Biomedical Applications of Layer‐by‐Layer Self‐Assembly for Cell Encapsulation: Current Status and Future Perspectives
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
Encapsulating living cells within multilayer functional shells is a crucial extension of cellular functions and a further development of cell surface engineering. In the last decade, cell encapsulation has been widely utilized in many cutting-edge biomedical fields. Compared with other techniques for cell encapsulation, layer-by-layer (LbL) self-assembly technology, due to the versatility and tunability to fabricate diverse multilayer shells with controllable compositions and structures, is considered as a promising approach for cell encapsulation. This review summarizes the state-of-the-art and potential future biomedical applications of LbL cell encapsulation. First of all, a brief introduction to the LbL self-assembly technique, including assembly mechanisms and technologies, is made. Next, different cell encapsulation strategies by LbL self-assembly techniques are explained. Then, the biomedical applications of LbL cell encapsulation in cell-based biosensors, cell transplantation, cell/molecule delivery, and tissue engineering, are highlighted. Finally, discussions on the current limitations and future perspectives of LbL cell encapsulation are also provided.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 it