A molecular map of the human spinal dorsal and ventral horn defines arrangement of neuronal types and glial sex differences
Bibliographic record
Abstract
The spinal cord is the gateway for sensory information from the body as it ascends to the brain, as well as a major motor output center of the nervous system. It is also a key location for sensory-motor integration, and a processing site for nociceptive information that eventually drives pain perception in the brain. Tremendous progress has been made in understanding spinal cord circuits using genetic and single cell sequencing approaches in mice. Recently, several groups have conducted single-nucleus and spatial sequencing studies in postmortem human spinal cord tissue. However, the spatial properties of spinal cord cellular diversity and potential sex differences that might be important for human physiology remain unexplored. We conducted deep single-nucleus sequencing on dissected lumbar dorsal and ventral spinal cord samples from 11 organ donors, including 6 females and 5 males, and anatomically annotated spinal cord cell types with 10X Xenium single-molecule spatial transcriptomics. We identified 34 spatially and genetically defined neuron classes, many of which have clearly recognizable conserved orthologs in the rodent spinal cord. We also identified sex specific cell types and states within multiple glial types, but not neurons, demonstrating sexual dimorphism at the transcriptomic cell-type level in the adult human spinal cord. The spatial and single-nucleus atlas resulting from our work build upon previous knowledge to better understand human spinal cord physiology and to identify drug targets for neurological diseases affecting the spinal cord, in particular pain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".