Evidence map›Paper›PMID 37367010›Full record

ArticleBiosensors2023

Ultrasensitive Silicon Nanowire Biosensor with Modulated Threshold Voltages and Ultra-Small Diameter for Early Kidney Failure Biomarker Cystatin C.

Jiawei Hu, Yinglu Li, Xufang Zhang, Yanrong Wang, Jing Zhang, Jiang Yan, Junjie Li, Zhaohao Zhang, Huaxiang Yin, Qianhui Wei and 3 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

10 citing papers in PubMed, 25 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 3 institutions in 1 country.

Jiawei HuSchool of Information Science and Technology, North China University of Technology, Beijing 100144, China.
Yinglu LiSchool of Information Science and Technology, North China University of Technology, Beijing 100144, China.
Xufang ZhangSchool of Information Science and Technology, North China University of Technology, Beijing 100144, China.
Yanrong WangSchool of Information Science and Technology, North China University of Technology, Beijing 100144, China.
Jing ZhangSchool of Information Science and Technology, North China University of Technology, Beijing 100144, China.
Jiang YanSchool of Information Science and Technology, North China University of Technology, Beijing 100144, China.
Junjie LiAdvanced Integrated Circuits R&D Center, Institute of Microelectronic of the Chinese Academy of Sciences, Beijing 100029, China.ORCID 0000-0001-5191-7992
Zhaohao ZhangAdvanced Integrated Circuits R&D Center, Institute of Microelectronic of the Chinese Academy of Sciences, Beijing 100029, China.
Huaxiang YinAdvanced Integrated Circuits R&D Center, Institute of Microelectronic of the Chinese Academy of Sciences, Beijing 100029, China.ORCID 0000-0001-8066-6002
Qianhui WeiState Key Laboratory of Advanced Materials for Smart Sensing, General Research Institute for Nonferrous Metals, Beijing 101402, China.
Qifeng JiangSchool of Information Science and Technology, North China University of Technology, Beijing 100144, China.
Shuhua WeiSchool of Information Science and Technology, North China University of Technology, Beijing 100144, China.
Qingzhu ZhangAdvanced Integrated Circuits R&D Center, Institute of Microelectronic of the Chinese Academy of Sciences, Beijing 100029, China.ORCID 0000-0003-0035-0652
North China University of Technology · CNChinese Academy of Sciences · CNGeneral Research Institute for Nonferrous Metals (China) · CN

Funding

R&D Program of Beijing Municipal Education Commission under Grant Z202210009014the Science and Technology program of Beijing Nova Program under grant Z201100006820084the "Strategic Priority Research Program" of the Chinese Academy of Sciences under Grant E1XDC2X002the Youth Innovation Promotion Association, Chinese Academy of Sciences under grants Y9YQ01R004
6 · The paper itself

Abstract

Acute kidney injury (AKI) is a frequently occurring severe disease with high mortality. Cystatin C (Cys-C), as a biomarker of early kidney failure, can be used to detect and prevent acute renal injury. In this paper, a biosensor based on a silicon nanowire field-effect transistor (SiNW FET) was studied for the quantitative detection of Cys-C. Based on the spacer image transfer (SIT) processes and channel doping optimization for higher sensitivity, a wafer-scale, highly controllable SiNW FET was designed and fabricated with a 13.5 nm SiNW. In order to improve the specificity, Cys-C antibodies were modified on the oxide layer of the SiNW surface by oxygen plasma treatment and silanization. Furthermore, a polydimethylsiloxane (PDMS) microchannel was involved in improving the effectiveness and stability of detection. The experimental results show that the SiNW FET sensors realize the lower limit of detection (LOD) of 0.25 ag/mL and have a good linear correlation in the range of Cys-C concentration from 1 ag/mL to 10 pg/mL, exhibiting its great potential in the future real-time application.

Indexed as

Biosensing TechniquesNanowiresRenal InsufficiencyBiomarkersCystatin CHumansSiliconTransistors, ElectronicBiomarkersCystatin CSiliconacute kidney injury (AKI)biosensorcystatin C (Cys-C)field effect transistor (FET)silicon nanowire (SiNW)

Identifiers

PMID37367010
PMCPMC10296041
OpenAlexW4380484486

What Socratic 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 Socratic graph.