Evidence map›Paper›PMID 29430214›Full record

ArticleIEEE sensors journal2017

Angular photodiode array-based device to detect bacterial pathogens in a wound model.

Robin E Sweeney, Jeong-Yeol Yoon

Abstract read
In one paragraph

Article in IEEE sensors journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Robin E SweeneyDepartment of Biomedical Engineering at the University of Arizona, Tucson, AZ 85721, USA.
Jeong-Yeol YoonDepartment of Biomedical Engineering at the University of Arizona, Tucson, AZ 85721, USA.

Funding

Cardiovascular Biomedical Engineering Training GrantT32HL007955 · NHLBI · UNIVERSITY OF ARIZONA · PI BARTON, JENNIFER KEHLET · 2001 to 2020
$5.1M
NHLBI NIH HHS T32 HL007955
6 · The paper itself

Abstract

We have developed a device that is able to rapidly and specifically diagnose bacterial pathogens in a wound model based on Mie scatter spectra from a tissue surface. The Mie scatter spectra collected is defined as the intensity of Mie scatter over the angle of detection from a tissue surface. A 650 nm LED perpendicular to the surface illuminates a tissue sample (90°) and photodiodes positioned in 10° increments from 10° to 80° of backscatter act as the detectors to collect these Mie scatter spectra. Through principal component analysis of the Mie scatter spectra collected, we have shown significant differences between Mie scatter spectra of tissues with bacterial pathogens versus those without, as well as significant differences between each species of bacteria tested. The device developed has been tested with a porcine dermis wound model, with samples inoculated with one of three bacterial species (Staphylococcus aureus, Escherichia coli, or Salmonella Typhimurium). Such a device could be critical in the monitoring of a wound for infection and rapid, specific diagnosis of a bacterial wound infection, which would significantly reduce the time and cost associated with specific diagnosis of a bacterial wound infection currently.

Indexed as

Escherichia coliMie scatterStaphylococcus aureuswound infection

Identifiers

PMID29430214
PMCPMC5802419

What OpenQuestion holds

Textmetadata
LicenceTDM
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.