Homogeneous hydroxyapatite/alginate composite hydrogel promotes calcified cartilage matrix deposition with potential for three-dimensional bioprinting
Bibliographic record
Abstract
Calcified cartilage regeneration plays an important role in successful osteochondral repair, since it provides a biological and mechanical transition from the unmineralized cartilage at the articulating surface to the underlying mineralized bone. To biomimic native calcified cartilage in engineered constructs, here we test the hypothesis that hydroxyapatite (HAP) stimulates chondrocytes to secrete the characteristic matrix of calcified cartilage. Sodium citrate (SC) was added as a dispersant of HAP within alginate (ALG), and homogeneous dispersal of HAP within ALG hydrogel was confirmed using sedimentation tests, electron microscopy, and energy dispersive spectroscopy. To examine the biological performance of ALG/HAP composites, chondrocyte survival and proliferation, extracellular matrix production, and mineralization potential were evaluated in the presence or absence of the HAP phase. Chondrocytes in ALG/HAP constructs survived well and proliferated, but also expressed higher levels of calcified cartilage markers compared to controls, including Collagen type X secretion, alkaline phosphatase (ALP) activity, and mineral deposition. Compared to controls, ALG/HAP constructs also showed an elevated level of mineralized matrix in vivo when implanted subcutaneously in mice. The printability of ALG/HAP composite hydrogel precursors was verified by 3D printing of ALG/HAP hydrogel scaffolds with a porous structure. In summary, these results confirm the hypothesis that HAP in ALG hydrogel stimulates chondrocytes to secrete calcified matrix in vitro and in vivo and reveal that ALG/HAP composites have the potential for 3D bioprinting and osteochondral regeneration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".