Identification of ion-channel modulators that protect against aminoglycoside-induced hair cell death
Bibliographic record
Abstract
Aminoglycoside antibiotics are used to treat life-threatening bacterial infections but can cause deafness due to hair cell death in the inner ear. Compounds have been described that protect zebrafish lateral line hair cells from aminoglycosides, but few are effective in the cochlea. As the aminoglycosides interact with several ion channels, including the mechanoelectrical transducer (MET) channels by which they can enter hair cells, we screened 160 ion-channel modulators, seeking compounds that protect cochlear outer hair cells (OHCs) from aminoglycoside-induced death in vitro. Using zebrafish, 72 compounds were identified that either reduced loading of the MET-channel blocker FM 1-43FX, decreased Texas red-conjugated neomycin labeling, or reduced neomycin-induced hair cell death. After testing these 72 compounds, and 6 structurally similar compounds that failed in zebrafish, 13 were found that protected against gentamicin-induced death of OHCs in mouse cochlear cultures, 6 of which are permeant blockers of the hair cell MET channel. None of these compounds abrogated aminoglycoside antibacterial efficacy. By selecting those without adverse effects at high concentrations, 5 emerged as leads for developing pharmaceutical otoprotectants to alleviate an increasing clinical problem.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".