early, rapid, and minimally invasive detection of AD biomarkers. Recent progress in the development of microfluidic systems for detecting key AD biomarkers includes amyloid-beta, phosphorylated tau, neurofilament light chain, and exosome-associated microRNAs. Herein, we discuss various microfluidic formats, including lab-on-a-chip, paper-based devices, droplet microfluidics, and organ-on-a-chip, and their integration with detection modalities such as electrochemical sensing, fluorescence, and surface-enhanced Raman spectroscopy. Recent advances and challenges in clinical translation, and future directions involving AI-driven analysis and multi-omics integration are presented. This review underscores the promise of microfluidic platforms in enabling point-of-care, personalised diagnostics for Alzheimer’s disease accelerating the transition from bench to bedside.

Indexed as

Alzheimer DiseaseMicrofluidic Analytical TechniquesPoint-of-Care SystemsAmyloid beta-PeptidesBiomarkersHumansLab-On-A-Chip DevicesMicroRNAstau ProteinsAmyloid beta-PeptidesBiomarkersMicroRNAstau ProteinsAlzheimer’s diseaseAmyloid-betaBiomarkersExosome-associated microRNAMicrofluidicsPoint-of-care diagnosticsTau protein

Identifiers

What Socratic holds

Textmetadata
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.