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Record W2000256899 · doi:10.1177/000348940711600609

Dysfunction of the Recurrent Laryngeal Nerve and the Potential of Gene Therapy

2007· review· en· W2000256899 on OpenAlexaff
S. Brett Heavner, Adam D. Rubin, Kevin Fung, Matthew Old, Norman D. Hogikyan, Eva L. Feldman

Bibliographic record

VenueAnnals of Otology Rhinology & Laryngology · 2007
Typereview
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineNucleus ambiguusRecurrent laryngeal nerveParesisParalysisSwallowingNerve injuryRegeneration (biology)Genetic enhancementNeurotrophic factorsDiseaseAnesthesiaSurgeryPathologyInternal medicineMedulla oblongataBiologyCentral nervous systemGene

Abstract

fetched live from OpenAlex

Injury to the recurrent laryngeal nerve causes vocal fold paresis or paralysis resulting in poor voice quality, and possibly swallowing dysfunction and/or airway compromise. Injury can occur as part of a neurodegenerative disease process or can be due to direct nerve trauma or tumor invasion. Management depends upon symptoms, the cause and severity of injury, and the prognosis for recovery of nerve function. Surgical treatment techniques can improve symptoms, but do not restore physiologic motion. Gene therapy may be a useful adjunct to enhance nerve regeneration in the setting of neurodegenerative disease or trauma. Remote injection of viral vectors into the recurrent laryngeal nerve is the least invasive way to deliver neurotrophic factors to the nerve's cell bodies within the nucleus ambiguus, and in turn to promote nerve regeneration and enhance both nuclear and nerve survival. The purpose of this review is to discuss the potential role for gene therapy in treatment of the unsolved problem of vocal fold paralysis.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.087
GPT teacher head0.369
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations23
Published2007
Admission routes1
Has abstractyes

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