Evidence map›Paper›PMID 41807363›Full record

ArticleMicrosystems & nanoengineering2026

Boron-doped diamond solution-gate field-effect transistor (BDD-SGFET) biosensor for gene mutation detection.

Zelong Lin, Yun Zheng, Yisen Chen, Chengyong Wang, Zhishan Yuan

Abstract read
In one paragraph

Article in Microsystems & nanoengineering, 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

5 authors.

Zelong Lin *School of Electro-Mechanical Engineering, Guangdong University of Technology, Guangzhou, China.
Yun Zheng *School of Electro-Mechanical Engineering, Guangdong University of Technology, Guangzhou, China.
Yisen Chen *School of Electro-Mechanical Engineering, Guangdong University of Technology, Guangzhou, China.
Chengyong WangSchool of Electro-Mechanical Engineering, Guangdong University of Technology, Guangzhou, China.
Zhishan YuanSchool of Electro-Mechanical Engineering, Guangdong University of Technology, Guangzhou, China. zhishanyuan@gdut.edu.cn.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 52175388
6 · The paper itself

Abstract

Gene mutation is one of the core pathogenic factors in numerous major diseases, making the detection of base mismatches resulting from these mutations critically important in both biological and clinical contexts. This study presents a high-performance boron-doped diamond solution-gated field-effect transistor (BDD-SGFET) biosensor, designed with a diamond microwire structure, for the label-free detection of base mismatches associated with EGFR gene mutations. The simulations examining the impact of variations in diamond microwire dimensions on the electrical properties of BDD-SGFET reveal that increasing the microwire width while reducing its length enhances the electrical performance of the device. Utilizing microwave plasma chemical vapor deposition (MPCVD), photolithography, and plasma etching, we successfully fabricated high-performance BDD-SGFETs featuring microwire structures that demonstrate outstanding transconductance, a reduced threshold voltage, and a limit of detection of 10 pM. Notably, the enhanced performance of the fabricated BDD-SGFET enables the successful identification of DNA molecules with two base-pair mismatches. Furthermore, the device exhibits impressive anti-interference capabilities and exceptional stability in complex environments. These findings highlight the significant potential of microscale BDD-SGFETs as rapid, label-free, and robust platforms for point-of-care testing in genetic mutation analysis pertinent to cancer diagnosis.

Identifiers

PMID41807363
PMCPMC12976043

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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.