Potential roles of stem cells in the management of sensorineural hearing loss
Bibliographic record
Abstract
BACKGROUND: In the management of sensorineural hearing loss, effective therapy for degenerated hair cells, third order neurons, ganglions, dendrites and synaptic areas of the vestibulo-cochleo-cerebral pathway remains an enigma. Transplantation of stem and progenitor cells appears to be an emerging potential solution, and is the focus of this review. AIM: To review recent developments in the management of sensorineural hearing loss in the field of stem cell research. MATERIALS AND METHOD: A systematic review of the English language literature included all experimental and non-experimental studies with a Jadad score of three or more, published between 2000 and 2010 and included in the following databases: Cochrane Library Ear, Nose and Throat Disorders; Medline; Google Scholar; Hinari; and the Online Library of Toronto University. RESULTS: Of the 455 and 29 600 articles identified from Medline and Google Scholar, respectively, 48 met the inclusion criteria. These were independently reviewed and jointly analysed. CONCLUSION: Although there is not yet any evidence from successful human studies, stem cell and 'alternative stem cell' technology seems to represent the future of sensorineural hearing loss management.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".