Numb is Required for the Production of Terminal Asymmetric Cell Divisions in the Developing Mouse Retina
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the developing nervous system, cell diversification depends on the ability of neural progenitor cells to divide asymmetrically to generate daughter cells that acquire different identities. While much work has recently focused on the mechanisms controlling self-renewing asymmetric divisions producing a differentiating daughter and a progenitor, little is known about mechanisms regulating how distinct differentiating cell types are produced at terminal divisions. Here we study the role of the endocytic adaptor protein Numb in the developing mouse retina. Using clonal numb inactivation in retinal progenitor cells (RPCs), we show that Numb is required for normal cell-cycle progression at early stages, but is dispensable for the production of self-renewing asymmetric cell divisions. At late stages, however, Numb is no longer required for cell-cycle progression, but is critical for the production of terminal asymmetric cell divisions. In the absence of Numb, asymmetric terminal divisions that generate a photoreceptor and a non-photoreceptor cell are decreased in favor of symmetric terminal divisions generating two photoreceptors. Using live imaging in retinal explants, we show that a Numb fusion protein is asymmetrically inherited by the daughter cells of some late RPC divisions. Together with our finding that Numb antagonizes Notch signaling in late-stage RPCs, and that blocking Notch signaling in late RPCs almost completely abolishes the generation of terminal asymmetric divisions, these results suggest a model in which asymmetric inheritance of Numb in sister cells of terminal divisions might create unequal Notch activity, which in turn drives the production of terminal asymmetric divisions.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 it