Stimuli-responsive biomaterials: smart avenue toward 4D bioprinting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
3D bioprinting is an advanced technology combining cells and bioactive molecules within a single bioscaffold; however, this scaffold cannot change, modify or grow in response to a dynamic implemented environment. Lately, a new era of smart polymers and hydrogels has emerged, which can add another dimension, e.g., time to 3D bioprinting, to address some of the current approaches' limitations. This concept is indicated as 4D bioprinting. This approach may assist in fabricating tissue-like structures with a configuration and function that mimic the natural tissue. These scaffolds can change and reform as the tissue are transformed with the potential of specific drug or biomolecules released for various biomedical applications, such as biosensing, wound healing, soft robotics, drug delivery, and tissue engineering, though 4D bioprinting is still in its early stages and more works are required to advance it. In this review article, the critical challenge in the field of 4D bioprinting and transformations from 3D bioprinting to 4D phases is reviewed. Also, the mechanistic aspects from the chemistry and material science point of view are discussed too.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.006 |
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