CNTF/LIF/gp130 receptor complex signaling maintains a VZ precursor differentiation gradient in the developing ventral forebrain
Bibliographic record
Abstract
The extrinsic signaling pathways responsible for the formation and maintenance of the unique laminar organization of the forebrain germinal zones are largely unknown. In the present study, we asked whether ciliary neurotrophic factor (CNTF)/leukemia inhibitory factor (LIF)/gp130 signaling plays a role in the development of the germinal layers in the lateral ganglionic eminence. We found that CNTF/LIF/gp130 receptor signaling promotes the self-renewal/expansion of a subpopulation of fibroblast growth factor-responsive ventricular zone (VZ) precursors in the ventral forebrain. Analysis of Lifr-/- mice suggests that CNTF/LIF/gp130 signaling maintains a subpopulation of GSH2+ VZ precursors, which are necessary for normal growth of the early ventral forebrain and for maintaining a gradient of VZ precursor differentiation in the lateral ganglionic eminence, as defined by GSH2, MASH1 and DLX2 expression. Furthermore, addition of exogenous CNTF to embryonic forebrain explant cultures deprived of choroid plexus-derived CNTF, was sufficient to promote a VZ differentiation gradient. In contrast to the forebrain, CNTF/LIF/gp130 signaling reduced, rather than enhanced, precursor self-renewal/expansion in the spinal cord. These results demonstrate a novel region-specific role for CNTF/LIF/gp130 signaling in the development of the germinal layers of the embryonic telencephalon.
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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) | 0.000 | 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 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".