Bioengineered larynx and vocal folds: where are we today? A review
Bibliographic record
Abstract
Abstract The larynx is responsible for breathing, producing sound, and protecting the trachea against food aspiration through the cough reflex. Nowadays, scaffolding surgery has made it easier to regenerate damaged tissues by facilitating the influx of cells and growth factors. This review provides a comprehensive overview of the current knowledge on tissue engineering of the larynx and vocal folds. It also discusses the achievements and challenges of data sources. In conducting a literature search for relevant papers, we included 68 studies from January 2000 to November 2023, sourced from PubMed and Scholar Google databases. We found a need for collaboration between voice care practitioners, voice scientists, bioengineers, chemists, and biotechnologists to develop safe and clinically valid solutions for patients with laryngeal and vocal fold injuries. It is crucial for patients to be knowledgeable about the available choices of laryngeal tissue engineering for successful tissue repair. Although few human trials have been conducted, future works should build upon previously completed in-vivo studies in an effort to move towards more human models.
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 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 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".