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Record W4394960280 · doi:10.7759/cureus.58562

Green Synthesis, Characterization, and Evaluation of the Antimicrobial Properties and Compressive Strength of Hydroxyapatite Nanoparticle-Incorporated Glass Ionomer Cement

2024· article· en· W4394960280 on OpenAlexaff
Priyan Ilancheran, Jessy Paulraj, Subhabrata Maiti, Rajeshkumar Shanmugam

Bibliographic record

VenueCureus · 2024
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsGlass ionomer cementCompressive strengthMaterials scienceCementNanoparticleCharacterization (materials science)Composite materialAntimicrobialMechanical strengthNanotechnologyChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Background Glass ionomer cement (GIC) plays a vital role in dental restorative procedures, serving purposes such as filling, luting, and adhesion. However, its inadequate mechanical properties pose challenges, especially in areas experiencing significant stress. To overcome this limitation, nanohydroxyapatite (nHA), known for its bioactive phosphate content, is added to the GIC at specific concentrations to improve its properties. Aim We aim to evaluate the antimicrobial property and compressive strength of green-mediated nHA-incorporated GIC. Material and methods Green synthesis of hydroxyapatite nanoparticles was prepared using Moringa oleifera extract in a solvent form and eggshell waste served as the calcium source. These nHA powders were then integrated into the GIC at varying concentrations (3%, 5%, and 10%) designated as Group I, Group II, and Group III, respectively, while Group IV (control) consisted of conventional GIC. Specimens were fabricated and subjected to chemical structure analysis through Fourier transform infrared spectroscopy (FTIR), energy dispersive X-ray (EDX), and scanning electron microscopy (SEM). The antimicrobial activity and compressive strength of all groups were investigated. The antimicrobial activity against Streptococcus mutans and Lactobacillus was evaluated through the minimum inhibitory concentration (MIC) test, while compressive strength was evaluated by measuring the maximum force endured by the specimen before fracturing. Data analysis utilized IBM SPSS Statistics software, employing repeated measures ANOVA to determine mean MIC values and compressive strength, with Tukey's posthoc test for pairwise comparisons. Results The results of the study showed that the antimicrobial efficacy of nHA GIC improved with increasing weight percent (% wt) of the additive, exhibiting significantly enhanced activity against Streptococcus mutans and Lactobacillus compared to the control group (Group IV) with statistical significance (p < 0.05). Moreover, the compressive strength exhibited notable enhancements in the modified groups, including Group I (172.55 ± 0.76), Group II (178.16 ± 0.760), and Group III (182.45 ± 0.950), when compared to the control (162.46 ± 1.606), with statistically significant differences (p < 0.05). Conclusion The study demonstrates that the incorporation of green-mediated nHA-containing GIC results in superior antimicrobial efficacy and compressive strength compared to the control group (Group IV). In particular, the highest concentration of nHA-modified GIC (10%) exhibited the most favorable antimicrobial properties along with increased strength. Therefore, utilizing green-mediated nHA in the GIC shows promise as an effective restorative material. Future investigations should delve into the molecular chemistry and bonding mechanisms to further explore its potential.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.168
Threshold uncertainty score0.278

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.024
GPT teacher head0.213
Teacher spread0.189 · 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 teacher head, 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

Citations9
Published2024
Admission routes1
Has abstractyes

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