Role for TGF-β superfamily signaling in telencephalic GABAergic neuron development
Bibliographic record
Abstract
Signaling mechanisms mediated by the Transforming Growth Factor-beta (TGF-beta) superfamily regulate a variety of developmental processes. Here we show that components of both bone morphogenetic protein/growth differentiation factor and TGF-beta/activin/Nodal branches of TGF-beta superfamily signaling are expressed in the developing subpallium. Furthermore, Smad proteins, transcriptional effectors of TGF-beta signaling, are co-expressed and physically interact in the basal ganglia with Dlx homeodomain transcription factors, which are critical regulators of the differentiation, migration and survival of telencephalic GABAergic neurons. We also show that Dlx and Smad proteins localize to promoters/enhancers of a number of common telencephalic genes in vivo and that Smad proteins co-activate transcription with Dlx family members, except with certain mutated human DLX proteins identified in autistic individuals. In agreement with these observations, expression of dominant-negative Smads in the developing basal ganglia phenocopies the cell migration defects observed in Dlx1/2-deficient mice. Together, these results suggest that TGF-beta superfamily signaling plays a role in telencephalic GABAergic neuron development through functional interactions with Dlx transcription factors. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11689-009-9035-6) contains supplementary material, which is available to authorized users.
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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) | 0.003 | 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".