Evidence map›Paper›PMID 37056625›Full record

ArticleNanoscale advances2023

Ibuprofen-loaded electrospun poly(ethylene-

Jean Schoeller, Karin Wuertz-Kozak, Stephen J Ferguson, Markus Rottmar, Jonathan Avaro, Yvonne Elbs-Glatz, Michael Chung, René M Rossi

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nanoscale advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 33% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

8 authors at 4 institutions in 3 countries.

Jean SchoellerEmpa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Biomimetic Membranes and Textiles 9014 St. Gallen Switzerland rene.rossi@empa.ch.ORCID https://orcid.org/0000-0003-1511-4732
Karin Wuertz-KozakRochester Institute of Technology (RIT), Department of Biomedical Engineering Rochester NY 14623 USA.
Stephen J FergusonETH Zürich, Institute for Biomechanics 8093 Zürich Switzerland.
Markus RottmarEmpa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Biointerfaces 9014 St. Gallen Switzerland.ORCID https://orcid.org/0000-0001-7636-428X
Jonathan AvaroEmpa, Swiss Federal Laboratories for Materials Science and Technology, Center for X-ray Analytics 8600 Dübendorf Switzerland.
Yvonne Elbs-GlatzEmpa, Swiss Federal Laboratories for Materials Science and Technology, Center for X-ray Analytics 8600 Dübendorf Switzerland.
Michael ChungSchool of Engineering, The University of Edinburgh King's Buildings EH9 3JL Edinburgh UK.
René M RossiEmpa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Biomimetic Membranes and Textiles 9014 St. Gallen Switzerland rene.rossi@empa.ch.ORCID https://orcid.org/0000-0003-0946-682X
Swiss Federal Laboratories for Materials Science and Technology · CHETH Zurich · CHRochester Institute of Technology · USUniversity of Edinburgh · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic wounds are characterized by a prolonged inflammation phase preventing the normal processes of wound healing and natural regeneration of the skin. To tackle this issue, electrospun nanofibers, inherently possessing a high surface-to-volume ratio and high porosity, are promising candidates for the design of anti-inflammatory drug delivery systems. In this study, we evaluated the ability of poly(ethylene-

Identifiers

PMID37056625
PMCPMC10089083
OpenAlexW4323528628

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.