A role for neural determination genes in specifying the dorsoventral identity of telencephalic neurons
Bibliographic record
Abstract
Neurogenin1 (Ngn1), Neurogenin2 (Ngn2), and Mash1 encode bHLH transcription factors with neuronal determination functions. In the telencephalon, the Ngns and Mash1 are expressed at high levels in complementary dorsal and ventral domains, respectively. We found that Ngn function is required to maintain these two separate expression domains, as Mash1 expression is up-regulated in the dorsal telencephalon of Ngn mutant embryos. We have taken advantage of the replacement of the Ngns by Mash1 in dorsal progenitors to address the role of the neural determination genes in neuronal-type specification in the telencephalon. In Ngn2 single and Ngn1; Ngn2 double mutants, a population of early born cortical neurons lose expression of dorsal-specific markers and ectopically express a subset of ventral telencephalic-specific markers. Analysis of Mash1; Ngn2 double mutant embryos and of embryos carrying a Ngn2 to Mash1 replacement mutation demonstrated that ectopic expression of Mash1 is required and sufficient to confer these ventral characteristics to cortical neurons. Our results indicate that in addition to acting as neuronal determinants, Mash1 and Ngns play a role in the specification of dorsal-ventral neuronal identity, directly linking pathways of neurogenesis and regional patterning in the forebrain.
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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".