Evidence map›Paper›PMID 28350811›Full record

ArticlePloS one2017

Sampling and detection of airborne influenza virus towards point-of-care applications.

Laila Ladhani, Gaspard Pardon, Hanne Meeuws, Liesbeth van Wesenbeeck, Kristiane Schmidt, Lieven Stuyver, Wouter van der Wijngaart

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–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

26 citing papers in PubMed.

  1. Review
  2. Article
  3. Development of a Platform forAerosol science and technology : the journal of the American Association for Aerosol Research · 2026
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Micro and Nanoscale Technologies for Diagnosis of Viral Infections.Small (Weinheim an der Bergstrasse, Germany) · 2021
    Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. COVID-19: impact on colorectal surgery.Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland · 2020
    Article
  20. Bioaerosol Sampling: Classical Approaches, Advances, and Perspectives.Aerosol science and technology : the journal of the American Association for Aerosol Research · 2020
    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.

Laila LadhaniKTH Royal Institute of Technology, Department of Micro and Nanosystems, Stockholm, Sweden.
Gaspard PardonKTH Royal Institute of Technology, Department of Micro and Nanosystems, Stockholm, Sweden.ORCID http://orcid.org/0000-0001-9177-1174
Hanne MeeuwsJanssen Diagnostics, Beerse, Belgium.
Liesbeth van WesenbeeckJanssen Diagnostics, Beerse, Belgium.
Kristiane SchmidtJanssen Diagnostics, Beerse, Belgium.
Lieven StuyverJanssen Diagnostics, Beerse, Belgium.
Wouter van der WijngaartKTH Royal Institute of Technology, Department of Micro and Nanosystems, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Airborne transmission of the influenza virus contributes significantly to the spread of this infectious pathogen, particularly over large distances when carried by aerosol droplets with long survival times. Efficient sampling of virus-loaded aerosol in combination with a low limit of detection of the collected virus could enable rapid and early detection of airborne influenza virus at the point-of-care setting. Here, we demonstrate a successful sampling and detection of airborne influenza virus using a system specifically developed for such applications. Our system consists of a custom-made electrostatic precipitation (ESP)-based bioaerosol sampler that is coupled with downstream quantitative polymerase chain reaction (qPCR) analysis. Aerosolized viruses are sampled directly into a miniaturized collector with liquid volume of 150 μL, which constitutes a simple and direct interface with subsequent biological assays. This approach reduces sample dilution by at least one order of magnitude when compared to other liquid-based aerosol bio-samplers. Performance of our ESP-based sampler was evaluated using influenza virus-loaded sub-micron aerosols generated from both cultured and clinical samples. Despite the miniaturized collection volume, we demonstrate a collection efficiency of at least 10% and sensitive detection of a minimum of 3721 RNA copies. Furthermore, we show that an improved extraction protocol can allow viral recovery of down to 303 RNA copies and a maximum sampler collection efficiency of 47%. A device with such a performance would reduce sampling times dramatically, from a few hours with current sampling methods down to a couple of minutes with our ESP-based bioaerosol sampler.

Indexed as

Air MicrobiologyAerosolsEnvironmental MonitoringEquipment DesignHumansInfluenza A Virus, H1N1 SubtypeInfluenza A Virus, H3N2 SubtypeInfluenza, HumanPoint-of-Care SystemsRNA, ViralAerosolsRNA, Viral

Identifiers

PMID28350811
PMCPMC5369763

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.