Bone-repair properties of biodegradable hydroxyapatite nano-rod superstructures
Bibliographic record
Abstract
Nano-hydroxyapatite (nano-HAp) materials show an analogous chemical composition to the biogenic mineral components of calcified tissues and depending on their topography they may mimic the specific arrangement of the crystals in bone. In this work, we have evaluated the potential of four synthesized nano-HAp superstructures for the in vitro conditions of bone-repair. Experiments are underway to investigate the effects of the material microstructure, surface roughness and hydrophilicity on their osseo-integration, osteo-conduction and osteo-induction abilities. Materials were tested in the presence of both, rat primary osteoblasts and rabbit mesenchymal stem cells. The following aspects are discussed: (i) cytotoxicity and material degradation; (ii) rat osteoblast spreading, proliferation and differentiation; and (iii) rabbit mesenchymal stem cell adhesion on nano-HAp and nano-HAp/collagen type I coatings. We effectively prepared a material based on biomimetic HAp nano-rods displaying the appropriate surface topography, hydrophilicity and degradation properties to induce the in vitro desired cellular responses for bone bonding and healing. Cells seeded on the selected material readily attached, proliferated and differentiated, as confirmed by cell viability, mitochondrial metabolic activity, alkaline phosphatase (ALP) activity and cytoskeletal integrity analysis by immunofluorescence localization of alpha-smooth muscle actin (α-SMA) protein. These results highlight the influence of material's surface characteristics to determine their tissue regeneration potential and their future use in engineering osteogenic scaffolds for orthopedic implants.
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How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".