Evidence map›Paper›PMID 40325219›Full record

ReviewMikrochimica acta2025

Biosensors based on organic transistors for intraoral biomarker detection.

Ruotong Mai, Yixin Zhou, Kangning Zhao, Miao Xie, Yufei Tang, Xingrui Li, Wei Huang, Lin Xiang

Abstract readReview
PubMed Publisher
In one paragraph

Review in Mikrochimica acta, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

8 authors.

Ruotong MaiState Key Laboratory of Oral Diseases & National Center for Stomatology &, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China.
Yixin ZhouSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, China.
Kangning ZhaoState Key Laboratory of Oral Diseases & National Center for Stomatology &, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China.
Miao XieSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, China.
Yufei TangState Key Laboratory of Oral Diseases & National Center for Stomatology &, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China.
Xingrui LiState Key Laboratory of Oral Diseases & National Center for Stomatology &, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China.
Wei HuangSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, China. whuang@uestc.edu.cn.
Lin XiangState Key Laboratory of Oral Diseases & National Center for Stomatology &, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China. dentistxiang@126.com.

Funding

Aeronautical Science Foundation of China 20230024080002Key Technologies Research and Development Program 2024YFB3211600National Natural Science Foundation of China 82370996Sichuan Science and Technology Program 2024NSFSC0537
6 · The paper itself

Abstract

Intraoral biomarkers are important indicators for the diagnosis and prediction of oral and systemic diseases. Among various intraoral biomarkers, the biomarkers in saliva have been the main focus of research, due to their abundance, non-invasiveness, and correlation with health status. Nonetheless, detecting low-abundance intraoral biomarkers poses significant challenges, and the conventional assays are unsuitable for swift large-scale analysis due to their complex procedures. Hence, an immediate demand arises for innovative methods to supplant traditional assay techniques. Organic transistor-based biosensors have emerged as promising devices for the detection of these intraoral biomarkers, especially in point-of-care (POC) settings. These biosensors offer advantages such as high sensitivity, selectivity, ease of integration, and biocompatibility. This review provides an overview of the evolution and utilization of biosensors that rely on functional organic transistors, with a focus on electrolyte-gated organic field-effect transistors (EGOFETs) and organic electrochemical transistors (OECTs). First, the working principles and sensing mechanisms of various organic transistors are summarized. Then, recent progress and challenges in developing organic transistor-based biosensing platforms for detecting intraoral biomarkers are summarized, along with examples from representative studies. Last, prospects and opportunities for the advancement of organic transistor-based biosensors for oral health monitoring are discussed.

Indexed as

BiomarkersBiosensing TechniquesTransistors, ElectronicElectrochemical TechniquesHumansSalivaBiomarkersBiosensorIntraoral biomarkerOral fluid detectionOrganic transistor

Identifiers

PMID40325219

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.