Development of a Self-Oscillating Mechanical Model to Investigate the Biological Response of Human Vocal Fold Fibroblasts to Phono-Mimetic Stimulation
Bibliographic record
Abstract
The human vocal folds are subjected to complex dynamic biomechanical stimulation during phonation. The aim of the present study was to develop and evaluate an airflow-induced self-oscillating mechanical model, i.e., a bioreactor, which mimics the geometry and the mechanical microenvironment of the human vocal folds. The bioreactor consisted of two composite synthetic vocal fold replicas loaded into a custom-built airflow supplied tube. A cell-scaffold mixture was injected into cavities within the replicas. The folds were phonated using a variable speed centrifugal blower for two hours a day over a period of seven days. The static and dynamic subglottal pressures and the dynamic supraglottal pressure were monitored. A similar bioreactor without mechanical excitation was used as positive control. The cell-scaffold mixture was harvested for cell viability and collagen type I immunohistochemistry tests seven days after injection. The flow-induced self-oscillations of the vocal fold replicas were shown to produce mechanical excitations that are typical of those in the human vocal fold lamina propria during phonation. The results confirmed that human vocal fold fibroblasts survived inside the present bioreactor, and maintained cellular functions of protein production.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".