Kremen1 regulates mechanosensory hair cell development in the mammalian cochlea and the zebrafish lateral line
Bibliographic record
Abstract
Here we present spatio-temporal localization of Kremen1, a transmembrane receptor, in the mammalian cochlea, and investigate its role in the formation of sensory organs in mammal and fish model organisms. We show that Kremen1 is expressed in prosensory cells during cochlear development and in supporting cells of the adult mouse cochlea. Based on this expression pattern, we investigated whether Kremen1 functions to modulate cell fate decisions in the prosensory domain of the developing cochlea. We used gain and loss-of-function experiments to show that Kremen1 is sufficient to bias cells towards supporting cell fate, and is implicated in suppression of hair cell formation. In addition to our findings in the mouse cochlea, we examined the effects of over expression and loss of Kremen1 in the zebrafish lateral line. In agreement with our mouse data, we show that over expression of Kremen1 has a negative effect on the number of mechanosensory cells that form in the zebrafish neuromasts, and that fish lacking Kremen1 protein develop more hair cells per neuromast compared to wild type fish. Collectively, these data support an inhibitory role for Kremen1 in hair cell fate specification.
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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) | 0.002 | 0.001 |
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".