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Record W1904808493 · doi:10.1111/cid.12358

Combined Treatment Effects Using Bioactive‐Coated Implants and Ceramic Granulate in a Rabbit Femoral Condyle Model

2015· article· en· W1904808493 on OpenAlexvenueno aff
Reghunathan S. Preethanath, P. Rajesh, Harikrishna Varma, Sukumaran Anil, John A. Jansen, Jeroen J.J.P. van den Beucken

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2015
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsnot available
Fundersnot available
KeywordsImplantMaterials scienceCondyleOsseointegrationBiomedical engineeringDentistryCeramicFEMORAL CONDYLETitaniumMedicineSurgeryAnatomyComposite material

Abstract

fetched live from OpenAlex

BACKGROUND: Resolution of peri-implant defects resulting from implant placement in the freshly extracted site demands for a bone graft substitute that stimulates bone regeneration and hence facilitates implant integration. In view of this, the addition of silica to hydroxyapatite (HASi) could enhance the bioactive behavior of ceramic materials and implant surfaces coated with bioactive ceramics might benefit the interaction between bone and implant. PURPOSE: To evaluate the bone response to implants coated with hydroxyapatite-silica (HASi) or hydroxyapatite (HA) and either or not combined with HASi and HA ceramic bone substitute particles, respectively, on bone-to-implant contact (BIC) and bone formation using a rabbit femoral condyle implant model with a gap design. MATERIAL AND METHODS: A total of 32 custom-made, titanium implants (Ti: diameter 5 mm, length 8 mm) with two-sided gaps were fabricated and coated with either HASi or HA using pulsed laser deposition (PLD). The implants were installed bilaterally in the femoral condyles of 16 New Zealand white rabbits. According to a randomization protocol, one gap of HASi-coated and HA-coated implants was filled with HASi particles and HA particles, respectively, and the other gap was left empty. After an implantation period of 8 weeks, the retrieved specimens were analyzed via histology and histomorphometry (i.e., bone to implant contact [BIC] and bone volume [BV]). RESULTS: The BIC and BV around the implants were analysed for HASi- and HA-coated implants with and without the use of HASi and HA bone substitute material. Comparison of HASi- and HA-coated implants showed similar BIC for HASi- (55.7 + 11.0) and HA-coated implants (50.3 + 19.7). When coated implants were combined with bone substitute materials, HASi-coated and particle-filled implants showed higher BIC (64.3 ± 6.8%) compared with HA-coated and HA-filled implants (54.5 ± 10.9%). Similarly, the BV within the region of interest showed significantly higher values for the HASi-coated and HASi-filled implants (21.1 ± 1.7%) compared with HA-coated and HA-filled implants (12.8 ± 4.9%). CONCLUSIONS AND CLINICAL IMPLICATIONS: Within the limitations of this study, it can be concluded that silicon substitution in HA favors bone regeneration compared with HA, especially when used as bone substitute material. Further studies using different healing periods will elucidate the resorption pattern of HASi granules in comparison with HA.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
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 communication0.0000.000
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 head0.168
GPT teacher head0.418
Teacher spread0.250 · 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 designObservational
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

Citations6
Published2015
Admission routes1
Has abstractyes

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