Evidence map›Paper›PMID 39996988›Full record

ArticleBiosensors2025

The Effect of GO Flake Size on Field-Effect Transistor (FET)-Based Biosensor Performance for Detection of Ions and PACAP 38.

Seungjun Lee, Jongdeok Park, Jaeyoon Song, Jae-Joon Lee, Jinsik Kim

Abstract read
In one paragraph

Article in Biosensors, 2025. 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
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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

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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.

Seungjun LeeDepartment of Medical Biotechnology, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of Korea.
Jongdeok ParkResearch Center for Photoenergy Harvesting & Conversion Technology (phct), Department of Energy and Materials Engineering, Dongguk University, Seoul 04620, Republic of Korea.ORCID 0009-0009-5399-2369
Jaeyoon SongDepartment of Medical Biotechnology, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of Korea.ORCID 0000-0001-5663-238X
Jae-Joon LeeResearch Center for Photoenergy Harvesting & Conversion Technology (phct), Department of Energy and Materials Engineering, Dongguk University, Seoul 04620, Republic of Korea.ORCID 0000-0001-8966-0336
Jinsik KimDepartment of Medical Biotechnology, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of Korea.

Funding

Korea Evaluation Institute of Industrial Technology RS-2023-00235283Korea Evaluation Institute of Industrial Technology RS-2023-00257607Korea Institute for Advancement of Technology P0017805National Research Foundation of Korea 2023R1A2C2007147
6 · The paper itself

Abstract

The performance development of rGO-FET biosensors by analyzing the influence of GO flake size on biosensing efficacy. GO flakes of varying sizes, from 1 µm to 20 µm, were prepared under controlled conditions, followed by characterization through SEM and XPS to evaluate their size, surface area, and C/O ratio. The biosensing performance was systematically assessed by rGO-FET biosensors, examining the effects of GO flake size, C/O ratio, and film thickness. PACAP38 was employed as a biomarker for receptor-mediated detection, while chlorine ions served as model analytes for receptor-free small molecule detection. The results indicate that decreasing the GO flake size enhanced the performance for both target biomolecules. These findings highlight the crucial importance of selecting GO flake sizes specific to target analytes and detection strategies, thereby optimizing biosensor efficiency.

Indexed as

Biosensing TechniquesGraphitePituitary Adenylate Cyclase-Activating PolypeptideIonsTransistors, Electronicgraphene oxideGraphiteIonsPituitary Adenylate Cyclase-Activating PolypeptidebiomoleculesC/O ratioreduced graphene oxide (rGO)rGO-FETsurface area

Identifiers

PMID39996988
PMCPMC11853402

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Registered trials

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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.