Specificity Protein 1 is essential for the limb trajectory of ephrin-mediated spinal motor axons
Bibliographic record
Abstract
Abstract The precise organization of neural circuits requires highly specific axon guidance, facilitated by cell-surface guidance receptors on axonal growth cones that help neurons reach their target destinations. Despite a limited repertoire of known guidance receptors and ligands, neural systems achieve complex axonal networks, suggesting that additional regulatory mechanisms exist. One proposed strategy is the co-expression of ligands and their receptors on the same axons, allowing modulation of receptor responsiveness to guidance cues. To investigate this mechanism, we studied the spinal lateral motor column (LMC) motor neurons, which make a binary axon pathfinding decision toward limb targets. We hypothesized that specificity protein 1 (Sp1), a transcription factor, regulates ephrin expression in LMC neurons, thereby modulating receptor functions via cis -attenuation to ensure accurate axonal pathfinding. Our results show that Sp1 is indeed expressed in LMC neurons during critical axonal extension periods. Manipulating Sp1 activity disrupted LMC axon trajectory selection, and RNA-Seq analysis indicated that Sp1 regulates genes associated with axon guidance, including ephrins. We found that Sp1 knockdown affected ephrin/Eph cis -binding and trans -signaling, highlighting Sp1’s role in controlling axonal projections through ephrin gene regulation. Additionally, coactivators p300 and CBP are essential for Sp1’s regulatory function. These findings identify Sp1 as a key transcription factor in LMC neurons, essential for ephrin expression and ephrin/Eph-mediated axon guidance, providing insights into the molecular mechanisms of neural circuit formation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".