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Record W2789649381 · doi:10.3389/fnmol.2018.00077

Reprogramming Glia Into Neurons in the Peripheral Auditory System as a Solution for Sensorineural Hearing Loss: Lessons From the Central Nervous System

2018· review· en· W2789649381 on OpenAlexafffund
Steven J. Meas, Chun‐Li Zhang, Alain Dabdoub

Bibliographic record

VenueFrontiers in Molecular Neuroscience · 2018
Typereview
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsSunnybrook HospitalUniversity of Toronto
FundersJapan Society for the Promotion of ScienceCanada First Research Excellence FundMitacsUniversity of Toronto
KeywordsSpiral ganglionReprogrammingNeuroscienceAuditory systemCochleaHearing lossPopulationBiologySensory systemPresbycusisAudiologyMedicineCell

Abstract

fetched live from OpenAlex

Disabling hearing loss affects over 5% of the world's population and impacts the lives of individuals from all age groups. Within the next three decades, the worldwide incidence of hearing impairment is expected to double. Since a leading cause of hearing loss is the degeneration of primary auditory neurons (PANs), the sensory neurons of the auditory system that receive input from mechanosensory hair cells in the cochlea, it may be possible to restore hearing by regenerating PANs. A direct reprogramming approach can be used to convert the resident spiral ganglion glial cells into induced neurons to restore hearing. This review summarizes recent advances in reprogramming glia in the CNS to suggest future steps for regenerating the peripheral auditory system. In the coming years, direct reprogramming of spiral ganglion glial cells has the potential to become one of the leading biological strategies to treat hearing impairment.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.885
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0000.001
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 head0.058
GPT teacher head0.315
Teacher spread0.258 · 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 designNot applicable
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
Published2018
Admission routes2
Has abstractyes

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