Magnetic hydroxyapatite nanobelt‐stem cell hybrid spheroids for remotely patterning bone tissues
Bibliographic record
Abstract
Abstract The low survival rate and poor differentiation efficiency of stem cells, as well as the insufficient integration of implanted stem cells, limit the regeneration of bone defects. Here, we have developed magnetic ferroferric oxide‐hydroxyapatite‐polydopamine (Fe3O4‐HAp‐PDA) nanobelts to assemble mesenchymal stem cells (MSCs) into a three‐dimensional hybrid spheroid for patterning bone tissue. These nanobelts, which are featured by their high‐aspect ratio and contain Fe3O4 nanospheres with a PDA coating, can be manipulated by a magnetic field and foster enhanced cell‐nanobelt interactions. This strategy has been demonstrated to be effective for both bone marrow mesenchymal stem cells and adipose‐derived mesenchymal stem cells, enabling remote manipulation of stem cell spheroids and efficient spheroid fusion, which in turn accelerates osteogenic differentiation. Consequently, this methodology serves as an efficient and general tool for bone tissue printing and can potentially overcome the low survival rate and poor differentiation efficiency of stem cells, as well as mismatched interface fusion issues.
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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) | 0.001 | 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".