Coordinating progenitor cell cycle exit and differentiation in the developing vertebrate retina
Bibliographic record
Abstract
The proper development of the vertebrate retina relies heavily on producing the correct number and type of differentiated retinal cell types. To achieve this, proliferating retinal progenitor cells (RPCs) must exit the cell cycle at an appropriate time and correctly express a subset of differentiation markers that help specify retinal cell fate. Homeobox genes, which encode a family of transcription factors, have been accredited to both these processes, implicated in the transcriptional regulation of important cell cycle components, such as cyclins and cyclin-dependent kinases, and proneural genes. This dual regulation of homeobox genes allows these factors to help co-ordinate the transition from the proliferating RPC to postmitotic, differentiated cell. However, understanding the exact molecular targets of these factors remains a challenging task. This commentary highlights the current knowledge we have about how these factors regulate cell cycle progression and differentiation, with particular emphasis on a recent discovery from our lab demonstrating an antagonistic relationship between Vsx2 and Dmbx1 to control RPC proliferation. Future studies should aim to further understand the direct transcriptional targets of these genes, additional co-factors/interacting proteins and the possible recruitment of epigenetic machinery by these homeobox genes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".