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Record W4410630409 · doi:10.1039/d5cp00324e

Nucleation of biomimetic hydroxyapatite nanoparticles on the surface of human type I collagen using a hybrid all-atom and coarse-grained model

2025· article· en· W4410630409 on OpenAlexaff
Zhiyu Xue, Xing Ye, Yao Cai, Xinyun Tan, Xiaomeng Wu, Fang Wu, Fei Li, Dingguo Xu

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2025
Typearticle
Languageen
FieldMaterials Science
TopicCollagen: Extraction and Characterization
Canadian institutionsUniversity of Toronto
FundersSichuan Province Science and Technology Support ProgramChina Postdoctoral Science FoundationNational Natural Science Foundation of ChinaSichuan Provincial Postdoctoral Science Foundation
KeywordsNucleationNanoparticleAtom (system on chip)Materials scienceSurface (topology)Type (biology)NanotechnologyChemical engineeringChemical physicsChemistryCrystallographyOrganic chemistryGeometryGeology

Abstract

fetched live from OpenAlex

Inorganic mineral/collagen composite materials are one of the most attractive implant materials for bone repair engineering. Mineralized collagen composites have a similar hierarchical structure and biological activity to natural bone; however, the mechanism of the mineralization process is complex, and the properties of mineralized materials are difficult to control during the preparation process. Currently, this is a significant challenge in coarse-grained organic-inorganic systems. Thus, a coarse-grained/all-atom multiscale model was employed to investigate the biomineralization process. Based on the free energy of the all-atom ion association, we obtained the coupling parameters of the multiscale model, which were similar to those of the all-atom model. In this multiscale simulation model, coarse-grained models were used for type I collagen protein and water molecules and all-atom models for phosphate and calcium ions. The coarse-grained/all-atom multiscale model of mineralized collagen identified the same nucleation site and calcium phosphate aggregation process as the all-atom model. Additionally, the calcium phosphate clusters still retained site-selectivity around the coarse-grained collagen surface during the nucleation process. At the same time, the clusters tended to have a certain crystal structure morphology during the long-time simulation. This new strategy will help accelerate biomaterial design and optimization.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.028
GPT teacher head0.282
Teacher spread0.254 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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