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Record W3040393302 · doi:10.1002/jbm.a.37051

Biomimetic trace metals improve bone regenerative properties of calcium phosphate bioceramics

2020· article· en· W3040393302 on OpenAlexafffund
Alaa Mansour, Lina Abu Nada, Amir A. El hadad, Mohamed A. Mezour, Ala’ Ersheidat, Ahmed Alsubaie, Hanan Moussa, Marco Laurenti, Mari T. Kaartinen, Faleh Tamimi

Bibliographic record

VenueJournal of Biomedical Materials Research Part A · 2020
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsMcGill University
FundersRéseau de Recherche en Santé Buccodentaire et OsseuseNatural Sciences and Engineering Research Council of CanadaQatar National LibraryMcGill University
KeywordsMaterials scienceBioceramicApatiteCalciumBiomineralizationChemical engineeringBiomedical engineeringMineralogyNanotechnologyMetallurgyChemistry

Abstract

fetched live from OpenAlex

The bone regenerative capacity of synthetic calcium phosphates (CaPs) can be enhanced through the enrichment with selected metal trace ions. However, defining the optimal elemental composition required for bone formation is challenging due to many possible concentrations and combinations of these elements. We hypothesized that the ideal elemental composition exists in the inorganic phase of the bone extracellular matrix (ECM). To study our hypothesis, we first obtained natural hydroxyapatite through the calcination of bovine bone, which was then investigated its reactivity with acidic phosphates to produce CaP cements. Bioceramic scaffolds fabricated using these cements were assessed for their composition, properties, and in vivo regenerative performance and compared with controls. We found that natural hydroxyapatite could react with phosphoric acid to produce CaP cements with biomimetic trace metals. These cements present significantly superior in vivo bone regenerative performance compared with cements prepared using synthetic apatite. In summary, this study opens new avenues for further advancements in the field of CaP bone biomaterials by introducing a simple approach to develop biomimetic CaPs. This work also sheds light on the role of the inorganic phase of bone and its composition in defining the regenerative properties of natural bone xenografts.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.076
GPT teacher head0.307
Teacher spread0.230 · 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

Citations21
Published2020
Admission routes2
Has abstractyes

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Same venueJournal of Biomedical Materials Research Part ASame topicBone Tissue Engineering MaterialsFrench-language works237,207