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Nanocrystalline Hydroxyapatite Bone Substitute Leads to Sufficient Bone Tissue Formation Already after 3 Months: Histological and Histomorphometrical Analysis 3 and 6 Months following Human Sinus Cavity Augmentation

2012· article· en· W2119373432 on OpenAlexvenueno aff
Shahram Ghanaati, Mike Barbeck, Inés Willershausen, Benjamin W. Thimm, Stefan Stuebinger, Tadas Koržinskas, Karina Obreja, Constantin A. Landes, C. James Kirkpatrick, Robert Sader

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2012
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsnot available
Fundersnot available
KeywordsDentistrySinus (botany)MedicineMaxillary sinusBone formationBiomaterialBone remodelingBone tissueImplantSurgeryAnatomyBiomedical engineeringBiology

Abstract

fetched live from OpenAlex

PURPOSE: In this study the de novo bone formation capacity of a nanocrystalline hydroxyapatite bone substitute was assessed 3 and 6 months after its insertion into the human sinus cavity. MATERIALS AND METHODS: Sinus cavity augmentation was performed in a total of 14 patients (n = 7 implantation after 3 months; n = 7 implantation after 6 months) with severely atrophic maxillary bone. The specimens obtained after 3 and 6 months were analyzed histologically and histomorphometrically with special focus on bone metabolism within the residual bone and the augmented region. RESULTS: This study revealed that bone tissue formation started from the bone-biomaterial-interface and was directed into the most cranial parts of the augmented region. There was no statistically significant difference in new bone formation after 3 and 6 months (24.89 ± 10.22% vs 31.29 ± 2.29%), respectively. CONCLUSIONS: Within the limits of the present study and according to previously published data, implant insertion in regions augmented with this bone substitute material could be considered already after 3 months. Further clinical studies with bone substitute materials are necessary to validate these findings.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.052
GPT teacher head0.367
Teacher spread0.315 · 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 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

Citations48
Published2012
Admission routes1
Has abstractyes

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