Basic Helix-Loop-Helix Transcription Factors Cooperate To Specify a Cortical Projection Neuron Identity
Bibliographic record
Abstract
Several transcription factors are essential determinants of a cortical projection neuron identity, but their mode of action (instructive versus permissive) and downstream genetic cascades remain poorly defined. Here, we demonstrate that the proneural basic helix-loop-helix (bHLH) gene Ngn2 instructs a partial cortical identity when misexpressed in ventral telencephalic progenitors, inducing ectopic marker expression in a defined temporal sequence, including early (24 h; Nscl2), intermediate (48 h; BhlhB5), and late (72 h; NeuroD, NeuroD2, Math2, and Tbr1) target genes. Strikingly, cortical gene expression was much more rapidly induced by Ngn2 in the dorsal telencephalon (within 12 to 24 h). We identify the bHLH gene Math3 as a dorsally restricted Ngn2 transcriptional target and cofactor, which synergizes with Ngn2 to accelerate target gene transcription in the cortex. Using a novel in vivo luciferase assay, we show that Ngn2 generates only approximately 60% of the transcriptional drive in ventral versus dorsal telencephalic domains, an activity that is augmented by Math3, providing a mechanistic basis for regional differences in Ngn2 function. Cortical bHLH genes thus cooperate to control transcriptional strength, thereby temporally coordinating downstream gene expression.
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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) | 0.001 | 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".