Evidence map›Paper›PMID 29651022›Full record

ArticleScientific reports2018

Disposable all-printed electronic biosensor for instantaneous detection and classification of pathogens.

Shawkat Ali, Arshad Hassan, Gul Hassan, Chang-Ho Eun, Jinho Bae, Chong Hyun Lee, In-Jung Kim

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

20 citing papers in PubMed, 65 citations in OpenAlex.

  1. Review
  2. Article
  3. Machine-Learning-Aided Advanced Electrochemical Biosensors.Advanced materials (Deerfield Beach, Fla.) · 2025
    Review
  4. Review
  5. Review
  6. Machine Learning in Bioelectrocatalysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. Review
  12. Article
  13. Review
  14. Review
  15. Review
  16. Article
  17. Review
  18. Article
  19. Emerging Analytical Techniques for Rapid Pathogen Identification and Susceptibility Testing.Annual review of analytical chemistry (Palo Alto, Calif.) · 2019
    Review
  20. 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

7 authors at 2 institutions in 2 countries.

Shawkat AliDepartment of Ocean System Engineering, Jeju National University, 102 Jejudaehakro, Jeju, 63243, South Korea.
Arshad HassanDepartment of Ocean System Engineering, Jeju National University, 102 Jejudaehakro, Jeju, 63243, South Korea.
Gul HassanDepartment of Ocean System Engineering, Jeju National University, 102 Jejudaehakro, Jeju, 63243, South Korea.
Chang-Ho EunSubtropical/tropical Organism Gene Bank, Jeju National University, Jeju, 63243, Republic of Korea.
Jinho BaeDepartment of Ocean System Engineering, Jeju National University, 102 Jejudaehakro, Jeju, 63243, South Korea. baejh@jejunu.ac.kr.ORCID 0000-0002-5298-0122
Chong Hyun LeeDepartment of Ocean System Engineering, Jeju National University, 102 Jejudaehakro, Jeju, 63243, South Korea.
In-Jung KimSubtropical/tropical Organism Gene Bank, Jeju National University, Jeju, 63243, Republic of Korea.
Jeju National University · KRNational University of Computer and Emerging Sciences · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel disposable all-printed electronic biosensor is proposed for a fast detection and classification of bacteria. This biosensor is applied to classify three types of popular pathogens: Salmonella typhimurium, and the Escherichia coli strains JM109 and DH5-α. The proposed sensor consists of inter-digital silver electrodes fabricated through an inkjet material printer and silver nanowires uniformly decorated on the electrodes through the electrohydrodynamic technique on a polyamide based polyethylene terephthalate substrate. The best sensitivity of the proposed sensor is achieved at 200 µm teeth spaces of the inter-digital electrodes along the density of the silver nanowires at 30 × 10

Indexed as

Biosensing TechniquesDisposable EquipmentElectrodesElectronicsEscherichia coliHumansNanowiresSalmonella typhimuriumSilverSilver

Identifiers

PMID29651022
PMCPMC5897556
OpenAlexW2889883444

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.