Evidence map›Paper›PMID 35480473›Full record

ArticleRSC advances2021

Low-fouling CNT-PEG-hydrogel coated quartz crystal microbalance sensor for saliva glucose detection.

Shiwen Wang, Guanjiang Liu, Bei Yang, Zifeng Zhang, Debo Hu, Chenchen Wu, Yaling Qin, Qian Dou, Qing Dai, Wenping Hu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in RSC advances, 2021. 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
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

3 citing papers in PubMed, 19 citations in OpenAlex.

  1. Review
  2. A Study on the OSensors (Basel, Switzerland) · 2023
    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

10 authors at 2 institutions in 3 countries.

Shiwen WangTianjin Key Laboratory of Molecular Optoelectronic Sciences, Department of Chemistry, School of Sciences, Tianjin University Tianjin 300072 China huwp@tju.edu.cn.
Guanjiang LiuDivision of Nanophotonics, CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology Beijing 100190 P. R. China douq@nanoctr.cn +86-010-82545720.
Bei YangDivision of Nanophotonics, CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology Beijing 100190 P. R. China douq@nanoctr.cn +86-010-82545720.
Zifeng ZhangDivision of Nanophotonics, CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology Beijing 100190 P. R. China douq@nanoctr.cn +86-010-82545720.
Debo HuDivision of Nanophotonics, CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology Beijing 100190 P. R. China douq@nanoctr.cn +86-010-82545720.ORCID https://orcid.org/0000-0001-9432-1670
Chenchen WuDivision of Nanophotonics, CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology Beijing 100190 P. R. China douq@nanoctr.cn +86-010-82545720.
Yaling QinDivision of Nanophotonics, CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology Beijing 100190 P. R. China douq@nanoctr.cn +86-010-82545720.
Qian DouDivision of Nanophotonics, CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology Beijing 100190 P. R. China douq@nanoctr.cn +86-010-82545720.ORCID https://orcid.org/0000-0002-3632-6200
Qing DaiDivision of Nanophotonics, CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology Beijing 100190 P. R. China douq@nanoctr.cn +86-010-82545720.ORCID https://orcid.org/0000-0002-1750-0867
Wenping HuTianjin Key Laboratory of Molecular Optoelectronic Sciences, Department of Chemistry, School of Sciences, Tianjin University Tianjin 300072 China huwp@tju.edu.cn.
Center for NanoScience · DETianjin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Saliva glucose detection based on a quartz crystal microbalance (QCM) sensor has emerged as a promising tool and a non-invasive diagnostic technique for diabetes. However, the low glucose concentration and strong protein interference in the saliva hinder the QCM sensors from practical applications. In this study, we present a robust and simple anti-fouling CNT-PEG-hydrogel film-coated QCM sensor for the detection of saliva glucose with high sensitivity. The CNT-PEG-hydrogel film consists of two layers; the bottom base PBA-hydrogel film is designed to recognize the glucose while the top CNT-PEG layer is used to restrict protein adsorption and improve the biocompatibility. Our results show that this CNT-PEG-hydrogel film exhibited a 10-fold enhancement on the detection limit compared to the PBA-hydrogel. Meanwhile, the adsorption of proteins on the surface of the CNT-PEG-hydrogel film, including bovine serum albumin (BSA), mucin (MUC), and fibrinogen (FIB), were reduced by 99.1%, 77.8%, and 83.7%, respectively. The CNT-PEG-hydrogel film could detect the typical saliva glucose level (0-50 mg L

Identifiers

PMID35480473
PMCPMC9034414
OpenAlexW3176294333

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.