Two-dimensional superlattice films of gold nanoparticle-polystyrene composites: a bioactive platform for bone homeostasis maintenance
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Osseo-integration between the implant and bone is a crucial factor to create a strong, durable bond that allows the implant to function effectively. However, regular implant surface with poor osseo-integration ability may cause aseptic loosening, resulting in the failure of implants. Herein, a serial of macroscopic one-particle thick superlattice films generated by self-assembly of diverse size of gold nanoparticles (GNPs) were termed as SFGs and were considered as bioactive implant coatings for enhancing osseo-integration. A hydroquinone-assisted seed method is established to fabricate homogenous GNPs with controllable sizes (20, 60, and 90 nm), which were further employed as building blocks to generate macroscopic one-particle thick superlattice films of GNPs (SFGs-20, SFGs-60, and SFGs-90) with the assistance of ploystryrene. The SFGs present a size-dependent performance on bone homeostasis, where SFGs-90 demonstrated the most pronounced facilitation of osteogenic differentiation of osteoblasts as well as deactivation of osteoclasts compared with SFGs-20 and SFGs-60. Considering the universal applicability of SFGs for depositing on various substrates, these SFGs with enhanced osseo-integration capabilities could serve as a bioactive platform for surface modification of orthopedic implants, effectively addressing the issue of aseptic loosening. Graphical abstract Two-dimensional superlattice films of gold nanoparticle-polystyrene composites exhibit enhanced osteogenic-stimulation and osteoclastic-inhibition effects for regulating bone homeostasis maintenance.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it