Evidence map›Paper›PMID 33740542›Full record

ArticleBiosensors & bioelectronics2021

5G-enabled ultra-sensitive fluorescence sensor for proactive prognosis of COVID-19.

Jiuchuan Guo, Shuqin Chen, Shulin Tian, Ke Liu, Jian Ni, Ming Zhao, Yuejun Kang, Xing Ma, Jinhong Guo

Abstract read
In one paragraph

Article in Biosensors & bioelectronics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 3 pooled it
–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

56 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Review
  5. Article
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  13. Coronavirus Anatomy and Its Analytical Approaches for Targeting COVID-19.Advances in experimental medicine and biology · 2024
    Review
  14. Article
  15. Review
  16. Review
  17. Article
  18. Engineering Innovative Interfaces for Point-of-Care Diagnostics.Current opinion in colloid & interface science · 2023
    Review
  19. Portable sensing devices for smart healthcare and prevention of lead poisoning.Journal of the Chinese Medical Association : JCMA · 2023
    Review
  20. 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

9 authors.

Jiuchuan GuoSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, PR China.
Shuqin ChenSchool of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, PR China.
Shulin TianSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, PR China.
Ke LiuSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, PR China.
Jian NiState Key Lab of Advanced Welding and Joining, Harbin Insititude of Technology (Shenzhen), Shenzhen, 518055, PR China.
Ming ZhaoState Key Lab of Advanced Welding and Joining, Harbin Insititude of Technology (Shenzhen), Shenzhen, 518055, PR China.
Yuejun KangSchool of Materials and Energy, Southwest University, Chongqing, 400715, PR China.
Xing MaSchool of Materials Science and Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, PR China; Shenzhen Bay Laboratory, No.9 Duxue Road, Shenzhen, 518055, PR China. Electronic address: maxing@hit.edu.cn.
Jinhong GuoSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, PR China. Electronic address: guojinhong@uestc.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading around the globe since December 2019. There is an urgent need to develop sensitive and online methods for on-site diagnosing and monitoring of suspected COVID-19 patients. With the huge development of Internet of Things (IoT), the impact of Internet of Medical Things (IoMT) provides an impressive solution to this problem. In this paper, we proposed a 5G-enabled fluorescence sensor for quantitative detection of spike protein and nucleocapsid protein of SARS-CoV-2 by using mesoporous silica encapsulated up-conversion nanoparticles (UCNPs@mSiO

Indexed as

Biosensing TechniquesComputer SystemsImmunoassayCOVID-19FluorescenceHumansPrognosisSARS-CoV-25G communication5G-enabled fluorescence sensorInternet of medical thingsLateral flow immunoassayProactive prognosis of COVID-19

Identifiers

PMID33740542
PMCPMC7954646

What OpenQuestion holds

Textmetadata
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.