Evidence map›Paper›PMID 39698540›Full record

ReviewExtracellular vesicles and circulating nucleic acids2024

Electrochemical detection of extracellular vesicles for early diagnosis: a focus on disease biomarker analysis.

Jintao Zheng, Runzhi Zhou, Bing Wang, Chang He, Shiyao Bai, Haoyang Yan, Jiacheng Yu, Huaiguang Li, Bo Peng, Zhaoli Gao and 4 more

Abstract readReview
In one paragraph

Review in Extracellular vesicles and circulating nucleic acids, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. Review
  8. Review
  9. Article
  10. Harnessing artificial intelligence for engineering extracellular vesicles.Extracellular vesicles and circulating nucleic acids · 2025
    Review
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

14 authors.

Jintao ZhengBiotechnology and Food Engineering, Guangdong Technion-Israel Institute of Technology (GTIIT), Shantou 515063, Guangdong, China.
Runzhi ZhouBiotechnology and Food Engineering, Guangdong Technion-Israel Institute of Technology (GTIIT), Shantou 515063, Guangdong, China.
Bing WangNMPA Key Laboratory for Bioequivalence Research of Generic Drug Evaluation, Shenzhen Institute for Drug Control, Shenzhen 518057, Guangdong, China.
Chang HeBiotechnology and Food Engineering, Guangdong Technion-Israel Institute of Technology (GTIIT), Shantou 515063, Guangdong, China.
Shiyao BaiSchool of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China.
Haoyang YanBiotechnology and Food Engineering, Guangdong Technion-Israel Institute of Technology (GTIIT), Shantou 515063, Guangdong, China.
Jiacheng YuBiotechnology and Food Engineering, Guangdong Technion-Israel Institute of Technology (GTIIT), Shantou 515063, Guangdong, China.
Huaiguang LiSchool of Science and Engineering, The Chinese University of Hong Kong, Shenzhen 518172, Guangdong, China.
Bo PengFrontiers Science Center for Flexible Electronics, Xi'an Institute of Flexible Electronics (IFE) and Xi'an Institute of Biomedical Materials & Engineering, Northwestern Polytechnical University, Xi'an 710072, shaanxi, China.
Zhaoli GaoDepartment of Biomedical Engineering, Chinese University of Hong Kong, Shatin, Hong Kong, China.
Xiean YuNMPA Key Laboratory for Bioequivalence Research of Generic Drug Evaluation, Shenzhen Institute for Drug Control, Shenzhen 518057, Guangdong, China.
Chenzhong LiSchool of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China.
Cheng JiangSchool of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China.
Keying GuoBiotechnology and Food Engineering, Guangdong Technion-Israel Institute of Technology (GTIIT), Shantou 515063, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review article presents a detailed examination of the integral role that electrochemical detection of extracellular vesicles (EVs) plays, particularly focusing on the potential application for early disease diagnostics through EVs biomarker analysis. Through an exploration of the benefits and challenges presented by electrochemical detection vetted for protein, lipid, and nucleic acid biomarker analysis, we underscore the significance of these techniques. Evidence from recent studies renders this detection modality imperative in identifying diverse biomarkers from EVs, leading to early diagnosis of diseases such as cancer and neurodegenerative disorders. Recent advancements that have led to enhanced sensitivity, specificity and point-of-care testing (POCT) potential are elucidated, along with equipment deployed for electrochemical detection. The review concludes with a contemplation of future perspectives, recognizing the potential shifts in disease diagnostics and prognosis, necessary advances for broad adoption, and potential areas of ongoing research. The objective is to propel further investigation into this rapidly burgeoning field, thereby facilitating a potential paradigm shift in disease detection, monitoring, and treatment toward human health management.

Indexed as

early disease diagnosticselectrochemical detectionExtracellular vesicles (EVs)

Identifiers

PMID39698540
PMCPMC11648401

What OpenQuestion holds

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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.