A Flow Perfusion Bioreactor System for Vocal Fold Tissue Engineering Applications
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Bibliographic record
Abstract
The human vocal folds (VFs) undergo complex biomechanical stimulation during phonation. The aim of the present study was to develop and validate a phono-mimetic VF flow perfusion bioreactor, which mimics the mechanical microenvironment of the human VFs in vitro. The bioreactor uses airflow-induced self-oscillations, which have been shown to produce mechanical loading and contact forces that are representative of human phonation. The bioreactor consisted of two synthetic VF replicas within a silicone body. A cell-scaffold mixture (CSM) consisting of human VF fibroblasts, hyaluronic acid, gelatin, and a polyethylene glycol cross-linker was injected into cavities within the replicas. Cell culture medium (CCM) was perfused through the scaffold by using a customized secondary flow loop. After the injection, the bioreactor was operated with no stimulation over a 3-day period to allow for cell adaptation. Phonation was subsequently induced by using a variable speed centrifugal blower for 2 h each day over a period of 4 days. A similar bioreactor without biomechanical stimulation was used as the nonphonatory control. The CSM was harvested from both VF replicas 7 days after the injection. The results confirmed that the phono-mimetic bioreactor supports cell viability and extracellular matrix proteins synthesis, as expected. Many scaffold materials were found to degrade because of challenges from phonation-induced biomechanical stimulation as well as due to biochemical reactions with the CCM. The bioreactor concept enables future investigations of the effects of different phonatory characteristics, that is, voice regimes, on the behavior of the human VF cells. It will also help study the long-term functional outcomes of the VF-specific biomaterials before animal and clinical studies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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