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Record W2741325192 · doi:10.2147/ijn.s142857

Inhibitory effect of zirconium oxide nanoparticles on <em>Candida albicans</em> adhesion to repaired polymethyl methacrylate denture bases and interim removable prostheses: a new approach for denture stomatitis prevention

2017· article· en· W2741325192 on OpenAlexaff
Mohammed M. Gad, Ahmad M. Al‐Thobity, Suliman Shahin, Badar Alsaqer, A. Ali

Bibliographic record

VenueInternational Journal of Nanomedicine · 2017
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of Toronto
FundersUniversity of Dammam
KeywordsCubic zirconiaAcrylic resinMaterials scienceNanoparticleCandida albicansNuclear chemistryMethacrylateComposite materialPolymerizationChemistryPolymerCeramicMicrobiologyNanotechnology

Abstract

fetched live from OpenAlex

Background: Despite drawbacks, cold-cured acrylic resin is still the most common material used in denture repair. Zirconia nanoparticles were among the reinforcements added to increase the strength of the resin. The effect on Candida due to the addition of zirconia nanoparticles to the resin has not been investigated. Purpose: The aim of this study was to evaluate the effect of zirconia nanoparticles added to cold-cured acrylic resin on Candida albicans adhesion. Materials and methods: A total of 120 acrylic resin specimens with dimensions measuring 22×10×2.5 mm 3 were prepared and divided into two equal groups. One group (repair) comprised heat-polymerized specimens that were sectioned at the center and prepared to create a 2 mm repair area that was repaired with cold-cured resin reinforced with 0% wt, 2.5% wt, 5% wt, and 7.5% wt zirconia nanoparticles. The second group contained intact cold-cured acrylic resin specimens reinforced with 0% wt, 2.5% wt, 5% wt, and 7.5% wt zirconia nanoparticles. Specimens were incubated at 37°C in artificial saliva containing C . albicans , and the effect of zirconia nanoparticles on C . albicans was assessed using two methods: 1) a slide count method and 2) a direct culture test. Variations in the number of living Candida were observed in relation to the different concentrations of zirconia nanoparticles. Analysis of variance (ANOVA) and post hoc Tukey’s tests were performed for data analysis. If the P -value was ≤0.05, then the difference was considered as statistically significant. Results: It was found that C . albicans adhesion to repaired specimens was significantly decreased by the addition of zirconia nanoparticles ( P <0.00001) in comparison with the control group. Intact cold-cured groups and groups repaired with cold-cured resin reinforced with 7.5% wt zirconia nanoparticles showed the lowest Candida count. Tukey’s test showed a significant difference between the repaired group and the intact cold-cured group, while the later demonstrated a lower Candida count. Conclusion: The addition of zirconia nanoparticles to cold-cured acrylic resin is an effective method for reducing Candida adhesion to repaired polymethyl methacrylate (PMMA) denture bases and cold-cured removable prosthesis. Clinical significance: Based on the results of the current study, zirconia nanoparticles have an antifungal effect, which could be incorporated in the repair material for repairing denture bases and in PMMA removable prostheses as a possible approach for denture stomatitis prevention. Keywords: Candida albicans , denture base repair, PMMA, interim prosthesis, reinforcement, zirconium oxide nanoparticles

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.314
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations107
Published2017
Admission routes1
Has abstractyes

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