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Record W4417442352 · doi:10.37988/1811-153x_2025_4_88

Residual monomer release dynamics in heat- and cold-cured dental polymethyl methacrylates: a pilot study

2025· article· ru· W4417442352 on OpenAlexaff
Yaser N. Kharakh, Л. В. Дубова, O. I. Manin, S.V. Stakhanova, Natalia Mikhailova, Alexey I. Salimon, I. A. Zorin, Iuliia A. Sadykova, Eugene S. Statnik, Alexander M. Korsunsky, В. П. Чуев, Evgeniy Kravchuk, S. D. Arutyunov

Bibliographic record

VenueClinical Dentistry (Russia) · 2025
Typearticle
Languageru
FieldDentistry
TopicDental materials and restorations
Canadian institutionsOptech (Canada)
Fundersnot available
KeywordsPolymethyl methacrylateMonomerMethyl methacrylateMethacrylateResidual

Abstract

fetched live from OpenAlex

Residual methyl methacrylate (MMA) in polymethyl methacrylate (PMMA) is a risk factor in removable prostheses due to its potential cytotoxicity. Objective. To assess the release dynamics of MMA from domestically produced heat- and cold-cured PMMA samples during the first 10 days post-polymerization. Materials and methods. Standardized specimens (10×10×4 mm) were fabricated from heat-cured PMMA and cold-cured PMMA. Samples were stored in deionized water at 37°C, and the MMA concentration in the eluates was measured on days 1, 3, 6, and 10 by micellar electrokinetic capillary chromatography. Results. In the heat-cured group, the mean MMA concentration ranged from 0.237 to 0.641 µg/mL (p=0.480), while in the cold-cured group it ranged from 0.796 to 5.443 µg/mL (p=0.109). No statistically significant changes in MMA levels were observed over the monitoring period (p> 0.05). Conclusions. Under the conditions tested—storage in deionized water for up to 10 days—the storage duration does not affect the residual monomer content in PMMA. These findings are important for developing PMMA post-curing protocols prior to clinical application.

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 score0.004

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 head0.051
GPT teacher head0.386
Teacher spread0.335 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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