Evidence map›Paper›PMID 34931124›Full record

ArticleInternational journal of dentistry2021

Evaluation of the Surface Hardness and Roughness of a Resin-Modified Glass Ionomer Cement Containing Bacterial Cellulose Nanocrystals.

Maryam Saadat, Marzieh Moradian, Babak Mirshekari

Abstract read
In one paragraph

Article in International journal of dentistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Smart Monochromatic Composite: A Literature Review.International journal of dentistry · 2022
    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

3 authors.

Maryam SaadatOral and Dental Disease Research Center, Department of Operative Dentistry, School of Dentistry, Shiraz University of Medical Sciences, Shiraz, Iran.ORCID https://orcid.org/0000-0003-2809-9316
Marzieh MoradianOral and Dental Disease Research Center, Department of Operative Dentistry, School of Dentistry, Shiraz University of Medical Sciences, Shiraz, Iran.ORCID https://orcid.org/0000-0002-0635-0023
Babak MirshekariStudent Research Committee, School of Dentistry, Shiraz University of Medical Sciences, Shiraz, Iran.ORCID https://orcid.org/0000-0002-8837-9646

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study was to evaluate the performance of a resin-modified glass ionomer cement (RMGIC) to which bacterial cellulose nanocrystals (BCNs) were added. BCNs were incorporated into the RMGIC powder in ratios of 0.3%, 0.5%, and 1% (w/w). One control and three experimental groups were enrolled in the study: unmodified RMGIC (control), 0.3% (w/w) BCN-modified RMGIC, 0.5% (w/w) BCN-modified RMGIC, and 1% (w/w) BCN-modified RMGIC. The surface hardness and surface roughness were the parameters assessed. The materials were characterized by scanning electron microscopy (SEM). The data were analyzed using the one-way ANOVA and Kruskal-Wallis tests for surface hardness and roughness, respectively. The addition of BCN resulted in the improvement of surface roughness in all the specimens compared with the control material. The RMGIC modified by 1% (w/w) BCN showed the lowest surface roughness (decreased by 52%) among all tested groups. However, BCN had a negative effect on the surface hardness of RMGIC. The group with 0.3% (w/w) BCN had the least decrease in microhardness (13%). According to the results, the RMGIC group modified by 1% (w/w) BCN had a smoother surface than the other groups. The surface microhardness of the RMGIC decreased after BCNs were added to it.

Identifiers

PMID34931124
PMCPMC8684512

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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.