<i>In vivo</i> human embryonic spinal cord atlas validates stem cell–derived human dorsal interneurons and reveals ASD spinal signatures
Bibliographic record
Abstract
Abstract Restoring somatosensory function after spinal cord injury (SCI) faces fundamental challenges: neuronal subtypes must match both axial position and circuit identity, yet the developmental patterning of human dorsal spinal interneurons (dIs) remains incompletely defined. Here, we integrate six single-cell transcriptomics datasets derived from human embryonic spinal cord tissue spanning gestational weeks 4-25 to generate a reference atlas of early human somatosensory circuit development. The atlas reveals molecular signatures underlying expansion and specialization of dI4 and dI5 interneuron populations associated with mechanosensory and nociceptive processing. Guided by this resource, we established a neuromesodermal progenitor–based differentiation approach that generates dorsal interneurons spanning anterior–posterior identities. Comparison of in vivo and in vitro dI4/dI5 subclasses identified conserved gene networks associated with sensory modalities and revealed enrichment of autism spectrum disorder–associated genes within mechanosensory interneuron populations. Together, these findings clarify how human dorsal spinal interneuron diversity is established.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".