Multilineage Constructs for Scaffold‐Based Tissue Engineering: A Review of Tissue‐Specific Challenges
Bibliographic record
Abstract
There is a growing interest in the regeneration of tissue in interfacial regions, where biological, physical, and chemical attributes vary across tissue type. The simultaneous use of distinct cell lineages can help in developing in vitro structures, analogous to native composite tissues. This literature review gathers the recent reports that have investigated multiple cell types of various sources and lineages in a coculture system for tissue-engineered constructs. Such studies aim at mimicking the native organization of tissues and their interfaces, and/or to improve the development of complex tissue substitutes. This paper thus distinguishes itself from those focusing on technical aspects of coculturing for a single specific tissue. The first part of this review is dedicated to variables of cocultured tissue engineering such as scaffold, cells, and in vitro culture environment. Next, tissue-specific coculture methods and approaches are covered for the most studied tissues. Finally, cross-analysis is performed to highlight emerging trends in coculture principles and to discuss how tissue-specific challenges can inspire new approaches for regeneration of different interfaces to improve the outcomes of various tissue engineering strategies.
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.
How this classification was reachedexpand
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".