Bioreactors for Tissue Engineering: Focus on Mechanical Constraints. A Comparative Review
Bibliographic record
Abstract
Considering the current techniques in cell culture, the stimulation of cellular proliferation and the formation of bidimensional tissues such as skin are widely performed in academic and industrial research laboratories. However, the formation of cohesive, organized, and functional tissues by three-dimensional (3D) cell culture is complex. A suitable environment is required, which is achieved and maintained in a specific bioreactor, a device that reproduces the physiological environment (including biochemical and mechanical functions) specific to the tissue that is to be regenerated. Bioreactors can also be used to apply mechanical constraints during maturation of the regenerating tissue for studying and understanding the mechanical factors influencing tissue regeneration. In this work, the main types of bioreactors used for tissue engineering and regeneration, as well as their most common applications, were reviewed and compared. The importance of the mechanical properties applied to the scaffolds and the regenerating constructs has been often neglected. This review focused on the influence of mechanical stresses and strains during the culture period that leads to the final mechanical properties of the construct.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".