HoxD transcription factors define monosynaptic sensory-motor specificity in the developing spinal cord
Bibliographic record
Abstract
The specificity of monosynaptic connections between proprioceptive sensory neurons and their recipient spinal motor neurons depends on multiple factors, including motor neuron positioning and dendrite morphology, axon projection patterns of proprioceptive sensory neurons in the spinal cord, and the ligand-receptor molecules involved in cell-to-cell recognition. However, with few exceptions, the transcription factors engaged in this process are poorly characterized. Here, we show that members of the HoxD family of transcription factors play a crucial role in the specificity of monosynaptic sensory-motor connections. Mice lacking Hoxd9, Hoxd10 and Hoxd11 exhibit defects in locomotion but have no obvious defects in motor neuron positioning or dendrite morphology through the medio-lateral and rostro-caudal axes. However, we found that quadriceps motor neurons in these mice show aberrant axon development and receive inappropriate inputs from proprioceptive sensory axons innervating the obturator muscle. These genetic studies demonstrate that the HoxD transcription factors play an integral role in the synaptic specificity of monosynaptic sensory-motor connections in the developing spinal cord.
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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".