Evidence map›Paper›PMID 36679421›Full record

ArticleSensors (Basel, Switzerland)2023

Ultrasensitive Detection of Interleukin 6 by Using Silicon Nanowire Field-Effect Transistors.

Wen-Pin Hu, Yu-Ming Wu, Cao-An Vu, Wen-Yih Chen

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.4field-weighted citation impact, top 12% of its field
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

7 citing papers in PubMed, 22 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

4 authors at 2 institutions in 1 country.

Wen-Pin HuDepartment of Bioinformatics and Medical Engineering, Asia University, Taichung 41354, Taiwan.ORCID 0000-0003-1826-7689
Yu-Ming WuDepartment of Chemical and Materials Engineering, National Central University, Taoyuan City 32001, Taiwan.ORCID 0000-0003-2552-5367
Cao-An VuDepartment of Chemical and Materials Engineering, National Central University, Taoyuan City 32001, Taiwan.ORCID 0000-0001-7646-1039
Wen-Yih ChenDepartment of Chemical and Materials Engineering, National Central University, Taoyuan City 32001, Taiwan.
National Central University · TWAsia University · TW

Funding

National Science and Technology Council, Taiwan MOST 111-2221-E-008-008
6 · The paper itself

Abstract

Interleukin 6 (IL-6) has been regarded as a biomarker that can be applied as a predictor for the severity of COVID-19-infected patients. The IL-6 level also correlates well with respiratory dysfunction and mortality risk. In this work, three silanization approaches and two types of biorecognition elements were used on the silicon nanowire field-effect transistors (SiNW-FETs) to investigate and compare the sensing performance on the detection of IL-6. Experimental data revealed that the mixed-SAMs-modified silica surface could have superior surface morphology to APTES-modified and APS-modified silica surfaces. According to the data on detecting various concentrations of IL-6, the detection range of the aptamer-functionalized SiNW-FET was broader than that of the antibody-functionalized SiNW-FET. In addition, the lowest concentration of valid detection for the aptamer-functionalized SiNW-FET was 2.1 pg/mL, two orders of magnitude lower than the antibody-functionalized SiNW-FET. The detection range of the aptamer-functionalized SiNW-FET covered the concentration of IL-6, which could be used to predict fatal outcomes of COVID-19. The detection results in the buffer showed that the anti-IL-6 aptamer could produce better detection results on the SiNW-FETs, indicating its great opportunity in applications for sensing clinical samples.

Indexed as

Biosensing TechniquesCOVID-19NanowiresAntibodiesHumansInterleukin-6SiliconSilicon DioxideTransistors, ElectronicAntibodiesInterleukin-6SiliconSilicon DioxideaptamerCOVID-19field-effect transistorsinfectious diseasesinterleukin 6

Identifiers

PMID36679421
PMCPMC9865274
OpenAlexW4313509727

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.