Gene Therapy for Cisplatin-Induced Ototoxicity
Bibliographic record
Abstract
OBJECTIVE: Ototoxicity is a frequent adverse event of cisplatin treatment. No therapy is currently available for cisplatin-induced ototoxicity. A systematic review of experimental animal studies and in vitro experiments was conducted to evaluate gene therapy as a potential future therapeutic option. DATA SOURCES: Eligible studies were identified through searches of electronic databases Ovid MEDLINE, Ovid MEDLINE In-Process, Embase, PubMed, Biosis Previews, Scopus, ISI Web of Science, and The Cochrane Library. STUDY SELECTION: Articles obtained from the search were independently reviewed by 2 authors using specific criteria to identify experimental animal studies and in vitro experiments conducted to evaluate gene therapy for cisplatin-induced ototoxicity. No restriction was applied to publication dates or languages. DATA EXTRACTION: Data extracted included experiment type, cell type, species, targeted gene, gene expression, method, administration, inner ear site evaluated, outcome measures for cytotoxicity, and significant results. RESULTS: Fourteen articles were included in this review. In vitro and in vivo experiments have been performed to evaluate the potential of gene expression manipulation for cisplatin-induced ototoxicity. Twelve different genes were targeted including NTF3, GDNF, HO-1, XIAP, Trpv1, BCL2, Otos, Nfe2l2, Nox1, Nox3, Nox4, and Ctr1. All of the included articles demonstrated a benefit of gene therapy on cytotoxicity caused by cisplatin. CONCLUSION: Experimental animal studies and in vitro experiments have demonstrated the efficacy of gene therapy for cisplatin-induced ototoxicity. However, further investigation regarding safety, immunogenicity, and consequences of genetic manipulation in the inner ear tissues must be completed to develop future therapeutic options.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".