Evidence map›Paper›PMID 40246821›Full record

ArticleMicrosystems & nanoengineering2025

Extracellular vesicle-based point-of-care testing for diagnosis and monitoring of Alzheimer's disease.

Xiang Li, Jie Chen, Yang Yang, Hongwei Cai, Zheng Ao, Yantao Xing, Kangle Li, Kaiyuan Yang, Weihua Guan, James Friend and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Microsystems & nanoengineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Xiang Li *Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, 47405, USA.ORCID http://orcid.org/0000-0002-4916-524X
Jie Chen *Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
Yang Yang *Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, 47405, USA.
Hongwei CaiDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, IN, 47405, USA.
Zheng AoDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, IN, 47405, USA.
Yantao XingDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, IN, 47405, USA.
Kangle LiDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, IN, 47405, USA.
Kaiyuan YangDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, IN, 47405, USA.
Weihua GuanDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, IN, 47405, USA.ORCID http://orcid.org/0000-0002-8435-9672
James FriendDepartment of Mechanical and Aerospace Engineering, and Department of Surgery, University of California San Diego, La Jolla, CA, 92093, USA.ORCID http://orcid.org/0000-0003-0416-2165
Luke P LeeDepartment of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA. lplee@bwh.harvard.edu.ORCID http://orcid.org/0000-0002-1436-4054
Nian WangAdvanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA. Nian.Wang@UTSouthwestern.edu.
Feng GuoDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, IN, 47405, USA. fengguo@iu.edu.ORCID http://orcid.org/0000-0001-9103-3235

Funding

An automated portable system for detecting and treating opioid induced respiratory depressionU01DA056242 · NIDA · TRUSTEES OF INDIANA UNIVERSITY · PI GUO, FENG, MACKIE, KENNETH · 2022 to 2024
$3.8M
Early detection of type 1 diabetes via Exosome Technology with Optoelectronics Lab-on-chip: EXTOLR01DK133864 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI GAGLIA, JASON, GUO, FENG · 2022 to 2025
$3.0M
An acoustofluidic avidity cytometer for massive parallel profiling single autoreactive T cell in autoimmune diseaseDP2AI160242 · NIAID · TRUSTEES OF INDIANA UNIVERSITY · PI GUO, FENG · 2020 to 2020
$2.4M
NIAID NIH HHS DP2 AI160242NIDA NIH HHS U01 DA056242NIDDK NIH HHS R01 DK133864
6 · The paper itself

Abstract

Extracellular vesicles (EVs) show potential for early diagnosis of Alzheimer's disease (AD) and monitoring of its progression. However, EV-based AD diagnosis faces challenges due to the small size and low abundance of biomarkers. Here, we report a fully integrated organic electrochemical transistor (OECT) sensor for ultrafast, accurate, and convenient point-of-care testing (POCT) of serum EVs from AD patients. By utilizing acoustoelectric enrichment, the EVs can be quickly propelled, significantly enriched, and specifically bound to the OECT detection area, achieving a gain of over 280 times response in 30 s. The integrated POCT sensor can detect serum EVs from AD patients with a limit of detection as low as 500 EV particles/mL and a reduced detection time of just two minutes. Furthermore, the integrated POCT sensors were used to monitor AD progression in an AD mouse model by testing the mouse Aβ EVs at different time courses (up to 18 months) and compared with the Aβ accumulation using high-resolution magnetic resonance imaging (MRI). This innovative technology has the potential for accurate and rapid diagnosis of Alzheimer's and other neurodegenerative diseases, and monitoring of disease progression and treatment response.

Identifiers

PMID40246821
PMCPMC12006457

What OpenQuestion holds

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LicenceCC BY-NC-ND
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 OpenQuestion graph.