Progress in Vocal Fold Regenerative Biomaterials: An Immunological Perspective
Bibliographic record
Abstract
Vocal folds, housed in the upper respiratory tract, are important to daily breathing, speech and swallowing functions. Irreversible changes to the vocal fold mucosae, such as scarring and atrophy, require a regenerative medicine approach to promote a controlled regrowth of the extracellular matrix (ECM)-rich mucosa. Various biomaterial systems have been engineered with an emphasis on stimulating local vocal fold fibroblasts to produce new ECM. At the same time, it is imperative to limit the foreign body reaction and associated immune components that can hinder the integration of the biomaterial into the host tissue. Modern biomaterial designs have become increasingly focused on actively harnessing the immune system to accelerate and optimize the process of tissue regeneration. An array of physical and chemical biomaterial parameters have been reported to effectively modulate local immune cells, such as macrophages, to initiate tissue repair, stimulate ECM production, promote biomaterial-tissue integration, and restore the function of the vocal folds. In this perspective paper, the unique immunological profile of the vocal folds will first be reviewed. Key physical and chemical biomaterial properties relevant to immunomodulation will then be highlighted and discussed. A further examination of the physicochemical properties of recent vocal fold biomaterials will follow to generate deeper insights into corresponding immune-related outcomes. Lastly, a perspective will be offered on the opportunity of integrating material-led immunomodulatory strategies into future vocal fold tissue engineering therapies.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".