A review of the current state of the art in gelatin methacryloyl-based printing inks in bone tissue engineering
Bibliographic record
Abstract
Achieving efficient scaffolds for bone tissue engineering (TE) requires smartly defined parameters for reaching a balance between physical–chemical properties, biocompatibility and complex architectures. Three-dimensional (3D) printing offers precise geometry control of the desired scaffold at micro-scale. However, the performance of 3D printing is highly dependent on the formulation, the challenge being to achieve the suitable ink and establish the most efficient printing parameters. Gelatin methacryloyl (GelMA) emerges as a promising ink due to superior biological properties, photocrosslinking ability and printability. The present review focuses on the evolution of GelMA-based inks and bioinks from the simplest to the most advanced multicomponent formulations capable of bone tissue regeneration. Additionally, a comparative analysis between the different photoinitiators is covered, indicating each one's advantages and disadvantages. Furthermore, the main printing and bioprinting methods that are used in GelMA printing are outlined with the required parameters and their influence on the final product performance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".