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Record W2984014483 · doi:10.1371/journal.pone.0224022

BDNF, NT-3 and Trk receptor agonist monoclonal antibodies promote neuron survival, neurite extension, and synapse restoration in rat cochlea ex vivo models relevant for hidden hearing loss

2019· article· en· W2984014483 on OpenAlexafffund
Stephanie Szobota, Pranav Dinesh Mathur, Sairey Siegel, KristenAnn Black, H. Uri Saragovi, Alan C. Foster

Bibliographic record

VenuePLoS ONE · 2019
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsMcGill UniversityJewish General Hospital
FundersCanadian Institutes of Health ResearchOtonomy
KeywordsSpiral ganglionCochleaTropomyosin receptor kinase BTrk receptorNeurotrophinNeuriteNeuroscienceBiologySynapseNeurotrophic factorsReceptor

Abstract

fetched live from OpenAlex

Neurotrophins and their mimetics are potential treatments for hearing disorders because of their trophic effects on spiral ganglion neurons (SGNs) whose connections to hair cells may be compromised in many forms of hearing loss. Studies in noise or ototoxin-exposed animals have shown that local delivery of NT-3 or BDNF has beneficial effects on SGNs and hearing. We evaluated several TrkB or TrkC monoclonal antibody agonists and small molecules, along with BDNF and NT-3, in rat cochlea ex vivo models. The TrkB agonists BDNF and a monoclonal antibody, M3, had the greatest effects on SGN survival, neurite outgrowth and branching. In organotypic cochlear explants, BDNF and M3 enhanced synapse formation between SGNs and inner hair cells and restored these connections after excitotoxin-induced synaptopathy. Loss of these synapses has recently been implicated in hidden hearing loss, a condition characterized by difficulty hearing speech in the presence of background noise. The unique profile of M3 revealed here warrants further investigation, and the broad activity profile of BDNF observed underpins its continued development as a hearing loss therapeutic.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.092
GPT teacher head0.272
Teacher spread0.180 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations52
Published2019
Admission routes2
Has abstractyes

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Same venuePLoS ONESame topicHearing, Cochlea, Tinnitus, GeneticsFrench-language works237,207