Evidence map›Paper›PMID 38045132›Full record

ArticleHeliyon2023

Characterization and

Erfan Dorkhani, Bahareh Darzi, Laleh Foroutani, Zahra Ebrahim Soltani, Seyed Mohsen Ahmadi Tafti

Abstract read
In one paragraph

Article in Heliyon, 2023. 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. 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

5 authors.

Erfan DorkhaniResearch Center for Advanced Technologies in Cardiovascular Medicine, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran 1411713138, Iran.
Bahareh DarziResearch Center for Advanced Technologies in Cardiovascular Medicine, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran 1411713138, Iran.
Laleh ForoutaniResearch Center for Advanced Technologies in Cardiovascular Medicine, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran 1411713138, Iran.
Zahra Ebrahim SoltaniExperimental Medicine Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Seyed Mohsen Ahmadi TaftiResearch Center for Advanced Technologies in Cardiovascular Medicine, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran 1411713138, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The most widely taken medical approach toward hernia repair involves the implementation of a prosthetic mesh to cover the herniated site and reinforce the weakened area of the abdominal wall. Biodegradable meshes can serve as biocompatible grafts with a low risk of infection. However, their major complication is associated with a high rate of degradation and hernia recurrence. We proposed a facile and cost-effective method to fabricate a poly(vinyl alcohol)-based mesh, using the solution casting technique. The inclusion of zinc oxide nanoparticles, citric acid, and three cycles of freeze-thaw were intended to ameliorate the mechanical properties of poly(vinyl alcohol). Several characterization, cell culture, and animal studies were conducted. Swelling and water contact angle measurements confirmed good water uptake capacity and wetting behavior of the final mesh sample. The synthesized mesh acquired a high mechanical strength of 52.8 MPa, and its weight loss was decreased to 39 %. No cytotoxicity was found in all samples.

Indexed as

Citric acidFreeze-thawHernia repairpoly(vinyl alcohol)Solution castingZinc oxide nanoparticles

Identifiers

PMID38045132
PMCPMC10689958

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.