Rapid cell-cycle reentry and cell death after acute inactivation of the retinoblastoma gene product in postnatal cochlear hair cells
Bibliographic record
Abstract
Unlike lower vertebrates, mammals are unable to replace damaged mechanosensory hair cells (HCs) in the cochlea. Recently, ablation of the retinoblastoma protein (Rb) in undifferentiated mouse HC precursors was shown to cause cochlear HC proliferation and the generation of new HCs, raising the hope that inactivation of Rb in postmitotic HCs could trigger cell division and regenerate functional HCs postnatally. Here, we acutely inactivated Rb in nearly all cochlear HCs of newborn mice, using a newly developed HC-specific inducible Cre mouse line. Beginning 48 h after Rb deletion, approximately 40% of HCs were in the S and M phases of the cell cycle, demonstrating an overriding role for Rb in maintaining the quiescent state of postnatal HCs. Unlike Rb-null HC precursors, such HCs failed to undergo cell division and died rapidly. HC clusters were restricted to the less differentiated cochlear regions, consistent with differentiation-dependent roles of Rb. Moreover, outer HCs expressed the maturation marker prestin, suggesting an embryonic time window for Rb-dependent HC specification. We conclude that Rb plays essential and age-dependent roles during HC proliferation and differentiation, and, in contrast to previous hypotheses, cell death after forced cell-cycle reentry presents a major challenge for mammalian HC regeneration from residual postnatal HCs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".