Evidence map›Paper›PMID 35222865›Full record

ArticleIranian journal of microbiology2021

Optimization of antimicrobial efficiency of silver nanoparticles against three oral microorganisms in irreversible hydrocolloid impressions.

Ahmad Jafari, Ramin Mazaheri Nezhad Fard, Sima Shahabi, Farid Abbasi, Golshid Javdani Shahedin, Ronak Bakhtiari

Abstract read
In one paragraph

Article in Iranian journal of microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Ahmad JafariDepartment of Pediatric Dentistry, School of Dentistry, Tehran University of Medical Sciences, Tehran, Iran.
Ramin Mazaheri Nezhad FardDivision of Microbiology, Department of Pathobiology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Sima ShahabiDepartment of Dental Material, School of Dentistry, Tehran University of Medial Sciences, Tehran, Iran.
Farid AbbasiDepartment of Oral Medicine, Faculty of Dentistry, Shahed University, Tehran, Iran.
Golshid Javdani ShahedinDepartment of Quality Control, Production and Research Complex, Pasteur Institute of Iran, Karaj, Iran.
Ronak BakhtiariDivision of Microbiology, Department of Pathobiology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesSilver nanoparticles (Ag-NPs) are potent antimicrobial agents, which have recently been used in dentistry. The aim of the current study was to optimize antimicrobial activity of Ag-NPs used in preparing irreversible hydrocolloid impressions against three microorganisms of MATERIALS AND

methodsAfter assessing antimicrobial activity of the compound using disk diffusion method, three parameters of concentration of Ag-NPs (250-1000 ppm), ratio of hydrocolloid impression material powder to water (0.30-0.50) and time of mixing (20.0-60.0 s), affecting antimicrobial activity of irreversible hydrocolloid impression materials against the three microorganisms, were optimized. This combined process was successfully modeled and optimized using Box-Behnken design with response surface methodology (RSM). Decreases in colony number of

resultsQualitative antimicrobial assessments respectively showed average zone of inhibition (ZOI) of 3.7 mm for

conclusionDisinfection efficiency dramatically increased with increasing of Ag-NP concentration, powder-to-water ratio and mixing time.

Indexed as

Dental impression materialsMicroorganismNanotechnology

Identifiers

PMID35222865
PMCPMC8816690

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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.