Evidence map›Paper›PMID 35049652›Full record

ArticleBiosensors2022

An Ultrasensitive Silicon-Based Electrolyte-Gated Transistor for the Detection of Peanut Allergens.

Donghoon Kim, Bo Jin, Sol-A Kim, Wonyeong Choi, Seonghwan Shin, Jiwon Park, Won-Bo Shim, Kihyun Kim, Jeong-Soo Lee

Abstract read
In one paragraph

Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

9 authors.

Donghoon KimDepartment of Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea.
Bo JinDepartment of Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea.ORCID 0000-0003-4407-1954
Sol-A KimDivision of Applied Life Science, Graduate School, Gyeongsang National University, Jinju 52828, Korea.ORCID 0000-0002-4055-7511
Wonyeong ChoiDepartment of Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea.
Seonghwan ShinDepartment of Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea.
Jiwon ParkDepartment of Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea.ORCID 0000-0002-1380-5938
Won-Bo ShimDepartment of Food Science and Technology, Gyeongsang National University, Jinju 52828, Korea.
Kihyun KimDivision of Electronics Engineering, Jeonbuk National University, Jeonju 54896, Korea.ORCID 0000-0001-7578-7977
Jeong-Soo LeeDepartment of Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea.

Funding

Ministry of Agriculture, Food and Rural Affairs 120091-02-1-CG000National Research Foundation of Korea 2009-0082580
6 · The paper itself

Abstract

The highly sensitive detection of peanut allergens (PAs) using silicon-based electrolyte-gated transistors (Si-EGTs) was demonstrated. The Si-EGT was made using a top-down technique. The fabricated Si-EGT showed excellent intrinsic electrical characteristics, including a low threshold voltage of 0.7 V, low subthreshold swing of <70 mV/dec, and low gate leakage of <10 pA. Surface functionalization and immobilization of antibodies were performed for the selective detection of PAs. The voltage-related sensitivity (

Indexed as

ArachisSiliconTransistors, ElectronicAllergensElectrolytesAllergensElectrolytesSiliconBioFETbiosensorelectrolyte gatelimit of detectionpeanut allergen

Identifiers

PMID35049652
PMCPMC8773534

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.