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Record W4403330904 · doi:10.2196/51351

A Comparison of Conventional Root Canal Sealers With Ones That Use Green Synthesized Nanoparticles for Antimicrobial Activity: Protocol for a Systematic Review

2024· review· en· W4403330904 on OpenAlexvenueno aff
Abubaker Mohamed, Enas Ismail, Razia Zulfikar Adam

Bibliographic record

VenueJMIR Research Protocols · 2024
Typereview
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsRoot canalDentistryProtocol (science)Enterococcus faecalisScopusSystematic reviewEndodonticsWeb of scienceCandida albicansRestorative dentistryAntimicrobialMedicineMEDLINEMeta-analysisAlternative medicinePathologyMicrobiologyStaphylococcus aureusBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Root canal failure and secondary endodontic infection are frequent clinical scenarios in dentistry. The main microorganisms implicated in root canal therapy failure are persistent Enterococcus faecalis, Candida albicans, and Staphylococcus aureus. To combat the impact of disease resistance, scientists are concentrating on alternative antimicrobial root canal sealers. Nanomaterials are a recent development in endodontic materials that exhibit great antimicrobial properties, making them an ideal material choice for root canal sealers. OBJECTIVE: This systematic review aims to compare the antimicrobial properties of conventional root canal sealers to those incorporating green synthesized nanoparticles between 2010 and 2024. METHODS: A well-constructed protocol was established and registered with PROSPERO (CRD42021286373). Ethics approval was obtained from the Biomedical Research and Ethics Committee from the University of the Western Cape (UWC; BM22/1/4). PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) reporting guidelines were followed. The included criteria demonstrate the green synthesized nanoparticles studies where the nanoparticles (NPs) are incorporated in root canal sealers. MeSH (Medical Subject Headings) terms were used for the search strategy of the systematic electronic databases for articles published in English between 2010 and 2024. The selected databases included Scopus, PubMed, Web of Science, Science Direct, EBSCOhost, SpringerLink, and Wiley Online. A quality assessment tool for laboratory studies will be used to critically appraise the included studies. If applicable, statistical measures (mean, SD, etc) will be used for data analysis and presentation of the results. RESULTS: The protocol is registered with PROSPERO. A preliminary search was conducted using a determined search strategy across 8 electronic databases, and the review is now complete. CONCLUSIONS: It is anticipated that the results of this systematic review may reveal the increased interest and application for nanoparticle-enhanced root canal sealers. This will aid in the future development of root canal sealants and mitigate the risk of endodontic failure. TRIAL REGISTRATION: PROSPERO CRD42021286373; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=286373. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/51351.

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)0.054
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.054
Threshold uncertainty score0.286

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0540.071
Meta-epidemiology (narrow)0.0060.004
Meta-epidemiology (broad)0.0220.023
Bibliometrics0.0130.013
Science and technology studies0.0040.005
Scholarly communication0.0070.007
Open science0.0040.004
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0440.005

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 head0.619
GPT teacher head0.635
Teacher spread0.017 · 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 designSystematic review
Domainnot available
GenreProtocol

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

Citations2
Published2024
Admission routes1
Has abstractyes

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