Evidence map›Paper›PMID 30424405›Full record

ArticleMicromachines2018

A 3D-Printed Millifluidic Platform Enabling Bacterial Preconcentration and DNA Purification for Molecular Detection of Pathogens in Blood.

Yonghee Kim, Jinyeop Lee, Sungsu Park

Open access · goldAbstract read
In one paragraph

Article in Micromachines, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

14 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. ABiosensors · 2022
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. 3D-printed Bioreactors forInternational journal of bioprinting · 2020
    Review
  12. Article
  13. Review
  14. 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

3 authors at 1 institution in 1 country.

Yonghee KimSchool of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Korea. hanskim723@gmail.com.
Jinyeop LeeSchool of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Korea. softmemsljy@naver.com.
Sungsu ParkSchool of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Korea. nanopark@skku.edu.ORCID 0000-0003-3062-1302
Sungkyunkwan University · KR

Funding

National Research Foundation of Korea H-guard NRF-2018M3A6B2057299
6 · The paper itself

Abstract

Molecular detection of pathogens in clinical samples often requires pretreatment techniques, including immunomagnetic separation and magnetic silica-bead-based DNA purification to obtain the purified DNA of pathogens. These two techniques usually rely on handling small tubes containing a few millilitres of the sample and manual operation, implying that an automated system encompassing both techniques is needed for larger quantities of the samples. Here, we report a three-dimensional (3D)-printed millifluidic platform that enables bacterial preconcentration and genomic DNA (gDNA) purification for improving the molecular detection of target pathogens in blood samples. The device consists of two millichannels and one chamber, which can be used to preconcentrate pathogens bound to antibody-conjugated magnetic nanoparticles (Ab-MNPs) and subsequently extract gDNA using magnetic silica beads (MSBs) in a sequential manner. The platform was able to preconcentrate very low concentrations (1⁻1000 colony forming units (CFU)) of

Indexed as

3D printingbacterial pathogenDNA purificationimmunomagnetic separation (IMS)molecular diagnosticspreconcentration

Identifiers

PMID30424405
PMCPMC6187281
OpenAlexW2889841277

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.