Evidence map›Paper›PMID 24696687›Full record

ArticleInternational journal of biomaterials2014

A Novel Qualitative and Quantitative Biofilm Assay Based on 3D Soft Tissue.

Bodil Hakonen, Linnea K Lönnberg, Eva Larkö, Kristina Blom

Open access · goldAbstract read
In one paragraph

Article in International journal of biomaterials, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-weighted citation impact, top 32% 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

7 citing papers in PubMed, 15 citations in OpenAlex.

  1. Assessing Virulence Factor Genes in Pig-DerivedPathogens (Basel, Switzerland) · 2026
    Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. 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

4 authors at 1 institution in 1 country.

Bodil HakonenMedibiome AB, 431 53 Mölndal, Sweden.
Linnea K LönnbergMedibiome AB, 431 53 Mölndal, Sweden ; Department of Medical Microbiology and Immunology, Sahlgrenska Academy, University of Gothenburg, 413 45 Göteborg, Sweden.
Eva LarköMedibiome AB, 431 53 Mölndal, Sweden.
Kristina BlomMedibiome AB, 431 53 Mölndal, Sweden.
University of Gothenburg · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The lack of predictable in vitro methods to analyze antimicrobial activity could play a role in the development of resistance to antibiotics. Current used methods analyze planktonic cells but for the method to be clinically relevant, biofilm in in vivo like conditions ought to be studied. Hence, our group has developed a qualitative and quantitative method with in vivo like 3D tissue for prediction of antimicrobial activity in reality. Devices (wound dressings) were applied on top of Pseudomonas aeruginosa inoculated Muller-Hinton (MH) agar or 3D synthetic soft tissues (SST) and incubated for 24 hours. The antibacterial activity was then analyzed visually and by viable counts. On MH agar two out of three silver containing devices showed zone of inhibitions (ZOI) and on SST, ZOI were detected for all three. Corroborating results were found upon evaluating the bacterial load in SST and shown to be silver concentration dependent. In conclusion, a novel method was developed combining visual rapid screening and quantitative evaluation of the antimicrobial activity in both tissue and devices. It uses tissue allowing biofilm formation thus mimicking reality closely. These conditions are essential in order to predict antimicrobial activity of medical devices in the task to prevent device related infections.

Identifiers

PMID24696687
PMCPMC3948644
OpenAlexW2091846056

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.