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Record W4313544409 · doi:10.1111/cid.13172

Bioactive glass air‐abrasion promotes healing around contaminated implant surfaces surrounded by circumferential bone defects: An experimental study in the rat

2023· article· en· W4313544409 on OpenAlexvenueno aff
Faleh Abushahba, Nagat Areid, Mervi Gürsoy, Jaana Willberg, Varpu Laine, Emrah Yatkin, Leena Hupa, Timo Närhi

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2023
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsnot available
FundersTurun Yliopisto
KeywordsDentistryOsseointegrationAbrasion (mechanical)BiofilmBioactive glassImplantTitaniumMaterials scienceNuclear chemistryChemistryMedicineComposite materialMetallurgySurgery

Abstract

fetched live from OpenAlex

OBJECTIVES: The present study aimed to evaluate the healing of experimentally induced bone defects around contaminated dental implants after air-abrasion using 45S5 or zinc oxide (ZnO)-containing bioactive glasses (BAGs). MATERIALS AND METHODS: One maxillary first molar was extracted from each Sprague-Dawley rat (n = 30). After 4-week healing, a titanium implant was placed in the extraction site with a circumferential bone defect. The rats were randomized into five different groups: (1) implants with Fusobacterium nucleatum and Porphyromonas gingivalis dual-species biofilm (IB); (2) implants with biofilm subjected to inert glass air-abrasion (inert); (3) sterile implants (S); (4) implants with biofilm subjected to 45S5 BAG air-abrasion (45S5); and (5) implants with biofilm subjected to ZnO-containing BAG air-abrasion (Zn4). After 8-week healing, maxillae were dissected, and histomorphometric analyses were performed. RESULTS: The first bone-to-implant contact was significantly shorter for the inert (1.58 ± 1.16 mm; p = 0.016), S (0.28 ± 0.13 mm; p < 0.001), 45S5 (0.41 ± 0.28 mm; p < 0.001), and Zn4 (0.26 ± 0.16 mm; p < 0.001) groups compared to IB group. Also, significantly more bone-to-implant contact was seen for S (72.35% ± 8.32%; p < 0.001), 45S5 (57.91% ± 24.10%; p = 0.002), and Zn4 (70.49% ± 12.74%; p < 0.001) groups than the IB group. The bone volume with the threads demonstrated significantly higher value for S (69.32% ± 9.15%; p < 0.001), 45S5 (58.93% ± 23.53%; p = 0.001), and Zn4 (68.65% ± 12.41%; p < 0.001) groups compared to the IB group. The bone volume within the defects was significantly higher for S (68.79% ± 11.77%; p < 0.001), 45S5 (62.51% ± 20.51%; p = 0.002), and Zn4 (73.81% ± 15.07%; p < 0.001) groups compared to the IB group. CONCLUSIONS: This study suggests that air-abrasion of contaminated moderately rough implant surfaces with either 45S5 or ZnO-containing BAGs enhances osseointegration and bone defect regeneration.

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.089
GPT teacher head0.408
Teacher spread0.319 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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